Observation List

HTTP 200 OK
Allow: GET, POST, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "count": 10256,
    "next": "https://api.catalogue.ceda.ac.uk/api/v3/observations/?format=api&limit=100&offset=9200",
    "previous": "https://api.catalogue.ceda.ac.uk/api/v3/observations/?format=api&limit=100&offset=9000",
    "results": [
        {
            "ob_id": 40405,
            "uuid": "d34388ce844740d9ad5b8b1aa4186fb6",
            "title": "MOASA flight M253: airborne observations from the Clean Air project over the north east of the UK",
            "abstract": "Observations collected during flight M253 on 20 September 2019 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the north east of the UK  in a  ground network survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.  Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:51:13.663134",
            "lastUpdatedDate": "2023-08-11T15:51:13",
            "latestDataUpdateTime": "2023-09-13T14:51:17",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T15:20:01",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3901,
                "bboxName": "MOASA M253",
                "eastBoundLongitude": 0.251578,
                "westBoundLongitude": -1.918502,
                "southBoundLatitude": 50.778881,
                "northBoundLatitude": 53.016964
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40406,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M253",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 106760725,
                "numberOfFiles": 45,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11216,
                "startTime": "2019-09-20T10:20:00",
                "endTime": "2019-09-20T12:01:00"
            },
            "resultQuality": {
                "ob_id": 4355,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40407,
                "uuid": "c49f6bae3eee4c06b8d037e9edd75270",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M253: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                196965,
                196966,
                196967,
                196968,
                196969,
                196970,
                196971,
                196964,
                196972
            ],
            "onlineresource_set": [
                84082
            ]
        },
        {
            "ob_id": 40409,
            "uuid": "44c589f14c5749de8b283f73707f9b79",
            "title": "MOASA flight M256: airborne observations from the Clean Air project over the south west of the UK",
            "abstract": "Observations collected during flight M256 on 22 October 2019 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the south west of the UK,  in a ground network survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.  Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:51:24.558352",
            "lastUpdatedDate": "2023-08-11T15:51:24",
            "latestDataUpdateTime": "2023-08-11T16:23:33",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T15:19:43",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3902,
                "bboxName": "",
                "eastBoundLongitude": -1.614825,
                "westBoundLongitude": -4.30014,
                "southBoundLatitude": 50.347507,
                "northBoundLatitude": 51.507874
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40410,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M256",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 153575430,
                "numberOfFiles": 25,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11217,
                "startTime": "2019-10-22T10:40:00",
                "endTime": "2019-10-22T12:40:00"
            },
            "resultQuality": {
                "ob_id": 4356,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40411,
                "uuid": "87f5b86ea11d48bf958b56684187ddb7",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M256: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                196976,
                196977,
                196978,
                196979,
                196980,
                196981,
                196982,
                196983,
                196984
            ],
            "onlineresource_set": [
                84083
            ]
        },
        {
            "ob_id": 40413,
            "uuid": "2bbcb7b923bc4e49b33f7814e27d2224",
            "title": "MOASA flight M257: airborne observations from the Clean Air project over Port Talbot, UK",
            "abstract": "Observations collected during flight M257 on 23 October 2019 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in situ atmospheric composition measurements over Port Talbot, UK  in a high density spatial mapping flight pattern.\r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Port Talbot, UK  in a high density spatial mapping flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:51:33.251099",
            "lastUpdatedDate": "2023-08-11T15:51:33",
            "latestDataUpdateTime": "2023-08-11T16:23:39",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T15:19:30",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3903,
                "bboxName": "",
                "eastBoundLongitude": -1.789804,
                "westBoundLongitude": -3.971626,
                "southBoundLatitude": 50.778912,
                "northBoundLatitude": 51.61729
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40414,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M257",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 171678718,
                "numberOfFiles": 25,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11218,
                "startTime": "2019-10-23T10:27:00",
                "endTime": "2019-10-23T12:05:00"
            },
            "resultQuality": {
                "ob_id": 4357,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40415,
                "uuid": "3b3fec49889941bb84a80d01bd6364c2",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M257: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                196988,
                196989,
                196990,
                196991,
                196992,
                196993,
                196994,
                196995,
                196996
            ],
            "onlineresource_set": [
                84084
            ]
        },
        {
            "ob_id": 40417,
            "uuid": "6bc38ceb9178415c9826bc8ad7c4d550",
            "title": "MOASA flight M258: airborne observations from the Clean Air project over the south coast of the UK",
            "abstract": "Observations collected during flight M258 on 30 October 2019 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the south coast of the UK  in a South coast survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.  Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:51:40.826724",
            "lastUpdatedDate": "2023-08-11T15:51:40",
            "latestDataUpdateTime": "2024-03-09T02:41:57",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T15:19:17",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3904,
                "bboxName": "",
                "eastBoundLongitude": 1.485153,
                "westBoundLongitude": -1.825932,
                "southBoundLatitude": 50.740498,
                "northBoundLatitude": 51.230667
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40418,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M258",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 107154202,
                "numberOfFiles": 18,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11219,
                "startTime": "2019-10-30T12:05:00",
                "endTime": "2019-10-30T14:00:00"
            },
            "resultQuality": {
                "ob_id": 4358,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40419,
                "uuid": "8a33c89474c442109dc56934801daf5e",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M258: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197000,
                197001,
                197002,
                197003,
                197004,
                197005,
                197006,
                197007,
                197008
            ],
            "onlineresource_set": [
                84085
            ]
        },
        {
            "ob_id": 40421,
            "uuid": "4a9ed1f4b93a4d52b6a14432c49d3ce2",
            "title": "MOASA flight M262: airborne observations from the Clean Air project over the north east of the UK",
            "abstract": "Observations collected during flight M262 on 10 January 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the north east of the UK  in a ground network survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.  Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:51:51.361860",
            "lastUpdatedDate": "2023-08-11T15:51:51",
            "latestDataUpdateTime": "2023-08-11T16:23:58",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T15:19:02",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3905,
                "bboxName": "",
                "eastBoundLongitude": 0.300421,
                "westBoundLongitude": -1.907496,
                "southBoundLatitude": 50.740494,
                "northBoundLatitude": 52.98111
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40422,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M262",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 258900370,
                "numberOfFiles": 33,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11220,
                "startTime": "2020-01-10T12:15:00",
                "endTime": "2020-01-10T14:56:00"
            },
            "resultQuality": {
                "ob_id": 4359,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40423,
                "uuid": "c237d79e870443958ab844a6d5b1e1ab",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M262: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197012,
                197013,
                197014,
                197015,
                197016,
                197017,
                197018,
                197019,
                197020
            ],
            "onlineresource_set": [
                84086
            ]
        },
        {
            "ob_id": 40425,
            "uuid": "af8181dcc3084098a612e2cb84f0412d",
            "title": "MOASA flight M263: airborne observations from the Clean Air project over the south west of the UK",
            "abstract": "Observations collected during flight M263 on 15 January 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the south west of the UK,  in a ground network survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.  Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:52:05.935700",
            "lastUpdatedDate": "2023-08-11T15:52:05",
            "latestDataUpdateTime": "2023-08-11T16:24:05",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T15:18:50",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3906,
                "bboxName": "",
                "eastBoundLongitude": -1.827222,
                "westBoundLongitude": -4.302867,
                "southBoundLatitude": 50.360588,
                "northBoundLatitude": 51.548019
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40426,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M263",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 169952491,
                "numberOfFiles": 27,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11221,
                "startTime": "2020-01-15T12:08:00",
                "endTime": "2020-01-15T14:40:00"
            },
            "resultQuality": {
                "ob_id": 4360,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40427,
                "uuid": "6940a1329701485aaab0ebf608ef8246",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M263: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197024,
                197025,
                197026,
                197027,
                197028,
                197029,
                197030,
                197031,
                197032
            ],
            "onlineresource_set": [
                84087
            ]
        },
        {
            "ob_id": 40429,
            "uuid": "301eea0daed8410395198b2474aa7a77",
            "title": "MOASA flight M264: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M264 on 20 January 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:52:20.337619",
            "lastUpdatedDate": "2023-08-11T15:52:20",
            "latestDataUpdateTime": "2023-08-11T16:24:11",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T15:18:35",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3907,
                "bboxName": "",
                "eastBoundLongitude": 0.524218,
                "westBoundLongitude": -1.902065,
                "southBoundLatitude": 50.747059,
                "northBoundLatitude": 51.681206
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40430,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M264",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 41633851,
                "numberOfFiles": 27,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11222,
                "startTime": "2020-01-20T12:29:00",
                "endTime": "2020-01-20T14:48:00"
            },
            "resultQuality": {
                "ob_id": 4361,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40431,
                "uuid": "89046ccfbfa04df98fb91a6ea571ce8b",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M264: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197036,
                197037,
                197038,
                197039,
                197040,
                197041,
                197042,
                197043,
                197044
            ],
            "onlineresource_set": [
                84088
            ]
        },
        {
            "ob_id": 40433,
            "uuid": "6bcac7e3b76f464ca930af5af40425cd",
            "title": "MOASA flight M265: airborne observations from the Clean Air project over the south coast of the UK",
            "abstract": "Observations collected during flight M265 on 21 January 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the south coast of the UK  in a South coast survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.  Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:52:32.059740",
            "lastUpdatedDate": "2023-08-11T15:52:32",
            "latestDataUpdateTime": "2023-09-13T14:53:18",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T15:18:12",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3908,
                "bboxName": "MOASA M265",
                "eastBoundLongitude": 0.299037,
                "westBoundLongitude": -3.762882,
                "southBoundLatitude": 50.53737,
                "northBoundLatitude": 50.855534
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40434,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M265",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 108386710,
                "numberOfFiles": 34,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11223,
                "startTime": "2020-01-21T12:18:00",
                "endTime": "2020-01-21T15:05:00"
            },
            "resultQuality": {
                "ob_id": 4362,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40435,
                "uuid": "a365ca6d7c54484ab7fd82dd1373a45d",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M265: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197048,
                197049,
                197050,
                197051,
                197052,
                197053,
                197054,
                197055,
                197056
            ],
            "onlineresource_set": [
                84089
            ]
        },
        {
            "ob_id": 40437,
            "uuid": "4a637f182162494b892699cb6f658c1a",
            "title": "MOASA flight M266: airborne observations from the Clean Air project over the south west of the UK",
            "abstract": "Observations collected during flight M266 on 06 February 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the south west of the UK,  in a ground network survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.  Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:52:42.191728",
            "lastUpdatedDate": "2023-08-11T15:52:42",
            "latestDataUpdateTime": "2023-08-11T16:24:27",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T15:17:58",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3909,
                "bboxName": "",
                "eastBoundLongitude": -1.03141,
                "westBoundLongitude": -4.30737,
                "southBoundLatitude": 50.358425,
                "northBoundLatitude": 51.491978
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40438,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M266",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 155054308,
                "numberOfFiles": 33,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11224,
                "startTime": "2020-02-06T11:37:56",
                "endTime": "2020-02-06T14:25:00"
            },
            "resultQuality": {
                "ob_id": 4363,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40439,
                "uuid": "1cce679cc66347648e36ef0d55766d83",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M266: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197060,
                197061,
                197062,
                197063,
                197064,
                197065,
                197066,
                197067,
                197068
            ],
            "onlineresource_set": [
                84090
            ]
        },
        {
            "ob_id": 40441,
            "uuid": "05d80bfcf6bd46baacd0b27073c0b944",
            "title": "MOASA flight M267: airborne observations from the Clean Air project over the south west of the UK",
            "abstract": "Observations collected during flight M267 on 16 March 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the south west of the UK,  in a ground network survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.  Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:52:52.499518",
            "lastUpdatedDate": "2023-08-11T15:52:52",
            "latestDataUpdateTime": "2023-08-11T16:24:36",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T15:17:43",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3910,
                "bboxName": "",
                "eastBoundLongitude": -0.99142,
                "westBoundLongitude": -4.230991,
                "southBoundLatitude": 50.354568,
                "northBoundLatitude": 51.493919
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40442,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M267",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 359152386,
                "numberOfFiles": 32,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11225,
                "startTime": "2020-03-16T11:57:28",
                "endTime": "2020-03-16T14:45:00"
            },
            "resultQuality": {
                "ob_id": 4364,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40443,
                "uuid": "c819e84fdc4847399e3cafea7aa3ce65",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M267: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197072,
                197073,
                197074,
                197075,
                197076,
                197077,
                197078,
                197079,
                197080
            ],
            "onlineresource_set": [
                84091
            ]
        },
        {
            "ob_id": 40445,
            "uuid": "67c39c04f97d43d49e3c7a587cf584b6",
            "title": "MOASA flight M269: airborne observations from the Clean Air project over the south coast of the UK",
            "abstract": "Observations collected during flight M269 on 10 September 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the south coast of the UK, in a South coast survey and ships flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:53:02.814109",
            "lastUpdatedDate": "2023-08-11T15:53:02",
            "latestDataUpdateTime": "2023-08-11T16:24:45",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:56:09",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3911,
                "bboxName": "",
                "eastBoundLongitude": -1.2827,
                "westBoundLongitude": -3.124974,
                "southBoundLatitude": 50.566139,
                "northBoundLatitude": 50.913994
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40446,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M269",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 103217203,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11226,
                "startTime": "2020-09-10T11:27:00",
                "endTime": "2020-09-10T13:00:00"
            },
            "resultQuality": {
                "ob_id": 4365,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40447,
                "uuid": "6e98e4a2d4e94bdf982ae4637c400061",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M269: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197084,
                197085,
                197086,
                197087,
                197088,
                197089,
                197090,
                197091,
                197092
            ],
            "onlineresource_set": [
                84092
            ]
        },
        {
            "ob_id": 40449,
            "uuid": "4ad5f8572f104e71a51907d623953e0e",
            "title": "MOASA flight M272: airborne observations from the Clean Air project over the south coast of the UK",
            "abstract": "Observations collected during flight M272 on 07 October 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the south coast of the UK, in a Coastal transition flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:53:12.004742",
            "lastUpdatedDate": "2023-08-11T15:53:12",
            "latestDataUpdateTime": "2023-08-11T16:24:57",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:56:34",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3912,
                "bboxName": "",
                "eastBoundLongitude": -0.039028,
                "westBoundLongitude": -1.889851,
                "southBoundLatitude": 50.572315,
                "northBoundLatitude": 51.003906
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40450,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M272",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 199466576,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11227,
                "startTime": "2020-10-07T10:35:00",
                "endTime": "2020-10-07T12:26:00"
            },
            "resultQuality": {
                "ob_id": 4366,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40451,
                "uuid": "0f0f3cce62a44e3f8a40a9e2d4acc931",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M272: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197096,
                197097,
                197098,
                197099,
                197100,
                197101,
                197102,
                197103,
                197104
            ],
            "onlineresource_set": [
                84093
            ]
        },
        {
            "ob_id": 40453,
            "uuid": "f69d4649c7fe49b29a8eef13ea8fec23",
            "title": "MOASA flight M273: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M273 on 05 November 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK, in a city survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:53:22.793055",
            "lastUpdatedDate": "2023-08-11T15:53:22",
            "latestDataUpdateTime": "2023-08-11T16:25:08",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:56:50",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3913,
                "bboxName": "",
                "eastBoundLongitude": 0.381059,
                "westBoundLongitude": -1.916944,
                "southBoundLatitude": 50.728817,
                "northBoundLatitude": 51.702118
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40454,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M273",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 124043299,
                "numberOfFiles": 33,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11228,
                "startTime": "2020-11-05T13:45:00",
                "endTime": "2020-11-05T15:44:04"
            },
            "resultQuality": {
                "ob_id": 4367,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40455,
                "uuid": "b25268be87194368ad8ff5e219bbd98b",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M273: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197108,
                197109,
                197110,
                197111,
                197112,
                197113,
                197114,
                197115,
                197116
            ],
            "onlineresource_set": [
                84094
            ]
        },
        {
            "ob_id": 40457,
            "uuid": "653e3ddb75b74e15ae8f4795e2725d41",
            "title": "MOASA flight M274: airborne observations from the Clean Air project over the south coast of the UK",
            "abstract": "Observations collected during flight M274 on 06 November 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol)  over the south coast of the UK  in a South coast survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:53:30.843264",
            "lastUpdatedDate": "2023-08-11T15:53:30",
            "latestDataUpdateTime": "2023-08-11T16:25:17",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:57:05",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3914,
                "bboxName": "",
                "eastBoundLongitude": 1.776001,
                "westBoundLongitude": -1.895355,
                "southBoundLatitude": 50.688671,
                "northBoundLatitude": 51.335415
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40458,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M274",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 51376508,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11229,
                "startTime": "2020-11-06T12:00:00",
                "endTime": "2020-11-06T14:30:00"
            },
            "resultQuality": {
                "ob_id": 4368,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40459,
                "uuid": "1b41a489d3dd44acb7b4f246ceb4f65d",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M274: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197120,
                197121,
                197122,
                197123,
                197124,
                197125,
                197126,
                197127,
                197128
            ],
            "onlineresource_set": [
                84095
            ]
        },
        {
            "ob_id": 40461,
            "uuid": "4f04423b7465484fa57f7100879caeb3",
            "title": "MOASA flight M275: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M275 on 26 November 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK, in a city survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:53:40.238630",
            "lastUpdatedDate": "2023-08-11T15:53:40",
            "latestDataUpdateTime": "2023-08-11T16:25:25",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:57:19",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3915,
                "bboxName": "",
                "eastBoundLongitude": 0.359104,
                "westBoundLongitude": -1.939926,
                "southBoundLatitude": 50.757847,
                "northBoundLatitude": 51.704109
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40462,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M275",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 40938038,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11230,
                "startTime": "2020-11-26T12:03:00",
                "endTime": "2020-11-26T13:55:00"
            },
            "resultQuality": {
                "ob_id": 4369,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40463,
                "uuid": "b7b4e1c8feb547328c757feb024cd1db",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M275: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197132,
                197133,
                197134,
                197135,
                197136,
                197137,
                197138,
                197139,
                197140
            ],
            "onlineresource_set": [
                84096
            ]
        },
        {
            "ob_id": 40465,
            "uuid": "499078b3fca44780b1ed46746ab45fba",
            "title": "MOASA flight M276: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M276 on 01 December 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK, in a city survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:53:48.790478",
            "lastUpdatedDate": "2023-08-11T15:53:48",
            "latestDataUpdateTime": "2023-08-11T16:25:31",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:57:47",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3916,
                "bboxName": "",
                "eastBoundLongitude": 0.340693,
                "westBoundLongitude": -1.902018,
                "southBoundLatitude": 50.773205,
                "northBoundLatitude": 51.68969
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40466,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M276",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 206609931,
                "numberOfFiles": 25,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11231,
                "startTime": "2020-12-01T11:48:00",
                "endTime": "2020-12-01T13:59:00"
            },
            "resultQuality": {
                "ob_id": 4370,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40467,
                "uuid": "57445c0973f74922b516993f52f31be5",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M276: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197144,
                197145,
                197146,
                197147,
                197148,
                197149,
                197150,
                197151,
                197152
            ],
            "onlineresource_set": [
                84097
            ]
        },
        {
            "ob_id": 40469,
            "uuid": "d0878e5bf555430ca33701fcee277998",
            "title": "MOASA flight M277: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M277 on 09 December 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK, in a city survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:54:02.904549",
            "lastUpdatedDate": "2023-08-11T15:54:02",
            "latestDataUpdateTime": "2023-08-11T16:25:46",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:58:09",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3917,
                "bboxName": "",
                "eastBoundLongitude": 0.324652,
                "westBoundLongitude": -1.898513,
                "southBoundLatitude": 50.742733,
                "northBoundLatitude": 51.701019
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40470,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M277",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 50272069,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11232,
                "startTime": "2020-12-09T11:39:39",
                "endTime": "2020-12-09T14:09:31"
            },
            "resultQuality": {
                "ob_id": 4371,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40471,
                "uuid": "e43638d5dd4644a98a15c062ccf67de8",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M277: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197156,
                197157,
                197158,
                197159,
                197160,
                197161,
                197162,
                197163,
                197164
            ],
            "onlineresource_set": [
                84098
            ]
        },
        {
            "ob_id": 40473,
            "uuid": "835562400939439391a1da98fbc84fe2",
            "title": "MOASA flight M279: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M279 on 08 March 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK, in a city survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:54:11.586199",
            "lastUpdatedDate": "2023-08-11T15:54:11",
            "latestDataUpdateTime": "2023-08-11T16:25:54",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:58:23",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3918,
                "bboxName": "",
                "eastBoundLongitude": 0.323331,
                "westBoundLongitude": -1.897261,
                "southBoundLatitude": 50.773979,
                "northBoundLatitude": 51.701244
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40474,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M279",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 48978571,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11233,
                "startTime": "2021-03-08T14:02:00",
                "endTime": "2021-03-08T16:27:49"
            },
            "resultQuality": {
                "ob_id": 4372,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40475,
                "uuid": "731030cc1f1a4b9d9419d9dd59aea248",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M279: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197168,
                197169,
                197170,
                197171,
                197172,
                197173,
                197174,
                197175,
                197176
            ],
            "onlineresource_set": [
                84099
            ]
        },
        {
            "ob_id": 40477,
            "uuid": "c07c3920ab7e474e886fd24b91030404",
            "title": "MOASA flight M280: airborne observations from the Clean Air project over the south coast of the UK",
            "abstract": "Observations collected during flight M280 on 09 March 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol)over the south coast of the UK, in a Coastal Transition flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:54:27.755496",
            "lastUpdatedDate": "2023-08-11T15:54:27",
            "latestDataUpdateTime": "2023-08-11T16:26:02",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:58:46",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3919,
                "bboxName": "",
                "eastBoundLongitude": 0.773807,
                "westBoundLongitude": -1.891159,
                "southBoundLatitude": 50.514748,
                "northBoundLatitude": 51.005615
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40478,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M280",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 43791758,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11234,
                "startTime": "2021-03-09T12:26:20",
                "endTime": "2021-03-09T14:55:00"
            },
            "resultQuality": {
                "ob_id": 4373,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40479,
                "uuid": "104f1153f73c4cd99cfbb36c16dc35cc",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M280: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197180,
                197181,
                197182,
                197183,
                197184,
                197185,
                197186,
                197187,
                197188
            ],
            "onlineresource_set": [
                84100
            ]
        },
        {
            "ob_id": 40481,
            "uuid": "2aa31428dda845c1b76ddb09eb5e1964",
            "title": "MOASA flight M281: airborne observations from the Clean Air project over Port Talbot, UK",
            "abstract": "Observations collected during flight M281 on 17 March 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Port Talbot, UK, in a high density spatial mapping flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:54:39.346121",
            "lastUpdatedDate": "2023-08-11T15:54:39",
            "latestDataUpdateTime": "2023-08-11T16:26:10",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:59:11",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3920,
                "bboxName": "",
                "eastBoundLongitude": -1.83052,
                "westBoundLongitude": -3.892079,
                "southBoundLatitude": 50.774914,
                "northBoundLatitude": 51.641956
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40482,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M281",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 50590731,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11235,
                "startTime": "2021-03-17T12:20:48",
                "endTime": "2021-03-17T14:55:00"
            },
            "resultQuality": {
                "ob_id": 4374,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40483,
                "uuid": "9e997509aa7145fd9dd80baa4f617bbe",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M281: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197192,
                197193,
                197194,
                197195,
                197196,
                197197,
                197198,
                197199,
                197200
            ],
            "onlineresource_set": [
                84101
            ]
        },
        {
            "ob_id": 40485,
            "uuid": "e09b78180d184ea8b1304115c01796ec",
            "title": "MOASA flight M282: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M282 on 19 March 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK, in a city survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:54:47.620561",
            "lastUpdatedDate": "2023-08-11T15:54:47",
            "latestDataUpdateTime": "2023-08-11T16:26:19",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:59:31",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3921,
                "bboxName": "",
                "eastBoundLongitude": 0.328636,
                "westBoundLongitude": -2.081633,
                "southBoundLatitude": 50.747086,
                "northBoundLatitude": 51.685352
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40486,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M282",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 92714698,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11236,
                "startTime": "2021-03-19T12:13:00",
                "endTime": "2021-03-19T14:18:00"
            },
            "resultQuality": {
                "ob_id": 4375,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40487,
                "uuid": "3ce9027496ce4b84a022f6e6a67319b1",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M282: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197204,
                197205,
                197206,
                197207,
                197208,
                197209,
                197210,
                197211,
                197212
            ],
            "onlineresource_set": [
                84102
            ]
        },
        {
            "ob_id": 40489,
            "uuid": "646625bc262e45d9834615c08c6839b2",
            "title": "MOASA flight M284: airborne observations from the Clean Air project over Port Talbot, UK",
            "abstract": "Observations collected during flight M284 on 24 March 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Port Talbot, UK,  in a high density spatial mapping flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:54:56.221468",
            "lastUpdatedDate": "2023-08-11T15:54:56",
            "latestDataUpdateTime": "2023-08-11T16:26:32",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:59:50",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3922,
                "bboxName": "",
                "eastBoundLongitude": -1.639886,
                "westBoundLongitude": -3.917587,
                "southBoundLatitude": 50.769745,
                "northBoundLatitude": 51.629463
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40490,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M284",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 100771447,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11237,
                "startTime": "2021-03-24T12:12:35",
                "endTime": "2021-03-24T14:55:00"
            },
            "resultQuality": {
                "ob_id": 4376,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40491,
                "uuid": "4c848bb15cd94b339a7b12ac6374e827",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M284: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197216,
                197217,
                197218,
                197219,
                197220,
                197221,
                197222,
                197223,
                197224
            ],
            "onlineresource_set": [
                84103
            ]
        },
        {
            "ob_id": 40493,
            "uuid": "f31e66e5052a4aaaad04ed29fee03b00",
            "title": "MOASA flight M286: airborne observations from the Clean Air project over the south west of the UK",
            "abstract": "Observations collected during flight M286 on 31 March 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the south west of the UK,  in a ground network survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:55:09.338598",
            "lastUpdatedDate": "2023-08-11T15:55:09",
            "latestDataUpdateTime": "2023-08-11T16:26:43",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T15:00:08",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3923,
                "bboxName": "",
                "eastBoundLongitude": -1.638563,
                "westBoundLongitude": -4.318208,
                "southBoundLatitude": 50.355751,
                "northBoundLatitude": 51.493408
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40494,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M286",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 55279736,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11238,
                "startTime": "2021-03-31T11:23:35",
                "endTime": "2021-03-31T13:59:20"
            },
            "resultQuality": {
                "ob_id": 4377,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40495,
                "uuid": "e0aadfeba90a49169e998ab7007d8bdd",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M286: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197228,
                197229,
                197230,
                197231,
                197232,
                197233,
                197234,
                197235,
                197236
            ],
            "onlineresource_set": [
                84104
            ]
        },
        {
            "ob_id": 40497,
            "uuid": "fffaf9f00b8e4ef5aefed9b717c87a27",
            "title": "MOASA flight M287: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M287 on 22 April 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK, in a city survey flight pattern, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:55:19.124341",
            "lastUpdatedDate": "2023-08-11T15:55:19",
            "latestDataUpdateTime": "2023-08-11T16:26:51",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T15:00:27",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3924,
                "bboxName": "",
                "eastBoundLongitude": 0.321972,
                "westBoundLongitude": -1.938759,
                "southBoundLatitude": 50.768471,
                "northBoundLatitude": 51.729191
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40498,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M287",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 45407408,
                "numberOfFiles": 32,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11239,
                "startTime": "2021-04-22T11:04:50",
                "endTime": "2021-04-22T13:05:20"
            },
            "resultQuality": {
                "ob_id": 4378,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40499,
                "uuid": "28e40b6712be4d0d9daed0f70b80733d",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M287: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197240,
                197241,
                197242,
                197243,
                197244,
                197245,
                197246,
                197247,
                197248
            ],
            "onlineresource_set": [
                84105
            ]
        },
        {
            "ob_id": 40501,
            "uuid": "21ce9ff5905347d282f5f099f98afb65",
            "title": "MOASA flight M288: airborne observations from the Clean Air project over the south west of the UK",
            "abstract": "Observations collected during flight M288 on 19 May 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the south west of the UK  in a ground network survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:55:30.034082",
            "lastUpdatedDate": "2023-08-11T15:55:30",
            "latestDataUpdateTime": "2023-08-11T16:27:01",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:43:53",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3925,
                "bboxName": "",
                "eastBoundLongitude": -1.649749,
                "westBoundLongitude": -4.377921,
                "southBoundLatitude": 50.357269,
                "northBoundLatitude": 51.496922
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40502,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M288",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 64713014,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11240,
                "startTime": "2021-05-19T11:01:07",
                "endTime": "2021-05-19T13:11:00"
            },
            "resultQuality": {
                "ob_id": 4379,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40503,
                "uuid": "9872279e3fe8457e86c5ee147548aa89",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M288: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197252,
                197253,
                197254,
                197255,
                197256,
                197257,
                197258,
                197259,
                197260
            ],
            "onlineresource_set": [
                84106
            ]
        },
        {
            "ob_id": 40505,
            "uuid": "1e6a48ceb8de462392114433c9e79d9f",
            "title": "MOASA flight M289: airborne observations from the Clean Air project over the south coast of the UK",
            "abstract": "Observations collected during flight M289 on 27 May 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the south coast of the UK  in a Coastal transition flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:55:38.610554",
            "lastUpdatedDate": "2023-08-11T15:55:38",
            "latestDataUpdateTime": "2023-08-11T16:27:13",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:44:09",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3926,
                "bboxName": "",
                "eastBoundLongitude": 1.931849,
                "westBoundLongitude": -1.889118,
                "southBoundLatitude": 50.633308,
                "northBoundLatitude": 51.269035
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40506,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M289",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 54310679,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11241,
                "startTime": "2021-05-27T11:05:00",
                "endTime": "2021-05-27T14:55:00"
            },
            "resultQuality": {
                "ob_id": 4380,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40507,
                "uuid": "09448708dd2344d8b034205c8fe58979",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M289: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197264,
                197265,
                197266,
                197267,
                197268,
                197269,
                197270,
                197271,
                197272
            ],
            "onlineresource_set": [
                84107
            ]
        },
        {
            "ob_id": 40509,
            "uuid": "2b7f7bd8bed54b1d9bb4c970b32453b4",
            "title": "MOASA flight M290: airborne observations from the Clean Air project over Birmingham, UK",
            "abstract": "Observations collected during flight M290 on 09 June 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Birmingham, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:55:47.452240",
            "lastUpdatedDate": "2023-08-11T15:55:47",
            "latestDataUpdateTime": "2023-08-11T16:27:21",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:44:27",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3927,
                "bboxName": "",
                "eastBoundLongitude": -1.473886,
                "westBoundLongitude": -2.299048,
                "southBoundLatitude": 50.772888,
                "northBoundLatitude": 52.746925
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40510,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M290",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 44444211,
                "numberOfFiles": 32,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11242,
                "startTime": "2021-06-09T11:17:15",
                "endTime": "2021-06-09T13:55:00"
            },
            "resultQuality": {
                "ob_id": 4381,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40511,
                "uuid": "f51bdb8672ab4ff6b9cb36e2f8c40509",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M290: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197276,
                197277,
                197278,
                197279,
                197280,
                197281,
                197282,
                197283,
                197284
            ],
            "onlineresource_set": [
                84108
            ]
        },
        {
            "ob_id": 40513,
            "uuid": "bc6e847dacac499291a47615c87c1cb2",
            "title": "MOASA flight M293: airborne observations from the Clean Air over Manchester, UK",
            "abstract": "Observations collected during flight M293 on 15 June 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Manchester, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.  Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:55:56.616062",
            "lastUpdatedDate": "2023-08-11T15:55:56",
            "latestDataUpdateTime": "2023-08-11T16:27:29",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:44:41",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3928,
                "bboxName": "",
                "eastBoundLongitude": -1.844403,
                "westBoundLongitude": -3.013451,
                "southBoundLatitude": 50.745502,
                "northBoundLatitude": 53.636303
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40514,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M293",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 57639995,
                "numberOfFiles": 32,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11243,
                "startTime": "2021-06-15T10:02:07",
                "endTime": "2021-06-15T12:30:40"
            },
            "resultQuality": {
                "ob_id": 4382,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40515,
                "uuid": "92098c4023fd441fb0ab9cb8b1bff420",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M293: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197288,
                197289,
                197290,
                197291,
                197292,
                197293,
                197294,
                197295,
                197296
            ],
            "onlineresource_set": [
                84109
            ]
        },
        {
            "ob_id": 40517,
            "uuid": "db20623d4fe44d9ea1f9a891a8513576",
            "title": "MOASA flight M294: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M294 on 16 June 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:56:06.032804",
            "lastUpdatedDate": "2023-08-11T15:56:06",
            "latestDataUpdateTime": "2023-08-11T16:27:36",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:44:55",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3929,
                "bboxName": "",
                "eastBoundLongitude": 0.366089,
                "westBoundLongitude": -1.910779,
                "southBoundLatitude": 50.770988,
                "northBoundLatitude": 51.703045
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40518,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M294",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 55549834,
                "numberOfFiles": 32,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11244,
                "startTime": "2021-06-16T10:32:12",
                "endTime": "2021-06-16T13:11:35"
            },
            "resultQuality": {
                "ob_id": 4383,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40519,
                "uuid": "a520869a8aea4009adce71df165adf76",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M294: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197300,
                197301,
                197302,
                197303,
                197304,
                197305,
                197306,
                197307,
                197308
            ],
            "onlineresource_set": [
                84110
            ]
        },
        {
            "ob_id": 40521,
            "uuid": "577d48297fc9413f86f9e530174c75d6",
            "title": "MOASA flight M316: airborne observations from the Clean Air project over Birmingham, UK",
            "abstract": "Observations collected during flight M316 on 10 February 2022 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Birmingham, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:56:18.283401",
            "lastUpdatedDate": "2023-08-11T15:56:18",
            "latestDataUpdateTime": "2023-08-11T16:27:46",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:45:07",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3930,
                "bboxName": "",
                "eastBoundLongitude": -1.552184,
                "westBoundLongitude": -2.238877,
                "southBoundLatitude": 50.774036,
                "northBoundLatitude": 52.666534
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40522,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M316",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 61482718,
                "numberOfFiles": 32,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11245,
                "startTime": "2022-02-10T11:42:28",
                "endTime": "2022-02-10T14:45:00"
            },
            "resultQuality": {
                "ob_id": 4384,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40523,
                "uuid": "b5154dbce8044e9ab7b7f4258f512bb4",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M316: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197312,
                197313,
                197314,
                197315,
                197316,
                197317,
                197318,
                197319,
                197320
            ],
            "onlineresource_set": [
                84111
            ]
        },
        {
            "ob_id": 40525,
            "uuid": "e07189e956d5478dbdec7d03e5a988c4",
            "title": "MOASA flight M322: airborne observations from the Clean Air project over the south coast of the UK",
            "abstract": "Observations collected during flight M322 on 08 March 2022 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the south coast of the UK  in a Coastal transition flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T15:56:29.153590",
            "lastUpdatedDate": "2023-08-11T15:56:29",
            "latestDataUpdateTime": "2023-08-11T16:27:53",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:45:34",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3931,
                "bboxName": "",
                "eastBoundLongitude": 1.49586,
                "westBoundLongitude": -1.909407,
                "southBoundLatitude": 50.664444,
                "northBoundLatitude": 51.273361
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40526,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M322",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 68049411,
                "numberOfFiles": 32,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11246,
                "startTime": "2022-03-08T11:08:00",
                "endTime": "2022-03-08T13:45:00"
            },
            "resultQuality": {
                "ob_id": 4385,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40527,
                "uuid": "2578f05b8640455b86166d6efc27fe64",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M322: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197324,
                197325,
                197326,
                197327,
                197328,
                197329,
                197330,
                197331,
                197332
            ],
            "onlineresource_set": [
                84112
            ]
        },
        {
            "ob_id": 40529,
            "uuid": "8abc4eefb7bd4cb4ae6b2f3a37351386",
            "title": "MOASA flight M270: airborne observations from the Clean Air project over the north east of the UK",
            "abstract": "Observations collected during flight M270 on 15 September 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over the north east of the UK in a ground network survey flight pattern, including stacked level runs north of Cambridge during warm temperatures, as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:13:59.016026",
            "lastUpdatedDate": "2023-08-11T16:13:59",
            "latestDataUpdateTime": "2023-04-14T13:56:14",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:45:49",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3932,
                "bboxName": "",
                "eastBoundLongitude": 0.485233,
                "westBoundLongitude": -1.890303,
                "southBoundLatitude": 50.777073,
                "northBoundLatitude": 52.331795
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40530,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M270",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 43850351,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11247,
                "startTime": "2020-09-15T11:10:00",
                "endTime": "2020-09-15T13:38:00"
            },
            "resultQuality": {
                "ob_id": 4386,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40531,
                "uuid": "e68dc355642542d2a78e07083785eee6",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M270: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197336,
                197337,
                197338,
                197339,
                197340,
                197341,
                197342,
                197343,
                197344
            ],
            "onlineresource_set": [
                84113
            ]
        },
        {
            "ob_id": 40533,
            "uuid": "1bc7d305e9a44bc08fde728836405f46",
            "title": "MOASA flight M278: airborne observations from the Clean Air project near Chilbolton, Hampshire, UK",
            "abstract": "Observations collected during flight M278 on 17 December 2020 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) from a flight over Chilbolton, Hampshire, UK with stacked level runs as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:14:51.293588",
            "lastUpdatedDate": "2023-08-11T16:14:51",
            "latestDataUpdateTime": "2023-04-14T13:56:33",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:46:03",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3933,
                "bboxName": "",
                "eastBoundLongitude": 0.35525,
                "westBoundLongitude": -1.898027,
                "southBoundLatitude": 50.773411,
                "northBoundLatitude": 51.708035
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40534,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M278",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 242214085,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11248,
