Observation List
Get a list of Observation objects.
GET /api/v3/observations/?format=api&offset=9400
{ "count": 10256, "next": "https://api.catalogue.ceda.ac.uk/api/v3/observations/?format=api&limit=100&offset=9500", "previous": "https://api.catalogue.ceda.ac.uk/api/v3/observations/?format=api&limit=100&offset=9300", "results": [ { "ob_id": 41502, "uuid": "d174d45cae2745f9af08ab078aade0f2", "title": "Ozone Abundance Data from Model 49i Ozone Analyzer Instrument at the Birmingham Air Quality Site, 2019 onwards", "abstract": "Mass Fraction of Ozone (O3) in air measured at 2 metres above ground level by a Thermo Model 49i Ozone Analyzer Instrument at the Birmingham Air Quality Site (MAQS) for the Integrated Research Observation System for Clean Air (OSCA) project.", "creationDate": "2022-08-23T16:26:27.509628", "lastUpdatedDate": "2022-08-23T16:26:27", "latestDataUpdateTime": null, "updateFrequency": "monthly", "dataLineage": "Data are collected by the project team and transfered directly from the instrument to the computer database, before being transferred to the general database, where it is processed, averaged over minute time intervals and flagged where data is suspect. Once complete, data are uploaded to CEDA for archiving.\r\nData processing software found in: https://github.com/ncasuk/AMF_CVs/releases/tag/v1.0.0", "removedDataReason": "", "keywords": "OSCA, air quality, supersite, O3,baqs,OSCA-AQ", "publicationState": "preview", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 3610, "bboxName": "", "eastBoundLongitude": -2.214244, "westBoundLongitude": -2.214244, "southBoundLatitude": 53.456636, "northBoundLatitude": 53.456636 }, "verticalExtent": null, "result_field": { "ob_id": 41503, "dataPath": "/badc/osca/data/birmingham/OSCA_BAQS_Thermol_49i_O3/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 121709696, "numberOfFiles": 91, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 11572, "startTime": "2019-04-01T00:00:00", "endTime": null }, "resultQuality": { "ob_id": 4065, "explanation": "This data is then audited using a baseline zero level and the response factor every 6 month audit. If the zero-corrected O3 level falls below 0 or above 300 ppb it is flagged. ", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2022-08-23" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 41504, "uuid": "a67b799f60624060bc91eb14e493cbf8", "short_code": "acq", "title": "Acquisition for: Ozone Abundance Data from Model 49i Ozone Analyzer Instrument at Birmingham Air Quality Site 2019-22", "abstract": "Acquisition for: Ozone Abundance Data from Model 49i Ozone Analyzer Instrument at Birmingham Air Quality Site 2019-22" }, "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": 37963, "uuid": "ab605b618884401c91afd0274c92144e", "short_code": "proj", "title": "Integrated Research Observation System for Clean Air (OSCA)", "abstract": "The Integrated Research Observation System for Clean Air (OSCA) is a multidisciplinary research project, combining atmospheric observations, laboratory studies, data processing development and integrated scientific synthesis to deliver improved understanding of urban air pollution in the UK, and enable delivery of key objectives of the Clean Air: Analysis and Solutions Programme. OSCA exploits recent significant UK investment in air pollution measurement infrastructure - the air pollution supersites in London, Birmingham and Manchester - and other new UKRI-funded capability developed for field, modelling and laboratory studies of air pollution processes. \r\n\r\nThe project brings together a research team spanning 5 UK HEIs and 2 NERC centres across disciplines of atmospheric science, engineering, mathematics, chemistry, physics and computer science and includes investigators with direct involvement in the provision of science advice in support of policy development - through established links with (e.g.) Department for Environment, Food and Rural Affairs (Defra), Department for Transport (DfT), Department of Health (DoH), regional policymakers, and international bodies. OSCA will provide scientific insights that will