                "startTime": "2020-12-17T11:33:00",
                "endTime": "2020-12-17T14:12:00"
            },
            "resultQuality": {
                "ob_id": 4387,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40535,
                "uuid": "aba6ca37d6a942d79b88e1bb3757efad",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M278: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197348,
                197349,
                197350,
                197351,
                197352,
                197353,
                197354,
                197355,
                197356
            ],
            "onlineresource_set": [
                84114
            ]
        },
        {
            "ob_id": 40537,
            "uuid": "a82e518d899a4b4781ac289b665c5d53",
            "title": "MOASA flight M285: airborne observations from the Clean Air project over the south coast of the UK",
            "abstract": "Observations collected during flight M285 on 30 March 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over the south coast of the UKin a Coastal transition flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:15:05.617227",
            "lastUpdatedDate": "2023-08-11T16:15:05",
            "latestDataUpdateTime": "2023-04-14T13:56:04",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:46:18",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3934,
                "bboxName": "",
                "eastBoundLongitude": 1.943674,
                "westBoundLongitude": -1.918275,
                "southBoundLatitude": 50.628853,
                "northBoundLatitude": 51.313744
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40538,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M285",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 112179611,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11249,
                "startTime": "2021-03-30T12:01:00",
                "endTime": "2021-03-30T15:05:00"
            },
            "resultQuality": {
                "ob_id": 4388,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40539,
                "uuid": "f70323cece344e48ad3bdbd6af56d939",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M285: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197360,
                197361,
                197362,
                197363,
                197364,
                197365,
                197366,
                197367,
                197368
            ],
            "onlineresource_set": [
                84115
            ]
        },
        {
            "ob_id": 40541,
            "uuid": "af06cfa8c73b415abf09dcc2eeaa664e",
            "title": "MOASA flight M291: airborne observations from the Clean Air project  over Birmingham",
            "abstract": "Observations collected during flight M291 on 10 June 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Birmingham, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:15:44.923843",
            "lastUpdatedDate": "2023-08-11T16:15:44",
            "latestDataUpdateTime": "2023-04-14T13:55:48",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:20:08",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3935,
                "bboxName": "",
                "eastBoundLongitude": -1.481767,
                "westBoundLongitude": -2.26843,
                "southBoundLatitude": 50.790844,
                "northBoundLatitude": 52.729591
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40542,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M291",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 49741012,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11250,
                "startTime": "2021-06-10T11:02:45",
                "endTime": "2021-06-10T13:41:00"
            },
            "resultQuality": {
                "ob_id": 4389,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40543,
                "uuid": "f6f55dcf8ae446e3baf69cd443d79806",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M291: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197372,
                197373,
                197374,
                197375,
                197376,
                197377,
                197378,
                197379,
                197380
            ],
            "onlineresource_set": [
                84116
            ]
        },
        {
            "ob_id": 40545,
            "uuid": "f1c9db94001048a4915420658d1b2fc5",
            "title": "MOASA flight M292: airborne observations from the Clean Air project over Manchester, UK",
            "abstract": "Observations collected during flight M292 on 14 June 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Manchester, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.  Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:15:55.418776",
            "lastUpdatedDate": "2023-08-11T16:15:55",
            "latestDataUpdateTime": "2023-04-14T13:58:11",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:21:00",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3936,
                "bboxName": "",
                "eastBoundLongitude": -1.827253,
                "westBoundLongitude": -2.680546,
                "southBoundLatitude": 50.774654,
                "northBoundLatitude": 53.617439
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40546,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M292",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 57555687,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11251,
                "startTime": "2021-06-14T13:50:00",
                "endTime": "2021-06-14T16:12:22"
            },
            "resultQuality": {
                "ob_id": 4390,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40547,
                "uuid": "c7a5e52fe3d1410f8282c5703d7d740b",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M292: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197384,
                197385,
                197386,
                197387,
                197388,
                197389,
                197390,
                197391,
                197392
            ],
            "onlineresource_set": [
                84117
            ]
        },
        {
            "ob_id": 40549,
            "uuid": "8efd6b9e25984ba9bf9c322650fce615",
            "title": "MOASA flight M295: airborne observations from the Clean Air project over Birmingham, UK",
            "abstract": "Observations collected during flight M295 on 23 June 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Birmingham, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:16:09.062170",
            "lastUpdatedDate": "2023-08-11T16:16:09",
            "latestDataUpdateTime": "2023-04-14T13:58:05",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:28:59",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3937,
                "bboxName": "",
                "eastBoundLongitude": -1.545873,
                "westBoundLongitude": -2.298122,
                "southBoundLatitude": 50.735073,
                "northBoundLatitude": 52.673141
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40550,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M295",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 57033125,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11252,
                "startTime": "2021-06-23T10:56:51",
                "endTime": "2021-06-23T14:06:40"
            },
            "resultQuality": {
                "ob_id": 4391,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40551,
                "uuid": "fee02c76cd94485e9c3d5c6ddde3eb45",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M295: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197396,
                197397,
                197398,
                197399,
                197400,
                197401,
                197402,
                197403,
                197404
            ],
            "onlineresource_set": [
                84118
            ]
        },
        {
            "ob_id": 40553,
            "uuid": "2046e062500f4e5b97fa6929fc2b8f09",
            "title": "MOASA flight M296: airborne observations from the Clean Air project over Birmingham, UK",
            "abstract": "Observations collected during flight M296 on 01 July 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Birmingham, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:16:22.379531",
            "lastUpdatedDate": "2023-08-11T16:16:22",
            "latestDataUpdateTime": "2023-04-14T13:55:42",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:28:40",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3938,
                "bboxName": "",
                "eastBoundLongitude": -1.575698,
                "westBoundLongitude": -2.282629,
                "southBoundLatitude": 50.772797,
                "northBoundLatitude": 52.670547
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40554,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M296",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 76805951,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11253,
                "startTime": "2021-07-01T10:41:06",
                "endTime": "2021-07-01T13:35:56"
            },
            "resultQuality": {
                "ob_id": 4392,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40555,
                "uuid": "4451262e9a4647c2a9a013071b8f2a26",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M296: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197408,
                197409,
                197410,
                197411,
                197412,
                197413,
                197414,
                197415,
                197416
            ],
            "onlineresource_set": [
                84119
            ]
        },
        {
            "ob_id": 40557,
            "uuid": "109702a6eed144b784bf1a480a30f470",
            "title": "MOASA flight M297: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M297 on 02 July 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:16:31.548659",
            "lastUpdatedDate": "2023-08-11T16:16:31",
            "latestDataUpdateTime": "2023-04-14T13:55:35",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:27:55",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3939,
                "bboxName": "",
                "eastBoundLongitude": 0.345067,
                "westBoundLongitude": -1.917305,
                "southBoundLatitude": 50.772469,
                "northBoundLatitude": 51.696075
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40558,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M297",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 63313527,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11254,
                "startTime": "2021-07-02T10:48:03",
                "endTime": "2021-07-02T13:27:15"
            },
            "resultQuality": {
                "ob_id": 4393,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40559,
                "uuid": "e58a2627693549f0a5f7f99e098a3b02",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M297: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197420,
                197421,
                197422,
                197423,
                197424,
                197425,
                197426,
                197427,
                197428
            ],
            "onlineresource_set": [
                84120
            ]
        },
        {
            "ob_id": 40561,
            "uuid": "b25eac4e91c64fbca635f513f1f94fb5",
            "title": "MOASA flight M298: airborne observations from the Clean Air project over Manchester, UK",
            "abstract": "Observations collected during flight M298 on 08 July 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Manchester, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.  Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:17:16.497592",
            "lastUpdatedDate": "2023-08-11T16:17:16",
            "latestDataUpdateTime": "2023-04-14T13:57:48",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:27:37",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3940,
                "bboxName": "",
                "eastBoundLongitude": -1.83086,
                "westBoundLongitude": -3.01514,
                "southBoundLatitude": 50.770073,
                "northBoundLatitude": 53.641689
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40562,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M298",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 54277820,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11255,
                "startTime": "2021-07-08T12:59:03",
                "endTime": "2021-07-08T16:06:30"
            },
            "resultQuality": {
                "ob_id": 4394,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40563,
                "uuid": "259b4be7c5564d70be29db6cdf9ddf4e",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M298: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197432,
                197433,
                197434,
                197435,
                197436,
                197437,
                197438,
                197439,
                197440
            ],
            "onlineresource_set": [
                84121
            ]
        },
        {
            "ob_id": 40565,
            "uuid": "7b4137e682724eeebe50c6fc7d505d07",
            "title": "MOASA flight M299: airborne observations from the Clean Air project over Manchester, UK",
            "abstract": "Observations collected during flight M299 on 09 July 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Manchester, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.  Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:17:25.084263",
            "lastUpdatedDate": "2023-08-11T16:17:25",
            "latestDataUpdateTime": "2023-04-14T13:57:43",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:27:21",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3941,
                "bboxName": "",
                "eastBoundLongitude": -1.993315,
                "westBoundLongitude": -3.014474,
                "southBoundLatitude": 52.566292,
                "northBoundLatitude": 53.608742
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40566,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M299",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 53522925,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11256,
                "startTime": "2021-07-09T10:16:40",
                "endTime": "2021-07-09T12:48:27"
            },
            "resultQuality": {
                "ob_id": 4395,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40567,
                "uuid": "cdf21ce1139e4f1da06e9dabc558dc2c",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M299: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197444,
                197445,
                197446,
                197447,
                197448,
                197449,
                197450,
                197451,
                197452
            ],
            "onlineresource_set": [
                84122
            ]
        },
        {
            "ob_id": 40569,
            "uuid": "f1043cddd5974c0f9fa598c8546af209",
            "title": "MOASA flight M300: airborne observations from the Clean Air project over Manchester, UK",
            "abstract": "Observations collected during flight M300 on 20 July 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Manchester, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.  Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:17:36.085134",
            "lastUpdatedDate": "2023-08-11T16:17:36",
            "latestDataUpdateTime": "2023-04-14T13:55:20",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:26:50",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3942,
                "bboxName": "",
                "eastBoundLongitude": -2.033891,
                "westBoundLongitude": -2.53194,
                "southBoundLatitude": 50.93652,
                "northBoundLatitude": 53.636173
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40570,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M300",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 41315911,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11257,
                "startTime": "2021-07-20T12:55:54",
                "endTime": "2021-07-20T15:14:46"
            },
            "resultQuality": {
                "ob_id": 4396,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40571,
                "uuid": "2aa8200961424499ad490d4ffafa2b10",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M300: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197456,
                197457,
                197458,
                197459,
                197460,
                197461,
                197462,
                197463,
                197464
            ],
            "onlineresource_set": [
                84123
            ]
        },
        {
            "ob_id": 40573,
            "uuid": "37299fcbd0c24a67afee4712a874b07d",
            "title": "MOASA flight M301: airborne observations from the Clean Air project over the south coast of the UK",
            "abstract": "Observations collected during flight M301 on 21 July 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol)  over the south coast of the UK in a south coast survey flight pattern in warm conditions as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:17:45.332786",
            "lastUpdatedDate": "2023-08-11T16:17:45",
            "latestDataUpdateTime": "2023-04-14T13:55:14",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:26:24",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3943,
                "bboxName": "",
                "eastBoundLongitude": -1.258261,
                "westBoundLongitude": -1.959985,
                "southBoundLatitude": 50.588165,
                "northBoundLatitude": 50.914295
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40574,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M301",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 34454092,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11258,
                "startTime": "2021-07-21T13:34:00",
                "endTime": "2021-07-21T15:00:00"
            },
            "resultQuality": {
                "ob_id": 4397,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40575,
                "uuid": "9c5350e941eb458f89ff7113fcb0391e",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M301: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197468,
                197469,
                197470,
                197471,
                197472,
                197473,
                197474,
                197475,
                197476
            ],
            "onlineresource_set": [
                84124
            ]
        },
        {
            "ob_id": 40577,
            "uuid": "2e5eecdde87a422aad7cb62f1d87c5b6",
            "title": "MOASA flight M302: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M302 on 22 July 2021 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:17:57.355952",
            "lastUpdatedDate": "2023-08-11T16:17:57",
            "latestDataUpdateTime": "2023-04-14T13:57:24",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:24:42",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3944,
                "bboxName": "",
                "eastBoundLongitude": 0.349333,
                "westBoundLongitude": -1.839551,
                "southBoundLatitude": 50.770535,
                "northBoundLatitude": 51.768097
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40578,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M302",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 48233731,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11259,
                "startTime": "2021-07-22T10:37:24",
                "endTime": "2021-07-22T12:40:43"
            },
            "resultQuality": {
                "ob_id": 4398,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40579,
                "uuid": "a9fcb26a9be444a496d4ce51afe7acf9",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M302: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79128,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197480,
                197481,
                197482,
                197483,
                197484,
                197485,
                197486,
                197487,
                197488
            ],
            "onlineresource_set": [
                84125
            ]
        },
        {
            "ob_id": 40581,
            "uuid": "232e37b3e3b84d348c920f04edc16bd3",
            "title": "MOASA flight M310: airborne observations from the Clean Air project over Birmingham, UK",
            "abstract": "Observations collected during flight M310 on 27 January 2022 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Birmingham, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:18:08.073565",
            "lastUpdatedDate": "2023-08-11T16:18:08",
            "latestDataUpdateTime": "2023-04-14T13:57:18",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:18:09",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3945,
                "bboxName": "",
                "eastBoundLongitude": -1.618963,
                "westBoundLongitude": -2.269309,
                "southBoundLatitude": 50.773411,
                "northBoundLatitude": 52.668938
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40582,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M310",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 43757317,
                "numberOfFiles": 31,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11260,
                "startTime": "2022-01-27T12:56:25",
                "endTime": "2022-01-27T15:56:16"
            },
            "resultQuality": {
                "ob_id": 4399,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40583,
                "uuid": "3bc3e1a710314988b1e694ef745280f4",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M310: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197492,
                197493,
                197494,
                197495,
                197496,
                197497,
                197498,
                197499,
                197500
            ],
            "onlineresource_set": [
                84126
            ]
        },
        {
            "ob_id": 40585,
            "uuid": "c88f3f2b82964acb889c8a54e8c6676a",
            "title": "MOASA flight M311: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M311 on 28 January 2022 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:18:20.410866",
            "lastUpdatedDate": "2023-08-11T16:18:20",
            "latestDataUpdateTime": "2023-04-14T13:55:07",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:14:36",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3946,
                "bboxName": "",
                "eastBoundLongitude": 0.334548,
                "westBoundLongitude": -2.111455,
                "southBoundLatitude": 50.763306,
                "northBoundLatitude": 51.757881
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40586,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M311",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 45818392,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11261,
                "startTime": "2022-01-28T11:51:54",
                "endTime": "2022-01-28T14:20:00"
            },
            "resultQuality": {
                "ob_id": 4400,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40587,
                "uuid": "15c63e481dc24651aa94fa46006b53ca",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M311: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197504,
                197505,
                197506,
                197507,
                197508,
                197509,
                197510,
                197511,
                197512
            ],
            "onlineresource_set": [
                84127
            ]
        },
        {
            "ob_id": 40589,
            "uuid": "58467eab1666415eb3a263d474788050",
            "title": "MOASA flight M312: airborne observations from the Clean Air project over Birmingham, UK",
            "abstract": "Observations collected during flight M312 on 02 February 2022 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Birmingham, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n \r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:18:31.031642",
            "lastUpdatedDate": "2023-08-11T16:18:31",
            "latestDataUpdateTime": "2023-09-13T14:52:44",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:13:37",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3947,
                "bboxName": "MOASA M312",
                "eastBoundLongitude": -1.642985,
                "westBoundLongitude": -2.254451,
                "southBoundLatitude": 50.772709,
                "northBoundLatitude": 52.669926
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40590,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M312",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 196338996,
                "numberOfFiles": 39,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11262,
                "startTime": "2022-02-02T11:58:48",
                "endTime": "2022-02-02T14:50:00"
            },
            "resultQuality": {
                "ob_id": 4401,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40591,
                "uuid": "380721f03f94426981c9e5e3a119aa2f",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M312: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197516,
                197517,
                197518,
                197519,
                197520,
                197521,
                197522,
                197523,
                197524
            ],
            "onlineresource_set": [
                84128
            ]
        },
        {
            "ob_id": 40593,
            "uuid": "69d3588403e54a3a8fb3030a05346619",
            "title": "MOASA flight M313: airborne observations from the Clean Air project over Birmingham, UK",
            "abstract": "Observations collected during flight M313 on 03 February 2022 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Birmingham, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:18:40.191639",
            "lastUpdatedDate": "2023-08-11T16:18:40",
            "latestDataUpdateTime": "2023-04-14T13:56:53",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:12:15",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3948,
                "bboxName": "",
                "eastBoundLongitude": -1.601569,
                "westBoundLongitude": -2.244919,
                "southBoundLatitude": 50.775433,
                "northBoundLatitude": 52.66552
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40594,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M313",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 93474780,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11263,
                "startTime": "2022-02-03T12:16:00",
                "endTime": "2022-02-03T15:15:00"
            },
            "resultQuality": {
                "ob_id": 4402,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40595,
                "uuid": "d9c465587ed3477491a3b91bad96a68d",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M313: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197528,
                197529,
                197530,
                197531,
                197532,
                197533,
                197534,
                197535,
                197536
            ],
            "onlineresource_set": [
                84129
            ]
        },
        {
            "ob_id": 40597,
            "uuid": "04019f530812432e9bb29edc7f2b486f",
            "title": "MOASA flight M314: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M314 on 04 February 2022 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:18:50.053340",
            "lastUpdatedDate": "2023-08-11T16:18:50",
            "latestDataUpdateTime": "2024-03-09T02:55:44",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:11:19",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3949,
                "bboxName": "",
                "eastBoundLongitude": 0.355507,
                "westBoundLongitude": -1.989108,
                "southBoundLatitude": 50.770954,
                "northBoundLatitude": 51.767944
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40598,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M314",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 47304151,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11264,
                "startTime": "2022-02-04T12:09:46",
                "endTime": "2022-02-04T14:35:35"
            },
            "resultQuality": {
                "ob_id": 4403,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40599,
                "uuid": "700621a96505459f87856d09b20789a1",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M314: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197540,
                197541,
                197542,
                197543,
                197544,
                197545,
                197546,
                197547,
                197548
            ],
            "onlineresource_set": [
                84130
            ]
        },
        {
            "ob_id": 40601,
            "uuid": "d624b92a893745c6b9394b8da5759b10",
            "title": "MOASA flight M315: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M315 on 08 February 2022 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period. Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:18:58.309060",
            "lastUpdatedDate": "2023-08-11T16:18:58",
            "latestDataUpdateTime": "2023-04-14T13:54:55",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T14:10:34",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3950,
                "bboxName": "",
                "eastBoundLongitude": 0.318968,
                "westBoundLongitude": -1.903446,
                "southBoundLatitude": 50.77079,
                "northBoundLatitude": 51.684967
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40602,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M315",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 48504093,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11265,
                "startTime": "2022-02-08T11:33:15",
                "endTime": "2022-02-08T14:20:45"
            },
            "resultQuality": {
                "ob_id": 4404,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40603,
                "uuid": "873edd600d4e4b7ba50c8b7a66d93c57",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M315: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197552,
                197553,
                197554,
                197555,
                197556,
                197557,
                197558,
                197559,
                197560
            ],
            "onlineresource_set": [
                84131
            ]
        },
        {
            "ob_id": 40605,
            "uuid": "305e7cdb1c734c419ca3e77a670d5b28",
            "title": "MOASA flight M317: airborne observations from the Clean Air project over Manchester, UK",
            "abstract": "Observations collected during flight M317 on 11 February 2022 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over Manchester, UK, in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.  Quicklook plots are also included.\r\n\r\nFull flight track and other MOASA flights can be seen via the CEDA Flight Finder tool linked to on this record.",
            "creationDate": "2023-08-11T16:19:08.298129",
            "lastUpdatedDate": "2023-08-11T16:19:08",
            "latestDataUpdateTime": "2023-04-14T13:54:45",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T13:58:58",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3951,
                "bboxName": "",
                "eastBoundLongitude": -1.840724,
                "westBoundLongitude": -2.974378,
                "southBoundLatitude": 50.771549,
                "northBoundLatitude": 53.6003
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40606,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M317",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 55000590,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11266,
                "startTime": "2022-02-11T11:07:02",
                "endTime": "2022-02-11T13:58:53"
            },
            "resultQuality": {
                "ob_id": 4405,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40607,
                "uuid": "afda00ff75f2430ea8e5d7ab653f55c1",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M317: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197564,
                197565,
                197566,
                197567,
                197568,
                197569,
                197570,
                197571,
                197572
            ],
            "onlineresource_set": [
                84132
            ]
        },
        {
            "ob_id": 40609,
            "uuid": "6db598f645284d369716952625271fe1",
            "title": "MOASA flight M319: airborne observations from the Clean Air project over London, UK",
            "abstract": "Observations collected during flight M319 on 25 February 2022 by the Clean Air instrument suite on board the Met Office Atmospheric Survey Aircraft (MOASA) for the MOASA Clean Air project. \r\n\r\nThis dataset contains in meteorological and situ atmospheric composition measurements  (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) over London, UK in a city survey flight pattern as part of the Strategic Priorities Fund (SPF) Clean Air Programme Intense Observational Period.",
            "creationDate": "2023-08-11T16:19:21.877856",
            "lastUpdatedDate": "2023-08-11T16:19:21",
            "latestDataUpdateTime": "2023-04-14T13:54:38",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected and processed by the project team at the Met Office and submitted to the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "MOASA, aircraft, meteorology, Clean Air, Met Office,  nitrogen dioxide, NO2, ozone, O3, sulphur dioxide, SO2, PM2.5, aerosol",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-19T13:56:38",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3952,
                "bboxName": "",
                "eastBoundLongitude": 0.374918,
                "westBoundLongitude": -1.896553,
                "southBoundLatitude": 50.763725,
                "northBoundLatitude": 51.770336
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40610,
                "dataPath": "/badc/deposited2023/moasa_clean_air_data/M319",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 49589106,
                "numberOfFiles": 38,
                "fileFormat": "NetCDF format"
            },
            "timePeriod": {
                "ob_id": 11267,
                "startTime": "2022-02-25T11:45:00",
                "endTime": "2022-02-25T14:10:00"
            },
            "resultQuality": {
                "ob_id": 4406,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40611,
                "uuid": "2b8953a066d74c34a995573c52b89f38",
                "short_code": "acq",
                "title": "Acquisition for: MOASA flight M319: airborne observations from the Clean Air project",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 39906,
                    "uuid": "e1d0be90d6794a398c190d1bd14dd8cf",
                    "short_code": "proj",
                    "title": "MOASA Clean Air Project",
                    "abstract": "The Met Office Atmospheric Survey Aircraft (MOASA) Clean Air project collected air pollution data over the UK between August 2019 to April 2022.  During this time 60 flights were made (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties including  two intensive data collection periods, one in summer and one in winter, flying upwind and downwind of the the Natural Environment Research Council (NERC) ‘supersites’ in London, Manchester and Birmingham and circling over them at various altitudes.\r\n\r\nThe aircraft was equipped with with air monitoring instrumentation to observe the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol).\r\n\r\nThis project was part of the Strategic Priorities Fund (SPF) Clean Air Programme, delivered by UKRI."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                63234,
                63235,
                63236,
                63237,
                63238,
                63239,
                63240,
                63241,
                63242,
                63243,
                63244,
                63245,
                63246,
                63247,
                63248,
                63249,
                63250,
                63251,
                63252,
                63253,
                63254,
                63255,
                63256,
                63257,
                63258,
                63259,
                63260,
                63261,
                63262,
                63263,
                63264,
                63265,
                63267,
                63268,
                63269,
                63270,
                63271,
                63272,
                63273,
                63274,
                63275,
                63276,
                63277,
                63278,
                63279,
                63280,
                63281,
                63282,
                63283,
                63284,
                63285,
                63286,
                63287,
                63288,
                63289,
                63290,
                63292,
                63293,
                63294,
                63295,
                63296,
                63297,
                63298,
                63299,
                63300,
                63301,
                63302,
                63303,
                63304,
                63305,
                63306,
                63307,
                63308,
                63309,
                63310,
                63311,
                63312,
                63313,
                63314,
                63315,
                63316,
                63317,
                63318,
                63319,
                63320,
                63321,
                63322,
                63323,
                63324,
                63325,
                63326,
                63327,
                63328,
                63329,
                63330,
                63331,
                63332,
                63333,
                63334,
                63335,
                63336,
                63337,
                63338,
                63339,
                63340,
                63341,
                63342,
                63343,
                63344,
                63345,
                63346,
                63347,
                63348,
                63349,
                63350,
                63351,
                63352,
                63353,
                63354,
                63355,
                63356,
                63357,
                63358,
                79123,
                79124,
                79125,
                79126,
                79127,
                79129,
                83975
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 39574,
                    "uuid": "0aa1ec0cf18e4065bdae8ae39260fe7d",
                    "short_code": "coll",
                    "title": "MOASA Clean Air Project: airborne atmospheric measurements collection",
                    "abstract": "A long-term quality assured dataset of the three-dimensional distribution of pollutants (gaseous nitrogen dioxide, ozone, sulphur dioxide and fine mode (PM2.5) aerosol) collected over southern UK, from August 2019 to April 2022, using the instrumented Met Office Atmospheric Survey Aircraft (MOASA). It includes 60 flights (totalling over 153 hours of atmospheric sampling), across 8 repeatable sorties made for the MOASA Clean Air project.\r\n\r\nData are presented as one NetCDF file per flight, containing quality assured, time synchronised, three-dimensionally geo-located time-series of observed pollutants. \r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included for each flight, detailing any calibration constants and/or corrections applied to data alongside general information about the data and instruments. \r\n\r\nA full list of NetCDF variables can be found in “Long-term airborne measurements of pollutants over the United Kingdom to support air quality model development and evaluation”, A. Mynard et al, 2023. This paper also provides a technical introduction to the MOASA measurement platform, information on instrumentation, flight strategies and data, as well as example case studies comparing flight observations to the Met Office Air Quality in the Unified Model (AQUM) and the ground based Automated Urban and Rural Network. This paper should be referenced in any research/publications pertaining from this dataset."
                }
            ],
            "responsiblepartyinfo_set": [
                197576,
                197577,
                197578,
                197579,
                197580,
                197581,
                197582,
                197583,
                197584
            ],
            "onlineresource_set": [
                84133
            ]
        },
        {
            "ob_id": 40613,
            "uuid": "61853c0567fd4d6dbab41c0505041524",
            "title": "Daily cloud cover data: from China Meteorological Administration",
            "abstract": "These data were obtained from 2072 gauge stations across China from the China Meteorological Administration, covered the period from 1961 to 2013.",
            "creationDate": "2023-08-14T15:43:56.935115",
            "lastUpdatedDate": "2023-08-14T15:46:36.774238",
            "latestDataUpdateTime": "2023-08-14T15:43:56.935126",
            "updateFrequency": "notPlanned",
            "dataLineage": "These data were obtained from the China Meteorological Administration.",
            "removedDataReason": "",
            "keywords": "cloud cover",
            "publicationState": "preview",
            "nonGeographicFlag": true,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "pending",
            "dataPublishedTime": null,
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": null,
            "verticalExtent": null,
            "result_field": null,
            "timePeriod": {
                "ob_id": 11270,
                "startTime": "1961-01-01T00:00:00",
                "endTime": "2013-12-31T00:00:00"
            },
            "resultQuality": {
                "ob_id": 4407,
                "explanation": "",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-14"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [],
            "projects": [],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                197588,
                197589,
                197590,
                197591,
                197592,
                197593,
                197594
            ],
            "onlineresource_set": []
        },
        {
            "ob_id": 40615,
            "uuid": "c65f6acdf85d467bbac5d1e1a3a58cda",
            "title": "CDs_data",
            "abstract": "The dataset contains monthly Cloud Days, from 2072 gauge stations across China from the China Meteorological Administration.",
            "creationDate": "2023-08-15T05:21:03.103902",
            "lastUpdatedDate": "2023-08-15T05:21:03.103908",
            "latestDataUpdateTime": "2023-08-15T05:21:03.103912",
            "updateFrequency": "notPlanned",
            "dataLineage": "The dataset contains monthly Cloud Days from the China Meteorological Administration.",
            "removedDataReason": "",
            "keywords": "CloudDays",
            "publicationState": "working",
            "nonGeographicFlag": true,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "pending",
            "dataPublishedTime": null,
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": null,
            "verticalExtent": null,
            "result_field": null,
            "timePeriod": {
                "ob_id": 11272,
                "startTime": "1961-01-01T00:00:00",
                "endTime": "2013-12-31T00:00:00"
            },
            "resultQuality": {
                "ob_id": 4409,
                "explanation": "",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-08-15"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [],
            "projects": [],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                197602,
                197603,
                197604,
                197605,
                197606,
                197607,
                197608
            ],
            "onlineresource_set": []
        },
        {
            "ob_id": 40618,
            "uuid": "755bc61b5524498db67f9468a92d8cfc",
            "title": "HadISDH.marine: gridded global monthly ocean surface humidity data version 1.4.1.2022f",
            "abstract": "This is the HadISDH.marine 1.4.1.2022f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.marine is a near-global gridded monthly mean marine surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships. The observations have been quality controlled and bias-adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2022.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the previous version to the end of 2022. Users are advised to read the update document in the Docs section for full details on all changes from the previous release.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of\r\nthe HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,\r\n12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,\r\nBerry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,\r\nRayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to\r\nthe historical marine climate record. International Journal of Climatology.\r\ndoi:10.1002/joc.4775.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57",
            "latestDataUpdateTime": "2023-08-17T17:42:48",
            "updateFrequency": "notPlanned",
            "dataLineage": "HadISDH.marine is a global ocean surface (~10 m) humidity dataset and is produced by the Met Office Hadley Centre in collaboration with NOC. It is based on the sub-daily ship observations from ICOADS. It is passed to CEDA for archiving and distribution.",
            "removedDataReason": "",
            "keywords": "HadISDH, humidity, surface, marine, gridded, station, specific humidity, temperature, dew point temperature, wet bulb temperature, dew point temperature, vapour pressure, in-situ",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "superseded",
            "dataPublishedTime": "2024-06-06T11:21:00",
            "doiPublishedTime": "2024-06-06T16:14:39.638236",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 1,
                "bboxName": "",
                "eastBoundLongitude": 180.0,
                "westBoundLongitude": -180.0,
                "southBoundLatitude": -90.0,
                "northBoundLatitude": 90.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40620,
                "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISDH-marine/mon/HadISDHTable/r1/v1-4-1-2022f/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 247233146,
                "numberOfFiles": 8,
                "fileFormat": "Data are NetCDF formatted"
            },
            "timePeriod": {
                "ob_id": 11273,
                "startTime": "1973-01-01T00:00:00",
                "endTime": "2022-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 3043,
                "explanation": "Uncertainty estimates are provided as part of the dataset both at the station and gridbox level, this includes information covering station uncertainty (climatological, homogenisation and measurement uncertainty), gridbox spatial and temporal sampling uncertainty and combined station and sampling uncertainty. See dataset associated documentation for full details.",
                "passesTest": true,
                "resultTitle": "HadISDH Data Quality Statement",
                "date": "2016-06-14"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": {
                "ob_id": 30534,
                "uuid": "07fae730332a41e1acc37d917574fb63",
                "short_code": "comp",
                "title": "HadISDH.marine: gridded global ocean surface (~10 m) humidity dataset produced by the Met Office Hadley Centre",
                "abstract": "HadISDH utilises simultaneous sub-daily temperature and dew point temperature data from the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) ship data. All humidity variables are calculated at hourly resolution. Quality control, buddy checking and bias adjustment is applied at hourly resolution to adjust all observations to an observing height of 10 m, accounting for changing ship heights over time, and to adjust all non-ventilated instruments to mitigate the moist bias. Gridded monthly means, monthly mean anomalies and 1981 to 2010 climatologies are created. \r\n\r\nSee Docs 'HadISDH.marine process diagram'. Observation measurement, climatological, whole number presence and bias adjustment uncertainties are estimated for each observation and then gridded. 5° by 5° gridboxes are centred on -177.5°W and -87.5°S to 177.5°E and 87.5°N. Given the uneven distribution of observations over time and space, sampling uncertainty is estimated for each gridbox month. \r\n\r\nFor greater detail please see: \r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I.: Development of the HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data, doi:10.5194/essd-12-2853-2020, 2020. \r\n\r\nDocs contains links to this publication."
            },
            "procedureCompositeProcess": null,
            "imageDetails": [
                157
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2526,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 13164,
                    "uuid": "ce252c81a7bd4717834055e31716b265",
                    "short_code": "proj",
                    "title": "Met Office Hadley Centre - Observations and Climate",
                    "abstract": "The Met Office Hadley Centre is one of the UK's foremost climate change research centres.\r\n\r\nThe Hadley Centre produces world-class guidance on the science of climate change and provide a focus in the UK for the scientific issues associated with climate science.\r\n\r\nLargely co-funded by Department of Energy and Climate Change (DECC) and Defra (the Department for Environment, Food and Rural Affairs), the centre provides in-depth information to, and advise, the Government on climate science issues.\r\n\r\nAs one of the world's leading centres for climate science research, the Hadley Centre scientists make significant contributions to peer-reviewed literature and to a variety of climate science reports, including the Assessment Report of the IPCC. The Hadley Centre climate projections were the basis for the Stern Review on the Economics of Climate Change."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                56887,
                56888,
                56889,
                56891,
                56892,
                56894,
                56895,
                60438,
                67680,
                70709,
                70710,
                70711,
                70712,
                70713,
                70714,
                70715,
                70716,
                70717,
                70718,
                70720,
                70721,
                70722,
                70724,
                70726,
                70729,
                70730,
                70731,
                70732,
                70733,
                70734,
                70735,
                70736,
                70737,
                70738,
                70739,
                70740,
                70741,
                70742,
                70743,
                70744,
                70745,
                70746,
                70747,
                70748,
                70749,
                70752,
                70754,
                73571,
                73572,
                73573,
                73600,
                73601,
                73602,
                73603,
                73604,
                73605,
                73606,
                73607,
                73608,
                73609,
                73610,
                73611,
                73612,
                73613
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12920
            ],
            "observationcollection_set": [
                {
                    "ob_id": 13522,
                    "uuid": "251474c7b09449d8b9e7aeaf1461858f",
                    "short_code": "coll",
                    "title": "HadISDH: global surface humidity data",
                    "abstract": "HadISDH (Integrated Surface Database Humidity) is a monthly 5° by 5° gridded global surface humidity climate monitoring dataset created from in-situ sub-daily synoptic data. The data have been quality controlled and homogenised (land), bias adjusted (marine) and buddy checked (marine). \r\n\r\nMonthly mean climate anomalies are provided alongside uncertainty estimates, actual values, climatological means and standard deviations for specific humidity, relative humidity, vapour pressure, dew point temperature, wet bulb temperature, dew point depression in addition to the simultaneously observed temperature."
                }
            ],
            "responsiblepartyinfo_set": [
                197614,
                197615,
                197616,
                197617,
                197618,
                197619,
                197620,
                197621,
                197622,
                197625,
                197623,
                197624,
                197626,
                197627
            ],
            "onlineresource_set": [
                84142,
                84143,
                84144,
                84145,
                84140,
                84141,
                84146,
                84154
            ]
        },
        {
            "ob_id": 40619,
            "uuid": "dc11996a68c446abb342e917efdaac30",
            "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Climatology Climate Data Record, version 2.2",
            "abstract": "This v2.2 SST_cci Climatology Data Record (CDR) consists of daily climatological mean sea surface temperature on a global 0.05 degree latitude-longitude grid, derived from the SST CCI analysis data for the period 1982 to 2010 (29 years). This climatology includes the post-hoc dust corrections from Merchant and Embury (2020) https://doi.org/10.3390/rs12162554.\r\n\r\nThe changes from climatology v2.1 are:\r\n* Inclusion of post-hoc dust corrections from Merchant and Embury (2020) reduces biases in affected regions (tropical Atlantic Ocean and the Mediterranean, Red, and Arabian Seas).\r\n* Improved compliance with CF Conventions.\r\n\r\nData are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ . \r\n\r\nWhen citing this dataset please also cite the associated data paper: Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. (2019) Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223. http://doi.org/10.1038/s41597-019-0236-x",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57",
            "latestDataUpdateTime": "2023-09-06T14:44:45",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were processed by the ESA CCI SST project team and supplied to the Centre for Environmental Data Analysis (CEDA) for archiving in the context of the ESA Climate Data Centre and the National Centre for Earth Observation (NCEO).",
            "removedDataReason": "",
            "keywords": "SST, ESA Climate Change Initiative, CCI",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": true,
            "language": "English",
            "resolution": "0.05 degrees",
            "status": "completed",
            "dataPublishedTime": "2023-10-05T12:54:52",
            "doiPublishedTime": "2023-10-05T12:54:29.179139",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 529,
                "bboxName": "Global (-180 to 180)",
                "eastBoundLongitude": 180.0,
                "westBoundLongitude": -180.0,
                "southBoundLatitude": -90.0,
                "northBoundLatitude": 90.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40689,
                "dataPath": "/neodc/esacci/sst/data/CDR_v2/Climatology/L4/v2.2/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 3449840495,
                "numberOfFiles": 366,
                "fileFormat": "Data are in NetCDF format"
            },
            "timePeriod": {
                "ob_id": 7406,
                "startTime": "1982-01-01T00:00:00",
                "endTime": "2010-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 3276,
                "explanation": "As provided by the CCI SST team",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2019-04-01"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": {
                "ob_id": 11010,
                "uuid": "2d125dda9d6e44ed804191a3b7b41bc5",
                "short_code": "comp",
                "title": "CCI SST Processor",
                "abstract": "This computation involved: CCI SST Processor.  This processor was developed in the ESA Climate Change Initiative, Sea Surface Temperature Project"
            },
            "procedureCompositeProcess": null,
            "imageDetails": [
                137
            ],
            "discoveryKeywords": [
                {
                    "ob_id": 1140,
                    "name": "ESACCI"
                }
            ],
            "permissions": [
                {
                    "ob_id": 2523,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 4,
                        "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_sst_terms_and_conditions_v2.pdf",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 11008,
                    "uuid": "05fb7c9964b4172991a72082c46a3376",
                    "short_code": "proj",
                    "title": "Sea Surface Temperature Climate Change Initiative Project",
                    "abstract": "The Sea Surface Temperature Climate Change Initiative (SST_cci) project is part of the European Space Agency's Climate Change Initiative programme,  It aims to accurately mapping the surface temperature of the global oceans  using observations from many satellites, and to independently quantify SST to a quality suitable for climate research.\r\n\r\nThe team brings together European expertise in creating climate quality records of ocean temperatures from satellite data, with expertise in climate applications and computer engineering. Through the ESA funded Climate Change Initiative, the team have created a climate record of global sea surface temperature (SST) for the period 1981 to 2016. Based on satellite data, this record is independent of thermometer based measurements from ships and buoys. The new climate SST record complements and challenges existing knowledge of how ocean temperatures have evolved. \r\n\r\nThe project started in August 2010. It is part of a wider initiative by the European Space Agency (ESA) addressing several essential climate variables in addition to SST."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50415,
                50417,
                60312,
                60313,
                66256,
                66257,
                66259,
                66260,
                75579
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12715
            ],
            "observationcollection_set": [
                {
                    "ob_id": 11005,
                    "uuid": "1dc189bbf94209b48ed446c0e9a078af",
                    "short_code": "coll",
                    "title": "Collection of Sea Surface Temperature (SST) Data of the Global Oceans as part of the ESA Climate Change Initiative (CCI)",
                    "abstract": "The ESA Sea Surface Temperature Climate Change Initiative (ESA SST_cci) datasets accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nThe latest version (v2.1) of the data are described in the data paper:  Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x\r\n\r\nData are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ . To comply with the attribution aspect, please cite the above reference and the dataset citation given on the relevant dataset page."
                },
                {
                    "ob_id": 30128,
                    "uuid": "7fe9f59731ab47b6a20e792e0cba4641",
                    "short_code": "coll",
                    "title": "National Centre for Earth Observation (NCEO) partnered datasets",
                    "abstract": "The National Centre for Earth Observation (NCEO) has a proud tradition of being involved with some of the most successful international collaborations in the Earth observation. This Collection contains dataset generated and/or archived with the support of NCEO resource or scientific expertise. Some notable collaboration which generated data within this collection are as follows:\r\n\r\nThe European Space Agency (ESA)'s Climate Change Initiative (CCI) program. The program goal is to provide stable, long-term, satellite-based Essential Climate Variable (ECV) data products for climate modelers and researchers.\r\n\r\nThe EUSTACE (EU Surface Temperature for All Corners of Earth) project is produced publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques.\r\n\r\nFIDUCEO has created new climate datasets from Earth Observations with a rigorous treatment of uncertainty informed by the discipline of metrology. This response to the need for enhanced credibility for climate data, to support rigorous science, decision-making and climate services. The project approach was to develop methodologies for generating Fundamental Climate Data Records (FCDRs) and Climate Data Records (CDRs) that are widely applicable and metrologically rigorous. \r\n\r\nThe “BACI” project translates satellite data streams into novel “essential biodiversity variables” by integrating ground-based observations. The trans-disciplinary project offers new insights into the functioning and state of ecosystems and biodiversity. BACI enables the user community to detect abrupt and transient changes of ecosystems and quantify the implications for regional biodiversity.\r\n\r\nThe UK Natural Environment Research Council has established a knowledge transfer network called NCAVEO (Network for Calibration and Validation of EO data - NCAVEO) which has as its aim the promotion and support of methodologies based upon quantitative, traceable measurements in Earth observation. \r\n\r\nThe Geostationary Earth Radiation Budget 1 & 2 instruments (GERB-1 and GERB-2) make accurate measurements of the Earth Radiation Budget. They are specifically designed to be mounted on a geostationary satellite and are carried onboard the Meteosat Second Generation satellites operated by EUMETSAT. They were produced by a European consortium led by the UK (NERC) together with Belgium, Italy, and EUMETSAT, with funding from national agencies.\r\n\r\nGloboLakes analysed 20 years of data from more than 1000 large lakes across the globe to determine 'what controls the differential sensitivity of lakes to environmental perturbation'. This was an ambitious project that was only possible by bringing together a consortium of scientists with complementary skills. These include expertise in remote sensing of freshwaters and processing large volumes of satellite images, collation and analysis of large-scale environmental data, environmental statistics and the assessment of data uncertainty, freshwater ecology and mechanisms of environmental change and the ability to produce lake models to forecast future lake conditions.\r\n\r\nThis SPEI collaboration consists of high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset over the whole of Africa at different time scales from 1 month to 48 months. It is calculated based on precipitation estimates from the satellite-based Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and potential evaporation estimates by the Global Land Evaporation Amsterdam Model (GLEAM)."
                }
            ],
            "responsiblepartyinfo_set": [
                197636,
                197630,
                197628,
                197635,
                197634,
                197633,
                197632,
                197631,
                197629,
                197948
            ],
            "onlineresource_set": [
                84150,
                84153,
                84151,
                84148,
                84152,
                84149,
                84320,
                84966
            ]
        },
        {
            "ob_id": 40621,
            "uuid": "c3c1526fba8f4a5382d2f9fb86966d82",
            "title": "HadISDH.blend: gridded global monthly land and ocean surface humidity data version 1.4.1.2022f",
            "abstract": "This is the HadISDH.blend 1.4.1.2022f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.blend is a near-global gridded monthly mean surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships and weather stations. The observations have been quality controlled and homogenised / bias adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2022.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the previous version to the end of 2022. It combines the latest version of HadISDH.land and HadISDH.marine. and therefore their respective update notes. Users are advised to read the update documents in the Docs section for full details.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of\r\nthe HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,\r\n12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,\r\nBerry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,\r\nRayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to\r\nthe historical marine climate record. International Journal of Climatology.\r\ndoi:10.1002/joc.4775.\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E.,\r\nJones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and\r\ntemperature record for climate monitoring, Clim. Past, 10, 1983-2006,\r\ndoi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more\r\ndetail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de\r\nPodesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface\r\nspecific humidity product for climate monitoring. Climate of the Past, 9, 657-677,\r\ndoi:10.5194/cp-9-657-2013.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57",
            "latestDataUpdateTime": "2023-08-17T17:43:02",
            "updateFrequency": "notPlanned",
            "dataLineage": "HadISDH.blend is a global land (~2 m) and ocean (~10 m) surface humidity dataset and is produced by the Met Office Hadley Centre in collaboration with CRU, Maynooth University, NPL, NOAA-NCEI and NOC. It is based on the sub-daily station observations from HadISD (originally from ISD) and ship observations from ICOADS. It is passed to the Centre for Environmental Data Analysis (CEDA) for archiving and distribution. Gridboxes containing both land and marine data are combined using a weighted average with a minimum and maximum weighting of 25% and 75% respectively.",
            "removedDataReason": "",
            "keywords": "HadISDH, blend, humidity, surface, marine, gridded, station, specific humidity, temperature, dew point temperature, wet bulb temperature, dew point temperature, vapour pressure, in-situ",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "superseded",
            "dataPublishedTime": "2024-06-06T11:17:19",
            "doiPublishedTime": "2024-06-06T16:14:13",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 1,
                "bboxName": "",
                "eastBoundLongitude": 180.0,
                "westBoundLongitude": -180.0,
                "southBoundLatitude": -90.0,
                "northBoundLatitude": 90.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40622,
                "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISDH-blend/mon/HadISDHTable/r1/v1-4-1-2022f/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 173874765,
                "numberOfFiles": 8,
                "fileFormat": "Data are NetCDF formatted"
            },
            "timePeriod": {
                "ob_id": 11274,
                "startTime": "1973-01-01T00:00:00",
                "endTime": "2022-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 3043,
                "explanation": "Uncertainty estimates are provided as part of the dataset both at the station and gridbox level, this includes information covering station uncertainty (climatological, homogenisation and measurement uncertainty), gridbox spatial and temporal sampling uncertainty and combined station and sampling uncertainty. See dataset associated documentation for full details.",
                "passesTest": true,
                "resultTitle": "HadISDH Data Quality Statement",
                "date": "2016-06-14"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": {
                "ob_id": 30535,
                "uuid": "93fe7fab0099452aa79778ee34bd8619",
                "short_code": "comp",
                "title": "HadISDH.blend: gridded global land (~2 m) and ocean (~10 m) surface humidity dataset produced by the Met Office Hadley Centre",
                "abstract": "HadISDH.blend combines HadISDH.marine and HadISDH.land at the 5 degree by 5 degree gridbox monthly mean level. Gridboxes containing both land and marine data are combined using a weighted average with a minimum and maximum weighting of 25% and 75% respectively. HadISDH.marine utilises simultaneous sub-daily temperature and dew point temperature data from the International Comprehensive Ocean-Atmosphere Data Set (ICOADS) ship data. All humidity variables are calculated at hourly resolution. \r\n\r\nQuality control, buddy checking and bias adjustment is applied at hourly resolution to adjust all observations to an observing height of 10 m, accounting for changing ship heights over time, and to adjust all non-ventilated instruments to mitigate the moist bias. Gridded monthly means, monthly mean anomalies and 1981 to 2010 climatologies are created. \r\n\r\nSee Docs 'HadISDH.marine process diagram'. Observation measurement, climatological, whole number presence and bias adjustment uncertainties are estimated for each observation and then gridded. 5° by 5° gridboxes are centred on -177.5°W and -87.5°S to 177.5°E and 87.5°N. Given the uneven distribution of observations over time and space, sampling uncertainty is estimated for each gridbox month. \r\n\r\nFor greater detail please see: Willett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I.: Development of the HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data, doi:10.5194/essd-12-2853-2020, 2020. \r\n\r\nDocs contains links to this publication. \r\n\r\nHadISDH.land utilises simultaneous subdaily temperature and dew point temperature data from over 3000 quality controlled HadISD stations that have sufficiently long records. All humidity variables are calculated at hourly resolution and monthly means are created. Monthly means are homogenised to detect and adjust for features within the data that do not appear to be of climate origin. While unlikely to be perfect, this process does help remove large errors from the data an improve robustness of long-term climate monitoring. The NCEI's Pairwise Homogenisation Algorithm has been used directly on DPD and T. An indirect PHA method (ID PHA) is used whereby changepoints detected in DPD and T are used to make adjustments to q, e, Tw and RH. Changepoints from DPD are also applied to T. Td is derived from homogenised T and DPD. \r\n\r\nSee Docs 'HadISDH.land process diagram'. Station measurement, climatological and homogeneity adjustment uncertainties are estimated for each month. Climatological averages are calculated over 1981-2010 and monthly mean climate anomalies obtained. These anomalies (in addition to climatological mean and standard deviation, actual values and uncertainty components) are then averaged over 5° by 5° gridboxes centred on -177.5°W and -87.5°S to 177.5°E and 87.5°N. Given the uneven distribution of stations over time and space, sampling uncertainty is estimated for each gridbox month. \r\n\r\nFor greater detail please see: Willett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014. \r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013. \r\n\r\nDocs contains links to both these publications."
            },
            "procedureCompositeProcess": null,
            "imageDetails": [
                157
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2526,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 13164,
                    "uuid": "ce252c81a7bd4717834055e31716b265",
                    "short_code": "proj",
                    "title": "Met Office Hadley Centre - Observations and Climate",
                    "abstract": "The Met Office Hadley Centre is one of the UK's foremost climate change research centres.\r\n\r\nThe Hadley Centre produces world-class guidance on the science of climate change and provide a focus in the UK for the scientific issues associated with climate science.\r\n\r\nLargely co-funded by Department of Energy and Climate Change (DECC) and Defra (the Department for Environment, Food and Rural Affairs), the centre provides in-depth information to, and advise, the Government on climate science issues.\r\n\r\nAs one of the world's leading centres for climate science research, the Hadley Centre scientists make significant contributions to peer-reviewed literature and to a variety of climate science reports, including the Assessment Report of the IPCC. The Hadley Centre climate projections were the basis for the Stern Review on the Economics of Climate Change."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                56887,
                56888,
                56889,
                56891,
                56892,
                56894,
                56895,
                60438,
                67665,
                67666,
                67667,
                67668,
                67669,
                67670,
                67671,
                67672,
                67673,
                67674,
                67680,
                67681,
                67682,
                67683,
                67684,
                67685,
                67686,
                67687,
                67688,
                67689,
                67690,
                67691,
                67692,
                67693,
                67694,
                67695,
                67696,
                67697,
                67698,
                67699,
                67700,
                67701,
                67702,
                67703,
                67704,
                67705,
                67706,
                67707,
                67708,
                67709,
                67710,
                70752,
                70754,
                70756,
                70757,
                70758,
                70759,
                70760,
                73571,
                73572,
                73573
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12919
            ],
            "observationcollection_set": [
                {
                    "ob_id": 13522,
                    "uuid": "251474c7b09449d8b9e7aeaf1461858f",
                    "short_code": "coll",
                    "title": "HadISDH: global surface humidity data",
                    "abstract": "HadISDH (Integrated Surface Database Humidity) is a monthly 5° by 5° gridded global surface humidity climate monitoring dataset created from in-situ sub-daily synoptic data. The data have been quality controlled and homogenised (land), bias adjusted (marine) and buddy checked (marine). \r\n\r\nMonthly mean climate anomalies are provided alongside uncertainty estimates, actual values, climatological means and standard deviations for specific humidity, relative humidity, vapour pressure, dew point temperature, wet bulb temperature, dew point depression in addition to the simultaneously observed temperature."
                }
            ],
            "responsiblepartyinfo_set": [
                197641,
                197637,
                197644,
                197638,
                197639,
                197640,
                197642,
                197645,
                197643,
                197647,
                197646,
                197648,
                197649,
                197650,
                197651,
                197652,
                197653,
                197654,
                197655
            ],
            "onlineresource_set": [
                84161,
                84165,
                84157,
                84162,
                84158,
                84160,
                84159,
                84163,
                84167,
                84164,
                84166,
                84155,
                84156
            ]
        },
        {
            "ob_id": 40624,
            "uuid": "33138664259340c09737eba915d9cfbf",
            "title": "Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): nudged-full data produced by the SPEAR model at NOAA-GFDL",
            "abstract": "This dataset contains model data for SNAPSI experiment 'free' produced by scientists at NOAA-GFDL (National Oceanic and Atmospheric Administration- Geophysical Fluid Dynamics Laboratory) in Princeton, USA. This dataset contains all ensemble members  by the GFDL SPEAR model.\r\n\r\nThe SNAPSI project is a model intercomparison project to study the role of the stratosphere in subseasonal forecasts following stratospheric sudden warmings and the representation of stratosphere-troposphere coupling in subseasonal forecast models.\r\n\r\nThe nudged-full experiment is a set of retrospective, 45-day, 50-member ensemble forecasts. Following the initial date, stratospheric temperatures and horizontal winds are nudged towards the observed time-evolving state. The forecasts are initialized on the date indicated by the sub-experiment id; for instance, the sub-experiment 's20180125' is initialized on 25 January 2018. The ocean, sea-ice, land-surface and ozone are all initialized and run prognostically.\r\n\r\n------------------------------------------\r\nSources of additional information\r\n------------------------------------------\r\nThe following web links are provided in the Details/Docs section of this catalogue record:\r\n- Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): A Protocol for Investigating the Role of the Stratospheric Polar Vortex in Subseasonal to Seasonal Forecasts\r\n- New set of controlled numerical experiments: Stratospheric Nudging And Predictable Surface Impacts (SNAPSI)\r\n- GFDL SPEAR reference publication: Delworth et al. (2020)",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2023-02-07T16:04:12",
            "latestDataUpdateTime": "2023-09-08T19:36:33",
            "updateFrequency": "",
            "dataLineage": "The data is based on pressure-level output from the SPEAR model provided by Baoqiang Xiang. It has been lightly processed to conform to the SNAPSI data request. The data has been published by the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "nudged-full, SPEAR, NOAA-GFDL, stratosphere, arctic, antarctic, stratospheric polar vortex, SNAPSI, SNAP, APARC",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": true,
            "language": "English",
            "resolution": "50 km",
            "status": "ongoing",
            "dataPublishedTime": "2024-09-30T16:11:27",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 1,
                "bboxName": "",
                "eastBoundLongitude": 180.0,
                "westBoundLongitude": -180.0,
                "southBoundLatitude": -90.0,
                "northBoundLatitude": 90.0
            },
            "verticalExtent": {
                "ob_id": 249,
                "highestLevelBound": 40.0,
                "lowestLevelBound": 100000.0,
                "units": "Pa"
            },
            "result_field": {
                "ob_id": 40625,
                "dataPath": "/badc/snap/data/post-cmip6/SNAPSI/NOAA-GFDL/SPEAR/nudged-full",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 835752988792,
                "numberOfFiles": 5401,
                "fileFormat": "Files are Net-CDF formatted"
            },
            "timePeriod": {
                "ob_id": 11209,
                "startTime": "2018-02-08T00:00:00",
                "endTime": "2019-11-15T00:00:00"
            },
            "resultQuality": {
                "ob_id": 3916,
                "explanation": "Quality control checks performed at CEDA confirmed that the data meets the SNAPSI metadata requirements.",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2022-03-29"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": {
                "ob_id": 40378,
                "uuid": "96543a9250f54e409edeb6225cd28a6d",
                "short_code": "comp",
                "title": "NOAA-GFDL SPEAR Model",
                "abstract": "The underlying data was produced by the National Oceanic and Atmospheric Administration- Geophysical Fluid Dynamics Laboratory (NOAA-GFDL) SPEAR model for the SNAPSI project."
            },
            "procedureCompositeProcess": null,
            "imageDetails": [
                229
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2560,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 56,
                        "licenceURL": "https://creativecommons.org/licenses/by-sa/4.0/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 37088,
                    "uuid": "0a5a1ce22fb047749e040879efa8e9b5",
                    "short_code": "proj",
                    "title": "Stratospheric Nudging And Predictable Surface Impacts (SNAPSI)",
                    "abstract": "SNAPSI is a model intercomparison protocol designed to study the role of the Arctic and Antarctic stratospheric polar vortices in sub-seasonal to seasonal forecast models. Based on a set of controlled, sub-seasonal, ensemble forecasts of three recent events, the protocol aims to address four main scientific goals. \r\nFirst, to quantify the impact of improved stratospheric forecasts on near-surface forecast skill. \r\nSecond, to attribute specific extreme events to stratospheric variability. \r\nThird, to assess the mechanisms by which the stratosphere influences the troposphere in the forecast models, \r\nand fourth, to investigate the wave processes that lead to the stratospheric anomalies themselves. \r\nAlthough not a primary focus, the experiments are furthermore expected to shed light on coupling between the tropical stratosphere and troposphere. \r\nThe output requested will allow for a more detailed, process-based community analysis than has been possible with existing databases of sub-seasonal forecasts."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                6021,
                6022,
                6023,
                9045,
                50415,
                50417,
                50418,
                50419,
                50426,
                50427,
                50428,
                50429,
                50431,
                50445,
                50475,
                50481,
                50496,
                50498,
                50549,
                50566,
                50577,
                50579,
                50582,
                50587,
                50588,
                50590,
                50597,
                50605,
                50609,
                50615,
                52755,
                53111,
                54228,
                60438,
                62560,
                62561,
                64078,
                64080,
                66076,
                66077,
                66082,
                71614,
                71619,
                71634,
                74366,
                74367
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 40381,
                    "uuid": "300077b625e94c02b7d93e6521b4451d",
                    "short_code": "coll",
                    "title": "Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): data produced by the SPEAR model at NOAA-GFDL",
                    "abstract": "The SPEAR model contribution to the Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) project produced by scientists at the National Oceanic and Atmospheric Administration- Geophysical Fluid Dynamics Laboratory.\r\n\r\nThe SNAPSI project is a model intercomparison project to study the role of the stratosphere in subseasonal forecasts following stratospheric sudden warmings and the representation of stratosphere-troposphere coupling in subseasonal forecast models.\r\n\r\n\r\n------------------------------------------\r\nSources of additional information\r\n------------------------------------------\r\nThe following web links are provided in the Details/Docs section of this catalogue record:\r\n\r\n- Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): A Protocol for Investigating the Role of the Stratospheric Polar Vortex in Subseasonal to Seasonal Forecasts\r\n- New set of controlled numerical experiments: Stratospheric Nudging And Predictable Surface Impacts (SNAPSI)\r\n- GFDL SPEAR reference publication: Delworth et al. (2020)"
                }
            ],
            "responsiblepartyinfo_set": [
                197667,
                197668,
                197669,
                197670,
                197671,
                197672,
                197673,
                197674,
                197675
            ],
            "onlineresource_set": [
                84170,
                84168,
                84169
            ]
        },
        {
            "ob_id": 40626,
            "uuid": "113a9f64c89542b0bb3836ad117a77a2",
            "title": "QA4ECV MODIS Prior (2000-2016)",
            "abstract": "The Quality Assurance for Essential Climate Variables (QA4ECV) project produced MODIS priors as part of their processing chain.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57",
            "latestDataUpdateTime": null,
            "updateFrequency": "",
            "dataLineage": "Data are provided by the QA4ECV project for archival with CEDA. Data are in NetCDF format.",
            "removedDataReason": "",
            "keywords": "Albedo, Polar, Climate, Sea Ice, Radiometer",
            "publicationState": "working",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": null,
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 529,
                "bboxName": "Global (-180 to 180)",
                "eastBoundLongitude": 180.0,
                "westBoundLongitude": -180.0,
                "southBoundLatitude": -90.0,
                "northBoundLatitude": 90.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40627,
                "dataPath": "/neodc/qa4ecv/data/modis_prior/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 15360921200052,
                "numberOfFiles": 349943,
                "fileFormat": "These data are provided in netCDF format."
            },
            "timePeriod": {
                "ob_id": 7010,
                "startTime": "2000-03-31T23:00:00",
                "endTime": "2016-09-30T13:03:52"
            },
            "resultQuality": {
                "ob_id": 3217,
                "explanation": "Data as provided by the QA4ECV project, archived at CEDA",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2019-01-18"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                210
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2528,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 8,
                        "licenceURL": "http://creativecommons.org/licenses/by/4.0/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 25937,
                    "uuid": "130756538390418ea80ebe143542b01d",
                    "short_code": "proj",
                    "title": "Quality Assurance for Essential Climate Variables (QA4ECV)",
                    "abstract": "The FP7 QA4ECV project was initiated in 2014 to demonstrate how reliable and traceable quality information can be provided for satellite and ground-based measurements of climate and air quality parameters. The project developed and applied a Quality Assurance framework on new and improved multi-decadal data records of the Land ECVs Albedo, Leaf Area Index (LAI), and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and on the Atmosphere ECVs nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO).\r\n\r\nQA4ECV provides multi-decadal satellite data records for 3 Land Essential Climate Variables (ECVs) and 3 Atmosphere ECV precursors."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                18405,
                18408,
                71494,
                71495,
                71496,
                71497,
                71498,
                71499,
                71500,
                71501,
                71502,
                71503,
                71504,
                71505,
                71506,
                71507,
                71508,
                71509,
                71510,
                71511,
                71512,
                71513,
                71514,
                71515,
                71516,
                71517,
                71518,
                71519,
                71520,
                71521,
                71522,
                71523,
                71524,
                71525,
                71526,
                71527,
                71528,
                71529,
                71530,
                71531,
                71532,
                71533,
                71534,
                71535,
                71536,
                71537,
                71538,
                71539,
                71540,
                71541,
                71542,
                71543,
                71544,
                71545,
                71546,
                71547,
                71548,
                71549,
                71550,
                71551,
                71552,
                71553,
                71554,
                71555,
                71556,
                71557,
                71558,
                71559,
                71560,
                71561,
                71562,
                71563,
                71564,
                71565
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                197684,
                197685,
                197686,
                197687,
                197688,
                197689,
                197690,
                197691,
                197692,
                197693
            ],
            "onlineresource_set": [
                84171,
                84172
            ]
        },
        {
            "ob_id": 40629,
            "uuid": "c1091e99ca2d41fc846ec9bd71b4d09b",
            "title": "QA4ECV DHR-FAPAR level 3 (1982-2006)",
            "abstract": "Directional Hemispherical Reflectance (DHR) - Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) products derived from daily spectral measurements acquired by Advanced Very High Resolution Radiometer (AVHRR) onboard a series of National Oceanic and Atmospheric Administration (NOAA) platforms. This work is done in the framework of the Quality Assurance For Essential Climate Variable (QA4ECV) project.  The input data are the surface reflectance provided by the Land Long Term Data Record (LTDR) project.\r\n\r\nThese data are provided as time composite products of 10 days and monthly time periods at 0.05 degree resolution.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57",
            "latestDataUpdateTime": null,
            "updateFrequency": "",
            "dataLineage": "Data are provided by the QA4ECV project for archival with CEDA. Data are in NetCDF format.",
            "removedDataReason": "",
            "keywords": "FAPAR",
            "publicationState": "working",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "0.05 deg",
            "status": "completed",
            "dataPublishedTime": null,
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 529,
                "bboxName": "Global (-180 to 180)",
                "eastBoundLongitude": 180.0,
                "westBoundLongitude": -180.0,
                "southBoundLatitude": -90.0,
                "northBoundLatitude": 90.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40630,
                "dataPath": "/neodc/qa4ecv/data/dhr_fapar/L3/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 130182811385,
                "numberOfFiles": 1199,
                "fileFormat": "These data are gzipped netCDF products."
            },
            "timePeriod": {
                "ob_id": 11276,
                "startTime": "1982-01-01T00:00:00",
                "endTime": "2006-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 3217,
                "explanation": "Data as provided by the QA4ECV project, archived at CEDA",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2019-01-18"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": {
                "ob_id": 40641,
                "uuid": "a3e86b3c0cee42d98fed49c5ddfa58df",
                "short_code": "cmppr",
                "title": "QA4ECV FAPAR processing",
                "abstract": "The algorithm described in this document is called JRC-TOC FAPAR with a versioning\r\nnumber 1.0. It is used to generate the daily Fraction of Absorbed Photosynthetically\r\nActive Radiation (FAPAR) products and its uncertainties. We also propose a timecompositing algorithm for making 10-days and monthly products."
            },
            "imageDetails": [
                210
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2528,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 8,
                        "licenceURL": "http://creativecommons.org/licenses/by/4.0/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 25937,
                    "uuid": "130756538390418ea80ebe143542b01d",
                    "short_code": "proj",
                    "title": "Quality Assurance for Essential Climate Variables (QA4ECV)",
                    "abstract": "The FP7 QA4ECV project was initiated in 2014 to demonstrate how reliable and traceable quality information can be provided for satellite and ground-based measurements of climate and air quality parameters. The project developed and applied a Quality Assurance framework on new and improved multi-decadal data records of the Land ECVs Albedo, Leaf Area Index (LAI), and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and on the Atmosphere ECVs nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO).\r\n\r\nQA4ECV provides multi-decadal satellite data records for 3 Land Essential Climate Variables (ECVs) and 3 Atmosphere ECV precursors."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                197694,
                197695,
                197696,
                197697,
                197698,
                197699,
                197700,
                197701,
                197702,
                197703
            ],
            "onlineresource_set": [
                84174,
                84175,
                84179,
                84180
            ]
        },
        {
            "ob_id": 40631,
            "uuid": "ade1bcb995ab490daf87fa50c535f6b9",
            "title": "QA4ECV FAPAR level 4 (1982-2006)",
            "abstract": "The Quality Assurance for Essential Climate Variables (QA4ECV) project produced... More info needed",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57",
            "latestDataUpdateTime": null,
            "updateFrequency": "",
            "dataLineage": "Data are provided by the QA4ECV project for archival with CEDA. Data are in NetCDF format.",
            "removedDataReason": "",
            "keywords": "FAPAR",
            "publicationState": "working",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": null,
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 529,
                "bboxName": "Global (-180 to 180)",
                "eastBoundLongitude": 180.0,
                "westBoundLongitude": -180.0,
                "southBoundLatitude": -90.0,
                "northBoundLatitude": 90.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40632,
                "dataPath": "/neodc/qa4ecv/data/dhr_fapar/L4/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 2173704497,
                "numberOfFiles": 1203,
                "fileFormat": "These data are gzipped netCDF products."
            },
            "timePeriod": {
                "ob_id": 11276,
                "startTime": "1982-01-01T00:00:00",
                "endTime": "2006-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 3217,
                "explanation": "Data as provided by the QA4ECV project, archived at CEDA",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2019-01-18"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                210
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2528,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 8,
                        "licenceURL": "http://creativecommons.org/licenses/by/4.0/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 25937,
                    "uuid": "130756538390418ea80ebe143542b01d",
                    "short_code": "proj",
                    "title": "Quality Assurance for Essential Climate Variables (QA4ECV)",
                    "abstract": "The FP7 QA4ECV project was initiated in 2014 to demonstrate how reliable and traceable quality information can be provided for satellite and ground-based measurements of climate and air quality parameters. The project developed and applied a Quality Assurance framework on new and improved multi-decadal data records of the Land ECVs Albedo, Leaf Area Index (LAI), and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and on the Atmosphere ECVs nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO).\r\n\r\nQA4ECV provides multi-decadal satellite data records for 3 Land Essential Climate Variables (ECVs) and 3 Atmosphere ECV precursors."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                197707,
                197708,
                197709,
                197710,
                197711,
                197712,
                197713,
                197714,
                197716,
                197715
            ],
            "onlineresource_set": [
                84177,
                84176
            ]
        },
        {
            "ob_id": 40639,
            "uuid": "f78cc9301a2149b5a9f07e0904b60634",
            "title": "POLCOMS-WAM model run in the Irish Sea generating eastward and northward currents at 32 depth layers for the CoFEE project for 11 years from 1996.",
            "abstract": "This dataset consists of eastward and northward current components at 32 depth levels. The dataset is a gridded dataset, with grid resolution of 1.85 km. It covers the entire Irish Sea area, with a precise range from -2.7 degrees longitude to -7 degrees longitude and from 51 degrees latitude to 56 degrees latitude. The data are daily averages and cover the period from 01 January 1996 to 01 January 2007. The eastward and northward current components were used as input conditions into a coastal processes and sediment transport model which looked at the response of the north Liverpool coastline to extreme flooding events. The dataset was generated by the Proudman Oceanographic Laboratory Coastal Ocean Modelling System coupled with the Wave Modelling model (POLCOMS-WAM) as part of the Natural Environment Research Council (NERC) CoFEE project which ran from April 2007 to September 2010. The dataset consists of 132 data files in Climate and Forecast (CF) compliant NetCDF format.",
            "creationDate": "2023-08-21T12:43:24.146153",
            "lastUpdatedDate": "2023-08-21T12:42:42",
            "latestDataUpdateTime": "2023-08-21T13:11:42",
            "updateFrequency": "",
            "dataLineage": "The data are archived on the British Oceanographic Data Centre (BODC)'s space at the Centre for Environmental Data Analysis (CEDA) and assigned a DOI. No quality control procedures were applied by BODC.",
            "removedDataReason": "",
            "keywords": "",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "final",
            "dataPublishedTime": "2023-08-22T09:02:38",
            "doiPublishedTime": "2023-08-22T09:02:38",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3954,
                "bboxName": "Irish Sea and Liverpool Bay",
                "eastBoundLongitude": -2.7,
                "westBoundLongitude": -7.0,
                "southBoundLatitude": 51.0,
                "northBoundLatitude": 56.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40638,
                "dataPath": "/bodc/POL090139/POLCOMS_WAM_32UV",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 53563333543,
                "numberOfFiles": 134,
                "fileFormat": "Climate and Forecast compliant NetCDFs"
            },
            "timePeriod": {
                "ob_id": 11277,
                "startTime": "1996-01-01T00:00:00",
                "endTime": "2007-01-01T00:00:00"
            },
            "resultQuality": {
                "ob_id": 3732,
                "explanation": "The data are provided as-is with no quality control undertaken by the British Oceanographic Data Centre (BODC). The data suppliers have not indicated if any quality control has been undertaken on these data.",
                "passesTest": true,
                "resultTitle": "BODC Data Quality Statement",
                "date": "2021-07-02"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2569,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 36,
                        "licenceURL": "https://www.bodc.ac.uk/data/documents/nodb/599476/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                6023,
                50559,
                50561,
                86688,
                86689,
                86690,
                86691
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12703
            ],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                197725,
                197724,
                197723,
                197722,
                197728,
                197729,
                197732,
                197727,
                197726,
                197730,
                197731
            ],
            "onlineresource_set": []
        },
        {
            "ob_id": 40642,
            "uuid": "c276009e063e45b2ba40bbd3f9e39128",
            "title": "WCRP CMIP6: Natural Environment Research Council (NERC) UKESM1-0-LL model output for the \"volc-pinatubo-full\" experiment",
            "abstract": "The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the Natural Environment Research Council (NERC) UKESM1-0-LL model output for the \"Pinatubo experiment\" (volc-pinatubo-full) experiment. These are available at the following frequencies: AERmon, AERmonZ, Amon, CFday, Eday, EdayZ, Emon, EmonZ, LImon, Lmon, Omon, SIday, SImon and day. The runs included the ensemble members: r10i1p1f2, r11i1p1f2, r13i1p1f2, r14i1p1f2, r15i1p1f2, r16i1p1f2, r17i1p1f2, r18i1p1f2, r19i1p1f2, r1i1p1f2, r20i1p1f2, r21i1p1f2, r22i1p1f2, r24i1p1f2, r25i1p1f2, r26i1p1f2, r27i1p1f2, r2i1p1f2, r3i1p1f2, r4i1p1f2, r5i1p1f2, r6i1p1f2, r7i1p1f2, r8i1p1f2 and r9i1p1f2.\n\nCMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6).\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record.",
            "creationDate": "2023-08-23T12:13:06.026876",
            "lastUpdatedDate": "2023-08-23T12:13:06.026892",
            "latestDataUpdateTime": "2023-12-03T16:32:07",
            "updateFrequency": "asNeeded",
            "dataLineage": "Data were produced and verified by Natural Environment Research Council (NERC) scientists before publication via the Earth Systems Grid Federation (ESGF) and a copy obtained by the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "CMIP6, WCRP, climate change, NERC, UKESM1-0-LL, volc-pinatubo-full, AERmon, AERmonZ, Amon, CFday, Eday, EdayZ, Emon, EmonZ, LImon, Lmon, Omon, SIday, SImon, day",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-08-23T12:13:06.403819",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 529,
                "bboxName": "Global (-180 to 180)",
                "eastBoundLongitude": 180.0,
                "westBoundLongitude": -180.0,
                "southBoundLatitude": -90.0,
                "northBoundLatitude": 90.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40643,
                "dataPath": "/badc/cmip6/data/CMIP6/VolMIP/NERC/UKESM1-0-LL/volc-pinatubo-full",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 501762810483,
                "numberOfFiles": 5566,
                "fileFormat": "Data are netCDF formatted."
            },
            "timePeriod": {
                "ob_id": 11279,
                "startTime": "1991-06-01T12:00:00",
                "endTime": "1994-06-30T12:00:00"
            },
            "resultQuality": {
                "ob_id": 3334,
                "explanation": "The CMIP6 data are checked by CEDA to ensure that they conform to the CMOR metadata standards (https://cmor.llnl.gov) Where any CMIP6 data are identified as having a quality issue this is recorded in the CMIP6 errata service: https://errata.es-doc.org/static/index.html",
                "passesTest": true,
                "resultTitle": "CMIP6 Quality Statement - primary data",
                "date": "2017-02-14"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": {
                "ob_id": 40644,
                "uuid": "fe462053516f45cca693eda49ccce2d2",
                "short_code": "comp",
                "title": "Natural Environment Research Council (NERC) running: experiment volc-pinatubo-full using the UKESM1-0-LL model.",
                "abstract": "Natural Environment Research Council (NERC) running the \"Pinatubo experiment\" (volc-pinatubo-full) experiment using the UKESM1-0-LL model. See linked documentation for available information for each component."
            },
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [
                {
                    "ob_id": 1138,
                    "name": "NDGO0003"
                }
            ],
            "permissions": [
                {
                    "ob_id": 2520,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 1,
                        "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/CMIP6_Terms_of_Use.pdf",
                        "licenceClassifications": []
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 31082,
                    "uuid": "4d049989827d425fb87830d57209d956",
                    "short_code": "proj",
                    "title": "WCRP CMIP6: Natural Environment Research Council (NERC) contribution",
                    "abstract": "World Climate Research Programme (WCRP) Coupled Model Intercomparison Project Phase 6 contribution to the project by the Natural Environment Research Council (NERC)  team."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                6021,
                6022,
                6023,
                6255,
                9045,
                27828,
                27829,
                50415,
                50417,
                50418,
                50419,
                50424,
                50426,
                50427,
                50428,
                50429,
                50431,
                50432,
                50433,
                50435,
                50437,
                50445,
                50468,
                50475,
                50481,
                50496,
                50498,
                50542,
                50543,
                50549,
                50552,
                50554,
                50555,
                50557,
                50564,
                50566,
                50567,
                50568,
                50569,
                50570,
                50571,
                50572,
                50573,
                50574,
                50575,
                50577,
                50578,
                50579,
                50580,
                50581,
                50582,
                50583,
                50586,
                50587,
                50588,
                50589,
                50590,
                50591,
                50592,
                50596,
                50597,
                50598,
                50599,
                50600,
                50602,
                50603,
                50605,
                50608,
                50609,
                50610,
                50611,
                50612,
                50614,
                50615,
                50616,
                51210,
                51211,
                52744,
                52745,
                52746,
                52750,
                52755,
                53111,
                53128,
                53129,
                54207,
                54211,
                54212,
                54216,
                54217,
                54218,
                54219,
                54220,
                54221,
                54222,
                54227,
                54228,
                54232,
                54235,
                54236,
                54237,
                54238,
                54242,
                54243,
                54245,
                54246,
                54247,
                54248,
                54249,
                54253,
                54255,
                54257,
                54261,
                54262,
                54263,
                54264,
                54266,
                54268,
                54271,
                54272,
                54273,
                54274,
                54275,
                54276,
                54282,
                54285,
                54286,
                54287,
                54295,
                54299,
                54300,
                54303,
                54304,
                54305,
                54306,
                54307,
                54310,
                54313,
                54314,
                54322,
                54323,
                54324,
                54325,
                54335,
                54340,
                54345,
                54346,
                54348,
                54349,
                54355,
                54356,
                54357,
                54358,
                54364,
                54365,
                54366,
                54378,
                54415,
                54421,
                54439,
                54824,
                60438,
                62525,
                62715,
                62733,
                62736,
                62739,
                64080,
                71572,
                71573,
                71574,
                71584,
                71589,
                71613,
                71614,
                71615,
                71617,
                71629,
                71646,
                71648,
                71652,
                71657,
                71665,
                71678,
                71679,
                71686,
                71692,
                71818,
                71859,
                71871,
                74556,
                75345,
                82361
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 33485,
                    "uuid": "7e53d9bd279746029225667954764570",
                    "short_code": "coll",
                    "title": "WCRP CMIP6: Natural Environment Research Council (NERC) UKESM1-0-LL model output collection",
                    "abstract": "World Climate Research Programme (WCRP) Coupled Model Intercomparison Project Phase 6 (CMIP6): Collection of simulations from the Natural Environment Research Council (NERC) UKESM1-0-LL model.\n\nThe official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record."