inform implementation of the new UK Clean Air Strategy, contribute to development and evaluation of regional air quality policy measures, and enable the development and optimisation of emission abatement measures, for the protection of human health. The project provides a definitive assessment of the current state of UK urban air quality, and of trends in air pollutants - both those expected in response to policy and changing behaviour, and unanticipated consequences of these - and provides data and infrastructure to underpin other proposed projects in the Clean Air Programme. NE/T001984/1, \tNE/T001917/1, NE/T001909/2, NE/T001798/1, NE/T001925/1, NE/T001798/2, NE/T001976/1, NE/T001909/1." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 53936, 58082, 58083, 58292, 58299, 58312, 58350, 61969, 74433, 74434, 74435, 74436 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 45670, "uuid": "824c0c058de442ab885431eba938dc03", "short_code": "coll", "title": "NCAS archive of Air quality measurements from Manchester, Birmingham and London air quality supersites", "abstract": "This collection contains maeasurements of air quality parameters from a suite of instruments deployed at 3 urban supesites located in Manchester, Birmingham and London Honor Oak Park.\r\n\r\nMore details to follow." } ], "responsiblepartyinfo_set": [ 202253, 202254, 202255, 202256, 202257, 202258, 202259, 202260 ], "onlineresource_set": [ 86094 ] }, { "ob_id": 41507, "uuid": "b32f09c9aeba44d1846e6de9423e9895", "title": "Ozone Abundance Data from Teledyne T400 Instrument at London Honor Oak Park Air Quality Supersite", "abstract": "Mass Fraction of Ozone (O3) in air measured at 5 metres above ground level by a Teledyne T400 Ozone Analyzer Instrument at the London Honor Oak Park Air Quality Site (LHOP) for the Integrated Research Observation System for Clean Air (OSCA) project, 2019 onwards.", "creationDate": "2024-02-27T16:07:26.206626", "lastUpdatedDate": "2024-02-27T16:07:26", "latestDataUpdateTime": "2024-03-09T03:22:34", "updateFrequency": "notPlanned", "dataLineage": "Data is saved directly from the instrument to the computer, before being transferred to the general database, where it is processed, automatically averaged over minute time intervals and flagged where data is suspect. Once complete, data is uploaded to CEDA for archiving.", "removedDataReason": "", "keywords": "OSCA,O3,LHOP, LAQS,London", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2024-03-05T10:27:20", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 3866, "bboxName": "LAQS", "eastBoundLongitude": -0.04, "westBoundLongitude": -0.04, "southBoundLatitude": 51.45, "northBoundLatitude": 51.45 }, "verticalExtent": null, "result_field": { "ob_id": 41530, "dataPath": "/badc/osca/data/london/OSCA_LHOP_Teledyne_T400", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 35389815, "numberOfFiles": 49, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 11573, "startTime": "2019-01-24T00:00:00", "endTime": null }, "resultQuality": { "ob_id": 4536, "explanation": "The data is calibrated and scaled on a monthly basis using a baseline 0 and span from the internal O3 generator. The instrument is audited every 6 months. If the scaled and audited O3 level falls below 0 or above 150 ppb the data is flagged as suspect and is excluded.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-02-27" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 41508, "uuid": "8e7f575830974b568b7704048ec172a9", "short_code": "acq", "title": "Acquisition for: Ozone Abundance Data from Teledyne T400 Instrument at London Honor Oak Park Air Quality Supersite", "abstract": "Acquisition for: Ozone Abundance Data from Teledyne T400 Instrument at London Honor Oak Park Air Quality Supersite" }, "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": [], "inspireTheme": [], "topicCategory": [], "phenomena": [ 61969, 74172, 74173 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 45670, "uuid": "824c0c058de442ab885431eba938dc03", "short_code": "coll", "title": "NCAS archive of Air quality measurements from Manchester, Birmingham and London air quality supersites", "abstract": "This collection contains maeasurements of air quality parameters from a suite of instruments deployed at 3 urban supesites located in Manchester, Birmingham and London Honor Oak Park.