                }
            ],
            "responsiblepartyinfo_set": [
                197737,
                197738,
                197739,
                197740,
                197741,
                197742,
                197743,
                197745,
                197746,
                197744
            ],
            "onlineresource_set": [
                84183,
                84184,
                84186,
                84188,
                84190,
                84192,
                84194,
                84196,
                84198,
                84200,
                84202,
                84204,
                84206,
                84208,
                84210,
                84212,
                84214,
                84216,
                84218,
                84220,
                84222,
                84224,
                84226,
                84228,
                84230,
                84232,
                84234,
                84236,
                84237,
                84238
            ]
        },
        {
            "ob_id": 40647,
            "uuid": "1b89e025eedd49e8976ee0721ec6e9b5",
            "title": "POLCOMS-WAM model run in the Irish Sea generating depth-mean eastward and northward currents for the CoFEE project for 11 years from 1996.",
            "abstract": "This dataset consists of depth-averaged eastward and northward current components. Also present is the sea surface height above sea level. The dataset is a gridded dataset, with grid resolution of 1.85 km. It covers the entire Irish Sea area, with a precise range from -2.7 degrees longitude to -7 degrees longitude and from 51 degrees latitude to 56 degrees latitude. The data are 30 minute averages and cover the period from 01 January 1996 to 01 January 2007. The depth-averaged eastward and northward current components and sea surface height were used as input conditions into a coastal processes and sediment transport model which looked at the response of the north Liverpool coastline to extreme flooding events. The dataset was generated by the Proudman Oceanographic Laboratory Coastal Ocean Modelling System coupled with the Wave Modelling model (POLCOMS-WAM) as part of the Natural Environment Research Council (NERC) CoFEE project which ran from April 2007 to September 2010. The dataset consists of 264 data files in Climate and Forecast (CF) compliant NetCDF format.",
            "creationDate": "2023-08-24T14:01:27.973376",
            "lastUpdatedDate": "2023-08-24T14:01:00",
            "latestDataUpdateTime": "2024-03-09T02:48:50",
            "updateFrequency": "",
            "dataLineage": "The data are archived on the British Oceanographic Data Centre (BODC)'s space at the Centre for Environmental Data Analysis (CEDA) and assigned a DOI. No quality control procedures were applied by BODC.",
            "removedDataReason": "",
            "keywords": "",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "final",
            "dataPublishedTime": "2023-08-24T14:46:47",
            "doiPublishedTime": "2023-08-24T14:46:47",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3954,
                "bboxName": "Irish Sea and Liverpool Bay",
                "eastBoundLongitude": -2.7,
                "westBoundLongitude": -7.0,
                "southBoundLatitude": 51.0,
                "northBoundLatitude": 56.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40645,
                "dataPath": "/bodc/POL090139/POLCOMS_WAM_UV",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 120518698380,
                "numberOfFiles": 265,
                "fileFormat": "Climate and Forecast compliant NetCDFs"
            },
            "timePeriod": {
                "ob_id": 11280,
                "startTime": "1996-01-01T00:00:00",
                "endTime": "2007-01-01T00:00:00"
            },
            "resultQuality": {
                "ob_id": 3732,
                "explanation": "The data are provided as-is with no quality control undertaken by the British Oceanographic Data Centre (BODC). The data suppliers have not indicated if any quality control has been undertaken on these data.",
                "passesTest": true,
                "resultTitle": "BODC Data Quality Statement",
                "date": "2021-07-02"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2569,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 36,
                        "licenceURL": "https://www.bodc.ac.uk/data/documents/nodb/599476/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50559,
                50561,
                79248,
                79249,
                79250,
                79251,
                79252,
                79253,
                79254,
                79255,
                79256,
                79257,
                79258,
                79259,
                79260,
                79261,
                79262,
                79263,
                79264,
                79265,
                79266,
                79267,
                79268,
                79269,
                79270,
                79271,
                79272,
                79273,
                79274,
                79275,
                79276,
                79277,
                79278,
                79279,
                79280,
                79281,
                79282,
                79283,
                79284,
                79285,
                79286,
                79287,
                79288,
                79289,
                79290,
                79291,
                79292,
                79293,
                79294,
                79295,
                79296,
                79297,
                79298,
                79299,
                79300,
                79301,
                79302,
                79303,
                79304,
                79305,
                79306,
                79307,
                79308,
                79309,
                79310,
                79311,
                79312,
                79313,
                79314,
                79315,
                79316,
                79317,
                79318,
                79319,
                79320,
                79321,
                79322,
                79323,
                79324,
                79325,
                79326,
                79327,
                79328,
                79329,
                79330,
                79331,
                79332,
                79333,
                79334,
                79335,
                79336,
                79337,
                79338,
                79339,
                79340,
                79341,
                79342,
                79343,
                79344,
                79345,
                79346,
                79347,
                79348,
                79349,
                79350,
                79351,
                79352,
                79353,
                79354,
                79355,
                79356,
                79357,
                79358,
                79359,
                79360,
                79361,
                79362,
                79363,
                79364,
                79365,
                79366,
                79367,
                79368,
                79369,
                79370,
                79371,
                79372,
                79373,
                79374,
                79375,
                79376,
                79377,
                79378,
                79379,
                79380,
                79381,
                79382,
                79383,
                79384
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12702
            ],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                197755,
                197754,
                197753,
                197752,
                197758,
                197759,
                197762,
                197757,
                197756,
                197760,
                197761
            ],
            "onlineresource_set": []
        },
        {
            "ob_id": 40648,
            "uuid": "25188240530746c2b06c87f78adb98f3",
            "title": "POLCOMS-WAM model run in the Irish Sea generating surface wave data for the CoFEE project for 11 years from 1996.",
            "abstract": "This dataset consists of significant wave height, peak wave period, second moment wave period and nautical wave direction. The dataset is a gridded dataset, with grid resolution of 1.85 km. It covers the entire Irish Sea area, with a precise range -2.7 degrees longitude to -7 degrees longitude and from 51 degrees latitude to 56 degrees latitude. The data are hourly averages and cover the period from 01 January 1996 to 01 January 2007. The wave parameters generated by POLCOMS-WAM were used as input conditions into a coastal processes and sediment transport model which looked at the response of the north Liverpool coastline to extreme flooding events. The dataset was generated by the Proudman Oceanographic Laboratory Coastal Ocean Modelling System coupled with the Wave Modelling model (POLCOMS-WAM) as part of the Natural Environment Research Council (NERC) CoFEE project which ran from April 2007 to September 2010. The dataset consists of 132 data files in Climate and Forecast (CF) compliant NetCDF format.",
            "creationDate": "2023-08-24T14:09:39.392276",
            "lastUpdatedDate": "2023-08-24T14:09:09",
            "latestDataUpdateTime": "2024-03-09T02:48:19",
            "updateFrequency": "notPlanned",
            "dataLineage": "The data are archived on the British Oceanographic Data Centre (BODC)'s space at the Centre for Environmental Data Analysis (CEDA) and assigned a DOI. No quality control procedures were applied by BODC.",
            "removedDataReason": "",
            "keywords": "",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "final",
            "dataPublishedTime": "2023-08-24T14:46:33",
            "doiPublishedTime": "2023-08-24T14:46:33",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3954,
                "bboxName": "Irish Sea and Liverpool Bay",
                "eastBoundLongitude": -2.7,
                "westBoundLongitude": -7.0,
                "southBoundLatitude": 51.0,
                "northBoundLatitude": 56.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40646,
                "dataPath": "/bodc/POL100124/POLCOMS_WAM_WAVE",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 80344939094,
                "numberOfFiles": 134,
                "fileFormat": "Climate and Forecast compliant NetCDFs"
            },
            "timePeriod": {
                "ob_id": 11282,
                "startTime": "1996-01-01T00:00:00",
                "endTime": "2007-01-01T00:00:00"
            },
            "resultQuality": {
                "ob_id": 3732,
                "explanation": "The data are provided as-is with no quality control undertaken by the British Oceanographic Data Centre (BODC). The data suppliers have not indicated if any quality control has been undertaken on these data.",
                "passesTest": true,
                "resultTitle": "BODC Data Quality Statement",
                "date": "2021-07-02"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2569,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 36,
                        "licenceURL": "https://www.bodc.ac.uk/data/documents/nodb/599476/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50559,
                50561,
                79253,
                79254,
                79255,
                79256,
                79257,
                79258,
                79259,
                79260,
                79261,
                79262,
                79263,
                79264,
                79265,
                79266,
                79267,
                79268,
                79269,
                79270,
                79271,
                79272,
                79273,
                79274,
                79275,
                79276,
                79277,
                79278,
                79279,
                79280,
                79281,
                79282,
                79283,
                79284,
                79285,
                79286,
                79287,
                79288,
                79289,
                79290,
                79291,
                79292,
                79293,
                79294,
                79295,
                79296,
                79297,
                79298,
                79299,
                79300,
                79301,
                79302,
                79303,
                79304,
                79305,
                79306,
                79307,
                79308,
                79309,
                79310,
                79311,
                79312,
                79313,
                79314,
                79315,
                79316,
                79317,
                79318,
                79319,
                79320,
                79321,
                79322,
                79323,
                79324,
                79325,
                79326,
                79327,
                79328,
                79329,
                79330,
                79331,
                79332,
                79333,
                79334,
                79335,
                79336,
                79337,
                79338,
                79339,
                79340,
                79341,
                79342,
                79343,
                79344,
                79345,
                79346,
                79347,
                79348,
                79349,
                79350,
                79351,
                79352,
                79353,
                79354,
                79355,
                79356,
                79357,
                79358,
                79359,
                79360,
                79361,
                79362,
                79363,
                79364,
                79365,
                79366,
                79367,
                79368,
                79369,
                79370,
                79371,
                79372,
                79373,
                79374,
                79375,
                79376,
                79377,
                79378,
                79379,
                79380,
                79381,
                79382,
                79383,
                79384,
                86639,
                86640,
                86641,
                86642
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12686
            ],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                197766,
                197765,
                197764,
                197763,
                197769,
                197770,
                197773,
                197768,
                197767,
                197771,
                197772
            ],
            "onlineresource_set": []
        },
        {
            "ob_id": 40649,
            "uuid": "c21639861fb54623a749e502ebac74ed",
            "title": "MIDAS Open: UK hourly rainfall data, v202308",
            "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2022.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57",
            "latestDataUpdateTime": "2023-08-31T10:04:20",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data collated by the Met Office and archived in the Met Office's MIDAS database. Data are extracted from a sub-set of available tables and delivered to Centre for Environmental Data Analysis (CEDA) approximately on a yearly basis.",
            "removedDataReason": "",
            "keywords": "Met Office, MIDAS, UK, meteorology, rainfall, hourly",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "superseded",
            "dataPublishedTime": "2023-10-03T16:35:59",
            "doiPublishedTime": "2023-10-03T16:35:34",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 17,
                "bboxName": "",
                "eastBoundLongitude": 1.74002,
                "westBoundLongitude": -8.5636,
                "southBoundLatitude": 49.914,
                "northBoundLatitude": 60.8562
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40686,
                "dataPath": "/badc/ukmo-midas-open/data/uk-hourly-rain-obs/dataset-version-202308/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 5498351087,
                "numberOfFiles": 16165,
                "fileFormat": "Data are BADC-CSV formatted."
            },
            "timePeriod": {
                "ob_id": 11289,
                "startTime": "1915-01-01T18:00:00",
                "endTime": "2022-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 308,
                "explanation": "Data undergo quality checking by the Met Office. State of the data in the quality control process and level of data quality are indicated using version numbers and quality control flagging with the data. See documentation about how to use the quality control flagging and version numbers.\n\nThere are also some known data from commissioning trials in the data, which are given a src_id of 99999. These should be ignored by the user.",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2014-09-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 27188,
                "uuid": "b0418372412d4d79ba08d65681fc6f5d",
                "short_code": "acq",
                "title": "Acquisition Process for: UK Hourly Rainfall Data, Part of the Met Office Integrated Data Archive System (MIDAS) Open (excludes WAHRAIN)",
                "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Raingauge; PLATFORMS: SSER (Solid State Event Recorder) Station Network, AWSHRLY (Automatic Weather Station Hourly values) Station Network, SREW (Synoptic Rainfall Europe West) Station Network, DLY3208 (Daily observations from Metform 3208) Station Network, NCM (National Climate Message) Station Network;"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                69
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 1186,
                    "uuid": "245df050d57a500c183b88df509f5f5a",
                    "short_code": "proj",
                    "title": "Met Office Integrated Data Archive System (MIDAS)",
                    "abstract": "Since the early days of this century the Met Office has been responsible for maintaining the public memory of the weather. All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                76672,
                76674,
                76675,
                76678,
                76679,
                76680,
                76682,
                76683,
                76686,
                76690,
                76694,
                76695,
                76696,
                76697,
                76717,
                76718,
                76721,
                76740,
                76741
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12708
            ],
            "observationcollection_set": [
                {
                    "ob_id": 26184,
                    "uuid": "dbd451271eb04662beade68da43546e1",
                    "short_code": "coll",
                    "title": "Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)",
                    "abstract": "MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."
                }
            ],
            "responsiblepartyinfo_set": [
                197774,
                197777,
                197775,
                197776,
                197781,
                197778,
                197779,
                197780,
                197782
            ],
            "onlineresource_set": [
                84244,
                84239,
                84240,
                84242,
                84246,
                84245,
                84243,
                84241
            ]
        },
        {
            "ob_id": 40650,
            "uuid": "3f3809143a224c84962f52757d668f77",
            "title": "MIDAS Open: UK daily rainfall data, v202308",
            "abstract": "The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2022. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version (202207) of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57",
            "latestDataUpdateTime": "2023-08-31T13:06:24",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data collated by the Met Office and archived in the Met Office's MIDAS database. Data are extracted from a sub-set of available tables and delivered to Centre for Environmental Data Analysis (CEDA) approximately on a yearly basis.",
            "removedDataReason": "",
            "keywords": "Met Office, MIDAS, UK, meteorology, rainfall, diurnal, daily, monthly",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "superseded",
            "dataPublishedTime": "2023-10-03T16:43:35",
            "doiPublishedTime": "2023-10-03T16:43:40",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 18,
                "bboxName": "MIDAS UK table s geographic domain",
                "eastBoundLongitude": 1.74002,
                "westBoundLongitude": -5.54236,
                "southBoundLatitude": 50.1172,
                "northBoundLatitude": 60.7592
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40688,
                "dataPath": "/badc/ukmo-midas-open/data/uk-daily-rain-obs/dataset-version-202308/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 1093782713,
                "numberOfFiles": 52070,
                "fileFormat": "Data are BADC-CSV formatted"
            },
            "timePeriod": {
                "ob_id": 11290,
                "startTime": "1853-01-02T00:00:00",
                "endTime": "2022-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 297,
                "explanation": "Data undergo quality checking by the Met Office. State of the data in the quality control process and level of data quality are indicated using version numbers and quality control flagging with the data. See documentation about how to use the quality control flagging and version numbers.\n\nThere are also some known data from commissioning trials in the data, which are given a src_id of 99999. These should be ignored by the user.",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2014-09-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 27187,
                "uuid": "037f3eff9db941a583b252e800a94979",
                "short_code": "acq",
                "title": "Acquisition Process for: UK Daily Rainfall Data, Part of the Met Office Integrated Data Archive System (MIDAS) Open  - excludes WADRAIN and WAMRAIN",
                "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Raingauge; PLATFORMS: DLY3208 (Daily observations from Metform 3208) Station Network, SSER (Solid State Event Recorder) Station Network, WADRAIN (Water Authorities Daily RAINfall) Station Network, WAMRAIN (Water Authorities Monthly RAINfall value) Station Network, NCM (National Climate Message) Station Network, AWSDLY (Automatic Weather Station Daily values) Station Network;"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                69
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 1186,
                    "uuid": "245df050d57a500c183b88df509f5f5a",
                    "short_code": "proj",
                    "title": "Met Office Integrated Data Archive System (MIDAS)",
                    "abstract": "Since the early days of this century the Met Office has been responsible for maintaining the public memory of the weather. All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                76672,
                76674,
                76675,
                76678,
                76679,
                76680,
                76682,
                76690,
                76694,
                76695,
                76696,
                76697,
                76717,
                76718,
                76719,
                76720,
                76721,
                76722,
                76723
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12711
            ],
            "observationcollection_set": [
                {
                    "ob_id": 26184,
                    "uuid": "dbd451271eb04662beade68da43546e1",
                    "short_code": "coll",
                    "title": "Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)",
                    "abstract": "MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."
                }
            ],
            "responsiblepartyinfo_set": [
                197783,
                197785,
                197784,
                197789,
                197786,
                197787,
                197790,
                197788,
                197791
            ],
            "onlineresource_set": [
                84250,
                84247,
                84248,
                84249,
                84252,
                84254,
                84253,
                84251
            ]
        },
        {
            "ob_id": 40651,
            "uuid": "220b9b8ffbed43fcbbd323e739118f6c",
            "title": "MIDAS Open: UK daily temperature data, v202308",
            "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2022. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57",
            "latestDataUpdateTime": "2024-08-07T01:47:30",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data collated by the Met Office and archived in the Met Office's MIDAS database. Data are extracted from a sub-set of available tables and delivered to Centre for Environmental Data Analysis (CEDA) approximately on a yearly basis.",
            "removedDataReason": "",
            "keywords": "Met Office, MIDAS, UK, meteorology, temperature, diurnal, daily, monthly",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "superseded",
            "dataPublishedTime": "2023-10-03T15:50:34",
            "doiPublishedTime": "2023-10-04T08:34:41",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 18,
                "bboxName": "MIDAS UK table s geographic domain",
                "eastBoundLongitude": 1.74002,
                "westBoundLongitude": -5.54236,
                "southBoundLatitude": 50.1172,
                "northBoundLatitude": 60.7592
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40685,
                "dataPath": "/badc/ukmo-midas-open/data/uk-daily-temperature-obs/dataset-version-202308/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 2176671652,
                "numberOfFiles": 64081,
                "fileFormat": "Data are BADC-CSV formatted."
            },
            "timePeriod": {
                "ob_id": 11291,
                "startTime": "1853-01-01T00:00:00",
                "endTime": "2022-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 305,
                "explanation": "Data undergo quality checking by the Met Office. State of the data in the quality control process and level of data quality are indicated using version numbers and quality control flagging with the data. See documentation about how to use the quality control flagging and version numbers.\n\nThere are also some known data from commissioning trials in the data, which are given a src_id of 99999. These should be ignored by the user.",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2014-09-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 1243,
                "uuid": "93916103ebf54c5fad1e24fee0255e91",
                "short_code": "acq",
                "title": "Acquisition Process for: UK Daily Temperature Data, Part of the Met Office Integrated Data Archive System (MIDAS)",
                "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Thermometer; PLATFORMS: NCM (National Climate Message) Station Network, DLY3208 (Daily observations from Metform 3208) Station Network, AWSDLY (Automatic Weather Station Daily values) Station Network; "
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                69
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 1186,
                    "uuid": "245df050d57a500c183b88df509f5f5a",
                    "short_code": "proj",
                    "title": "Met Office Integrated Data Archive System (MIDAS)",
                    "abstract": "Since the early days of this century the Met Office has been responsible for maintaining the public memory of the weather. All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                76672,
                76674,
                76675,
                76678,
                76680,
                76690,
                76694,
                76695,
                76696,
                76697,
                76724,
                76725,
                76726,
                76727,
                76728,
                76729,
                76730,
                76731,
                76732,
                76733,
                76734,
                76735,
                76736,
                76737,
                76738,
                76739
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12714
            ],
            "observationcollection_set": [
                {
                    "ob_id": 26184,
                    "uuid": "dbd451271eb04662beade68da43546e1",
                    "short_code": "coll",
                    "title": "Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)",
                    "abstract": "MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."
                }
            ],
            "responsiblepartyinfo_set": [
                197792,
                197793,
                197794,
                197795,
                197796,
                197797,
                197798,
                197799,
                197800
            ],
            "onlineresource_set": [
                84260,
                84255,
                84256,
                84257,
                84258,
                84259,
                84261,
                84262
            ]
        },
        {
            "ob_id": 40652,
            "uuid": "1ce37461affc43bbbd78beaaacf5911d",
            "title": "MIDAS Open: UK daily weather observation data, v202308",
            "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1887 to 2022. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57",
            "latestDataUpdateTime": "2024-08-07T01:47:30",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data collated by the Met Office and archived in the Met Office's MIDAS database. Data are extracted from a sub-set of available tables and delivered to Centre for Environmental Data Analysis (CEDA) approximately on a yearly basis.",
            "removedDataReason": "",
            "keywords": "Met Office, MIDAS, UK, meteorology, daily, diurnal, monthly",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "superseded",
            "dataPublishedTime": "2023-10-03T15:47:02",
            "doiPublishedTime": "2023-10-03T15:47:29",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 18,
                "bboxName": "MIDAS UK table s geographic domain",
                "eastBoundLongitude": 1.74002,
                "westBoundLongitude": -5.54236,
                "southBoundLatitude": 50.1172,
                "northBoundLatitude": 60.7592
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40687,
                "dataPath": "/badc/ukmo-midas-open/data/uk-daily-weather-obs/dataset-version-202308/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 3099208789,
                "numberOfFiles": 49355,
                "fileFormat": "Data are BADC-CSV formatted."
            },
            "timePeriod": {
                "ob_id": 11292,
                "startTime": "1887-01-01T00:00:00",
                "endTime": "2022-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 306,
                "explanation": "Data undergo quality checking by the Met Office. State of the data in the quality control process and level of data quality are indicated using version numbers and quality control flagging with the data. See documentation about how to use the quality control flagging and version numbers.\n\nThere are also some known data from commissioning trials in the data, which are given a src_id of 99999. These should be ignored by the user.",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2014-09-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 1246,
                "uuid": "1efa07092762447189d030fe5d41e1fa",
                "short_code": "acq",
                "title": "Acquisition Process for: UK Daily Weather Observation Data, Part of the Met Office Integrated Data Archive System (MIDAS)",
                "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Station Observer, Sunshine Recorder, Cloud Recorder, Snow Depth Sensor, Present (and Past) Weather Sensor; PLATFORMS: Land SYNOP (surface synoptic observations) Station Network, NCM (National Climate Message) Station Network, DLY3208 (Daily observations from Metform 3208) Station Network, AWSDLY (Automatic Weather Station Daily values) Station Network; "
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                69
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 1186,
                    "uuid": "245df050d57a500c183b88df509f5f5a",
                    "short_code": "proj",
                    "title": "Met Office Integrated Data Archive System (MIDAS)",
                    "abstract": "Since the early days of this century the Met Office has been responsible for maintaining the public memory of the weather. All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                76672,
                76674,
                76675,
                76678,
                76679,
                76680,
                76682,
                76690,
                76694,
                76695,
                76696,
                76697,
                76808,
                76852,
                76853,
                76854,
                76855,
                76856,
                76857,
                76858,
                76859,
                76860,
                76861,
                76862,
                76863,
                76864,
                76865,
                76866,
                76867,
                76868,
                76869,
                76870,
                76871,
                76872,
                76873,
                76874,
                76875,
                76876
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12707
            ],
            "observationcollection_set": [
                {
                    "ob_id": 26184,
                    "uuid": "dbd451271eb04662beade68da43546e1",
                    "short_code": "coll",
                    "title": "Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)",
                    "abstract": "MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."
                }
            ],
            "responsiblepartyinfo_set": [
                197801,
                197802,
                197803,
                197804,
                197805,
                197806,
                197807,
                197808,
                197809
            ],
            "onlineresource_set": [
                84263,
                84265,
                84266,
                84264,
                84268,
                84270,
                84267,
                84269
            ]
        },
        {
            "ob_id": 40653,
            "uuid": "85596b72ff024837a64bf22a8d1a72be",
            "title": "MIDAS Open: UK soil temperature data, v202308",
            "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2022.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57",
            "latestDataUpdateTime": "2024-08-07T01:47:29",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data collated by the Met Office and archived in the Met Office's MIDAS database. Data are extracted from a sub-set of available tables and delivered to Centre for Environmental Data Analysis (CEDA) approximately on a yearly basis.",
            "removedDataReason": "",
            "keywords": "Met Office, MIDAS, UK, meteorology, soil temperatures",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "superseded",
            "dataPublishedTime": "2023-10-03T16:46:41",
            "doiPublishedTime": "2023-10-03T16:47:21",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 18,
                "bboxName": "MIDAS UK table s geographic domain",
                "eastBoundLongitude": 1.74002,
                "westBoundLongitude": -5.54236,
                "southBoundLatitude": 50.1172,
                "northBoundLatitude": 60.7592
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40682,
                "dataPath": "/badc/ukmo-midas-open/data/uk-soil-temperature-obs/dataset-version-202308/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 4170766533,
                "numberOfFiles": 23747,
                "fileFormat": "Data are BADC-CSV formatted."
            },
            "timePeriod": {
                "ob_id": 11293,
                "startTime": "1900-01-01T09:00:00",
                "endTime": "2022-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 301,
                "explanation": "Data undergo quality checking by the Met Office. State of the data in the quality control process and level of data quality are indicated using version numbers and quality control flagging with the data. See documentation about how to use the quality control flagging and version numbers.\n\nThere are also some known data from commissioning trials in the data, which are given a src_id of 99999. These should be ignored by the user.",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2014-09-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 1227,
                "uuid": "0c787dde18584b3293d4f55daf6ef431",
                "short_code": "acq",
                "title": "Acquisition Process for: UK Soil Temperature Data, Part of the Met Office Integrated Data Archive System (MIDAS)",
                "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Thermometer; PLATFORMS: NCM (National Climate Message) Station Network, HCM (Hourly Climate Messages) Station Network, DLY3208 (Daily observations from Metform 3208) Station Network, AWSHRLY (Automatic Weather Station Hourly values) Station Network;"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                69
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 1186,
                    "uuid": "245df050d57a500c183b88df509f5f5a",
                    "short_code": "proj",
                    "title": "Met Office Integrated Data Archive System (MIDAS)",
                    "abstract": "Since the early days of this century the Met Office has been responsible for maintaining the public memory of the weather. All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                76672,
                76674,
                76675,
                76678,
                76679,
                76680,
                76682,
                76690,
                76694,
                76695,
                76696,
                76697,
                76698,
                76699,
                76700,
                76701,
                76702,
                76703,
                76704,
                76705,
                76706,
                76707,
                76708,
                76709,
                76710,
                76711,
                76712,
                76713,
                76714,
                76715,
                76716
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12712
            ],
            "observationcollection_set": [
                {
                    "ob_id": 26184,
                    "uuid": "dbd451271eb04662beade68da43546e1",
                    "short_code": "coll",
                    "title": "Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)",
                    "abstract": "MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."
                }
            ],
            "responsiblepartyinfo_set": [
                197810,
                197811,
                197812,
                197813,
                197814,
                197815,
                197816,
                197817,
                197818
            ],
            "onlineresource_set": [
                84271,
                84274,
                84272,
                84277,
                84276,
                84278,
                84275,
                84273
            ]
        },
        {
            "ob_id": 40654,
            "uuid": "87eb67c08f5c4518a3723d0ca2d9b4b1",
            "title": "MIDAS Open: UK hourly solar radiation data, v202308",
            "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light. \r\n\r\nFor details about the different measurements made and the limited number of sites making them please see the MIDAS Solar Irradiance table linked to in the online resources section of this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2022.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57",
            "latestDataUpdateTime": "2023-09-29T09:15:37",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data collated by the Met Office and archived in the Met Office's MIDAS database. Data are extracted from a sub-set of available tables and delivered to Centre for Environmental Data Analysis (CEDA) approximately on a yearly basis.",
            "removedDataReason": "",
            "keywords": "Met Office, MIDAS, UK, meteorology, solar irradiance, hourly, global, diffuse, direct",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "superseded",
            "dataPublishedTime": "2023-10-03T16:49:38",
            "doiPublishedTime": "2023-10-03T16:49:24",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 17,
                "bboxName": "",
                "eastBoundLongitude": 1.74002,
                "westBoundLongitude": -8.5636,
                "southBoundLatitude": 49.914,
                "northBoundLatitude": 60.8562
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40681,
                "dataPath": "/badc/ukmo-midas-open/data/uk-radiation-obs/dataset-version-202308/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 3017656255,
                "numberOfFiles": 5562,
                "fileFormat": "Data are BADC-CSV formatted."
            },
            "timePeriod": {
                "ob_id": 11294,
                "startTime": "1947-01-01T00:00:00",
                "endTime": "2022-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 308,
                "explanation": "Data undergo quality checking by the Met Office. State of the data in the quality control process and level of data quality are indicated using version numbers and quality control flagging with the data. See documentation about how to use the quality control flagging and version numbers.\n\nThere are also some known data from commissioning trials in the data, which are given a src_id of 99999. These should be ignored by the user.",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2014-09-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 1240,
                "uuid": "051afeb5c56f46469683e9b8b0bb38b1",
                "short_code": "acq",
                "title": "Acquisition Process for: Global Radiation Observations, Part of the Met Office Integrated Data Archive System (MIDAS)",
                "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Pyranometer, Sunshine Recorder; PLATFORMS: DRADR35 (Daily Radiation Form 35) Station Network, AWSHRLY (Automatic Weather Station Hourly values) Station Network, MODLERAD (Hourly radiation values from Met Office Data Logging Equipment) Station Network, ESAWRADT (Enhanced Synoptic Automatic Weather station RADiaTion) Station Network, HCM (Hourly Climate Messages) Station Network, Land SYNOP (surface synoptic observations) Station Network; "
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                69
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 1186,
                    "uuid": "245df050d57a500c183b88df509f5f5a",
                    "short_code": "proj",
                    "title": "Met Office Integrated Data Archive System (MIDAS)",
                    "abstract": "Since the early days of this century the Met Office has been responsible for maintaining the public memory of the weather. All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                76672,
                76673,
                76674,
                76675,
                76676,
                76677,
                76678,
                76679,
                76680,
                76681,
                76682,
                76683,
                76684,
                76685,
                76686,
                76687,
                76688,
                76689,
                76690,
                76691,
                76692,
                76693,
                76694,
                76695,
                76696,
                76697
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12713
            ],
            "observationcollection_set": [
                {
                    "ob_id": 26184,
                    "uuid": "dbd451271eb04662beade68da43546e1",
                    "short_code": "coll",
                    "title": "Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)",
                    "abstract": "MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."
                }
            ],
            "responsiblepartyinfo_set": [
                197819,
                197820,
                197821,
                197822,
                197823,
                197824,
                197825,
                197826,
                197827
            ],
            "onlineresource_set": [
                84281,
                84282,
                84283,
                84279,
                84280,
                84285,
                84284,
                84287,
                84286
            ]
        },
        {
            "ob_id": 40655,
            "uuid": "c9663d0c525f4b0698f1ec4beae3688e",
            "title": "MIDAS Open: UK hourly weather observation data, v202308",
            "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2022.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57",
            "latestDataUpdateTime": "2024-08-07T01:47:29",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data collated by the Met Office and archived in the Met Office's MIDAS database. Data are extracted from a sub-set of available tables and delivered to Centre for Environmental Data Analysis (CEDA) approximately on a yearly basis.",
            "removedDataReason": "",
            "keywords": "Met Office, MIDAS, UK, meteorology, hourly",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "superseded",
            "dataPublishedTime": "2023-10-03T16:40:53",
            "doiPublishedTime": "2023-10-03T16:40:27",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 18,
                "bboxName": "MIDAS UK table s geographic domain",
                "eastBoundLongitude": 1.74002,
                "westBoundLongitude": -5.54236,
                "southBoundLatitude": 50.1172,
                "northBoundLatitude": 60.7592
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40684,
                "dataPath": "/badc/ukmo-midas-open/data/uk-hourly-weather-obs/dataset-version-202308/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 32757867711,
                "numberOfFiles": 52383,
                "fileFormat": "Data are BADC-CSV formatted."
            },
            "timePeriod": {
                "ob_id": 11295,
                "startTime": "1875-01-01T09:09:00",
                "endTime": "2022-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 300,
                "explanation": "Data undergo quality checking by the Met Office. State of the data in the quality control process and level of data quality are indicated using version numbers and quality control flagging with the data. See documentation about how to use the quality control flagging and version numbers.\n\nThere are also some known data from commissioning trials in the data, which are given a src_id of 99999. These should be ignored by the user.",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2014-09-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 27186,
                "uuid": "336b071077af4805a8394f1402c5c26b",
                "short_code": "acq",
                "title": "Acquisition Process for: UK Hourly Weather Observation Data, Part of the Met Office Integrated Data Archive System (MIDAS) Open version (excluded METARS)",
                "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Thermometer, Visiometer, Station Observer, Sunshine Recorder, Raingauge, Cloud Recorder, Snow Depth Sensor, Present (and Past) Weather Sensor; PLATFORMS: Land SYNOP (surface synoptic observations) Station Network, METAR (MEteorological Terminal Aviation Routine Weather Report) Station Network, NCM (National Climate Message) Station Network, DLY3208 (Daily observations from Metform 3208) Station Network, AWSHRLY (Automatic Weather Station Hourly values) Station Network, HSUN3445 (Hourly values of SUNshine duration from Metform 3445) Station Network;"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                69
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 1186,
                    "uuid": "245df050d57a500c183b88df509f5f5a",
                    "short_code": "proj",
                    "title": "Met Office Integrated Data Archive System (MIDAS)",
                    "abstract": "Since the early days of this century the Met Office has been responsible for maintaining the public memory of the weather. All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                76672,
                76674,
                76675,
                76679,
                76680,
                76682,
                76690,
                76694,
                76695,
                76696,
                76697,
                76709,
                76742,
                76743,
                76744,
                76745,
                76746,
                76747,
                76748,
                76749,
                76750,
                76751,
                76752,
                76753,
                76754,
                76755,
                76756,
                76757,
                76758,
                76759,
                76760,
                76761,
                76762,
                76763,
                76764,
                76765,
                76766,
                76767,
                76768,
                76769,
                76770,
                76771,
                76772,
                76773,
                76774,
                76775,
                76776,
                76777,
                76778,
                76779,
                76780,
                76781,
                76782,
                76783,
                76784,
                76785,
                76786,
                76787,
                76788,
                76789,
                76790,
                76791,
                76792,
                76793,
                76794,
                76795,
                76796,
                76797,
                76798,
                76799,
                76800,
                76801,
                76802,
                76803,
                76804,
                76805,
                76806,
                76807,
                76808,
                76809,
                76810,
                76811,
                76812,
                76813,
                76814,
                76815,
                76816,
                76817,
                76818,
                76819,
                76820,
                76821,
                76822,
                76823,
                76824,
                76825,
                76826,
                76827,
                76828,
                76829,
                76830,
                76831,
                76832,
                76833,
                76834,
                76835,
                76836,
                76837
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12710
            ],
            "observationcollection_set": [
                {
                    "ob_id": 26184,
                    "uuid": "dbd451271eb04662beade68da43546e1",
                    "short_code": "coll",
                    "title": "Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)",
                    "abstract": "MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."
                }
            ],
            "responsiblepartyinfo_set": [
                197828,
                197829,
                197830,
                197831,
                197832,
                197833,
                197834,
                197835,
                197836
            ],
            "onlineresource_set": [
                84288,
                84289,
                84290,
                84291,
                84295,
                84294,
                84293,
                84292
            ]
        },
        {
            "ob_id": 40656,
            "uuid": "68920a29caf44f21be6371d9f87f578b",
            "title": "MIDAS Open: UK mean wind data, v202308",
            "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2022.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.\r\n\r\nFor further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK,  section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57",
            "latestDataUpdateTime": "2023-08-31T10:05:40",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data collated by the Met Office and archived in the Met Office's MIDAS database. Data are extracted from a sub-set of available tables and delivered to Centre for Environmental Data Analysis (CEDA) approximately on a yearly basis.",
            "removedDataReason": "",
            "keywords": "Met Office, MIDAS, UK, meteorology, wind speed, wind direction, gust",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "superseded",
            "dataPublishedTime": "2023-10-03T16:38:21",
            "doiPublishedTime": "2023-10-03T16:37:56",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 17,
                "bboxName": "",
                "eastBoundLongitude": 1.74002,
                "westBoundLongitude": -8.5636,
                "southBoundLatitude": 49.914,
                "northBoundLatitude": 60.8562
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40683,
                "dataPath": "/badc/ukmo-midas-open/data/uk-mean-wind-obs/dataset-version-202308/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 8538744314,
                "numberOfFiles": 14935,
                "fileFormat": "Data are BADC-CSV formatted."
            },
            "timePeriod": {
                "ob_id": 11296,
                "startTime": "1949-01-01T00:00:00",
                "endTime": "2022-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 296,
                "explanation": "Data undergo quality checking by the Met Office. State of the data in the quality control process and level of data quality are indicated using version numbers and quality control flagging with the data. See documentation about how to use the quality control flagging and version numbers.\n\nThere are also some known data from commissioning trials in the data, which are given a src_id of 99999. These should be ignored by the user.",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2014-09-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 1194,
                "uuid": "38b9698404d64725bc8a0b9b6b6f15ae",
                "short_code": "acq",
                "title": "Acquisition Process for: UK Mean Wind Data, Part of the Met Office Integrated Data Archive System (MIDAS)",
                "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Anemometer; PLATFORMS: Land SYNOP (surface synoptic observations) Station Network, HCM (Hourly Climate Messages) Station Network, AWSHRLY (Automatic Weather Station Hourly values) Station Network, DLY3208 (Daily observations from Metform 3208) Station Network, HWND6910 (Hourly WIND from Metform 6910) Station Network, HWNDAUTO (Hourly WiND from AUTOmatic recording devices) Station Network; "
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                69
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 1186,
                    "uuid": "245df050d57a500c183b88df509f5f5a",
                    "short_code": "proj",
                    "title": "Met Office Integrated Data Archive System (MIDAS)",
                    "abstract": "Since the early days of this century the Met Office has been responsible for maintaining the public memory of the weather. All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                76672,
                76674,
                76675,
                76678,
                76679,
                76680,
                76682,
                76683,
                76686,
                76690,
                76694,
                76695,
                76696,
                76697,
                76838,
                76839,
                76840,
                76841,
                76842,
                76843,
                76844,
                76845,
                76846,
                76847,
                76848,
                76849,
                76850,
                76851,
                78250,
                78251,
                78252,
                78253,
                78255,
                78256,
                78257,
                78258,
                78259
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12709
            ],
            "observationcollection_set": [
                {
                    "ob_id": 26184,
                    "uuid": "dbd451271eb04662beade68da43546e1",
                    "short_code": "coll",
                    "title": "Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)",
                    "abstract": "MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."
                }
            ],
            "responsiblepartyinfo_set": [
                197837,
                197838,
                197839,
                197840,
                197841,
                197842,
                197843,
                197844,
                197845
            ],
            "onlineresource_set": [
                84303,
                84302,
                84296,
                84297,
                84298,
                84300,
                84299,
                84301
            ]
        },
        {
            "ob_id": 40659,
            "uuid": "a038af544a604e4495a9d1f217cb03ae",
            "title": "FAAM C335 SERMON flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for SERMON FAAM Aircraft Project project.",
            "creationDate": "2023-09-01T14:03:19.698662",
            "lastUpdatedDate": "2023-09-01T14:03:19.698678",
            "latestDataUpdateTime": "2023-09-01T14:03:19.698686",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "SERMON, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-06-19T14:08:12",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": null,
            "verticalExtent": null,
            "result_field": null,
            "timePeriod": {
                "ob_id": 11283,
                "startTime": "2022-12-20T00:00:00",
                "endTime": "2022-12-20T23:59:59"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [],
            "projects": [
                {
                    "ob_id": 40657,
                    "uuid": "72d29e13bd824c2ca7af5fcdb6e9d7c0",
                    "short_code": "proj",
                    "title": "SERMON FAAM Aircraft Project",
                    "abstract": "The SERMON project utilised the FAAM aircraft. Further details to follow."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                },
                {
                    "ob_id": 40660,
                    "uuid": "793cdd9b0b0142e3af5b6013d2076e22",
                    "short_code": "coll",
                    "title": "SERMON: in-situ airborne observations by the FAAM BAE-146 aircraft",
                    "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for SERMON FAAM Aircraft Project."
                }
            ],
            "responsiblepartyinfo_set": [
                197848,
                197849,
                197850,
                197851,
                197852,
                197853,
                197854,
                197855,
                197856,
                197857
            ],
            "onlineresource_set": [
                84305,
                84306
            ]
        },
        {
            "ob_id": 40671,
            "uuid": "8801a4055e614e8d93e0418f6218eedf",
            "title": "Colour corrected seafloor BioCam images collected from the Darwin Mounds Marine Protected Area during RRS Discovery cruise DY108/109 (2019).",
            "abstract": "The dataset consists of georeferenced colour corrected images collected from the Darwin Mounds Marine Protected Area (MPA) during RRS Discovery cruise DY108/109 in 2019. Images were acquired using the BioCam seafloor imaging device of the University of Southampton mounted on the Autosub6000 Autonomous Underwater Vehicle (AUV) of the National Oceanography Centre. Two strobes, one mounted at the front and one at the back of the AUV, illuminated the seafloor when the colour camera of BioCam, mounted at the centre of the AUV, acquired those images once every 3 s. Images were stored in raw format along with timestamped navigation data (DVL, USBL, GPS). Data from different navigation sensors were fused with the images in post-processing using an extended Kalman smoother (EKS) implemented in oplab-pipeline (https://doi.org/10.5281/zenodo.6623369) The images were then colour corrected using an algorithm implemented in oplab-pipeline. The imaging survey was undertaken to demonstrate the BioCam technology developed by University of Southampton scientists under the NERC OCEANIDS programme's BioCam project (NE/P020887/1) to generate wide area 3D visual reconstructions of seafloor features.",
            "creationDate": "2023-09-01T14:41:48.569670",
            "lastUpdatedDate": "2023-09-01T14:33:28",
            "latestDataUpdateTime": "2024-03-09T01:43:07",
            "updateFrequency": "",
            "dataLineage": "The data are archived on the British Oceanographic Data Centre (BODC)'s space at the Centre for Environmental Data Analysis (CEDA) and assigned a DOI. No quality control procedures were applied by BODC.",
            "removedDataReason": "",
            "keywords": "",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-09-01T14:58:59",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3955,
                "bboxName": "",
                "eastBoundLongitude": -7.354,
                "westBoundLongitude": -7.361,
                "southBoundLatitude": 59.809,
                "northBoundLatitude": 59.818
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40672,
                "dataPath": "/bodc/SMI230145/BioCam_images_DY108-109/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 227326601346,
                "numberOfFiles": 20661,
                "fileFormat": "PNG"
            },
            "timePeriod": {
                "ob_id": 11287,
                "startTime": "2019-09-16T00:00:00",
                "endTime": "2019-09-17T23:59:59"
            },
            "resultQuality": {
                "ob_id": 3732,
                "explanation": "The data are provided as-is with no quality control undertaken by the British Oceanographic Data Centre (BODC). The data suppliers have not indicated if any quality control has been undertaken on these data.",
                "passesTest": true,
                "resultTitle": "BODC Data Quality Statement",
                "date": "2021-07-02"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2526,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                197909,
                197910,
                197908,
                197907,
                197906,
                197928,
                197929,
                197911,
                197930,
                197931
            ],
            "onlineresource_set": []
        },
        {
            "ob_id": 40696,
            "uuid": "1e6795feceb447c086949952303c0e2e",
            "title": "FAAM C341 WESCON flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for WESCON FAAM Aircraft Project project.",
            "creationDate": "2023-09-08T16:25:00.389282",
            "lastUpdatedDate": "2023-09-08T16:25:00.389292",
            "latestDataUpdateTime": "2025-03-21T16:21:25",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "WESCON, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-08-18T13:39:59",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3957,
                "bboxName": "",
                "eastBoundLongitude": -0.48430604,
                "westBoundLongitude": -4.745288,
                "southBoundLatitude": 50.5001,
                "northBoundLatitude": 52.35365
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40695,
                "dataPath": "/badc/faam/data/2023/c341-jun-20",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 7156526666,
                "numberOfFiles": 45,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": {
                "ob_id": 11299,
                "startTime": "2023-06-20T09:06:09",
                "endTime": "2023-06-20T15:41:52"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40697,
                "uuid": "e89d550005bf4c97bf13215e666705cb",
                "short_code": "acq",
                "title": "FAAM Flight C341 Acquisition",
                "abstract": "FAAM Flight C341 Acquisition"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 37501,
                    "uuid": "3c72b5d38e9a499ead03e9e5f140972d",
                    "short_code": "proj",
                    "title": "WesCon: Wessex Convection experiment",
                    "abstract": "WesCon was a UK summer convection experiment in 2023 funded by the Met Office. It focused on understanding dynamical aspects of convection to provide observational data to develop next generation km scale and urban-scale models to improve prediction of convective storms in km scale Numerical Weather Prediction (NWP) and climate models.\r\n\r\nThe emphasis of WesCon was understanding of dynamical processes (particularly updrafts and turbulence) and their interaction with other processes of importance. \r\n\r\nThe project involved the use of the FAAM Bae-146 aircraft, the Jade-Dimona aircraft and groundbased instruments at Cardington, Netheravon, and nearby ground sites. This project ran in conjunction with WOEST: WesCon - Observing the Evolving Structures of Turbulence project involving groundbased, sonde and radar observations.  Both WesCon and WOEST were part of the wider ParaChute programme.\r\n\r\nThe Wessex Convection experiment  (WesCon) took place from during summer 2023"
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50842,
                50851,
                50853,
                50856,
                50857,
                50865,
                50880,
                50888,
                50889,
                50905,
                50907,
                50911,
                50932,
                50933,
                50934,
                50936,
                50937,
                50942,
                50947,
                50948,
                50949,
                50950,
                50952,
                50953,
                50965,
                50967,
                50969,
                50970,
                50971,
                50973,
                50978,
                50979,
                50982,
                50983,
                50984,
                50985,
                50986,
                50987,
                50988,
                50989,
                50990,
                50991,
                50992,
                50993,
                50994,
                50995,
                50996,
                50997,
                50998,
                50999,
                51000,
                51001,
                51002,
                51003,
                51004,
                51005,
                51006,
                51007,
                51008,
                51009,
                51010,
                51011,
                51012,
                51013,
                51014,
                51015,
                51016,
                51017,
                51018,
                51019,
                51020,
                51021,
                51022,
                51023,
                51024,
                51025,
                51026,
                51027,
                51028,
                51029,
                51030,
                51031,
                51032,
                51033,
                51034,
                51035,
                51036,
                51037,
                51038,
                51039,
                51040,
                51041,
                51042,
                51044,
                51045,
                51054,
                51055,
                51056,
                51057,
                51058,
                51059,
                51060,
                51061,
                51062,
                51063,
                51064,
                51065,
                51066,
                51067,
                51068,
                51069,
                51070,
                51071,
                51072,
                51073,
                51074,
                51075,
                51076,
                51077,
                51078,
                51079,
                51080,
                51081,
                51082,
                51083,
                51084,
                51087,
                51098,
                51222,
                51223,
                51225,
                51227,
                51228,
                51229,
                51230,
                51271,
                51272,
                51279,
                51280,
                53949,
                53951,
                53954,
                54967,
                54971,
                54975,
                54976,
                59964,
                59965,
                59966,
                59967,
                59968,
                59969,
                59970,
                59971,
                59972,
                59973,
                59974,
                59975,
                59976,
                60050,
                60051,
                60052,
                60053,
                60054,
                60055,
                60056,
                60057,
                60058,
                60059,
                60060,
                60061,
                60062,
                60063,
                60064,
                60065,
                60066,
                60067,
                60068,
                60069,
                60070,
                60071,
                60072,
                60073,
                60074,
                60075,
                60077,
                60078,
                60079,
                60080,
                60081,
                60087,
                60089,
                60090,
                60091,
                60092,
                60093,
                60094,
                60095,
                60096,
                60097,
                60098,
                60099,
                60100,
                60101,
                60102,
                60103,
                60104,
                60105,
                60106,
                60107,
                60108,
                60109,
                60110,
                60111,
                60112,
                60113,
                60114,
                60115,
                60116,
                60117,
                60118,
                60119,
                60172,
                60173,
                60202,
                60203,
                60204,
                60205,
                60206,
                60207,
                60208,
                60209,
                60210,
                60211,
                60212,
                60213,
                60214,
                60215,
                60216,
                60217,
                60218,
                60219,
                60220,
                60221,
                60222,
                60223,
                60224,
                60225,
                60226,
                60227,
                60228,
                60229,
                60230,
                60231,
                60232,
                60233,
                60234,
                60235,
                60236,
                60237,
                60238,
                60239,
                60240,
                60241,
                60242,
                60243,
                60244,
                60245,
                60246,
                60247,
                60248,
                60249,
                60250,
                60251,
                60252,
                60253,
                60254,
                60255,
                60256,
                60257,
                60258,
                60259,
                60260,
                60261,
                60262,
                60263,
                60264,
                60265,
                60266,
                60267,
                60268,
                60269,
                60270,
                60271,
                60272,
                60273,
                60274,
                60275,
                60276,
                60277,
                60278,
                60279,
                60280,
                60281,
                60282,
                60283,
                60284,
                60287,
                60308,
                60309,
                62304,
                62646,
                62647,
                62648,
                62649,
                62650,
                62651,
                62652,
                62653,
                62654,
                62655,
                62656,
                62657,
                62658,
                62659,
                62660,
                62661,
                62662,
                62663,
                62664,
                62665,
                62666,
                62669,
                62671,
                62678,
                62679,
                65806,
                71784,
                72012,
                73930,
                73931,
                73932,
                73933,
                73934,
                73935,
                73936,
                73937,
                73938,
                73939,
                73940,
                73941,
                73942,
                73943,
                73944,
                73945,
                73946,
                73947,
                73948,
                73949,
                73950,
                73951,
                73952,
                73953,
                73954,
                73955,
                73956,
                73957,
                73958,
                73959,
                73960,
                73961,
                73962,
                73963,
                73964,
                73965,
                73966,
                73967,
                74055,
                74056,
                74057,
                74058,
                74059,
                74060,
                74061,
                74062,
                74063,
                74064,
                74065,
                74066,
                74067,
                74068,
                74069,
                74070,
                74071,
                74072,
                74073,
                74074,
                74075,
                74076,
                74077,
                74078,
                74079,
                74080,
                74081,
                74082,
                74083,
                74084,
                74085,
                74086,
                74087,
                74088,
                74089,
                74090,
                74091,
                74092,
                74093,
                74094,
                74095,
                74096,
                74097,
                74098,
                74099,
                74100,
                74101,
                74102,
                74103,
                74104,
                74105,
                74155,
                74157,
                76041,
                76042,
                76043,
                76044,
                76045,
                76046,
                76047,
                76048,
                76049,
                76050,
                76051,
                76052,
                76053,
                76054
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                },
                {
                    "ob_id": 37504,
                    "uuid": "69bbdb1aedcb40fc9ff3e324b693f8b5",
                    "short_code": "coll",
                    "title": "WesCon: in-situ airborne observations by the FAAM BAE-146 aircraft and Jade-one Dimona aircraft",
                    "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for WesCon: Wessex summertime convection experiment.  \r\nMeteorological in-situ data were collected by a range of instruments on board the FAAM BAe-146 aircraft and the Jade-one Dimona aircraft during a series of flights from May to August 2023 over the southern UK.\r\nThese airborne measurements were made to complement groundbased, sonde and radar observations made for the concurrent WesCon - Observing the Evolving Structures of Turbulence (WOEST) project."
                }
            ],
            "responsiblepartyinfo_set": [
                197973,
                197974,
                197975,
                197976,
                197977,
                197978,
                197979,
                197980,
                197981,
                197982
            ],
            "onlineresource_set": [
                84836,
                84837
            ]
        },
        {
            "ob_id": 40700,
            "uuid": "b3d3ace2c49d41f9ad48db5fa7870c0d",
            "title": "FAAM C342 WESCON flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for WESCON FAAM Aircraft project.",
            "creationDate": "2023-09-08T16:25:52.511531",
            "lastUpdatedDate": "2023-09-08T16:25:52",
            "latestDataUpdateTime": "2025-03-21T16:12:00",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "WESCON, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-08-18T13:40:05",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3958,
                "bboxName": "",
                "eastBoundLongitude": -0.40313503,
                "westBoundLongitude": -3.0796828,
                "southBoundLatitude": 50.831142,
                "northBoundLatitude": 52.379898
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40699,
                "dataPath": "/badc/faam/data/2023/c342-jun-21",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 9073865407,
                "numberOfFiles": 46,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": {
                "ob_id": 11300,
                "startTime": "2023-06-21T07:32:26",
                "endTime": "2023-06-21T14:47:45"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40701,
                "uuid": "89e3daec517f4d6a9a757983c194c2a5",
                "short_code": "acq",
                "title": "FAAM Flight C342 Acquisition",
                "abstract": "FAAM Flight C342 Acquisition"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 37501,
                    "uuid": "3c72b5d38e9a499ead03e9e5f140972d",
                    "short_code": "proj",
                    "title": "WesCon: Wessex Convection experiment",
                    "abstract": "WesCon was a UK summer convection experiment in 2023 funded by the Met Office. It focused on understanding dynamical aspects of convection to provide observational data to develop next generation km scale and urban-scale models to improve prediction of convective storms in km scale Numerical Weather Prediction (NWP) and climate models.\r\n\r\nThe emphasis of WesCon was understanding of dynamical processes (particularly updrafts and turbulence) and their interaction with other processes of importance. \r\n\r\nThe project involved the use of the FAAM Bae-146 aircraft, the Jade-Dimona aircraft and groundbased instruments at Cardington, Netheravon, and nearby ground sites. This project ran in conjunction with WOEST: WesCon - Observing the Evolving Structures of Turbulence project involving groundbased, sonde and radar observations.  Both WesCon and WOEST were part of the wider ParaChute programme.\r\n\r\nThe Wessex Convection experiment  (WesCon) took place from during summer 2023"
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50842,
                50851,
                50853,
                50856,
                50857,
                50865,
                50880,
                50888,
                50889,
                50905,
                50907,
                50911,
                50932,
                50933,
                50934,
                50936,
                50937,
                50942,
                50947,
                50948,
                50949,
                50950,
                50952,
                50953,
                50965,
                50967,
                50969,
                50970,
                50971,
                50973,
                50978,
                50979,
                50982,
                50983,
                50984,
                50985,
                50986,
                50987,
                50988,
                50989,
                50990,
                50991,
                50992,
                50993,
                50994,
                50995,
                50996,
                50997,
                50998,
                50999,
                51000,
                51001,
                51002,
                51003,
                51004,
                51005,
                51006,
                51007,
                51008,
                51009,
                51010,
                51011,
                51012,
                51013,
                51014,
                51015,
                51016,
                51017,
                51018,
                51019,
                51020,
                51021,
                51022,
                51023,
                51024,
                51025,
                51026,
                51027,
                51028,
                51029,
                51030,
                51031,
                51032,
                51033,
                51034,
                51035,
                51036,
                51037,
                51038,
                51039,
                51040,
                51041,
                51042,
                51044,
                51045,
                51054,
                51055,
                51056,
                51057,
                51058,
                51059,
                51060,
                51061,
                51062,
                51063,
                51064,
                51065,
                51066,
                51067,
                51068,
                51069,
                51070,
                51071,
                51072,
                51073,
                51074,
                51075,
                51076,
                51077,
                51078,
                51079,
                51080,
                51081,
                51082,
                51083,
                51084,
                51087,
                51098,
                51222,
                51223,
                51225,
                51227,
                51228,
                51229,
                51230,
                51271,
                51272,
                51279,
                51280,
                53949,
                53951,
                53954,
                54967,
                54971,
                54975,
                54976,
                59964,
                59965,
                59966,
                59967,
                59968,
                59969,
                59970,
                59971,
                59972,
                59973,
                59974,
                59975,
                59976,
                60050,
                60051,
                60052,
                60053,
                60054,
                60055,
                60056,
                60057,
                60058,
                60059,
                60060,
                60061,
                60062,
                60063,
                60064,
                60065,
                60066,
                60067,
                60068,
                60069,
                60070,
                60071,
                60072,
                60073,
                60074,
                60075,
                60077,
                60078,
                60079,
                60080,
                60081,
                60087,
                60089,
                60090,
                60091,
                60092,
                60093,
                60094,
                60095,
                60096,
                60097,
                60098,
                60099,
                60100,
                60101,
                60102,
                60103,
                60104,
                60105,
                60106,
                60107,
                60108,
                60109,
                60110,
                60111,
                60112,
                60113,
                60114,
                60115,
                60116,
                60117,
                60118,
                60119,
                60172,
                60173,
                60202,
                60203,
                60204,
                60205,
                60206,
                60207,
                60208,
                60209,
                60210,
                60211,
                60212,
                60213,
                60214,
                60215,
                60216,
                60217,
                60218,
                60219,
                60220,
                60221,
                60222,
                60223,
                60224,
                60225,
                60226,
                60227,
                60228,
                60229,
                60230,
                60231,
                60232,
                60233,
                60234,
                60235,
                60236,
                60237,
                60238,
                60239,
                60240,
                60241,
                60242,
                60243,
                60244,
                60245,
                60246,
                60247,
                60248,
                60249,
                60250,
                60251,
                60252,
                60253,
                60254,
                60255,
                60256,
                60257,
                60258,
                60259,
                60260,
                60261,
                60262,
                60263,
                60264,
                60265,
                60266,
                60267,
                60268,
                60269,
                60270,
                60271,
                60272,
                60273,
                60274,
                60275,
                60276,
                60277,
                60278,
                60279,
                60280,
                60281,
                60282,
                60283,
                60284,
                60287,
                60308,
                60309,
                62646,
                62647,
                62648,
                62649,
                62650,
                62651,
                62652,
                62653,
                62654,
                62655,
                62656,
                62657,
                62658,
                62659,
                62660,
                62661,
                62662,
                62663,
                62664,
                62665,
                62666,
                62669,
                62671,
                62678,
                62679,
                65806,
                71784,
                72012,
                73930,
                73931,
                73932,
                73933,
                73934,
                73935,
                73936,
                73937,
                73938,
                73939,
                73940,
                73941,
                73942,
                73943,
                73944,
                73945,
                73946,
                73947,
                73948,
                73949,
                73950,
                73951,
                73952,
                73953,
                73954,
                73955,
                73956,
                73957,
                73958,
                73959,
                73960,
                73961,
                73962,
                73963,
                73964,
                73965,
                73966,
                73967,
                74055,
                74056,
                74057,
                74058,
                74059,
                74061,
                74062,
                74063,
                74064,
                74065,
                74066,
                74067,
                74068,
                74069,
                74070,
                74071,
                74072,
                74077,
                74078,
                74079,
                74080,
                74081,
                74082,
                74084,
                74086,
                74087,
                74088,
                74090,
                74092,
                74093,
                74095,
                74096,
                74097,
                74099,
                74100,
                74101,
                74102,
                74103,
                74104,
                74105,
                74152,
                74153,
                74154,
                74155,
                74156,
                74157,
                74158,
                74159,
                75683,
                75686,
                76041,
                76042,
                76043,
                76044,
                76045,
                76046,
                76047,
                76048,
                76049,
                76050,
                76051,
                76052,
                76053,
                76054,
                79241,
                79245,
                79246,
                85881
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                },
                {
                    "ob_id": 37504,
                    "uuid": "69bbdb1aedcb40fc9ff3e324b693f8b5",
                    "short_code": "coll",
                    "title": "WesCon: in-situ airborne observations by the FAAM BAE-146 aircraft and Jade-one Dimona aircraft",
                    "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for WesCon: Wessex summertime convection experiment.  \r\nMeteorological in-situ data were collected by a range of instruments on board the FAAM BAe-146 aircraft and the Jade-one Dimona aircraft during a series of flights from May to August 2023 over the southern UK.\r\nThese airborne measurements were made to complement groundbased, sonde and radar observations made for the concurrent WesCon - Observing the Evolving Structures of Turbulence (WOEST) project."
                }
            ],
            "responsiblepartyinfo_set": [
                197989,
                197990,
                197991,
                197992,
                197993,
                197994,
                197995,
                197996,
                197997,
                197998
            ],
            "onlineresource_set": [
                84839,
                84840
            ]
        },
        {
            "ob_id": 40704,
            "uuid": "769fced3cddd40ddbf0f48a7b98ec511",
            "title": "FAAM C340 WESCON flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for WESCON FAAM Aircraft project.",
            "creationDate": "2023-09-08T16:29:50.569026",
            "lastUpdatedDate": "2023-09-08T16:29:50",
            "latestDataUpdateTime": "2025-03-21T16:21:13",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "WESCON, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-08-18T13:39:54",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3959,
                "bboxName": "",
                "eastBoundLongitude": -0.44026318,
                "westBoundLongitude": -3.1739724,
                "southBoundLatitude": 50.7947,
                "northBoundLatitude": 52.374634
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40703,
                "dataPath": "/badc/faam/data/2023/c340-jun-19",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 7288571594,
                "numberOfFiles": 44,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": {
                "ob_id": 11301,
                "startTime": "2023-06-19T06:51:53",
                "endTime": "2023-06-19T13:35:08"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40705,
                "uuid": "e6de81ba930d434e9129dbd8dc6431df",
                "short_code": "acq",
                "title": "FAAM Flight C340 Acquisition",
                "abstract": "FAAM Flight C340 Acquisition"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 37501,
                    "uuid": "3c72b5d38e9a499ead03e9e5f140972d",
                    "short_code": "proj",
                    "title": "WesCon: Wessex Convection experiment",
                    "abstract": "WesCon was a UK summer convection experiment in 2023 funded by the Met Office. It focused on understanding dynamical aspects of convection to provide observational data to develop next generation km scale and urban-scale models to improve prediction of convective storms in km scale Numerical Weather Prediction (NWP) and climate models.\r\n\r\nThe emphasis of WesCon was understanding of dynamical processes (particularly updrafts and turbulence) and their interaction with other processes of importance. \r\n\r\nThe project involved the use of the FAAM Bae-146 aircraft, the Jade-Dimona aircraft and groundbased instruments at Cardington, Netheravon, and nearby ground sites. This project ran in conjunction with WOEST: WesCon - Observing the Evolving Structures of Turbulence project involving groundbased, sonde and radar observations.  Both WesCon and WOEST were part of the wider ParaChute programme.\r\n\r\nThe Wessex Convection experiment  (WesCon) took place from during summer 2023"
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50842,
                50851,
                50853,
                50856,
                50857,
                50865,
                50880,
                50888,
                50889,
                50905,
                50907,
                50911,
                50932,
                50933,
                50934,
                50936,
                50937,
                50942,
                50947,
                50948,
                50949,
                50950,
                50952,
                50953,
                50965,
                50967,
                50969,
                50970,
                50971,
                50973,
                50978,
                50979,
                50982,
                50983,
                50984,
                50985,
                50986,
                50987,
                50988,
                50989,
                50990,
                50991,
                50992,
                50993,
                50994,
                50995,
                50996,
                50997,
                50998,
                50999,
                51000,
                51001,
                51002,
                51003,
                51004,
                51005,
                51006,
                51007,
                51008,
                51009,
                51010,
                51011,
                51012,
                51013,
                51014,
                51015,
                51016,
                51017,
                51018,
                51019,
                51020,
                51021,
                51022,
                51023,
                51024,
                51025,
                51026,
                51027,
                51028,
                51029,
                51030,
                51031,
                51032,
                51033,
                51034,
                51035,
                51036,
                51037,
                51038,
                51039,
                51040,
                51041,
                51042,
                51044,
                51045,
                51054,
                51055,
                51056,
                51057,
                51058,
                51059,
                51060,
                51061,
                51062,
                51063,
                51064,
                51065,
                51066,
                51067,
                51068,
                51069,
                51070,
                51071,
                51072,
                51073,
                51074,
                51075,
                51076,
                51077,
                51078,
                51079,
                51080,
                51081,
                51082,
                51083,
                51084,
                51087,
                51098,
                51222,
                51223,
                51225,
                51227,
                51228,
                51229,
                51230,
                51271,
                51272,
                51279,
                51280,
                53949,
                53951,
                53954,
                54967,
                54971,
                54975,
                54976,
                59964,
                59965,
                59966,
                59967,
                59968,
                59969,
                59970,
                59971,
                59972,
                59973,
                59974,
                59975,
                59976,
                60050,
                60051,
                60052,
                60053,
                60054,
                60055,
                60056,
                60057,
                60058,
                60059,
                60060,
                60061,
                60062,
                60063,
                60064,
                60065,
                60066,
                60067,
                60068,
                60069,
                60070,
                60071,
                60072,
                60073,
                60074,
                60075,
                60077,
                60078,
                60079,
                60080,
                60081,
                60087,
                60089,
                60090,
                60091,
                60092,
                60093,
                60094,
                60095,
                60096,
                60097,
                60098,
                60099,
                60100,
                60101,
                60102,
                60103,
                60104,
                60105,
                60106,
                60107,
                60108,
                60109,
                60110,
                60111,
                60112,
                60113,
                60114,
                60115,
                60116,
                60117,
                60118,
                60119,
                60172,
                60173,
                60202,
                60203,
                60204,
                60205,
                60206,
                60207,
                60208,
                60209,
                60210,
                60211,
                60212,
                60213,
                60214,
                60215,
                60216,
                60217,
                60218,
                60219,
                60220,
                60221,
                60222,
                60223,
                60224,
                60225,
                60226,
                60227,
                60228,
                60229,
                60230,
                60231,
                60232,
                60233,
                60234,
                60235,
                60236,
                60237,
                60238,
                60239,
                60240,
                60241,
                60242,
                60243,
                60244,
                60245,
                60246,
                60247,
                60248,
                60249,
                60250,
                60251,
                60252,
                60253,
                60254,
                60255,
                60256,
                60257,
                60258,
                60259,
                60260,
                60261,
                60262,
                60263,
                60264,
                60265,
                60266,
                60267,
                60268,
                60269,
                60270,
                60271,
                60272,
                60273,
                60274,
                60275,
                60276,
                60277,
                60278,
                60279,
                60280,
                60281,
                60282,
                60283,
                60284,
                60287,
                62646,
                62647,
                62648,
                62649,
                62650,
                62651,
                62652,
                62653,
                62654,
                62655,
                62656,
                62657,
                62658,
                62659,
                62660,
                62661,
                62662,
                62663,
                62664,
                62665,
                62666,
                62669,
                62671,
                62678,
                65806,
                71784,
                72012,
                73930,
                73931,
                73932,
                73933,
                73934,
                73935,
                73936,
                73937,
                73938,
                73939,
                73940,
                73941,
                73942,
                73943,
                73944,
                73945,
                73946,
                73947,
                73948,
                73949,
                73950,
                73951,
                73952,
                73953,
                73954,
                73955,
                73956,
                73957,
                73958,
                73959,
                73960,
                73961,
                73962,
                73963,
                73964,
                73965,
                73966,
                73967,
                74155,
                74157,
                76041,
                76042,
                76043,
                76044,
                76045,
                76046,
                76047,
                76048,
                76049,
                76050,
                76051,
                76052,
                76053,
                76054
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                },
                {
                    "ob_id": 37504,
                    "uuid": "69bbdb1aedcb40fc9ff3e324b693f8b5",
                    "short_code": "coll",
                    "title": "WesCon: in-situ airborne observations by the FAAM BAE-146 aircraft and Jade-one Dimona aircraft",
                    "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for WesCon: Wessex summertime convection experiment.  \r\nMeteorological in-situ data were collected by a range of instruments on board the FAAM BAe-146 aircraft and the Jade-one Dimona aircraft during a series of flights from May to August 2023 over the southern UK.\r\nThese airborne measurements were made to complement groundbased, sonde and radar observations made for the concurrent WesCon - Observing the Evolving Structures of Turbulence (WOEST) project."
                }
            ],
            "responsiblepartyinfo_set": [
                198005,
                198006,
                198007,
                198008,
                198009,
                198010,
                198011,
                198012,
                198013,
                198014
            ],
            "onlineresource_set": [
                84842,
                84843
            ]
        },
        {
            "ob_id": 40716,
            "uuid": "99d9e44091cf4f429faaaa0c9212dea1",
            "title": "FAAM C339 WESCON flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for WESCON FAAM Aircraft project.",
            "creationDate": "2023-09-08T16:37:23.696522",
            "lastUpdatedDate": "2023-09-08T16:37:23",
            "latestDataUpdateTime": "2025-05-28T13:15:06",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "WESCON, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-09-02T00:40:53",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3964,
                "bboxName": "",
                "eastBoundLongitude": -0.46491534,
                "westBoundLongitude": -3.4201708,
                "southBoundLatitude": 51.08429,
                "northBoundLatitude": 52.374027
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40715,
                "dataPath": "/badc/faam/data/2023/c339-jun-15",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 6110698126,
                "numberOfFiles": 42,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": {
                "ob_id": 11306,
                "startTime": "2023-06-15T06:59:50",
                "endTime": "2023-06-15T13:05:19"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40717,
                "uuid": "8d55a62d1b6b46508b2378d9082909d5",
                "short_code": "acq",
                "title": "FAAM Flight C339 Acquisition",
                "abstract": "FAAM Flight C339 Acquisition"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 37501,
                    "uuid": "3c72b5d38e9a499ead03e9e5f140972d",
                    "short_code": "proj",
                    "title": "WesCon: Wessex Convection experiment",
                    "abstract": "WesCon was a UK summer convection experiment in 2023 funded by the Met Office. It focused on understanding dynamical aspects of convection to provide observational data to develop next generation km scale and urban-scale models to improve prediction of convective storms in km scale Numerical Weather Prediction (NWP) and climate models.\r\n\r\nThe emphasis of WesCon was understanding of dynamical processes (particularly updrafts and turbulence) and their interaction with other processes of importance. \r\n\r\nThe project involved the use of the FAAM Bae-146 aircraft, the Jade-Dimona aircraft and groundbased instruments at Cardington, Netheravon, and nearby ground sites. This project ran in conjunction with WOEST: WesCon - Observing the Evolving Structures of Turbulence project involving groundbased, sonde and radar observations.  Both WesCon and WOEST were part of the wider ParaChute programme.\r\n\r\nThe Wessex Convection experiment  (WesCon) took place from during summer 2023"
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50851,
                50853,
                50856,
                50857,
                50934,
                50936,
                50937,
                50942,
                50949,
                50950,
                50952,
                50953,
                50965,
                50967,
                50969,
                50970,
                50971,
                50973,
                50978,
                50979,
                50982,
                50983,
                50984,
                50985,
                50986,
                50987,
                50988,
                50989,
                50990,
                50991,
                50992,
                50993,
                50994,
                50995,
                50996,
                50997,
                50998,
                50999,
                51000,
                51001,
                51002,
                51003,
                51004,
                51005,
                51006,
                51007,
                51008,
                51009,
                51010,
                51011,
                51012,
                51013,
                51014,
                51015,
                51016,
                51017,
                51018,
                51019,
                51020,
                51021,
                51022,
                51023,
                51024,
                51025,
                51026,
                51027,
                51028,
                51029,
                51030,
                51031,
                51032,
                51033,
                51034,
                51035,
                51036,
                51037,
                51038,
                51039,
                51040,
                51041,
                51042,
                51044,
                51045,
                51054,
                51055,
                51056,
                51057,
                51058,
                51059,
                51060,
                51061,
                51062,
                51063,
                51064,
                51065,
                51066,
                51067,
                51068,
                51069,
                51070,
                51071,
                51072,
                51073,
                51074,
                51075,
                51076,
                51077,
                51078,
                51079,
                51080,
                51081,
                51082,
                51083,
                51084,
                51087,
                51222,
                51223,
                51225,
                51227,
                51228,
                51229,
                51230,
                51271,
                51272,
                51279,
                51280,
                53949,
                53951,
                53954,
                54967,
                54971,
                54975,
                54976,
                59964,
                59965,
                59966,
                59967,
                59968,
                59969,
                59970,
                59971,
                59972,
                59973,
                59974,
                59975,
                59976,
                60050,
                60051,
                60052,
                60053,
                60054,
                60055,
                60056,
                60057,
                60058,
                60059,
                60060,
                60061,
                60062,
                60063,
                60064,
                60065,
                60066,
                60067,
                60068,
                60069,
                60070,
                60071,
                60072,
                60073,
                60074,
                60075,
                60077,
                60078,
                60079,
                60080,
                60081,
                60087,
                60089,
                60090,
                60091,
                60092,
                60093,
                60094,
                60095,
                60096,
                60097,
                60098,
                60099,
                60100,
                60101,
                60102,
                60103,
                60104,
                60105,
                60106,
                60107,
                60108,
                60109,
                60110,
                60111,
                60112,
                60113,
                60114,
                60115,
                60116,
                60117,
                60118,
                60119,
                60172,
                60173,
                60202,
                60203,
                60204,
                60205,
                60206,
                60207,
                60208,
                60209,
                60210,
                60211,
                60212,
                60213,
                60214,
                60215,
                60216,
                60217,
                60218,
                60219,
                60220,
                60221,
                60222,
                60223,
                60224,
                60225,
                60226,
                60227,
                60228,
                60229,
                60230,
                60231,
                60232,
                60233,
                60234,
                60235,
                60236,
                60237,
                60238,
                60239,
                60240,
                60241,
                60242,
                60243,
                60244,
                60245,
                60246,
                60247,
                60248,
                60249,
                60250,
                60251,
                60252,
                60253,
                60254,
                60255,
                60256,
                60257,
                60258,
                60259,
                60260,
                60261,
                60262,
                60263,
                60264,
                60265,
                60266,
                60267,
                60268,
                60269,
                60270,
                60271,
                60272,
                60273,
                60274,
                60275,
                60276,
                60277,
                60278,
                60279,
                60280,
                60281,
                60282,
                60283,
                60284,
                60287,
                60308,
                60309,
                62646,
                62647,
                62648,
                62649,
                62650,
                62651,
                62652,
                62653,
                62654,
                62655,
                62656,
                62657,
                62658,
                62659,
                62660,
                62661,
                62662,
                62663,
                62664,
                62665,
                62666,
                62669,
                62671,
                62678,
                62679,
                72012,
                73930,
                73931,
                73932,
                73933,
                73934,
                73935,
                73936,
                73937,
                73938,
                73939,
                73940,
                73941,
                73942,
                73943,
                73944,
                73945,
                73946,
                73947,
                73948,
                73949,
                73950,
                73951,
                73952,
                73953,
                73954,
                73955,
                73956,
                73957,
                73958,
                73959,
                73960,
                73961,
                73962,
                73963,
                73964,
                73965,
                73966,
                73967,
                74055,
                74056,
                74057,
                74058,
                74059,
                74061,
                74062,
                74063,
                74064,
                74065,
                74066,
                74067,
                74068,
                74069,
                74070,
                74071,
                74072,
                74073,
                74074,
                74076,
                74077,
                74078,
                74079,
                74080,
                74081,
                74082,
                74084,
                74086,
                74087,
                74088,
                74089,
                74090,
                74091,
                74092,
                74093,
                74095,
                74096,
                74097,
                74098,
                74099,
                74100,
                74101,
                74102,
                74103,
                74104,
                74105,
                74152,
                74153,
                74154,
                74155,
                74156,
                74157,
                74158,
                74159
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                },
                {
                    "ob_id": 37504,
                    "uuid": "69bbdb1aedcb40fc9ff3e324b693f8b5",
                    "short_code": "coll",
                    "title": "WesCon: in-situ airborne observations by the FAAM BAE-146 aircraft and Jade-one Dimona aircraft",
                    "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for WesCon: Wessex summertime convection experiment.  \r\nMeteorological in-situ data were collected by a range of instruments on board the FAAM BAe-146 aircraft and the Jade-one Dimona aircraft during a series of flights from May to August 2023 over the southern UK.\r\nThese airborne measurements were made to complement groundbased, sonde and radar observations made for the concurrent WesCon - Observing the Evolving Structures of Turbulence (WOEST) project."