\r\n\r\nMore details to follow." } ], "responsiblepartyinfo_set": [ 202268, 202269, 202270, 202271, 202272, 202273, 202274, 202371, 202275 ], "onlineresource_set": [] }, { "ob_id": 41511, "uuid": "16cfebcfd225477cad0447ee2b6a3b64", "title": "FAAM C364 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": "2024-02-29T17:26:47.920507", "lastUpdatedDate": "2024-02-29T17:26:47", "latestDataUpdateTime": "2024-03-09T03:22:35", "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": "2024-02-29T13:41:15", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 4156, "bboxName": "", "eastBoundLongitude": -0.3273865, "westBoundLongitude": -6.9359426, "southBoundLatitude": 50.73606, "northBoundLatitude": 52.355835 }, "verticalExtent": null, "result_field": { "ob_id": 41510, "dataPath": "/badc/faam/data/2024/c364-jan-09", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 4911549324, "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": 11574, "startTime": "2024-01-09T10:08:39", "endTime": "2024-01-09T15:28:36" }, "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": 41512, "uuid": "b5f22ec4b1294d3187c9dece3a0f7466", "short_code": "acq", "title": "FAAM Flight C364 Acquisition", "abstract": "FAAM Flight C364 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, 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, 60172, 60173, 60202, 60203, 60204, 60205, 60206, 60207, 60208, 60209, 60213, 60214, 60215, 60216, 60217, 60218, 60219, 60220, 60221, 60222, 60223, 60224, 60225, 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, 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, 72012, 74162, 74163, 74164, 74165, 74166, 74167, 74168, 74169, 74171 ], "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": [ 202278, 202279, 202280, 202281, 202282, 202283, 202284, 202285, 202286, 202287 ], "onlineresource_set": [ 86096, 86097 ] }, { "ob_id": 41516, "uuid": "699488ed42734c6eb260d6d6d173d56d", "title": "FAAM C365 AMCCA 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 AMCCA FAAM Aircraft Project project.", "creationDate": "2024-02-29T17:26:57.621363", "lastUpdatedDate": "2024-02-29T17:26:57", "latestDataUpdateTime": "2024-06-19T12:16:05", "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": "AMCCA, FAAM, airborne, atmospheric measurments", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2024-02-29T11:35:46", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 4157, "bboxName": "", "eastBoundLongitude": -0.399125, "westBoundLongitude": -5.8867292, "southBoundLatitude": 50.91644, "northBoundLatitude": 52.360493 }, "verticalExtent": null, "result_field": { "ob_id": 41515, "dataPath": "/badc/faam/data/2024/c365-jan-12", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 10827531018, "numberOfFiles": 53, "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": 11575, "startTime": "2024-01-12T08:14:34", "endTime": "2024-01-12T15:18:45" }, "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": 41518, "uuid": "d0f10f4d550a43fe9e0e4913d0249e35", "short_code": "acq", "title": "FAAM Flight C365 Acquisition", "abstract": "FAAM Flight C365 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": 41514, "uuid": "215af4b50e78460faf0b55173b44ec8f", "short_code": "proj", "title": "Airborne Measurements of Charged Cloud and Aerosol (AMCCA)", "abstract": "The Airborne Measurements of Charged Cloud and Aerosol (AMCCA) project will use the FAAM BAe-146 aircraft to make measurements of electric charge at stratiform cloud and dust aerosol layer edges, in conjunction radiosonde measurements of electric charge released from the University of Reading Atmospheric Observatory. \r\n\r\nThis project will investigate how the natural electric fields always present in the atmosphere affect cloud and aerosol processes. These include the increased sticking probability of colliding droplets which are charged, an additional electrical uplift force reducing the rate of dust deposition, and enhanced removal of charged dust and aerosol by water droplets. Such effects are known to occur in and around stratiform cloud and above and within atmospheric dust layers.