                }
            ],
            "responsiblepartyinfo_set": [
                198021,
                198022,
                198023,
                198024,
                198025,
                198026,
                198027,
                198028,
                198029,
                198030
            ],
            "onlineresource_set": [
                84845,
                84846
            ]
        },
        {
            "ob_id": 40720,
            "uuid": "5c6b135746fc4201a9867f76aa59b542",
            "title": "FAAM C338 Instrument Test flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects (Instrument) project.",
            "creationDate": "2023-09-08T16:38:57.631052",
            "lastUpdatedDate": "2023-09-08T16:38:57",
            "latestDataUpdateTime": "2023-06-29T12:15:42",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "Instrument, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-09-02T00:40:51",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3965,
                "bboxName": "",
                "eastBoundLongitude": -0.409242,
                "westBoundLongitude": -4.088246,
                "southBoundLatitude": 50.901066,
                "northBoundLatitude": 52.373226
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40719,
                "dataPath": "/badc/faam/data/2023/c338-may-16",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 4054420538,
                "numberOfFiles": 25,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": {
                "ob_id": 11307,
                "startTime": "2023-05-16T07:32:07",
                "endTime": "2023-05-16T12:28:01"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40721,
                "uuid": "1664b1e788034345b36c626d9412e173",
                "short_code": "acq",
                "title": "FAAM Flight C338 Acquisition",
                "abstract": "FAAM Flight C338 Acquisition"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 12946,
                    "uuid": "718a0508440b4ee4b965c6d4e5843bc5",
                    "short_code": "proj",
                    "title": "FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects.",
                    "abstract": "Some flights  made on board the the FAAM (Facility for Airborne Atmospheric Measurement)  BAe-146 aircraft are for instrument testing, calibration or training purposes, as well as non-science demonstration flights. This flying differs from regular flights which are conducted for a specific project."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50851,
                50853,
                50856,
                50857,
                50934,
                50936,
                50937,
                50942,
                50949,
                50950,
                50952,
                50953,
                50965,
                51222,
                51223,
                51225,
                51227,
                51228,
                51229,
                51230,
                51271,
                51272,
                51279,
                51280,
                53949,
                53951,
                53954,
                59964,
                59965,
                59966,
                59967,
                59968,
                59969,
                59970,
                59971,
                59972,
                59973,
                59974,
                59975,
                59976,
                60050,
                60051,
                60052,
                60053,
                60054,
                60055,
                60056,
                60057,
                60058,
                60059,
                60060,
                60061,
                60062,
                60063,
                60064,
                60065,
                60066,
                60067,
                60068,
                60069,
                60070,
                60071,
                60072,
                60073,
                60074,
                60075,
                60077,
                60078,
                60079,
                60080,
                60081,
                60087,
                60172,
                60173,
                60202,
                60203,
                60204,
                60205,
                60206,
                60207,
                60208,
                60209,
                60210,
                60211,
                60212,
                60213,
                60214,
                60215,
                60216,
                60217,
                60218,
                60219,
                60220,
                60221,
                60222,
                60223,
                60224,
                60225,
                60226,
                60227,
                60228,
                60229,
                60230,
                60231,
                60232,
                60233,
                60234,
                60235,
                60236,
                60237,
                60238,
                60239,
                60240,
                60241,
                60242,
                60243,
                60244,
                60245,
                60246,
                60247,
                60248,
                60249,
                60250,
                60251,
                60252,
                60253,
                60254,
                60255,
                60256,
                60257,
                60258,
                60259,
                60260,
                60261,
                60262,
                60263,
                60264,
                60265,
                60266,
                60267,
                60268,
                60269,
                60270,
                60271,
                60272,
                60273,
                60274,
                60275,
                60276,
                60277,
                60278,
                60279,
                60280,
                60281,
                60282,
                60283,
                60284,
                60287,
                62646,
                62647,
                62648,
                62649,
                62650,
                62651,
                62652,
                62653,
                62654,
                62655,
                62656,
                62657,
                62658,
                62659,
                62660,
                62661,
                62662,
                62663,
                62664,
                62665,
                62666,
                72012
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                }
            ],
            "responsiblepartyinfo_set": [
                198037,
                198038,
                198039,
                198040,
                198041,
                198042,
                198043,
                217187,
                198045
            ],
            "onlineresource_set": [
                84848,
                84849
            ]
        },
        {
            "ob_id": 40724,
            "uuid": "4d0cd1c3f0784da9b250fc8b3db9299c",
            "title": "FAAM C337 Instrument Test flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects (Instrument) project.",
            "creationDate": "2023-09-08T16:39:28.107881",
            "lastUpdatedDate": "2023-09-08T16:39:28",
            "latestDataUpdateTime": "2023-06-19T21:15:53",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "Instrument, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-09-02T00:40:48",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3966,
                "bboxName": "",
                "eastBoundLongitude": -0.44781995,
                "westBoundLongitude": -5.9241138,
                "southBoundLatitude": 50.621777,
                "northBoundLatitude": 52.3398
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40723,
                "dataPath": "/badc/faam/data/2023/c337-may-10",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 5907571889,
                "numberOfFiles": 30,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": {
                "ob_id": 11308,
                "startTime": "2023-05-10T09:05:25",
                "endTime": "2023-05-10T15:22:45"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40725,
                "uuid": "a63fec2d49174d9bac0bc1e3f6bdb57f",
                "short_code": "acq",
                "title": "FAAM Flight C337 Acquisition",
                "abstract": "FAAM Flight C337 Acquisition"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 12946,
                    "uuid": "718a0508440b4ee4b965c6d4e5843bc5",
                    "short_code": "proj",
                    "title": "FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects.",
                    "abstract": "Some flights  made on board the the FAAM (Facility for Airborne Atmospheric Measurement)  BAe-146 aircraft are for instrument testing, calibration or training purposes, as well as non-science demonstration flights. This flying differs from regular flights which are conducted for a specific project."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50851,
                50853,
                50856,
                50857,
                50934,
                50936,
                50937,
                50942,
                50949,
                50950,
                50952,
                50953,
                50965,
                51222,
                51223,
                51225,
                51227,
                51228,
                51229,
                51230,
                51271,
                51272,
                51279,
                51280,
                53949,
                53951,
                53954,
                59964,
                59965,
                59966,
                59967,
                59968,
                59969,
                59970,
                59971,
                59972,
                59973,
                59974,
                59975,
                59976,
                60050,
                60051,
                60052,
                60053,
                60054,
                60055,
                60056,
                60057,
                60058,
                60059,
                60060,
                60061,
                60062,
                60063,
                60064,
                60065,
                60066,
                60067,
                60068,
                60069,
                60070,
                60071,
                60072,
                60073,
                60074,
                60075,
                60077,
                60078,
                60079,
                60080,
                60081,
                60087,
                60172,
                60173,
                60202,
                60203,
                60204,
                60205,
                60206,
                60207,
                60208,
                60209,
                60210,
                60211,
                60212,
                60213,
                60214,
                60215,
                60216,
                60217,
                60218,
                60219,
                60220,
                60221,
                60222,
                60223,
                60224,
                60225,
                60226,
                60227,
                60228,
                60229,
                60230,
                60231,
                60232,
                60233,
                60234,
                60235,
                60236,
                60237,
                60238,
                60239,
                60240,
                60241,
                60242,
                60243,
                60244,
                60245,
                60246,
                60247,
                60248,
                60249,
                60250,
                60251,
                60252,
                60253,
                60254,
                60255,
                60256,
                60257,
                60258,
                60259,
                60260,
                60261,
                60262,
                60263,
                60264,
                60265,
                60266,
                60267,
                60268,
                60269,
                60270,
                60271,
                60272,
                60273,
                60274,
                60275,
                60276,
                60277,
                60278,
                60279,
                60280,
                60281,
                60282,
                60283,
                60284,
                60287,
                62646,
                62647,
                62648,
                62649,
                62650,
                62651,
                62652,
                62653,
                62654,
                62655,
                62656,
                62657,
                62658,
                62659,
                62660,
                62661,
                62662,
                62663,
                62664,
                62665,
                62666,
                72012
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                }
            ],
            "responsiblepartyinfo_set": [
                198053,
                198054,
                198055,
                198056,
                198057,
                198058,
                198059,
                198060,
                198061,
                198062
            ],
            "onlineresource_set": [
                84852,
                84851
            ]
        },
        {
            "ob_id": 40728,
            "uuid": "0e16e853a28a4175a6f18ae622800333",
            "title": "FAAM C336 Instrument Test flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects (Instrument) project.",
            "creationDate": "2023-09-08T16:39:47.518327",
            "lastUpdatedDate": "2023-09-08T16:39:47",
            "latestDataUpdateTime": "2024-03-11T14:21:53",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "Instrument, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-09-02T00:40:46",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3967,
                "bboxName": "",
                "eastBoundLongitude": 0.95761174,
                "westBoundLongitude": -1.0788852,
                "southBoundLatitude": 51.938637,
                "northBoundLatitude": 53.90012
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40727,
                "dataPath": "/badc/faam/data/2023/c336-feb-23",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 5836610446,
                "numberOfFiles": 37,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": {
                "ob_id": 11309,
                "startTime": "2023-02-23T10:00:47",
                "endTime": "2023-02-23T16:18:09"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40729,
                "uuid": "d19522dc3f96498e975f3ec6605cc9cd",
                "short_code": "acq",
                "title": "FAAM Flight C336 Acquisition",
                "abstract": "FAAM Flight C336 Acquisition"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 12946,
                    "uuid": "718a0508440b4ee4b965c6d4e5843bc5",
                    "short_code": "proj",
                    "title": "FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects.",
                    "abstract": "Some flights  made on board the the FAAM (Facility for Airborne Atmospheric Measurement)  BAe-146 aircraft are for instrument testing, calibration or training purposes, as well as non-science demonstration flights. This flying differs from regular flights which are conducted for a specific project."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50851,
                50853,
                50856,
                50857,
                50934,
                50936,
                50937,
                50942,
                50949,
                50950,
                50952,
                50953,
                50965,
                50967,
                50969,
                50970,
                50971,
                50973,
                50978,
                50979,
                50982,
                50983,
                50984,
                50985,
                50986,
                50987,
                50988,
                50989,
                50990,
                50991,
                50992,
                50993,
                50994,
                50995,
                50996,
                50997,
                50998,
                50999,
                51000,
                51001,
                51002,
                51003,
                51004,
                51005,
                51006,
                51007,
                51008,
                51009,
                51010,
                51011,
                51012,
                51013,
                51014,
                51015,
                51016,
                51017,
                51018,
                51019,
                51020,
                51021,
                51022,
                51023,
                51024,
                51025,
                51026,
                51027,
                51028,
                51029,
                51030,
                51031,
                51032,
                51033,
                51034,
                51035,
                51036,
                51037,
                51038,
                51039,
                51040,
                51041,
                51042,
                51044,
                51045,
                51054,
                51055,
                51056,
                51057,
                51058,
                51059,
                51060,
                51061,
                51062,
                51063,
                51064,
                51065,
                51066,
                51067,
                51068,
                51069,
                51070,
                51071,
                51072,
                51073,
                51074,
                51075,
                51076,
                51077,
                51078,
                51079,
                51080,
                51081,
                51082,
                51083,
                51084,
                51087,
                51222,
                51223,
                51225,
                51227,
                51228,
                51229,
                51230,
                51271,
                51272,
                51279,
                51280,
                53949,
                53951,
                53954,
                54967,
                54971,
                54975,
                54976,
                59964,
                59965,
                59966,
                59967,
                59968,
                59969,
                59970,
                59971,
                59972,
                59973,
                59974,
                59975,
                60050,
                60051,
                60052,
                60053,
                60054,
                60057,
                60058,
                60059,
                60060,
                60061,
                60062,
                60063,
                60064,
                60065,
                60066,
                60069,
                60070,
                60071,
                60072,
                60073,
                60074,
                60075,
                60077,
                60078,
                60079,
                60080,
                60081,
                60087,
                60089,
                60090,
                60091,
                60092,
                60093,
                60094,
                60095,
                60096,
                60097,
                60098,
                60099,
                60100,
                60101,
                60102,
                60103,
                60104,
                60105,
                60106,
                60107,
                60108,
                60109,
                60110,
                60111,
                60112,
                60113,
                60114,
                60115,
                60116,
                60117,
                60118,
                60119,
                60172,
                60173,
                60202,
                60203,
                60204,
                60205,
                60206,
                60207,
                60208,
                60209,
                60210,
                60211,
                60212,
                60213,
                60214,
                60215,
                60216,
                60217,
                60218,
                60219,
                60220,
                60221,
                60222,
                60223,
                60224,
                60225,
                60226,
                60227,
                60228,
                60229,
                60230,
                60231,
                60232,
                60233,
                60234,
                60235,
                60236,
                60237,
                60238,
                60239,
                60240,
                60245,
                60246,
                60247,
                60248,
                60249,
                60250,
                60251,
                60252,
                60253,
                60254,
                60255,
                60256,
                60257,
                60258,
                60259,
                60260,
                60261,
                60262,
                60263,
                60264,
                60265,
                60266,
                60267,
                60268,
                60269,
                60270,
                60271,
                60272,
                60273,
                60274,
                60275,
                60276,
                60277,
                60278,
                60279,
                60280,
                60281,
                60282,
                60283,
                60284,
                60287,
                62646,
                62647,
                62648,
                62650,
                62651,
                62652,
                62653,
                62654,
                62655,
                62656,
                62657,
                62658,
                62659,
                62660,
                62661,
                62662,
                62663,
                62664,
                62665,
                62666,
                62669,
                62671,
                62678,
                62679,
                63157,
                63158,
                63159,
                63160,
                72012,
                74056,
                74063,
                74067,
                74068,
                74071,
                74078,
                74081,
                74084,
                74086,
                74087,
                74088,
                74090,
                74092,
                74095,
                74096,
                74097,
                74103,
                74104,
                74105,
                74120,
                74121,
                74122,
                74123,
                74124,
                74125,
                74126,
                74127,
                74128,
                74129,
                74130,
                74131,
                74132,
                74133,
                74134,
                74135,
                74136,
                74137,
                74138,
                74139,
                74140,
                74141,
                74142,
                74143,
                74144,
                74145,
                74146,
                74147,
                74148,
                74149,
                74150,
                74151,
                74152,
                74154,
                74156,
                74158,
                74159,
                74160,
                74161,
                74504,
                74505,
                74507,
                74511,
                74512,
                74513,
                74514,
                74515,
                74516,
                75674,
                75675,
                75678,
                75679,
                75680,
                75681,
                75682,
                75683,
                75684,
                75685,
                75686,
                82404
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                }
            ],
            "responsiblepartyinfo_set": [
                198069,
                198070,
                198071,
                198072,
                198073,
                198074,
                198075,
                198076,
                198077,
                198078
            ],
            "onlineresource_set": [
                84855,
                84854
            ]
        },
        {
            "ob_id": 40732,
            "uuid": "e0ffcf621c1645e2aae6598885408c27",
            "title": "FAAM C343 WESCON flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for WESCON FAAM Aircraft project.",
            "creationDate": "2023-09-08T16:40:18.880405",
            "lastUpdatedDate": "2023-09-08T16:40:18",
            "latestDataUpdateTime": "2025-03-21T16:12:13",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "WESCON, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-08-18T13:40:11",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3968,
                "bboxName": "",
                "eastBoundLongitude": -0.40628138,
                "westBoundLongitude": -3.042931,
                "southBoundLatitude": 50.82463,
                "northBoundLatitude": 52.378803
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40731,
                "dataPath": "/badc/faam/data/2023/c343-jul-04",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 7760796232,
                "numberOfFiles": 42,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": {
                "ob_id": 11310,
                "startTime": "2023-07-04T08:05:04",
                "endTime": "2023-07-04T14:25:37"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40733,
                "uuid": "85a1ed7a567940d197fb7fac4a5847f6",
                "short_code": "acq",
                "title": "FAAM Flight C343 Acquisition",
                "abstract": "FAAM Flight C343 Acquisition"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 37501,
                    "uuid": "3c72b5d38e9a499ead03e9e5f140972d",
                    "short_code": "proj",
                    "title": "WesCon: Wessex Convection experiment",
                    "abstract": "WesCon was a UK summer convection experiment in 2023 funded by the Met Office. It focused on understanding dynamical aspects of convection to provide observational data to develop next generation km scale and urban-scale models to improve prediction of convective storms in km scale Numerical Weather Prediction (NWP) and climate models.\r\n\r\nThe emphasis of WesCon was understanding of dynamical processes (particularly updrafts and turbulence) and their interaction with other processes of importance. \r\n\r\nThe project involved the use of the FAAM Bae-146 aircraft, the Jade-Dimona aircraft and groundbased instruments at Cardington, Netheravon, and nearby ground sites. This project ran in conjunction with WOEST: WesCon - Observing the Evolving Structures of Turbulence project involving groundbased, sonde and radar observations.  Both WesCon and WOEST were part of the wider ParaChute programme.\r\n\r\nThe Wessex Convection experiment  (WesCon) took place from during summer 2023"
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50851,
                50853,
                50856,
                50857,
                50934,
                50936,
                50937,
                50942,
                50949,
                50950,
                50952,
                50953,
                50965,
                50967,
                50969,
                50970,
                50971,
                50973,
                50978,
                50979,
                50982,
                50983,
                50984,
                50985,
                50986,
                50987,
                50988,
                50989,
                50990,
                50991,
                50992,
                50993,
                50994,
                50995,
                50996,
                50997,
                50998,
                50999,
                51000,
                51001,
                51002,
                51003,
                51004,
                51005,
                51006,
                51007,
                51008,
                51009,
                51010,
                51011,
                51012,
                51013,
                51014,
                51015,
                51016,
                51017,
                51018,
                51019,
                51020,
                51021,
                51022,
                51023,
                51024,
                51025,
                51026,
                51027,
                51028,
                51029,
                51030,
                51031,
                51032,
                51033,
                51034,
                51035,
                51036,
                51037,
                51038,
                51039,
                51040,
                51041,
                51042,
                51044,
                51045,
                51054,
                51055,
                51056,
                51057,
                51058,
                51059,
                51060,
                51061,
                51062,
                51063,
                51064,
                51065,
                51066,
                51067,
                51068,
                51069,
                51070,
                51071,
                51072,
                51073,
                51074,
                51075,
                51076,
                51077,
                51078,
                51079,
                51080,
                51081,
                51082,
                51083,
                51084,
                51087,
                51222,
                51223,
                51225,
                51227,
                51228,
                51229,
                51230,
                51271,
                51272,
                51279,
                51280,
                53949,
                53951,
                53954,
                54967,
                54971,
                54975,
                54976,
                59964,
                59965,
                59966,
                59967,
                59968,
                59969,
                59970,
                59971,
                59972,
                59973,
                59974,
                59975,
                59976,
                60050,
                60051,
                60052,
                60053,
                60054,
                60055,
                60056,
                60057,
                60058,
                60059,
                60060,
                60061,
                60062,
                60063,
                60064,
                60065,
                60066,
                60067,
                60068,
                60069,
                60070,
                60071,
                60072,
                60073,
                60074,
                60075,
                60077,
                60078,
                60079,
                60080,
                60081,
                60087,
                60089,
                60090,
                60091,
                60092,
                60093,
                60094,
                60095,
                60096,
                60097,
                60098,
                60099,
                60100,
                60101,
                60102,
                60103,
                60104,
                60105,
                60106,
                60107,
                60108,
                60109,
                60110,
                60111,
                60112,
                60113,
                60114,
                60115,
                60116,
                60117,
                60118,
                60119,
                60172,
                60173,
                60202,
                60203,
                60204,
                60205,
                60206,
                60207,
                60208,
                60209,
                60210,
                60211,
                60212,
                60213,
                60214,
                60215,
                60216,
                60217,
                60218,
                60219,
                60220,
                60221,
                60222,
                60223,
                60224,
                60225,
                60226,
                60227,
                60228,
                60229,
                60230,
                60231,
                60232,
                60233,
                60234,
                60235,
                60236,
                60237,
                60238,
                60239,
                60240,
                60241,
                60242,
                60243,
                60244,
                60245,
                60246,
                60247,
                60248,
                60249,
                60250,
                60251,
                60252,
                60253,
                60254,
                60255,
                60256,
                60257,
                60258,
                60259,
                60260,
                60261,
                60262,
                60263,
                60264,
                60265,
                60266,
                60267,
                60268,
                60269,
                60270,
                60271,
                60272,
                60273,
                60274,
                60275,
                60276,
                60277,
                60278,
                60279,
                60280,
                60281,
                60282,
                60283,
                60284,
                60287,
                60308,
                60309,
                62304,
                62646,
                62647,
                62648,
                62649,
                62650,
                62651,
                62652,
                62653,
                62654,
                62655,
                62656,
                62657,
                62658,
                62659,
                62660,
                62661,
                62662,
                62663,
                62664,
                62665,
                62666,
                62669,
                62671,
                62678,
                62679,
                72012,
                73930,
                73931,
                73932,
                73933,
                73934,
                73935,
                73936,
                73937,
                73938,
                73939,
                73940,
                73941,
                73942,
                73943,
                73944,
                73945,
                73946,
                73947,
                73948,
                73949,
                73950,
                73951,
                73952,
                73953,
                73954,
                73955,
                73956,
                73957,
                73958,
                73959,
                73960,
                73961,
                73962,
                73963,
                73964,
                73965,
                73966,
                73967,
                74055,
                74056,
                74057,
                74058,
                74059,
                74060,
                74061,
                74062,
                74063,
                74064,
                74065,
                74066,
                74067,
                74068,
                74069,
                74070,
                74071,
                74072,
                74073,
                74074,
                74075,
                74076,
                74077,
                74078,
                74079,
                74080,
                74081,
                74082,
                74083,
                74084,
                74085,
                74086,
                74087,
                74088,
                74089,
                74090,
                74091,
                74092,
                74093,
                74094,
                74095,
                74096,
                74097,
                74098,
                74099,
                74100,
                74101,
                74102,
                74103,
                74104,
                74105,
                74155,
                74157
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                },
                {
                    "ob_id": 37504,
                    "uuid": "69bbdb1aedcb40fc9ff3e324b693f8b5",
                    "short_code": "coll",
                    "title": "WesCon: in-situ airborne observations by the FAAM BAE-146 aircraft and Jade-one Dimona aircraft",
                    "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for WesCon: Wessex summertime convection experiment.  \r\nMeteorological in-situ data were collected by a range of instruments on board the FAAM BAe-146 aircraft and the Jade-one Dimona aircraft during a series of flights from May to August 2023 over the southern UK.\r\nThese airborne measurements were made to complement groundbased, sonde and radar observations made for the concurrent WesCon - Observing the Evolving Structures of Turbulence (WOEST) project."
                }
            ],
            "responsiblepartyinfo_set": [
                198085,
                198086,
                198087,
                198088,
                198089,
                198090,
                198091,
                198092,
                198093,
                198094
            ],
            "onlineresource_set": [
                84857,
                84858
            ]
        },
        {
            "ob_id": 40736,
            "uuid": "bf5b48e7cf4a4f959e9f9450dd7c5d2b",
            "title": "FAAM C344 WESCON flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for WESCON FAAM Aircraft project.",
            "creationDate": "2023-09-08T16:40:57.645898",
            "lastUpdatedDate": "2023-09-08T16:40:57",
            "latestDataUpdateTime": "2025-03-21T16:12:25",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "WESCON, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-08-18T13:41:51",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3969,
                "bboxName": "",
                "eastBoundLongitude": -0.44297487,
                "westBoundLongitude": -3.1843429,
                "southBoundLatitude": 50.630566,
                "northBoundLatitude": 52.368862
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40735,
                "dataPath": "/badc/faam/data/2023/c344-jul-05",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 9097670575,
                "numberOfFiles": 47,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": {
                "ob_id": 11311,
                "startTime": "2023-07-05T07:24:08",
                "endTime": "2023-07-05T14:13:03"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40737,
                "uuid": "ffe8b9b3a136428bbc1f8ceeb66abdea",
                "short_code": "acq",
                "title": "FAAM Flight C344 Acquisition",
                "abstract": "FAAM Flight C344 Acquisition"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 37501,
                    "uuid": "3c72b5d38e9a499ead03e9e5f140972d",
                    "short_code": "proj",
                    "title": "WesCon: Wessex Convection experiment",
                    "abstract": "WesCon was a UK summer convection experiment in 2023 funded by the Met Office. It focused on understanding dynamical aspects of convection to provide observational data to develop next generation km scale and urban-scale models to improve prediction of convective storms in km scale Numerical Weather Prediction (NWP) and climate models.\r\n\r\nThe emphasis of WesCon was understanding of dynamical processes (particularly updrafts and turbulence) and their interaction with other processes of importance. \r\n\r\nThe project involved the use of the FAAM Bae-146 aircraft, the Jade-Dimona aircraft and groundbased instruments at Cardington, Netheravon, and nearby ground sites. This project ran in conjunction with WOEST: WesCon - Observing the Evolving Structures of Turbulence project involving groundbased, sonde and radar observations.  Both WesCon and WOEST were part of the wider ParaChute programme.\r\n\r\nThe Wessex Convection experiment  (WesCon) took place from during summer 2023"
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50842,
                50851,
                50853,
                50856,
                50857,
                50865,
                50880,
                50888,
                50889,
                50905,
                50907,
                50911,
                50932,
                50933,
                50934,
                50936,
                50937,
                50942,
                50947,
                50948,
                50949,
                50950,
                50952,
                50953,
                50965,
                50967,
                50969,
                50970,
                50971,
                50973,
                50978,
                50979,
                50982,
                50983,
                50984,
                50985,
                50986,
                50987,
                50988,
                50989,
                50990,
                50991,
                50992,
                50993,
                50994,
                50995,
                50996,
                50997,
                50998,
                50999,
                51000,
                51001,
                51002,
                51003,
                51004,
                51005,
                51006,
                51007,
                51008,
                51009,
                51010,
                51011,
                51012,
                51013,
                51014,
                51015,
                51016,
                51017,
                51018,
                51019,
                51020,
                51021,
                51022,
                51023,
                51024,
                51025,
                51026,
                51027,
                51028,
                51029,
                51030,
                51031,
                51032,
                51033,
                51034,
                51035,
                51036,
                51037,
                51038,
                51039,
                51040,
                51041,
                51042,
                51044,
                51045,
                51054,
                51055,
                51056,
                51057,
                51058,
                51059,
                51060,
                51061,
                51062,
                51063,
                51064,
                51065,
                51066,
                51067,
                51068,
                51069,
                51070,
                51071,
                51072,
                51073,
                51074,
                51075,
                51076,
                51077,
                51078,
                51079,
                51080,
                51081,
                51082,
                51083,
                51084,
                51087,
                51098,
                51222,
                51223,
                51225,
                51227,
                51228,
                51229,
                51230,
                51271,
                51272,
                51279,
                51280,
                53949,
                53951,
                53954,
                54967,
                54971,
                54975,
                54976,
                59964,
                59965,
                59966,
                59967,
                59968,
                59969,
                59970,
                59971,
                59972,
                59973,
                59974,
                59975,
                59976,
                60050,
                60051,
                60052,
                60053,
                60054,
                60055,
                60056,
                60057,
                60058,
                60059,
                60060,
                60061,
                60062,
                60063,
                60064,
                60065,
                60066,
                60067,
                60068,
                60069,
                60070,
                60071,
                60072,
                60073,
                60074,
                60075,
                60077,
                60078,
                60079,
                60080,
                60081,
                60087,
                60089,
                60090,
                60091,
                60092,
                60093,
                60094,
                60095,
                60096,
                60097,
                60098,
                60099,
                60100,
                60101,
                60102,
                60103,
                60104,
                60105,
                60106,
                60107,
                60108,
                60109,
                60110,
                60111,
                60112,
                60113,
                60114,
                60115,
                60116,
                60117,
                60118,
                60119,
                60202,
                60203,
                60204,
                60205,
                60206,
                60207,
                60208,
                60209,
                60210,
                60211,
                60212,
                60213,
                60214,
                60215,
                60216,
                60217,
                60218,
                60219,
                60220,
                60221,
                60222,
                60223,
                60224,
                60225,
                60226,
                60227,
                60228,
                60229,
                60230,
                60231,
                60232,
                60233,
                60234,
                60235,
                60236,
                60237,
                60238,
                60239,
                60240,
                60241,
                60242,
                60243,
                60244,
                60245,
                60246,
                60247,
                60248,
                60249,
                60250,
                60251,
                60252,
                60253,
                60254,
                60255,
                60256,
                60257,
                60258,
                60259,
                60260,
                60261,
                60262,
                60263,
                60264,
                60265,
                60266,
                60267,
                60268,
                60269,
                60270,
                60271,
                60272,
                60273,
                60274,
                60275,
                60276,
                60277,
                60278,
                60279,
                60280,
                60281,
                60282,
                60283,
                60284,
                60287,
                60308,
                60309,
                62646,
                62647,
                62648,
                62649,
                62650,
                62651,
                62652,
                62653,
                62654,
                62655,
                62656,
                62657,
                62664,
                62665,
                62666,
                62669,
                62671,
                62678,
                62679,
                65806,
                71784,
                72012,
                73930,
                73931,
                73932,
                73933,
                73934,
                73935,
                73936,
                73937,
                73938,
                73939,
                73940,
                73941,
                73942,
                73943,
                73944,
                73945,
                73946,
                73947,
                73948,
                73949,
                73950,
                73951,
                73952,
                73953,
                73954,
                73955,
                73956,
                73957,
                73958,
                73959,
                73960,
                73961,
                73962,
                73963,
                73964,
                73965,
                73966,
                73967,
                74055,
                74056,
                74057,
                74058,
                74059,
                74061,
                74062,
                74063,
                74064,
                74065,
                74066,
                74067,
                74068,
                74069,
                74070,
                74071,
                74072,
                74073,
                74074,
                74076,
                74077,
                74078,
                74079,
                74080,
                74081,
                74082,
                74084,
                74086,
                74087,
                74088,
                74089,
                74090,
                74091,
                74092,
                74093,
                74095,
                74096,
                74097,
                74098,
                74099,
                74100,
                74101,
                74102,
                74103,
                74104,
                74105,
                74152,
                74153,
                74154,
                74155,
                74156,
                74157,
                74158,
                74159,
                76041,
                76042,
                76043,
                76044,
                76045,
                76046,
                76047,
                76048,
                76049,
                76050,
                76051,
                76052,
                76053,
                76054
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                },
                {
                    "ob_id": 37504,
                    "uuid": "69bbdb1aedcb40fc9ff3e324b693f8b5",
                    "short_code": "coll",
                    "title": "WesCon: in-situ airborne observations by the FAAM BAE-146 aircraft and Jade-one Dimona aircraft",
                    "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for WesCon: Wessex summertime convection experiment.  \r\nMeteorological in-situ data were collected by a range of instruments on board the FAAM BAe-146 aircraft and the Jade-one Dimona aircraft during a series of flights from May to August 2023 over the southern UK.\r\nThese airborne measurements were made to complement groundbased, sonde and radar observations made for the concurrent WesCon - Observing the Evolving Structures of Turbulence (WOEST) project."
                }
            ],
            "responsiblepartyinfo_set": [
                198101,
                198102,
                198103,
                198104,
                198105,
                198106,
                198107,
                198108,
                198109,
                198110
            ],
            "onlineresource_set": [
                84860,
                84861
            ]
        },
        {
            "ob_id": 40740,
            "uuid": "9a53365480914b9cbb1057ec8ea67f81",
            "title": "FAAM C345 WESCON flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for WESCON FAAM Aircraft project.",
            "creationDate": "2023-09-08T16:41:15.858803",
            "lastUpdatedDate": "2023-09-08T16:41:15",
            "latestDataUpdateTime": "2025-03-21T16:12:38",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "WESCON, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-08-18T13:41:57",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3970,
                "bboxName": "",
                "eastBoundLongitude": -0.40552512,
                "westBoundLongitude": -5.4888573,
                "southBoundLatitude": 50.128326,
                "northBoundLatitude": 52.376575
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40739,
                "dataPath": "/badc/faam/data/2023/c345-jul-11",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 8502221832,
                "numberOfFiles": 48,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": {
                "ob_id": 11312,
                "startTime": "2023-07-11T09:37:33",
                "endTime": "2023-07-11T16:17:33"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40741,
                "uuid": "17108444533d4e7d8e8decad3acebaa8",
                "short_code": "acq",
                "title": "FAAM Flight C345 Acquisition",
                "abstract": "FAAM Flight C345 Acquisition"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 37501,
                    "uuid": "3c72b5d38e9a499ead03e9e5f140972d",
                    "short_code": "proj",
                    "title": "WesCon: Wessex Convection experiment",
                    "abstract": "WesCon was a UK summer convection experiment in 2023 funded by the Met Office. It focused on understanding dynamical aspects of convection to provide observational data to develop next generation km scale and urban-scale models to improve prediction of convective storms in km scale Numerical Weather Prediction (NWP) and climate models.\r\n\r\nThe emphasis of WesCon was understanding of dynamical processes (particularly updrafts and turbulence) and their interaction with other processes of importance. \r\n\r\nThe project involved the use of the FAAM Bae-146 aircraft, the Jade-Dimona aircraft and groundbased instruments at Cardington, Netheravon, and nearby ground sites. This project ran in conjunction with WOEST: WesCon - Observing the Evolving Structures of Turbulence project involving groundbased, sonde and radar observations.  Both WesCon and WOEST were part of the wider ParaChute programme.\r\n\r\nThe Wessex Convection experiment  (WesCon) took place from during summer 2023"
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50842,
                50851,
                50853,
                50856,
                50857,
                50865,
                50880,
                50888,
                50889,
                50905,
                50907,
                50911,
                50932,
                50933,
                50934,
                50936,
                50937,
                50942,
                50947,
                50948,
                50949,
                50950,
                50952,
                50953,
                50965,
                50967,
                50969,
                50970,
                50971,
                50973,
                50978,
                50979,
                50982,
                50983,
                50984,
                50985,
                50986,
                50987,
                50988,
                50989,
                50990,
                50991,
                50992,
                50993,
                50994,
                50995,
                50996,
                50997,
                50998,
                50999,
                51000,
                51001,
                51002,
                51003,
                51004,
                51005,
                51006,
                51007,
                51008,
                51009,
                51010,
                51011,
                51012,
                51013,
                51014,
                51015,
                51016,
                51017,
                51018,
                51019,
                51020,
                51021,
                51022,
                51023,
                51024,
                51025,
                51026,
                51027,
                51028,
                51029,
                51030,
                51031,
                51032,
                51033,
                51034,
                51035,
                51036,
                51037,
                51038,
                51039,
                51040,
                51041,
                51042,
                51044,
                51045,
                51054,
                51055,
                51056,
                51057,
                51058,
                51059,
                51060,
                51061,
                51062,
                51063,
                51064,
                51065,
                51066,
                51067,
                51068,
                51069,
                51070,
                51071,
                51072,
                51073,
                51074,
                51075,
                51076,
                51077,
                51078,
                51079,
                51080,
                51081,
                51082,
                51083,
                51084,
                51087,
                51098,
                51222,
                51223,
                51225,
                51227,
                51228,
                51229,
                51230,
                51271,
                51272,
                51279,
                51280,
                53949,
                53951,
                53954,
                54967,
                54971,
                54975,
                54976,
                59964,
                59965,
                59966,
                59967,
                59968,
                59969,
                59970,
                59971,
                59972,
                59973,
                59974,
                59975,
                59976,
                60050,
                60051,
                60052,
                60053,
                60054,
                60055,
                60056,
                60057,
                60058,
                60060,
                60061,
                60062,
                60063,
                60064,
                60065,
                60066,
                60067,
                60068,
                60069,
                60070,
                60071,
                60072,
                60073,
                60074,
                60075,
                60077,
                60078,
                60079,
                60080,
                60081,
                60087,
                60089,
                60090,
                60091,
                60092,
                60093,
                60094,
                60095,
                60096,
                60097,
                60098,
                60099,
                60100,
                60101,
                60102,
                60103,
                60104,
                60105,
                60106,
                60107,
                60108,
                60109,
                60110,
                60111,
                60112,
                60113,
                60114,
                60115,
                60116,
                60117,
                60118,
                60119,
                60172,
                60173,
                60202,
                60203,
                60204,
                60205,
                60206,
                60207,
                60208,
                60209,
                60210,
                60211,
                60212,
                60213,
                60214,
                60215,
                60217,
                60218,
                60219,
                60220,
                60221,
                60222,
                60223,
                60224,
                60225,
                60226,
                60227,
                60228,
                60229,
                60230,
                60231,
                60232,
                60233,
                60234,
                60235,
                60236,
                60237,
                60238,
                60239,
                60240,
                60241,
                60242,
                60243,
                60244,
                60245,
                60246,
                60247,
                60248,
                60249,
                60250,
                60251,
                60252,
                60253,
                60254,
                60255,
                60256,
                60257,
                60258,
                60259,
                60260,
                60261,
                60262,
                60263,
                60264,
                60265,
                60266,
                60267,
                60268,
                60269,
                60270,
                60271,
                60272,
                60273,
                60274,
                60275,
                60276,
                60277,
                60278,
                60279,
                60280,
                60281,
                60282,
                60283,
                60284,
                60287,
                60308,
                60309,
                62646,
                62647,
                62648,
                62649,
                62650,
                62651,
                62652,
                62653,
                62654,
                62655,
                62656,
                62657,
                62658,
                62659,
                62660,
                62661,
                62662,
                62663,
                62664,
                62665,
                62666,
                62669,
                62671,
                62678,
                62679,
                65806,
                71784,
                72012,
                73930,
                73931,
                73932,
                73933,
                73934,
                73935,
                73936,
                73937,
                73938,
                73939,
                73940,
                73941,
                73942,
                73943,
                73944,
                73945,
                73946,
                73947,
                73948,
                73949,
                73950,
                73951,
                73952,
                73953,
                73954,
                73955,
                73956,
                73957,
                73958,
                73959,
                73960,
                73961,
                73962,
                73963,
                73964,
                73965,
                73966,
                73967,
                74055,
                74056,
                74057,
                74058,
                74059,
                74061,
                74062,
                74063,
                74064,
                74065,
                74066,
                74067,
                74068,
                74069,
                74070,
                74071,
                74072,
                74073,
                74074,
                74076,
                74077,
                74078,
                74079,
                74080,
                74081,
                74082,
                74084,
                74086,
                74087,
                74088,
                74089,
                74090,
                74091,
                74092,
                74093,
                74095,
                74096,
                74097,
                74098,
                74099,
                74100,
                74101,
                74102,
                74103,
                74104,
                74105,
                74152,
                74153,
                74154,
                74155,
                74156,
                74157,
                74158,
                74159,
                76041,
                76042,
                76043,
                76044,
                76045,
                76046,
                76047,
                76048,
                76049,
                76050,
                76051,
                76052,
                76053,
                76054,
                82404
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                },
                {
                    "ob_id": 37504,
                    "uuid": "69bbdb1aedcb40fc9ff3e324b693f8b5",
                    "short_code": "coll",
                    "title": "WesCon: in-situ airborne observations by the FAAM BAE-146 aircraft and Jade-one Dimona aircraft",
                    "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for WesCon: Wessex summertime convection experiment.  \r\nMeteorological in-situ data were collected by a range of instruments on board the FAAM BAe-146 aircraft and the Jade-one Dimona aircraft during a series of flights from May to August 2023 over the southern UK.\r\nThese airborne measurements were made to complement groundbased, sonde and radar observations made for the concurrent WesCon - Observing the Evolving Structures of Turbulence (WOEST) project."