\r\n\r\nThese flights will allow us to identify which in-cloud processes are affected by electric charge, and how dust size distributions relate to charge, which has never been quantified experimentally before.\r\n\r\nAMCCA is a FAAM Research Runway 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, 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, 60202, 60203, 60204, 60205, 60206, 60207, 60208, 60209, 60213, 60214, 60215, 60216, 60217, 60218, 60219, 60220, 60221, 60222, 60223, 60224, 60225, 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, 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, 62664, 62665, 62666, 62679, 72012, 74055, 74056, 74057, 74058, 74059, 74060, 74061, 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, 74092, 74093, 74095, 74096, 74097, 74099, 74100, 74101, 74102, 74103, 74104, 74105, 74162, 74163, 74164, 74165, 74166, 74167, 74168, 74169, 74171, 74504, 74505, 74507, 74508, 74509, 74510, 74511, 74512, 74513, 74514, 74515, 74516, 75198, 75199 ], "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": 41517, "uuid": "5572f4746ff74a5089fcdfbe62a6ecb5", "short_code": "coll", "title": "AMCCA: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for AMCCA FAAM Aircraft Project." } ], "responsiblepartyinfo_set": [ 202296, 202297, 202298, 202299, 202300, 202301, 202302, 202303, 202304, 202305 ], "onlineresource_set": [ 86099, 86100 ] }, { "ob_id": 41521, "uuid": "cc29461803694f95a8031e675b1f397d", "title": "FAAM C366 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": "2024-02-29T17:27:04.439450", "lastUpdatedDate": "2024-02-29T17:27:04", "latestDataUpdateTime": "2024-03-09T03:22:36", "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": "2024-02-29T11:35:53", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 4158, "bboxName": "", "eastBoundLongitude": -0.43090066, "westBoundLongitude": -6.4929814, "southBoundLatitude": 50.246323, "northBoundLatitude": 52.355167 }, "verticalExtent": null, "result_field": { "ob_id": 41520, "dataPath": "/badc/faam/data/2024/c366-jan-17", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 7726228164, "numberOfFiles": 35, "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": 11576, "startTime": "2024-01-17T08:11:28", "endTime": "2024-01-17T14:44:14" }, "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": 41522, "uuid": "4ffe33a1d08042948fc5bfdd22eba4a4", "short_code": "acq", "title": "FAAM Flight C366 Acquisition", "abstract": "FAAM Flight C366 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, 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, 60213, 60214, 60215, 60216, 60217, 60218, 60219, 60220, 60221, 60222, 60223, 60224, 60225, 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, 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, 72012, 74162, 74163, 74164, 74165, 74166, 74167, 74168, 74169, 74171 ], "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": [ 202322, 202323, 202324, 202325, 202326, 202327, 202328, 202329, 202330, 202331 ], "onlineresource_set": [ 86102, 86103 ] }, { "ob_id": 41525, "uuid": "4ed5b3ce664f4da0adf20bda0affd1cb", "title": "Delta development thresholds simulation input and output files", "abstract": "The simulations in this dataset were designed to explore the potential limiting effects of wave height and tidal range on delta formation, with results demonstrating that large enough combinations of these processes may prevent deltas from forming. Simulations use the open source model Delft3D. The simulations model an idealised coast (19.75 km alongshore by 9 km cross-shore) and river (width 250 m by length 50 km) with constant discharge of water (1280 m3 s-1) and sediment (128 kg s-1), and with various combinations of significant wave height (up to 2 m) and tidal range (up to 6 m). Data outputs include velocities, depths, sediment concentrations, and wave conditions, amongst others. Simulations represent either 36 or 72 years of morphological development.", "creationDate": "2024-03-04T10:53:32.170912", "lastUpdatedDate": "2024-03-04T10:53:32.170919", "latestDataUpdateTime": "2024-03-04T10:53:32.170924", "updateFrequency": "notPlanned", "dataLineage": "Model setup files were generated using a combination of the Delft3D UI and associated programs, text editors, and MATLAB scripts.