                }
            ],
            "responsiblepartyinfo_set": [
                198117,
                198118,
                198119,
                198120,
                198121,
                198122,
                198123,
                198124,
                198125,
                198126
            ],
            "onlineresource_set": [
                84863,
                84864
            ]
        },
        {
            "ob_id": 40744,
            "uuid": "fd9d971ffcf3484196249be5134e93a0",
            "title": "FAAM C346 WESCON flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for WESCON FAAM Aircraft project.",
            "creationDate": "2023-09-08T16:42:14.868926",
            "lastUpdatedDate": "2023-09-08T16:42:14",
            "latestDataUpdateTime": "2025-03-21T16:12:50",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "WESCON, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-08-18T13:42:02",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3971,
                "bboxName": "",
                "eastBoundLongitude": -0.5490214,
                "westBoundLongitude": -3.157894,
                "southBoundLatitude": 50.588505,
                "northBoundLatitude": 52.30814
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40743,
                "dataPath": "/badc/faam/data/2023/c346-jul-12",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 8780847986,
                "numberOfFiles": 52,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": {
                "ob_id": 11313,
                "startTime": "2023-07-12T07:57:37",
                "endTime": "2023-07-12T15:18:56"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40745,
                "uuid": "ad11c7212e7a42ccadd0b9955663d3c3",
                "short_code": "acq",
                "title": "FAAM Flight C346 Acquisition",
                "abstract": "FAAM Flight C346 Acquisition"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 37501,
                    "uuid": "3c72b5d38e9a499ead03e9e5f140972d",
                    "short_code": "proj",
                    "title": "WesCon: Wessex Convection experiment",
                    "abstract": "WesCon was a UK summer convection experiment in 2023 funded by the Met Office. It focused on understanding dynamical aspects of convection to provide observational data to develop next generation km scale and urban-scale models to improve prediction of convective storms in km scale Numerical Weather Prediction (NWP) and climate models.\r\n\r\nThe emphasis of WesCon was understanding of dynamical processes (particularly updrafts and turbulence) and their interaction with other processes of importance. \r\n\r\nThe project involved the use of the FAAM Bae-146 aircraft, the Jade-Dimona aircraft and groundbased instruments at Cardington, Netheravon, and nearby ground sites. This project ran in conjunction with WOEST: WesCon - Observing the Evolving Structures of Turbulence project involving groundbased, sonde and radar observations.  Both WesCon and WOEST were part of the wider ParaChute programme.\r\n\r\nThe Wessex Convection experiment  (WesCon) took place from during summer 2023"
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50851,
                50853,
                50856,
                50857,
                50934,
                50936,
                50937,
                50942,
                50949,
                50950,
                50952,
                50953,
                50965,
                50967,
                50969,
                50970,
                50971,
                50973,
                50978,
                50979,
                50982,
                50983,
                50984,
                50985,
                50986,
                50987,
                50988,
                50989,
                50990,
                50991,
                50992,
                50993,
                50994,
                50995,
                50996,
                50997,
                50998,
                50999,
                51000,
                51001,
                51002,
                51003,
                51004,
                51005,
                51006,
                51007,
                51008,
                51009,
                51010,
                51011,
                51012,
                51013,
                51014,
                51015,
                51016,
                51017,
                51018,
                51019,
                51020,
                51021,
                51022,
                51023,
                51024,
                51025,
                51026,
                51027,
                51028,
                51029,
                51030,
                51031,
                51032,
                51033,
                51034,
                51035,
                51036,
                51037,
                51038,
                51039,
                51040,
                51041,
                51042,
                51044,
                51045,
                51054,
                51055,
                51056,
                51057,
                51058,
                51059,
                51060,
                51061,
                51062,
                51063,
                51064,
                51065,
                51066,
                51067,
                51068,
                51069,
                51070,
                51071,
                51072,
                51073,
                51074,
                51075,
                51076,
                51077,
                51078,
                51079,
                51080,
                51081,
                51082,
                51083,
                51084,
                51087,
                51222,
                51223,
                51225,
                51227,
                51228,
                51229,
                51230,
                51271,
                51272,
                51279,
                51280,
                53949,
                53951,
                53954,
                54967,
                54971,
                54975,
                54976,
                59964,
                59965,
                59966,
                59967,
                59968,
                59969,
                59970,
                59971,
                59972,
                59973,
                59974,
                59975,
                60050,
                60051,
                60052,
                60053,
                60054,
                60055,
                60056,
                60057,
                60058,
                60060,
                60061,
                60062,
                60063,
                60064,
                60065,
                60066,
                60067,
                60068,
                60069,
                60070,
                60071,
                60072,
                60073,
                60074,
                60075,
                60077,
                60078,
                60079,
                60080,
                60081,
                60087,
                60089,
                60090,
                60091,
                60092,
                60093,
                60094,
                60095,
                60096,
                60097,
                60098,
                60099,
                60100,
                60101,
                60102,
                60103,
                60104,
                60105,
                60106,
                60107,
                60108,
                60109,
                60110,
                60111,
                60112,
                60113,
                60114,
                60115,
                60116,
                60117,
                60118,
                60119,
                60172,
                60173,
                60202,
                60203,
                60204,
                60205,
                60206,
                60207,
                60208,
                60209,
                60210,
                60211,
                60212,
                60213,
                60214,
                60215,
                60217,
                60218,
                60219,
                60220,
                60221,
                60222,
                60223,
                60224,
                60225,
                60226,
                60227,
                60228,
                60229,
                60230,
                60231,
                60232,
                60233,
                60234,
                60235,
                60236,
                60237,
                60238,
                60239,
                60240,
                60241,
                60242,
                60243,
                60244,
                60245,
                60246,
                60247,
                60248,
                60249,
                60250,
                60251,
                60252,
                60253,
                60254,
                60255,
                60256,
                60257,
                60258,
                60259,
                60260,
                60261,
                60262,
                60263,
                60264,
                60265,
                60266,
                60267,
                60268,
                60269,
                60270,
                60271,
                60272,
                60273,
                60274,
                60275,
                60276,
                60277,
                60278,
                60279,
                60280,
                60281,
                60282,
                60283,
                60284,
                60287,
                60308,
                60309,
                62646,
                62647,
                62648,
                62650,
                62651,
                62652,
                62653,
                62654,
                62655,
                62656,
                62657,
                62658,
                62659,
                62660,
                62661,
                62662,
                62663,
                62664,
                62665,
                62666,
                62669,
                62671,
                62678,
                62679,
                72012,
                73930,
                73931,
                73932,
                73933,
                73934,
                73935,
                73936,
                73937,
                73938,
                73939,
                73940,
                73941,
                73942,
                73943,
                73944,
                73945,
                73946,
                73947,
                73948,
                73949,
                73950,
                73951,
                73952,
                73953,
                73954,
                73955,
                73956,
                73957,
                73958,
                73959,
                73960,
                73961,
                73962,
                73963,
                73964,
                73965,
                73966,
                73967,
                74055,
                74056,
                74057,
                74058,
                74059,
                74061,
                74062,
                74063,
                74064,
                74065,
                74066,
                74067,
                74068,
                74069,
                74070,
                74071,
                74072,
                74073,
                74074,
                74076,
                74077,
                74078,
                74079,
                74080,
                74081,
                74082,
                74084,
                74086,
                74087,
                74088,
                74089,
                74090,
                74091,
                74092,
                74093,
                74095,
                74096,
                74097,
                74098,
                74099,
                74100,
                74101,
                74102,
                74103,
                74104,
                74105,
                74152,
                74153,
                74154,
                74155,
                74156,
                74157,
                74158,
                74159
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                },
                {
                    "ob_id": 37504,
                    "uuid": "69bbdb1aedcb40fc9ff3e324b693f8b5",
                    "short_code": "coll",
                    "title": "WesCon: in-situ airborne observations by the FAAM BAE-146 aircraft and Jade-one Dimona aircraft",
                    "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for WesCon: Wessex summertime convection experiment.  \r\nMeteorological in-situ data were collected by a range of instruments on board the FAAM BAe-146 aircraft and the Jade-one Dimona aircraft during a series of flights from May to August 2023 over the southern UK.\r\nThese airborne measurements were made to complement groundbased, sonde and radar observations made for the concurrent WesCon - Observing the Evolving Structures of Turbulence (WOEST) project."
                }
            ],
            "responsiblepartyinfo_set": [
                198133,
                198134,
                198135,
                198136,
                198137,
                198138,
                198139,
                198140,
                198141,
                198142
            ],
            "onlineresource_set": [
                84866,
                84867
            ]
        },
        {
            "ob_id": 40748,
            "uuid": "cd508dd27d204100bd1b4828a6a6ac7a",
            "title": "FAAM C347 WESCON flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for WESCON FAAM Aircraft project.",
            "creationDate": "2023-09-08T16:42:59.578259",
            "lastUpdatedDate": "2023-09-08T16:42:59",
            "latestDataUpdateTime": "2025-03-21T16:13:03",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "WESCON, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-08-18T13:42:17",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3972,
                "bboxName": "",
                "eastBoundLongitude": -0.6027913,
                "westBoundLongitude": -3.5021293,
                "southBoundLatitude": 50.7965,
                "northBoundLatitude": 52.224865
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40747,
                "dataPath": "/badc/faam/data/2023/c347-jul-13",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 9077967489,
                "numberOfFiles": 48,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": {
                "ob_id": 11314,
                "startTime": "2023-07-13T06:48:21",
                "endTime": "2023-07-13T13:54:26"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40749,
                "uuid": "bd774280f45a44f7b86bffdc95963d94",
                "short_code": "acq",
                "title": "FAAM Flight C347 Acquisition",
                "abstract": "FAAM Flight C347 Acquisition"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 37501,
                    "uuid": "3c72b5d38e9a499ead03e9e5f140972d",
                    "short_code": "proj",
                    "title": "WesCon: Wessex Convection experiment",
                    "abstract": "WesCon was a UK summer convection experiment in 2023 funded by the Met Office. It focused on understanding dynamical aspects of convection to provide observational data to develop next generation km scale and urban-scale models to improve prediction of convective storms in km scale Numerical Weather Prediction (NWP) and climate models.\r\n\r\nThe emphasis of WesCon was understanding of dynamical processes (particularly updrafts and turbulence) and their interaction with other processes of importance. \r\n\r\nThe project involved the use of the FAAM Bae-146 aircraft, the Jade-Dimona aircraft and groundbased instruments at Cardington, Netheravon, and nearby ground sites. This project ran in conjunction with WOEST: WesCon - Observing the Evolving Structures of Turbulence project involving groundbased, sonde and radar observations.  Both WesCon and WOEST were part of the wider ParaChute programme.\r\n\r\nThe Wessex Convection experiment  (WesCon) took place from during summer 2023"
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50967,
                50969,
                50970,
                50971,
                50973,
                50978,
                50979,
                50982,
                50983,
                50984,
                50985,
                50986,
                50987,
                50988,
                50989,
                50990,
                50991,
                50992,
                50993,
                50994,
                50995,
                50996,
                50997,
                50998,
                50999,
                51000,
                51001,
                51002,
                51003,
                51004,
                51005,
                51006,
                51007,
                51008,
                51009,
                51010,
                51011,
                51012,
                51013,
                51014,
                51015,
                51016,
                51017,
                51018,
                51019,
                51020,
                51021,
                51022,
                51023,
                51024,
                51025,
                51026,
                51027,
                51028,
                51029,
                51030,
                51031,
                51032,
                51033,
                51034,
                51035,
                51036,
                51037,
                51038,
                51039,
                51040,
                51041,
                51042,
                51044,
                51045,
                51054,
                51055,
                51056,
                51057,
                51058,
                51059,
                51060,
                51061,
                51062,
                51063,
                51064,
                51065,
                51066,
                51067,
                51068,
                51069,
                51070,
                51071,
                51072,
                51073,
                51074,
                51075,
                51076,
                51077,
                51078,
                51079,
                51080,
                51081,
                51082,
                51083,
                51084,
                51087,
                54967,
                54971,
                54975,
                54976,
                60089,
                60090,
                60091,
                60092,
                60093,
                60094,
                60095,
                60096,
                60097,
                60098,
                60099,
                60100,
                60101,
                60102,
                60103,
                60104,
                60105,
                60106,
                60107,
                60108,
                60109,
                60110,
                60111,
                60112,
                60113,
                60114,
                60115,
                60116,
                60117,
                60118,
                60119,
                60308,
                60309,
                62669,
                62671,
                62678,
                62679,
                73930,
                73931,
                73932,
                73933,
                73934,
                73935,
                73936,
                73937,
                73938,
                73939,
                73940,
                73941,
                73942,
                73943,
                73944,
                73945,
                73946,
                73947,
                73948,
                73949,
                73950,
                73951,
                73953,
                73954,
                73955,
                73956,
                73957,
                73958,
                73960,
                73961,
                73962,
                73963,
                73965,
                73966,
                74055,
                74056,
                74057,
                74058,
                74059,
                74061,
                74062,
                74063,
                74064,
                74065,
                74066,
                74067,
                74068,
                74069,
                74070,
                74071,
                74072,
                74073,
                74074,
                74076,
                74077,
                74078,
                74079,
                74080,
                74081,
                74082,
                74084,
                74086,
                74087,
                74088,
                74089,
                74090,
                74091,
                74092,
                74093,
                74095,
                74096,
                74097,
                74098,
                74099,
                74100,
                74101,
                74102,
                74103,
                74104,
                74105,
                74131,
                74152,
                74153,
                74154,
                74155,
                74156,
                74157,
                74158,
                74159
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                },
                {
                    "ob_id": 37504,
                    "uuid": "69bbdb1aedcb40fc9ff3e324b693f8b5",
                    "short_code": "coll",
                    "title": "WesCon: in-situ airborne observations by the FAAM BAE-146 aircraft and Jade-one Dimona aircraft",
                    "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for WesCon: Wessex summertime convection experiment.  \r\nMeteorological in-situ data were collected by a range of instruments on board the FAAM BAe-146 aircraft and the Jade-one Dimona aircraft during a series of flights from May to August 2023 over the southern UK.\r\nThese airborne measurements were made to complement groundbased, sonde and radar observations made for the concurrent WesCon - Observing the Evolving Structures of Turbulence (WOEST) project."
                }
            ],
            "responsiblepartyinfo_set": [
                198149,
                198150,
                198151,
                198152,
                198153,
                198154,
                198155,
                198156,
                198157,
                198158
            ],
            "onlineresource_set": [
                84869,
                84870
            ]
        },
        {
            "ob_id": 40752,
            "uuid": "d2a65de685f344c898d7cd7c9393c65a",
            "title": "FAAM C348 WESCON flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for WESCON FAAM Aircraft project.",
            "creationDate": "2023-09-08T16:44:51.365196",
            "lastUpdatedDate": "2023-09-08T16:44:51",
            "latestDataUpdateTime": "2025-03-21T16:13:15",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "WESCON, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-08-18T13:42:23",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3973,
                "bboxName": "",
                "eastBoundLongitude": -0.5140597,
                "westBoundLongitude": -3.0897985,
                "southBoundLatitude": 50.73325,
                "northBoundLatitude": 52.282993
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40751,
                "dataPath": "/badc/faam/data/2023/c348-jul-17",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 2059583303,
                "numberOfFiles": 25,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": {
                "ob_id": 11315,
                "startTime": "2023-07-17T06:32:01",
                "endTime": "2023-07-17T13:46:43"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40753,
                "uuid": "b6d266e35a3c49b7a73e649bb437e419",
                "short_code": "acq",
                "title": "FAAM Flight C348 Acquisition",
                "abstract": "FAAM Flight C348 Acquisition"
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 37501,
                    "uuid": "3c72b5d38e9a499ead03e9e5f140972d",
                    "short_code": "proj",
                    "title": "WesCon: Wessex Convection experiment",
                    "abstract": "WesCon was a UK summer convection experiment in 2023 funded by the Met Office. It focused on understanding dynamical aspects of convection to provide observational data to develop next generation km scale and urban-scale models to improve prediction of convective storms in km scale Numerical Weather Prediction (NWP) and climate models.\r\n\r\nThe emphasis of WesCon was understanding of dynamical processes (particularly updrafts and turbulence) and their interaction with other processes of importance. \r\n\r\nThe project involved the use of the FAAM Bae-146 aircraft, the Jade-Dimona aircraft and groundbased instruments at Cardington, Netheravon, and nearby ground sites. This project ran in conjunction with WOEST: WesCon - Observing the Evolving Structures of Turbulence project involving groundbased, sonde and radar observations.  Both WesCon and WOEST were part of the wider ParaChute programme.\r\n\r\nThe Wessex Convection experiment  (WesCon) took place from during summer 2023"
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50851,
                50853,
                50856,
                50857,
                50934,
                50936,
                50937,
                50942,
                50949,
                50950,
                50952,
                50953,
                50965,
                50967,
                50969,
                50970,
                50971,
                50973,
                50978,
                50979,
                50982,
                50983,
                50984,
                50985,
                50986,
                50987,
                50988,
                50989,
                50990,
                50991,
                50992,
                50993,
                50994,
                50995,
                50996,
                50997,
                50998,
                50999,
                51000,
                51001,
                51002,
                51003,
                51004,
                51005,
                51006,
                51007,
                51008,
                51009,
                51010,
                51011,
                51012,
                51013,
                51014,
                51015,
                51016,
                51017,
                51018,
                51019,
                51020,
                51021,
                51022,
                51023,
                51024,
                51025,
                51026,
                51027,
                51028,
                51029,
                51030,
                51031,
                51032,
                51033,
                51034,
                51035,
                51036,
                51037,
                51038,
                51039,
                51040,
                51041,
                51042,
                51044,
                51045,
                51054,
                51055,
                51056,
                51057,
                51058,
                51059,
                51060,
                51061,
                51062,
                51063,
                51064,
                51065,
                51066,
                51067,
                51068,
                51069,
                51070,
                51071,
                51072,
                51073,
                51074,
                51075,
                51076,
                51077,
                51078,
                51079,
                51080,
                51081,
                51082,
                51083,
                51084,
                51087,
                51222,
                51223,
                51225,
                51227,
                51228,
                51229,
                51230,
                51271,
                51272,
                51279,
                51280,
                53949,
                53951,
                53954,
                54967,
                54971,
                54975,
                54976,
                59964,
                59965,
                59966,
                59967,
                59968,
                59969,
                59970,
                59971,
                59972,
                59973,
                59974,
                59975,
                59976,
                60050,
                60051,
                60052,
                60053,
                60054,
                60055,
                60056,
                60057,
                60058,
                60060,
                60061,
                60062,
                60063,
                60064,
                60065,
                60066,
                60067,
                60068,
                60069,
                60070,
                60071,
                60072,
                60073,
                60074,
                60075,
                60077,
                60078,
                60079,
                60080,
                60081,
                60087,
                60089,
                60090,
                60091,
                60092,
                60093,
                60094,
                60095,
                60096,
                60097,
                60098,
                60099,
                60100,
                60101,
                60102,
                60103,
                60104,
                60105,
                60106,
                60107,
                60108,
                60109,
                60110,
                60111,
                60112,
                60113,
                60114,
                60115,
                60116,
                60117,
                60118,
                60119,
                60172,
                60173,
                60202,
                60203,
                60204,
                60205,
                60206,
                60207,
                60208,
                60209,
                60210,
                60211,
                60212,
                60213,
                60214,
                60215,
                60217,
                60218,
                60219,
                60220,
                60221,
                60222,
                60223,
                60224,
                60225,
                60226,
                60227,
                60228,
                60229,
                60230,
                60231,
                60232,
                60233,
                60234,
                60235,
                60236,
                60237,
                60238,
                60239,
                60240,
                60241,
                60242,
                60243,
                60244,
                60245,
                60246,
                60247,
                60248,
                60249,
                60250,
                60251,
                60252,
                60253,
                60254,
                60255,
                60256,
                60257,
                60258,
                60259,
                60260,
                60261,
                60262,
                60263,
                60264,
                60265,
                60266,
                60267,
                60268,
                60269,
                60270,
                60271,
                60272,
                60273,
                60274,
                60275,
                60276,
                60277,
                60278,
                60279,
                60280,
                60281,
                60282,
                60283,
                60284,
                60287,
                60308,
                60309,
                62646,
                62647,
                62648,
                62649,
                62650,
                62651,
                62652,
                62653,
                62654,
                62655,
                62656,
                62657,
                62658,
                62659,
                62660,
                62661,
                62662,
                62663,
                62664,
                62665,
                62666,
                62669,
                62671,
                62678,
                62679,
                72012,
                73930,
                73931,
                73932,
                73933,
                73934,
                73935,
                73936,
                73937,
                73938,
                73939,
                73940,
                73941,
                73942,
                73943,
                73944,
                73945,
                73946,
                73947,
                73948,
                73949,
                73950,
                73951,
                73952,
                73953,
                73954,
                73955,
                73956,
                73957,
                73958,
                73959,
                73960,
                73961,
                73962,
                73963,
                73964,
                73965,
                73966,
                73967,
                74055,
                74056,
                74057,
                74058,
                74059,
                74063,
                74064,
                74066,
                74067,
                74068,
                74069,
                74070,
                74071,
                74072,
                74073,
                74074,
                74076,
                74077,
                74078,
                74080,
                74081,
                74082,
                74084,
                74086,
                74087,
                74088,
                74089,
                74090,
                74091,
                74092,
                74093,
                74095,
                74096,
                74097,
                74098,
                74100,
                74101,
                74103,
                74104,
                74105,
                74152,
                74153,
                74154,
                74155,
                74156,
                74157,
                74158,
                74159,
                75672,
                75673,
                75674,
                75675,
                75676,
                75677
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                },
                {
                    "ob_id": 37504,
                    "uuid": "69bbdb1aedcb40fc9ff3e324b693f8b5",
                    "short_code": "coll",
                    "title": "WesCon: in-situ airborne observations by the FAAM BAE-146 aircraft and Jade-one Dimona aircraft",
                    "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for WesCon: Wessex summertime convection experiment.  \r\nMeteorological in-situ data were collected by a range of instruments on board the FAAM BAe-146 aircraft and the Jade-one Dimona aircraft during a series of flights from May to August 2023 over the southern UK.\r\nThese airborne measurements were made to complement groundbased, sonde and radar observations made for the concurrent WesCon - Observing the Evolving Structures of Turbulence (WOEST) project."
                }
            ],
            "responsiblepartyinfo_set": [
                198165,
                198166,
                198167,
                198168,
                198169,
                198170,
                198171,
                198172,
                198173,
                198174
            ],
            "onlineresource_set": [
                84872,
                84873
            ]
        },
        {
            "ob_id": 40756,
            "uuid": "3fa803ea494d4fbbb17f37494d87fc23",
            "title": "FAAM C349 WESCON flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for WESCON FAAM Aircraft project.",
            "creationDate": "2023-09-08T16:45:14.010262",
            "lastUpdatedDate": "2023-09-08T16:45:14",
            "latestDataUpdateTime": "2025-05-28T13:15:05",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "WESCON, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "ongoing",
            "dataPublishedTime": "2023-08-18T13:42:28",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3974,
                "bboxName": "",
                "eastBoundLongitude": -0.4139234,
                "westBoundLongitude": -3.3093169,
                "southBoundLatitude": 50.631325,
                "northBoundLatitude": 52.384876
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40755,
                "dataPath": "/badc/faam/data/2023/c349-jul-25",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 2009135612,
                "numberOfFiles": 27,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": {
                "ob_id": 11316,
                "startTime": "2023-07-25T07:39:21",
                "endTime": "2023-07-25T15:02:23"
            },
            "resultQuality": {
                "ob_id": 3074,
                "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).",
                "passesTest": true,
                "resultTitle": "FAAM to CEDA Data Quality Statement",
                "date": "2015-09-03"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                8
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2522,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 3,
                        "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50851,
                50853,
                50856,
                50857,
                50934,
                50936,
                50937,
                50942,
                50949,
                50950,
                50952,
                50953,
                50965,
                50967,
                50969,
                50970,
                50971,
                50973,
                50978,
                50979,
                50982,
                50983,
                50984,
                50985,
                50986,
                50987,
                50988,
                50989,
                50990,
                50991,
                50992,
                50993,
                50994,
                50995,
                50996,
                50997,
                50998,
                50999,
                51000,
                51001,
                51002,
                51003,
                51004,
                51005,
                51006,
                51007,
                51008,
                51009,
                51010,
                51011,
                51012,
                51013,
                51014,
                51015,
                51016,
                51017,
                51018,
                51019,
                51020,
                51021,
                51022,
                51023,
                51024,
                51025,
                51026,
                51027,
                51028,
                51029,
                51030,
                51031,
                51032,
                51033,
                51034,
                51035,
                51036,
                51037,
                51038,
                51039,
                51040,
                51041,
                51042,
                51044,
                51045,
                51054,
                51055,
                51056,
                51057,
                51058,
                51059,
                51060,
                51061,
                51062,
                51063,
                51064,
                51065,
                51066,
                51067,
                51068,
                51069,
                51070,
                51071,
                51072,
                51073,
                51074,
                51075,
                51076,
                51077,
                51078,
                51079,
                51080,
                51081,
                51082,
                51083,
                51084,
                51087,
                51222,
                51223,
                51225,
                51227,
                51228,
                51229,
                51230,
                51271,
                51272,
                51279,
                51280,
                53949,
                53951,
                53954,
                54967,
                54971,
                54975,
                54976,
                59964,
                59965,
                59966,
                59967,
                59968,
                59969,
                59970,
                59971,
                59972,
                59973,
                59974,
                59975,
                59976,
                60050,
                60051,
                60052,
                60053,
                60054,
                60055,
                60056,
                60057,
                60058,
                60060,
                60061,
                60062,
                60063,
                60064,
                60065,
                60066,
                60067,
                60068,
                60069,
                60070,
                60071,
                60072,
                60073,
                60074,
                60075,
                60077,
                60078,
                60079,
                60080,
                60081,
                60087,
                60089,
                60090,
                60091,
                60092,
                60093,
                60094,
                60095,
                60096,
                60097,
                60098,
                60099,
                60100,
                60101,
                60102,
                60103,
                60104,
                60105,
                60106,
                60107,
                60108,
                60109,
                60110,
                60111,
                60112,
                60113,
                60114,
                60115,
                60116,
                60117,
                60118,
                60119,
                60172,
                60173,
                60202,
                60203,
                60204,
                60205,
                60206,
                60207,
                60208,
                60209,
                60210,
                60211,
                60212,
                60213,
                60214,
                60215,
                60217,
                60218,
                60219,
                60220,
                60221,
                60222,
                60223,
                60224,
                60225,
                60226,
                60227,
                60228,
                60229,
                60230,
                60231,
                60232,
                60233,
                60234,
                60235,
                60236,
                60237,
                60238,
                60239,
                60240,
                60241,
                60242,
                60243,
                60244,
                60245,
                60246,
                60247,
                60248,
                60249,
                60250,
                60251,
                60252,
                60253,
                60254,
                60255,
                60256,
                60257,
                60258,
                60259,
                60260,
                60261,
                60262,
                60263,
                60264,
                60265,
                60266,
                60267,
                60268,
                60269,
                60270,
                60271,
                60272,
                60273,
                60274,
                60275,
                60276,
                60277,
                60278,
                60279,
                60280,
                60281,
                60282,
                60283,
                60284,
                60287,
                62646,
                62647,
                62648,
                62649,
                62650,
                62651,
                62652,
                62653,
                62654,
                62655,
                62656,
                62657,
                62658,
                62659,
                62660,
                62661,
                62662,
                62663,
                62664,
                62665,
                62666,
                62669,
                62671,
                62678,
                62679,
                72012,
                73930,
                73931,
                73932,
                73933,
                73934,
                73935,
                73936,
                73937,
                73938,
                73939,
                73940,
                73941,
                73942,
                73943,
                73944,
                73945,
                73946,
                73947,
                73948,
                73949,
                73950,
                73951,
                73952,
                73953,
                73954,
                73955,
                73956,
                73957,
                73958,
                73959,
                73960,
                73961,
                73962,
                73963,
                73964,
                73965,
                73966,
                73967,
                74055,
                74056,
                74057,
                74058,
                74059,
                74061,
                74062,
                74063,
                74064,
                74065,
                74066,
                74067,
                74068,
                74069,
                74070,
                74071,
                74072,
                74073,
                74074,
                74076,
                74077,
                74078,
                74079,
                74080,
                74081,
                74082,
                74084,
                74086,
                74087,
                74088,
                74089,
                74090,
                74091,
                74092,
                74093,
                74095,
                74096,
                74097,
                74098,
                74099,
                74100,
                74101,
                74102,
                74103,
                74104,
                74105,
                74120,
                74121,
                74122,
                74123,
                74124,
                74125,
                74126,
                74127,
                74128,
                74129,
                74130,
                74132,
                74133,
                74134,
                74135,
                74136,
                74137,
                74138,
                74139,
                74140,
                74141,
                74142,
                74143,
                74144,
                74145,
                74146,
                74147,
                74148,
                74149,
                74150,
                74151,
                74152,
                74153,
                74154,
                74155,
                74156,
                74157,
                74158,
                74159,
                74160,
                74161
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 5782,
                    "uuid": "affe775e8d8890a4556aec5bc4e0b45c",
                    "short_code": "coll",
                    "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights",
                    "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use."
                },
                {
                    "ob_id": 37504,
                    "uuid": "69bbdb1aedcb40fc9ff3e324b693f8b5",
                    "short_code": "coll",
                    "title": "WesCon: in-situ airborne observations by the FAAM BAE-146 aircraft and Jade-one Dimona aircraft",
                    "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for WesCon: Wessex summertime convection experiment.  \r\nMeteorological in-situ data were collected by a range of instruments on board the FAAM BAe-146 aircraft and the Jade-one Dimona aircraft during a series of flights from May to August 2023 over the southern UK.\r\nThese airborne measurements were made to complement groundbased, sonde and radar observations made for the concurrent WesCon - Observing the Evolving Structures of Turbulence (WOEST) project."
                }
            ],
            "responsiblepartyinfo_set": [
                198181,
                198182,
                198183,
                198184,
                198185,
                198186,
                198187,
                198188,
                198189,
                198190
            ],
            "onlineresource_set": [
                84875,
                84876
            ]
        },
        {
            "ob_id": 40759,
            "uuid": "319a7afc1cbf41c3a1ea4258e1f05506",
            "title": "TEST RORY JENNS BBUBL: 1 km gridded output from WRF v3.6.1 model runs for the Birmingham conurbation",
            "abstract": "This dataset contains a range of parameters from a 1 km gridded output from runs of version 3.6.1 of the Weather Research and Forecasting (WRF) model deployed on the ARCHER UK National Supercomputing Service. These runs were part of the NERC funded BBUBL project (Biotelemetry/Bio-aerial-platforms for the Urban Boundary Layer  - also known as City Flocks, NERC grant award NE/N003195/1). The domain of the model runs was over the set over Birmingham conurbation for all of 2015. This geo-temporal domain encompasses measurements of the urban boundary layer obtained from instrumentation attached to birds flown around the area. See related dataset.",
            "creationDate": "2023-09-11T10:43:07.815459",
            "lastUpdatedDate": "2023-09-11T10:43:07.815468",
            "latestDataUpdateTime": "2023-09-11T10:43:07.815474",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "urban meteorology,boundary layer,test",
            "publicationState": "preview",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "pending",
            "dataPublishedTime": null,
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3975,
                "bboxName": "",
                "eastBoundLongitude": -1.26129,
                "westBoundLongitude": -2.53084,
                "southBoundLatitude": 52.1007,
                "northBoundLatitude": 52.8473
            },
            "verticalExtent": null,
            "result_field": null,
            "timePeriod": {
                "ob_id": 11317,
                "startTime": "2015-01-01T00:00:00",
                "endTime": "2015-12-31T00:00:00"
            },
            "resultQuality": {
                "ob_id": 4412,
                "explanation": "Model output has only been checked for CF convention compliance, otherwise supplied as-is.",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-09-11"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [],
            "projects": [],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                198197,
                198198,
                198199,
                198200,
                198201,
                198202,
                198203,
                198204
            ],
            "onlineresource_set": [
                84877,
                84878,
                84879
            ]
        },
        {
            "ob_id": 40760,
            "uuid": "b80870de014a43a498fc2684e78f32af",
            "title": "Retrieved sulfur dioxide column amounts and heights from the IASI instrument (9-30 April 2021) v1.0",
            "abstract": "This dataset contains retrievals of sulfur dioxide (SO2) from the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp platforms. This is a global dataset for 9-30th April 2021 which includes plumes from La Soufrière (St Vincent), Sabancaya (Peru) and Sangay (Ecuador). \r\n\r\nTwo retrieval schemes have been used: (1) Walker et al. (2011,2012) linear retrieval which flags pixels containing SO2 and (2) Carboni et al. (2012,2016) iterative retrieval which quantifies information about the SO2 including the column amount, height and the associated errors. The retrieved outputs are provided for individual IASI orbits. \r\n\r\nThis dataset was used to study the large plume of SO2 from the April 2021 eruption of La Soufrière on St Vincent in the Eastern Caribbean.  \r\n\r\nThe data has been produced by the Earth Observation Data Group at the University of Oxford, as part of the NERC Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET).",
            "creationDate": "2023-09-13T12:36:50.712193",
            "lastUpdatedDate": "2023-09-18T16:26:45",
            "latestDataUpdateTime": "2023-09-26T15:07:23",
            "updateFrequency": "notPlanned",
            "dataLineage": "The dataset has been produced by the Earth Observation Data Group at the University of Oxford, as part of the NERC Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET). The Oxford linear and iterative SO2 retrievals have been applied to the IASI level 1c files available at CEDA. The results were then passed to CEDA to be archived.",
            "removedDataReason": "",
            "keywords": "SO2,volcanic plumes,IASI,volcanic emissions,satellite observations",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "pending",
            "dataPublishedTime": "2023-10-03T13:29:50",
            "doiPublishedTime": "2023-10-13T08:59:18.496525",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3976,
                "bboxName": "",
                "eastBoundLongitude": 180.0,
                "westBoundLongitude": -180.0,
                "southBoundLatitude": -90.0,
                "northBoundLatitude": 90.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40793,
                "dataPath": "/neodc/iasi_so2_oxford/data/orbit-by-orbit/la_soufriere/v1.0/2021/04",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 2189542230,
                "numberOfFiles": 937,
                "fileFormat": "netcdf"
            },
            "timePeriod": {
                "ob_id": 11324,
                "startTime": "2021-04-09T00:00:00",
                "endTime": "2021-04-30T00:00:00"
            },
            "resultQuality": {
                "ob_id": 4413,
                "explanation": "A quality control has been applied to the iterative retrieval portion of this dataset. This requires that the column amounts retrieved are positive, that the retrieval pressures are between 0 and 1100 hPa and the heights in kilometres are positive. Additionally, the retrieval must coverage within 10 iterations and the output should have a normalised cost of less than 10. The iterative retrieval outputs (column amounts, heights and effective radiating temperatures) all have errors associated with them. The user can opt to apply a stricter quality control by further restricting the retrieval cost or by considering the retrieval errors.",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-09-13"
            },
            "validTimePeriod": null,
            "procedureAcquisition": {
                "ob_id": 40761,
                "uuid": "265f3ce868914f2f9ec35a34d98f2cb2",
                "short_code": "acq",
                "title": "Acquisition for: Sulfur dioxide properties from the Infrared Atmospheric Sounding Interferometer (9-30 April 2021) ",
                "abstract": ""
            },
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                2
            ],
            "discoveryKeywords": [],
            "permissions": [],
            "projects": [
                {
                    "ob_id": 11687,
                    "uuid": "b46fbc668f6547fda79f2899046c29a9",
                    "short_code": "proj",
                    "title": "Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics",
                    "abstract": "The Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (COMET+) represents the Dynamic Earth and Geohazards research group within the National Centre for Earth Observation (NCEO)'s Theme 6 during NCEO phase 1. NCEO phase 1 was is funded by the Natural Environment Research Council (NERC). NCEO phase 2 no longer has the theme 6 within its remit, though COMT+ continues within NERC.\r\n\r\nCOMET+ involves scientists from the University of Oxford, University of Cambridge, University of Leeds, University of Bristol, University oSf Glasgow, University of Reading, and University College London. We aim to combine satellite observations of Earth's surface movements, topography and gas release with terrestrial observations and modelling to advance understanding of the earthquake cycle, continental deformation and volcanic eruptions, and to quantify seismic and volcanic hazards."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                50542,
                50543,
                75657,
                75658,
                75659,
                75660,
                75661,
                75662,
                75663,
                75664,
                75665,
                75666,
                75667,
                75668,
                75669,
                75670,
                75671
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12721
            ],
            "observationcollection_set": [
                {
                    "ob_id": 30127,
                    "uuid": "82b29f96b8c94db28ecc51a479f8c9c6",
                    "short_code": "coll",
                    "title": "National Centre for Earth Observation (NCEO) Core datasets",
                    "abstract": "This NCEO Core data set collection contains data generated by the National Centre for Earth Observation core scientific programmes. NCEO is a National Environment Research Council (NERC) research centre with more than 80 scientists distributed across leading UK universities and research organisations and led by Professor John Remedios at the University of Leicester.\r\n\r\nNCEO provides the UK with core expertise in Earth Observation science, data sets and merging techniques, and model evaluation to underpin Earth System research and the UK’s international contribution to environmental science. NCEO scientists work strategically with space agencies, play significant roles in mission planning, and generate internationally-recognised data products from 20 different satellite instruments."