\r\nModel output files were generated by running simulations using either standalone Delft3D-FLOW, or coupled Delft3D-FLOW and Delft3D-WAVE.\r\nModel animations were produced using MATLAB scripts.", "removedDataReason": "", "keywords": "Delft3D,Numerical modelling,Coastal,Waves,Tides", "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": 11577, "startTime": "0001-01-01T00:00:00", "endTime": "0001-01-02T00:00:00" }, "resultQuality": { "ob_id": 4537, "explanation": "-", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-03-04" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 41527, "uuid": "6527ec3db937453da915c0bad26d8bc3", "short_code": "comp", "title": "Delft3D 4", "abstract": "Delft3D numerically models hydrodynamics, waves, and sediment transport processes (amongst others)." }, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 41526, "uuid": "53b564727ccd40bfa0751815bfe4628c", "short_code": "proj", "title": "ENVISION doctoral training partnership", "abstract": "Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 202340, 202341, 202342, 202343, 202344, 202345, 202346, 202347, 202348, 202349 ], "onlineresource_set": [] }, { "ob_id": 41529, "uuid": "44a0f04f9b37423e8534cc96a8cbe990", "title": "Daily Transects and Areas from Light Detection and Ranging (LiDAR) scans of an eroding soft cliff at Happisburgh, UK (April-December 2019).", "abstract": "This dataset contains 236 transects and areas point-cloud elevation and colour intensity data collected daily along a 450 metre coastal stretch at Happisburgh, UK, over a time span of 9 months (April 6, 2019 to December 23, 2019). Included are subsets of these point-clouds, named transects and grids. Scans were taken approximately daily, and on some days only one scanner was run resulting in half-size scans. A single FARO S350 LiDAR scanner was placed at two fixed locations on the beach, spaced 178 metres alongshore and between 30 to 40 metres from the 10 metre high cliff. The duration of the scanning at each location was around 30 minutes. These data were collected to better understand the dynamic of beach-cliff and shore platform interaction along soft cliffed coasts. The shapefiles of the transects and areas are also included for a more complete description. ScanLAB Projects Ltd were responsible for the collection of the data, along with the British Geological Survey (BGS), funded by the UK Natural Environment Research Council (NE/M004996/1; BLUE-coast project).", "creationDate": "2024-03-04T13:47:06.818302", "lastUpdatedDate": "2024-03-04T13:47:06", "latestDataUpdateTime": "2024-03-04T13:47:06", "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": "", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "final", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 4153, "bboxName": "", "eastBoundLongitude": 1.54, "westBoundLongitude": 1.531, "southBoundLatitude": 52.823, "northBoundLatitude": 52.829 }, "verticalExtent": null, "result_field": { "ob_id": 41528, "dataPath": "/bodc/bgs240024", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1850132400594, "numberOfFiles": 14886, "fileFormat": null }, "timePeriod": { "ob_id": 11578, "startTime": "2019-04-06T00:00:00", "endTime": "2019-12-23T23:59:59" }, "resultQuality": { "ob_id": 4538, "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": "2024-03-04" }, "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": [ 12841 ], "observationcollection_set": [ { "ob_id": 40060, "uuid": "2c6f3201f01d4346a97ff8f08a8c15c9", "short_code": "coll", "title": "LiDAR (Light Detection And Ranging) images and model output from cliffs at Happisburgh, Norfolk, UK, 2019, from BLUE-coast and ScanLAB projects.", "abstract": "A colour LiDAR (Light Detection And Ranging) dataset was obtained at the cliffs at Happisburgh, Norfolk, UK, over