                }
            ],
            "responsiblepartyinfo_set": [
                198205,
                198206,
                198207,
                198208,
                198209,
                198210,
                198244,
                198424,
                198245
            ],
            "onlineresource_set": [
                84888,
                84889,
                84890,
                84891
            ]
        },
        {
            "ob_id": 40763,
            "uuid": "b0f5fc3a10cf4806ab57326edd8daf65",
            "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE product, Version 08.1",
            "abstract": "The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The ACTIVE product has been created by fusing scatterometer soil moisture products, derived from the active remote sensing instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created.\r\n\r\nThe v08.1 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2022-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": null,
            "latestDataUpdateTime": "2023-09-25T10:35:47",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project",
            "removedDataReason": "",
            "keywords": "ESA, Soil Moisture, CCI, Active",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": true,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-10-11T10:52:15",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 529,
                "bboxName": "Global (-180 to 180)",
                "eastBoundLongitude": 180.0,
                "westBoundLongitude": -180.0,
                "southBoundLatitude": -90.0,
                "northBoundLatitude": 90.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40787,
                "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/ACTIVE/v08.1",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 8909412709,
                "numberOfFiles": 11473,
                "fileFormat": "The data are provided in NetCDF format."
            },
            "timePeriod": {
                "ob_id": 11325,
                "startTime": "1991-08-05T00:00:00",
                "endTime": "2022-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 3571,
                "explanation": "See the Soil Moisture CCI documentation for information on data quality",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2020-11-13"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": {
                "ob_id": 40768,
                "uuid": "2a62ff003cd44740b92e70de37bf55ea",
                "short_code": "cmppr",
                "title": "ESA Soil Moisture Climate Change Initiative: Retrieval of Soil Moisture using Active sensors for version 08.1 data.",
                "abstract": "The ESA Soil Moisture Climate Change Initiative is using Active and Passive Sensors to derive information on soil moisture. The ACTIVE product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT."
            },
            "imageDetails": [
                111
            ],
            "discoveryKeywords": [
                {
                    "ob_id": 1140,
                    "name": "ESACCI"
                }
            ],
            "permissions": [
                {
                    "ob_id": 2535,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 15,
                        "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_soilmoisture_terms_and_conditions.pdf",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 13332,
                    "uuid": "c256fcfeef24460ca6eb14bf0fe09572",
                    "short_code": "proj",
                    "title": "ESA Soil Moisture Climate Change Initiative Project",
                    "abstract": "The European Space Agency Soil Moisture Climate Change Initiative (Soil_Moisture_cci) project is part of the ESA Climate Change Initiative (CCI) programme, which aims to produce datasets of Essential Climate Variables (ECV's) from satellite datasets.\r\n\r\nThe Soil Moisture CCI project was set up to :\r\n - Analyse the needs of the climate research community in terms of soil moisture data.\r\n - Adapt soil moisture satellite measurements for their use by the climate research community.\r\n - Create a long-term consistent soil moisture time series, based on active and passive data, suitable for climate change studies."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                52664,
                52665,
                54641,
                54644,
                54645,
                54646,
                54647,
                54648,
                54649,
                62745,
                75656
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 40767,
                    "uuid": "ff890589c21f4033803aa550f52c980c",
                    "short_code": "coll",
                    "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 08.1 data collection",
                    "abstract": "Soil Moisture data (version 08.1) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets alongside ancillary data products. The ACTIVE and PASSIVE products have been created by fusing satellite scatterometer and radiometer soil moisture products respectively. In the case of the ACTIVE product, these have been derived from the AMI-WS and ASCAT satellite instruments and for the PASSIVE product from the satellite instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP. The COMBINED product is generated from the Level 2 active and passive instruments.\r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the PASSIVE and COMBINED products covering the period (yyyy-mm-dd) 1978-11-01 to 2022-12-31 and the ACTIVE product covering 1991-08-05 to 2022-12-31. The soil moisture data for the PASSIVE and the COMBINED product are provided in volumetric units [m3 m-3], while the ACTIVE soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Additional documentation and information relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product User Guide.\r\n\r\nThe data set should be cited using all of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896."
                }
            ],
            "responsiblepartyinfo_set": [
                198246,
                198247,
                198248,
                198249,
                198250,
                198251,
                198252,
                198253,
                198254,
                198255,
                198259,
                198260,
                198262,
                198263,
                198264,
                198265,
                198381,
                198382,
                198383,
                198384
            ],
            "onlineresource_set": [
                84897,
                84895,
                84896,
                84898,
                84899,
                84901,
                84900,
                84977,
                84978,
                84949,
                84950
            ]
        },
        {
            "ob_id": 40764,
            "uuid": "16dc7da110324e5196e922191d962157",
            "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE product, Version 08.1",
            "abstract": "The Soil Moisture CCI PASSIVE dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The PASSIVE product has been created by merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP passive remote sensing satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v08.1 PASSIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2022-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": null,
            "latestDataUpdateTime": "2024-09-11T11:57:51",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project",
            "removedDataReason": "",
            "keywords": "ESA, CCI, Passive, Soil Moisture",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": true,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-10-11T10:52:35",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 529,
                "bboxName": "Global (-180 to 180)",
                "eastBoundLongitude": 180.0,
                "westBoundLongitude": -180.0,
                "southBoundLatitude": -90.0,
                "northBoundLatitude": 90.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40788,
                "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/PASSIVE/v08.1",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 20938474170,
                "numberOfFiles": 16133,
                "fileFormat": "The data are provided in NetCDF format."
            },
            "timePeriod": {
                "ob_id": 11326,
                "startTime": "1978-11-01T00:00:00",
                "endTime": "2022-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 3570,
                "explanation": "See the Soil Moisture CCI documentation for information on data quality",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2020-11-13"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": {
                "ob_id": 40771,
                "uuid": "5e8358c402494a91b9a103f0bb5a2881",
                "short_code": "cmppr",
                "title": "ESA Soil Moisture Climate Change Initiative: Retrieval of Soil Moisture using Passive sensors for version 08.1 data.",
                "abstract": "The ESA Soil Moisture Climate Change Initiative is using Active and Passive Sensors to derive information on soil moisture. The passive product has been created by merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP satellite instruments."
            },
            "imageDetails": [
                111
            ],
            "discoveryKeywords": [
                {
                    "ob_id": 1140,
                    "name": "ESACCI"
                }
            ],
            "permissions": [
                {
                    "ob_id": 2535,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 15,
                        "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_soilmoisture_terms_and_conditions.pdf",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 13332,
                    "uuid": "c256fcfeef24460ca6eb14bf0fe09572",
                    "short_code": "proj",
                    "title": "ESA Soil Moisture Climate Change Initiative Project",
                    "abstract": "The European Space Agency Soil Moisture Climate Change Initiative (Soil_Moisture_cci) project is part of the ESA Climate Change Initiative (CCI) programme, which aims to produce datasets of Essential Climate Variables (ECV's) from satellite datasets.\r\n\r\nThe Soil Moisture CCI project was set up to :\r\n - Analyse the needs of the climate research community in terms of soil moisture data.\r\n - Adapt soil moisture satellite measurements for their use by the climate research community.\r\n - Create a long-term consistent soil moisture time series, based on active and passive data, suitable for climate change studies."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                52664,
                52665,
                54641,
                54646,
                54647,
                54648,
                54649,
                54650,
                54651,
                62745,
                75656
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 40767,
                    "uuid": "ff890589c21f4033803aa550f52c980c",
                    "short_code": "coll",
                    "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 08.1 data collection",
                    "abstract": "Soil Moisture data (version 08.1) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets alongside ancillary data products. The ACTIVE and PASSIVE products have been created by fusing satellite scatterometer and radiometer soil moisture products respectively. In the case of the ACTIVE product, these have been derived from the AMI-WS and ASCAT satellite instruments and for the PASSIVE product from the satellite instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP. The COMBINED product is generated from the Level 2 active and passive instruments.\r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the PASSIVE and COMBINED products covering the period (yyyy-mm-dd) 1978-11-01 to 2022-12-31 and the ACTIVE product covering 1991-08-05 to 2022-12-31. The soil moisture data for the PASSIVE and the COMBINED product are provided in volumetric units [m3 m-3], while the ACTIVE soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Additional documentation and information relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product User Guide.\r\n\r\nThe data set should be cited using all of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896."
                }
            ],
            "responsiblepartyinfo_set": [
                198273,
                198266,
                198267,
                198268,
                198269,
                198270,
                198271,
                198272,
                198274,
                198275,
                198279,
                198280,
                198282,
                198283,
                198284,
                198285,
                198385,
                198386,
                198387,
                198388
            ],
            "onlineresource_set": [
                84980,
                84904,
                84905,
                84907,
                84908,
                84909,
                84910,
                84906,
                84945,
                84946,
                84979
            ]
        },
        {
            "ob_id": 40765,
            "uuid": "6f99cdb86a9e4d3da2d47c79612c00a2",
            "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED product, Version 08.1",
            "abstract": "The Soil Moisture CCI COMBINED dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The COMBINED product has been created by directly merging Level 2 scatterometer ('active' remote sensing) and radiometer ('passive' remote sensing) soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v08.1 COMBINED product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2022-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": null,
            "latestDataUpdateTime": "2024-09-11T11:57:43",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project",
            "removedDataReason": "",
            "keywords": "ESA, Soil Moisture, CCI, Combined",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": true,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-10-11T10:53:01",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 529,
                "bboxName": "Global (-180 to 180)",
                "eastBoundLongitude": 180.0,
                "westBoundLongitude": -180.0,
                "southBoundLatitude": -90.0,
                "northBoundLatitude": 90.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40789,
                "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/COMBINED/v08.1",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 23014733001,
                "numberOfFiles": 16133,
                "fileFormat": "The data are provided in NetCDF format."
            },
            "timePeriod": {
                "ob_id": 11328,
                "startTime": "1978-11-01T00:00:00",
                "endTime": "2022-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 3572,
                "explanation": "See the Soil Moisture CCI documentation for information on data quality",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2020-11-13"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": {
                "ob_id": 40776,
                "uuid": "169c4fccbb6940e9a72ae0486a0309da",
                "short_code": "cmppr",
                "title": "ESA Soil Moisture Climate Change Initiative: Retrieval of Soil Moisture using combined active and passive sensors for version 08.1 data.",
                "abstract": "The ESA Soil Moisture Climate Change Initiative is using Active and Passive Sensors to derive information on soil moisture. The combined product uses information from both active and passive sensors."
            },
            "imageDetails": [
                111
            ],
            "discoveryKeywords": [
                {
                    "ob_id": 1140,
                    "name": "ESACCI"
                }
            ],
            "permissions": [
                {
                    "ob_id": 2535,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 15,
                        "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_soilmoisture_terms_and_conditions.pdf",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 13332,
                    "uuid": "c256fcfeef24460ca6eb14bf0fe09572",
                    "short_code": "proj",
                    "title": "ESA Soil Moisture Climate Change Initiative Project",
                    "abstract": "The European Space Agency Soil Moisture Climate Change Initiative (Soil_Moisture_cci) project is part of the ESA Climate Change Initiative (CCI) programme, which aims to produce datasets of Essential Climate Variables (ECV's) from satellite datasets.\r\n\r\nThe Soil Moisture CCI project was set up to :\r\n - Analyse the needs of the climate research community in terms of soil moisture data.\r\n - Adapt soil moisture satellite measurements for their use by the climate research community.\r\n - Create a long-term consistent soil moisture time series, based on active and passive data, suitable for climate change studies."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                52664,
                52665,
                54641,
                54646,
                54647,
                54648,
                54649,
                54650,
                54651,
                62745,
                75656
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 40767,
                    "uuid": "ff890589c21f4033803aa550f52c980c",
                    "short_code": "coll",
                    "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 08.1 data collection",
                    "abstract": "Soil Moisture data (version 08.1) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets alongside ancillary data products. The ACTIVE and PASSIVE products have been created by fusing satellite scatterometer and radiometer soil moisture products respectively. In the case of the ACTIVE product, these have been derived from the AMI-WS and ASCAT satellite instruments and for the PASSIVE product from the satellite instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP. The COMBINED product is generated from the Level 2 active and passive instruments.\r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the PASSIVE and COMBINED products covering the period (yyyy-mm-dd) 1978-11-01 to 2022-12-31 and the ACTIVE product covering 1991-08-05 to 2022-12-31. The soil moisture data for the PASSIVE and the COMBINED product are provided in volumetric units [m3 m-3], while the ACTIVE soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Additional documentation and information relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product User Guide.\r\n\r\nThe data set should be cited using all of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896."
                }
            ],
            "responsiblepartyinfo_set": [
                198286,
                198287,
                198288,
                198289,
                198290,
                198291,
                198292,
                198293,
                198294,
                198295,
                198299,
                198300,
                198302,
                198303,
                198304,
                198305,
                198389,
                198390,
                198391,
                198392
            ],
            "onlineresource_set": [
                84915,
                84916,
                84917,
                84919,
                84920,
                84918,
                84981,
                84982,
                84951,
                84952,
                84953
            ]
        },
        {
            "ob_id": 40766,
            "uuid": "010243ea38f3473a885d2ccd9cfb77ab",
            "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the ACTIVE, PASSIVE and COMBINED products, Version 08.1",
            "abstract": "These ancillary datasets were used in the production of the ACTIVE, PASSIVE and COMBINED soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v08.1 Soil Moisture CCI data.\r\n\r\nThe ACTIVE, PASSIVE and COMBINED soil moisture products which these data were used to develop are fusions of scatterometer (i.e. active remote sensing) and radiometer (i.e. passive remote sensing) soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896.",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": null,
            "latestDataUpdateTime": "2024-09-11T13:13:14",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project",
            "removedDataReason": "",
            "keywords": "ESA, Soil Moisture, CCI, Ancillary",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": true,
            "language": "English",
            "resolution": "",
            "status": "completed",
            "dataPublishedTime": "2023-10-11T10:53:20",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 529,
                "bboxName": "Global (-180 to 180)",
                "eastBoundLongitude": 180.0,
                "westBoundLongitude": -180.0,
                "southBoundLatitude": -90.0,
                "northBoundLatitude": 90.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40790,
                "dataPath": "/neodc/esacci/soil_moisture/data/ancillary/v08.1",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 1558698,
                "numberOfFiles": 6,
                "fileFormat": "The data are provided in NetCDF format."
            },
            "timePeriod": null,
            "resultQuality": {
                "ob_id": 3547,
                "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA)",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2020-09-25"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [
                111
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2535,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 15,
                        "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_soilmoisture_terms_and_conditions.pdf",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 13332,
                    "uuid": "c256fcfeef24460ca6eb14bf0fe09572",
                    "short_code": "proj",
                    "title": "ESA Soil Moisture Climate Change Initiative Project",
                    "abstract": "The European Space Agency Soil Moisture Climate Change Initiative (Soil_Moisture_cci) project is part of the ESA Climate Change Initiative (CCI) programme, which aims to produce datasets of Essential Climate Variables (ECV's) from satellite datasets.\r\n\r\nThe Soil Moisture CCI project was set up to :\r\n - Analyse the needs of the climate research community in terms of soil moisture data.\r\n - Adapt soil moisture satellite measurements for their use by the climate research community.\r\n - Create a long-term consistent soil moisture time series, based on active and passive data, suitable for climate change studies."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                12066,
                52664,
                52665,
                54683,
                54684,
                54685,
                54686,
                60753,
                60754,
                63533,
                63534,
                63535,
                63536
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 40767,
                    "uuid": "ff890589c21f4033803aa550f52c980c",
                    "short_code": "coll",
                    "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 08.1 data collection",
                    "abstract": "Soil Moisture data (version 08.1) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets alongside ancillary data products. The ACTIVE and PASSIVE products have been created by fusing satellite scatterometer and radiometer soil moisture products respectively. In the case of the ACTIVE product, these have been derived from the AMI-WS and ASCAT satellite instruments and for the PASSIVE product from the satellite instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP. The COMBINED product is generated from the Level 2 active and passive instruments.\r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the PASSIVE and COMBINED products covering the period (yyyy-mm-dd) 1978-11-01 to 2022-12-31 and the ACTIVE product covering 1991-08-05 to 2022-12-31. The soil moisture data for the PASSIVE and the COMBINED product are provided in volumetric units [m3 m-3], while the ACTIVE soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Additional documentation and information relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product User Guide.\r\n\r\nThe data set should be cited using all of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896."
                }
            ],
            "responsiblepartyinfo_set": [
                198306,
                198307,
                198308,
                198309,
                198310,
                198311,
                198312,
                198313,
                198314,
                198315,
                198319,
                198320,
                198322,
                198323,
                198324,
                198325,
                198393,
                198394,
                198395,
                198396
            ],
            "onlineresource_set": [
                84925,
                84923,
                84924,
                84927,
                84929,
                84928,
                84926,
                84983,
                84984,
                84947,
                84948
            ]
        },
        {
            "ob_id": 40785,
            "uuid": "72b0e21daf3544b6bdfe4522ed4954a0",
            "title": "Expired ECMWF ENSemble Extended forecasts for renewable modelling in Europe",
            "abstract": "This dataset comprises past ensemble weather forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF). Originating from the ECMWF operational archive, the data spans potential weather scenarios equivalent to up to 10,000 years. Due to the chaotic nature of weather, these ensemble forecasts, initiated from slightly perturbed snapshots, offer diverse predictions on potential weather outcomes, including accurate spatial correlations. The dataset aims to provide a richer base for modelling renewable energy systems, especially in scenarios beyond the standard 40-year weather data, and facilitates the application of data-intensive machine learning techniques in energy modelling.",
            "creationDate": "2023-09-21T16:21:02.792832",
            "lastUpdatedDate": "2023-09-21T17:17:02.491583",
            "latestDataUpdateTime": "2023-09-21T16:21:02.792842",
            "updateFrequency": "notPlanned",
            "dataLineage": "in progress",
            "removedDataReason": "",
            "keywords": "ecmwf,renewables",
            "publicationState": "working",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "pending",
            "dataPublishedTime": null,
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3978,
                "bboxName": "",
                "eastBoundLongitude": 34.8,
                "westBoundLongitude": -12.0,
                "southBoundLatitude": 33.0,
                "northBoundLatitude": 72.0
            },
            "verticalExtent": null,
            "result_field": null,
            "timePeriod": {
                "ob_id": 11330,
                "startTime": "1997-01-01T00:00:00",
                "endTime": null
            },
            "resultQuality": {
                "ob_id": 4414,
                "explanation": "",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-09-21"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [],
            "projects": [],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                198397,
                198398,
                198399,
                198400,
                198401,
                198402,
                198403,
                198404
            ],
            "onlineresource_set": []
        },
        {
            "ob_id": 40786,
            "uuid": "7783f79c7080456088d98a34ca238bfa",
            "title": "Expired ECMWF ENSemble Extended forecasts and Reforcasts for Renewable power in Europe",
            "abstract": "This dataset comprises past ensemble weather forecasts and reforecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF).\r\nIt contains surface-level weather variables relevant for energy modelling over the European continent.  The data contains 50-member ensemble runs from ENS Extended (since 2012) and 20x10 member runs from the Reforecast (since 2016)\r\n\r\nCollected from the ECMWF archive, the data spans potential weather scenarios equivalent to several thousand years. Due to the chaotic nature of weather, these ensemble forecasts, initiated from slightly perturbed snapshots, offer diverse predictions on potential weather outcomes, including accurate spatial correlations. The dataset aims to provide a richer base for modelling renewable energy systems, especially in scenarios beyond the standard 40-year weather record data, and facilitates the application of data-intensive machine learning techniques in energy modelling.\r\n\r\nOnly certain years have been fully collected.",
            "creationDate": "2023-09-21T18:25:54.912686",
            "lastUpdatedDate": "2023-09-21T18:25:54",
            "latestDataUpdateTime": "2023-09-21T18:25:54",
            "updateFrequency": "notPlanned",
            "dataLineage": "This dataset comprises of outputs of ECMWF's numerical integration of their ENS Extended and Reforecast products.\r\n\r\nThe data has been collated from the ECMWF MARS archive through WebAPI requests.\r\n\r\nEach (re)forecast has been limited to selected variables, cropped to the European continent, and interpolated from the original Octohedral grid to 0.4° or 0.5° lat lon grid.\r\n\r\nThe temporal and ensemble extent has been limited to:\r\ntype D: full 50 ensembles, hours 360-1140 (2-6 weeks)\r\ntype E: first 5 ensembles, hours 0-1140 \r\ntype R: full 20 reforecasts years, 10 ensembles each, hours 0-1140",
            "removedDataReason": "",
            "keywords": "ecmwf,renewables,ensemble forecast",
            "publicationState": "working",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "pending",
            "dataPublishedTime": null,
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3979,
                "bboxName": "",
                "eastBoundLongitude": 34.8,
                "westBoundLongitude": -12.0,
                "southBoundLatitude": 33.0,
                "northBoundLatitude": 72.0
            },
            "verticalExtent": null,
            "result_field": null,
            "timePeriod": {
                "ob_id": 11331,
                "startTime": "1997-01-01T00:00:00",
                "endTime": null
            },
            "resultQuality": {
                "ob_id": 4415,
                "explanation": "The data has been collected with minimal processing directly from the ECMWF archive. All original metadata has been preserved.",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2023-09-21"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": {
                "ob_id": 3829,
                "uuid": "90554e086fef455fa829e219379f3f01",
                "short_code": "comp",
                "title": "ECMWF - Integrated Forecasting System deployed on ECMWF Computer",
                "abstract": "This computation involved: ECMWF - Integrated Forecasting System deployed on ECMWF Computer."
            },
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [],
            "projects": [],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                198405,
                198406,
                198407,
                198408,
                198409,
                198410,
                198411,
                198412,
                198413
            ],
            "onlineresource_set": []
        },
        {
            "ob_id": 40791,
            "uuid": "fef8f8b1e0c5489f9cce7876db079e56",
            "title": "Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): control data produced by the IFS model at ECMWF",
            "abstract": "This dataset contains model data for SNAPSI experiment 'control' produced by scientists at ECMWF (European Centre for Medium-Range Weather Forecasts, United Kingdom). This dataset contains all ensemble members produced by the ECMWF IFS model.\r\n\r\nThe SNAPSI project is a model intercomparison project to study the role of the stratosphere in subseasonal forecasts following stratospheric sudden warmings and the representation of stratosphere-troposphere coupling in subseasonal forecast models.\r\n\r\nThe control experiment is a set of retrospective, 45-day, 50-member ensemble forecasts. Following the initial date, the stratospheric zonal mean temperatures and zonal winds are nudged towards the time-evolving climatological state. The forecasts are initialized on the date indicated by the sub-experiment id; for instance, the sub-experiment 's20180125' is initialized on 25 January 2018. The ocean, sea-ice, land-surface and ozone are all initialized and run prognostically.\r\n\r\n------------------------------------------\r\nSources of additional information\r\n------------------------------------------\r\nThe following web links are provided in the Details/Docs section of this catalogue record:\r\n- Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): A Protocol for Investigating the Role of the Stratospheric Polar Vortex in Subseasonal to Seasonal Forecasts\r\n- New set of controlled numerical experiments: Stratospheric Nudging And Predictable Surface Impacts (SNAPSI)\r\n- ECMWF IFS model reference publication",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2023-02-07T16:04:12",
            "latestDataUpdateTime": "2023-09-28T10:20:54",
            "updateFrequency": "",
            "dataLineage": "The data is based on pressure-level output from the IFS model provided by Inna Polichtchouk. It has been lightly processed to conform to the SNAPSI data request. The data has been published by the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "control, IFS, ECMWF, stratosphere, arctic, antarctic, stratospheric polar vortex, SNAPSI, SNAP, APARC",
            "publicationState": "published",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": true,
            "language": "English",
            "resolution": "50 km",
            "status": "ongoing",
            "dataPublishedTime": "2024-09-30T16:04:04",
            "doiPublishedTime": null,
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 1,
                "bboxName": "",
                "eastBoundLongitude": 180.0,
                "westBoundLongitude": -180.0,
                "southBoundLatitude": -90.0,
                "northBoundLatitude": 90.0
            },
            "verticalExtent": {
                "ob_id": 249,
                "highestLevelBound": 40.0,
                "lowestLevelBound": 100000.0,
                "units": "Pa"
            },
            "result_field": {
                "ob_id": 40792,
                "dataPath": "/badc/snap/data/post-cmip6/SNAPSI/ECMWF/IFS/control",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 1800239377712,
                "numberOfFiles": 9793,
                "fileFormat": "Files are Net-CDF formatted"
            },
            "timePeriod": {
                "ob_id": 10988,
                "startTime": "2018-01-25T00:00:00",
                "endTime": "2019-11-15T00:00:00"
            },
            "resultQuality": {
                "ob_id": 3916,
                "explanation": "Quality control checks performed at CEDA confirmed that the data meets the SNAPSI metadata requirements.",
                "passesTest": true,
                "resultTitle": "CEDA Data Quality Statement",
                "date": "2022-03-29"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": {
                "ob_id": 40371,
                "uuid": "2c99b8a0b15746e9bc97a7f6a331c3c7",
                "short_code": "comp",
                "title": "ECMWF IFS Model",
                "abstract": "The underlying data was produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) IFS model for the SNAPSI project."
            },
            "procedureCompositeProcess": null,
            "imageDetails": [
                229
            ],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2560,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licence": {
                        "ob_id": 56,
                        "licenceURL": "https://creativecommons.org/licenses/by-sa/4.0/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [
                {
                    "ob_id": 37088,
                    "uuid": "0a5a1ce22fb047749e040879efa8e9b5",
                    "short_code": "proj",
                    "title": "Stratospheric Nudging And Predictable Surface Impacts (SNAPSI)",
                    "abstract": "SNAPSI is a model intercomparison protocol designed to study the role of the Arctic and Antarctic stratospheric polar vortices in sub-seasonal to seasonal forecast models. Based on a set of controlled, sub-seasonal, ensemble forecasts of three recent events, the protocol aims to address four main scientific goals. \r\nFirst, to quantify the impact of improved stratospheric forecasts on near-surface forecast skill. \r\nSecond, to attribute specific extreme events to stratospheric variability. \r\nThird, to assess the mechanisms by which the stratosphere influences the troposphere in the forecast models, \r\nand fourth, to investigate the wave processes that lead to the stratospheric anomalies themselves. \r\nAlthough not a primary focus, the experiments are furthermore expected to shed light on coupling between the tropical stratosphere and troposphere. \r\nThe output requested will allow for a more detailed, process-based community analysis than has been possible with existing databases of sub-seasonal forecasts."
                }
            ],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                6021,
                6022,
                6023,
                9045,
                50415,
                50417,
                50418,
                50419,
                50426,
                50427,
                50428,
                50429,
                50431,
                50445,
                50475,
                50481,
                50496,
                50498,
                50549,
                50566,
                50577,
                50579,
                50582,
                50587,
                50588,
                50590,
                50597,
                50605,
                50609,
                50615,
                52755,
                53111,
                54228,
                54350,
                60438,
                62560,
                62561,
                64078,
                66075,
                66077,
                71619,
                71634
            ],
            "vocabularyKeywords": [],
            "identifier_set": [],
            "observationcollection_set": [
                {
                    "ob_id": 40380,
                    "uuid": "d160e81ccf9842d0b1c0a25b56a5ddfa",
                    "short_code": "coll",
                    "title": "Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): data produced by the IFS model at ECMWF",
                    "abstract": "The IFS model contribution to the Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) project produced by scientists at the European Centre for Medium-Range Weather Forecasts (ECMWF). \r\n\r\n\r\nThe SNAPSI project is a model intercomparison project to study the role of the stratosphere in subseasonal forecasts following stratospheric sudden warmings and the representation of stratosphere-troposphere coupling in subseasonal forecast models.\r\n\r\n\r\n------------------------------------------\r\nSources of additional information\r\n------------------------------------------\r\nThe following web links are provided in the Details/Docs section of this catalogue record:\r\n\r\n- Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): A Protocol for Investigating the Role of the Stratospheric Polar Vortex in Subseasonal to Seasonal Forecasts\r\n- New set of controlled numerical experiments: Stratospheric Nudging And Predictable Surface Impacts (SNAPSI)\r\n- ECMWF IFS model reference publication"
                }
            ],
            "responsiblepartyinfo_set": [
                198414,
                198415,
                198416,
                198417,
                198418,
                198419,
                198420,
                198421,
                198422,
                198423
            ],
            "onlineresource_set": [
                84957,
                84958,
                84956
            ]
        },
        {
            "ob_id": 40795,
            "uuid": "0810c3abbaac4f09874d63982e1247b2",
            "title": "POLCOMS model run in the Northwest European continental shelf generating current data and sea surface elevation for 10 years from 1999.",
            "abstract": "The dataset consists of depth-averaged eastward and northward current velocities, sea surface heights above mean tidal level, and eastward and northward current induced stresses at the seabed. The dataset is a gridded dataset, with grid resolution of 1/9th x 1/6th degree, i.e. approximately 12 km. It covers the Northwest European continental shelf ranging from 48 to 63 degrees latitude and -12 to 13 degrees longitude. The data are 30 minute averages and cover the period from 01 January 1999 to 31 December 2008. The dataset was generated by the Proudman Oceanographic Laboratory Coastal Ocean Modelling System (POLCOMS) numerical model run by the National Oceanography Centre (NOC) Liverpool. It was funded by the Aggregate Levy Sustainability Fund (ALSF) under contract MEPF 09-P114 and Natural Environment Research Council (NERC) National Capability (NC) funding. The dataset consists of 120 data files in Climate and Forecast (CF) compliant NetCDF format.",
            "creationDate": "2023-09-27T13:18:56.602969",
            "lastUpdatedDate": "2023-09-27T13:18:56",
            "latestDataUpdateTime": "2023-09-13T10:23:47",
            "updateFrequency": "",
            "dataLineage": "The data are archived on the British Oceanographic Data Centre (BODC)'s space at the Centre for Environmental Data Analysis (CEDA) and assigned a DOI. No quality control procedures were applied by BODC.",
            "removedDataReason": "",
            "keywords": "",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "final",
            "dataPublishedTime": "2023-09-18T15:36:05",
            "doiPublishedTime": "2023-09-18T15:36:05",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3980,
                "bboxName": "",
                "eastBoundLongitude": 13.0,
                "westBoundLongitude": -12.0,
                "southBoundLatitude": 48.0,
                "northBoundLatitude": 63.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40794,
                "dataPath": "/bodc/POL150147/POLCOMS_HIGH_FREQUENCY_UV",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 142030898408,
                "numberOfFiles": 122,
                "fileFormat": "Climate and Forecast compliant NetCDFs"
            },
            "timePeriod": {
                "ob_id": 11332,
                "startTime": "1999-01-01T00:00:00",
                "endTime": "2008-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 4416,
                "explanation": "The data are provided as-is with no quality control undertaken by the British Oceanographic Data Centre (BODC). The data suppliers have not indicated if any quality control has been undertaken on these data.",
                "passesTest": true,
                "resultTitle": "BODC Data Quality Statement",
                "date": "2023-09-27"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2569,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 36,
                        "licenceURL": "https://www.bodc.ac.uk/data/documents/nodb/599476/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                75643,
                75649,
                75650,
                75651,
                75652,
                75653,
                75654,
                75655
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12700
            ],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                198431,
                198430,
                198429,
                198428,
                198434,
                198435,
                198436,
                198433,
                198432,
                198438,
                198437,
                198439
            ],
            "onlineresource_set": []
        },
        {
            "ob_id": 40797,
            "uuid": "910198c065af47518bc6a2522c0ebf73",
            "title": "WAM model run in the Northwest European continental shelf generating surface and bottom wave data for 10 years from 1999.",
            "abstract": "The dataset consists of significant wave heights (Hm0), peak and second moment wave periods, sea surface wave directions, friction velocities, bottom orbital peak frequencies, velocities, directions, and periods (second moment). The dataset is a gridded dataset, with grid resolution of 1/9th x 1/6th degree, i.e. approximately 12 km. It covers the Northwest European continental shelf ranging from 48 to 63 degrees latitude and -12 to 13 degrees longitude. The data are 1 hour averages and cover the period from 01 January 1999 to 31 December 2008. The dataset was generated by the Wave Modelling (WAM) model run by the National Oceanography Centre (NOC) Liverpool. It was funded by the Aggregate Levy Sustainability Fund (ALSF) under contract MEPF 09-P114 and Natural Environment Research Council (NERC) National Capability (NC) funding. The dataset consists of 120 data files in Climate and Forecast (CF) compliant NetCDF format.",
            "creationDate": "2023-09-27T13:59:55.301034",
            "lastUpdatedDate": "2023-09-27T13:59:55",
            "latestDataUpdateTime": "2025-01-18T03:20:16",
            "updateFrequency": "",
            "dataLineage": "The data are archived on the British Oceanographic Data Centre (BODC)'s space at the Centre for Environmental Data Analysis (CEDA) and assigned a DOI. No quality control procedures were applied by BODC.",
            "removedDataReason": "",
            "keywords": "",
            "publicationState": "citable",
            "nonGeographicFlag": false,
            "dontHarvestFromProjects": false,
            "language": "English",
            "resolution": "",
            "status": "final",
            "dataPublishedTime": "2023-09-18T16:38:13",
            "doiPublishedTime": "2023-09-18T16:38:13",
            "removedDataTime": null,
            "geographicExtent": {
                "ob_id": 3980,
                "bboxName": "",
                "eastBoundLongitude": 13.0,
                "westBoundLongitude": -12.0,
                "southBoundLatitude": 48.0,
                "northBoundLatitude": 63.0
            },
            "verticalExtent": null,
            "result_field": {
                "ob_id": 40796,
                "dataPath": "/bodc/POL150147/WAM_HOURLY_WAVE",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 127827601202,
                "numberOfFiles": 122,
                "fileFormat": "Climate and Forecast compliant NetCDFs"
            },
            "timePeriod": {
                "ob_id": 11332,
                "startTime": "1999-01-01T00:00:00",
                "endTime": "2008-12-31T23:59:59"
            },
            "resultQuality": {
                "ob_id": 4417,
                "explanation": "The data are provided as-is with no quality control undertaken by the British Oceanographic Data Centre (BODC). The data suppliers have not indicated if any quality control has been undertaken on these data.",
                "passesTest": true,
                "resultTitle": "BODC Data Quality Statement",
                "date": "2023-09-27"
            },
            "validTimePeriod": null,
            "procedureAcquisition": null,
            "procedureComputation": null,
            "procedureCompositeProcess": null,
            "imageDetails": [],
            "discoveryKeywords": [],
            "permissions": [
                {
                    "ob_id": 2569,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licence": {
                        "ob_id": 36,
                        "licenceURL": "https://www.bodc.ac.uk/data/documents/nodb/599476/",
                        "licenceClassifications": [
                            {
                                "ob_id": 3,
                                "classification": "any"
                            }
                        ]
                    }
                }
            ],
            "projects": [],
            "inspireTheme": [],
            "topicCategory": [],
            "phenomena": [
                75637,
                75638,
                75639,
                75640,
                75641,
                75642,
                75643,
                75644,
                75645,
                75646,
                75647,
                75648
            ],
            "vocabularyKeywords": [],
            "identifier_set": [
                12701
            ],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                198444,
                198443,
                198442,
                198441,
                198440,
                198446,
                198447,
                198448,
                198445,
                198449,
                198450,
                198451
            ],
            "onlineresource_set": []
        }
    ]
}