a period of 9 months (April 6, 2019 to December 23, 2019). The scans were taken daily for 90% of the study period using a FARO S350 TLS (Terrestrial LiDAR Scanner). Scans were carried out from two locations consecutively, positioned at around 40 m from the cliffs. The full scans are also split into smaller subsets: \"slices\", 1 m wide bands oriented perpendicular to the shoreline, and \"grids\", smaller areas of the beach, to assist analysis. The numerical model SWAN (Simulated Waves Nearshore) (v41.31a), run in non-stationary mode, was used to simulate hourly sea states at the study site to aid in the context of environmental conditions. Wind parameters from the ERA5 reanalysis and bathymetry from the OceanWise 1 arc second digital elevation model (DEM) were used to force the SWAN model, and obtained wave parameters in 4x6 km rectangular grid around the scanning site, with a 10m interval, and a 26x26 km square grid encompassing the smaller grid, with a 100 m interval. The LiDAR scans were also projected into both colour and intensity images, viewing the shoreline from above. This research was funded by the UK Natural Environment Research Council (NE/M004996/1; BLUE-coast project). The on-location LiDAR Scanning and Technical R&D operated by ScanLAB Projects Ltd was funded by Innovate UK's Audience of the Future Program (Multiscale 3D Scanning with Framerate for TV and Immersive Applications project). The first 6 months of LiDAR scans (April to September 2019) were funded by Innovate UK, and this project was continued by the NERC BLUE-coast funding for the last 3 months (October to December 2019)." } ], "responsiblepartyinfo_set": [ 202359, 202358, 202357, 202356, 202355, 202354, 202360, 202361, 202362, 202363, 202364, 202365, 202366, 202367, 202368, 202369, 202370 ], "onlineresource_set": [] }, { "ob_id": 41531, "uuid": "025b174a38404e8bbc69ef7f144e577d", "title": "SASSO data from the Met Office Unified Model", "abstract": "This dataset is the Met Office Unified Model data that was used in the SASSO-funded study:\r\nDamany-Pearce, L., Johnson, B., Wells, A. et al. Australian wildfires cause the largest stratospheric warming since Pinatubo and extends the lifetime of the Antarctic ozone hole. Sci Rep 12, 12665 (2022). https://doi.org/10.1038/s41598-022-15794-3\r\n\r\nAs part of the SASSO project researchers collaborated with the Met Office and used the UK Earth System Model (UKESM1) to investigate the impact of the intense wildfires and resulting smoke injections in the stratosphere. The work concluded that: Australian wildfires cause the largest stratospheric warming since Pinatubo and extended the lifetime of the Antarctic ozone hole. Data provided here is from the UKESM1 simulations used in those investigations.\r\n\r\nSpecifically the data consists of zonal mean air temperature (T) and horizonal wind (U) as monthly means. These are monthly means from a single year, since the simulations in the study ran just for a one year. In the dataset there are 3 groups of simulations, each with its own folder: \"aerosol_and_ozone\", \"aerosol_only\" and \"ozone_only\". In each group there are 10 simulations making up a 10 member ensemble. The zonal means are the average across all longitudes (-180 to 180).", "creationDate": "2024-03-05T11:46:49.242713", "lastUpdatedDate": "2024-03-05T11:46:49", "latestDataUpdateTime": "2024-09-11T13:12:24", "updateFrequency": "notPlanned", "dataLineage": "Met Office Unified Model version 11.1\r\n\r\nUKESM1 UKESM – The UK Earth System Modelling project [ukesm.ac.uk],\r\n\r\nUKESM1: Description and Evaluation of the U.K. Earth System Model [agupubs.onlinelibrary.wiley.com]", "removedDataReason": "", "keywords": "Aerosol, ozone, stratosphere, model, wildfire, SASSO", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-09-04T13:47:45", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 4583, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 41630, "dataPath": "/badc/deposited2024/SASSO/SASSO_UMDATA_JOHNSON_DAMANY-PE", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 19195756, "numberOfFiles": 241, "fileFormat": "Files are Net-CDF formatted" }, "timePeriod": { "ob_id": 11579, "startTime": "2020-01-01T00:00:00", "endTime": "2020-12-31T00:00:00" }, "resultQuality": { "ob_id": 4539, "explanation": "Data has been produced from Met Office outputs via Python Iris version 3.7", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-03-05" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 43071, "uuid": "6d38a9f1b40e48b5bae587a69d1bb297", "short_code": "comp", "title": "Data was generated from UKESM1, the UK Earth System Model Version 1, which is a configuration of the Met Office Unified Model. Simulations are described in Damany-Pearce et al. (2022): https://www.nature.com/articles/s41598-022-15794-3.", "abstract": "Data was generated from UKESM1, the UK Earth System Model Version 1, which is a configuration of the Met Office Unified Model. Simulations are described in Damany-Pearce et al. (2022): https://www.nature.com/articles/s41598-022-15794-3." }, "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": [ { "ob_id": 38101, "uuid": "7a4feaf0fd624dacaf34a0129f074fcc", "short_code": "proj", "title": "Soot Aerodynamic Size Selection for Optical properties (SASSO)", "abstract": "Black carbon (BC) and brown carbon (BrC) aerosols are widely studied components of atmospheric aerosol because they can absorb solar radiation and heat the atmosphere, causing positive radiative forcing of the climate. Although BC and BrC are very important for climate, they are poorly represented in atmospheric models. This is in part due to the complex microphysical properties of BC and the lack of accurate refractive index (RI) descriptions for both BC and BrC.\r\nSASSO capitalized on a unique combination of new technical and methodological developments at the University of Manchester and the University of Exeter to generate experimental data on a variety of soot types, providing much greater constraints on optical properties than previously possible. Specifically, SASSO used the Aerodynamic Aerosol Classifier (AAC) for size selection of emissions from wood burning, diesel combustion, and secondary organic aerosol (SOA) formation, prior to optical measurements using cavity ring-down and photoacoustic spectroscopy with the EXtinction, SCattering and Absorption of Light for AirBorne Aerosol Research (EXSCALABAR) instrumentation, custom-built by the Met Office.\r\nIn addition, to test the \"lensing effect,\" non-absorbing and weakly absorbing organic materials were condensed onto BC to form coated soot particles. The mass concentration of black carbon aerosol was measured using the Single Particle Soot Photometer (SP2), and chemical information was obtained via Aerosol Mass Spectrometry (AMS), allowing different optical models for mixed particles to be evaluated." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6023, 9042, 9043, 19039, 19043, 51186, 51187, 53106, 54871, 62353, 62540, 66241, 70293 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 202373, 202372, 202374, 202375, 202376, 202377, 202378, 202888, 202379 ], "onlineresource_set": [ 86225, 86614, 86615 ] }, { "ob_id": 41533, "uuid": "7545a606606c4e9bb6139dfc21a95264", "title": "Andes glaciers and ice caps outlines during the Little Ice Age (LIA)", "abstract": "This dataset comprises a shapefile of >5500 outlines of glaciers and ice caps during the Little Ice Age (LIA) approximately 1400 to 1850, spanning across the Andes from the equator to -60 degrees South. These outlines have been manually digitised by reshaping Randolph Glacier Inventory version 6 (RGI_v6) (https://doi.org/10.7265/4m1f-gd79) outlines to the extent interpreted to best represent the LIA. The LIA extent was deduced manually-visually by interpreting geomorphological evidence; primarily moraine crests and trimlines, within high-resolution aerial imagery; primarily WorldView and GeoEye. More methodological details and usage of this dataset for analysis of glacier area changes from the LIA to post year 2000 are presented in the parent paper: Carrivick et al., 2024. Accelerating glacier area loss across the Andes since the Little Ice Age. Geophysical Research Letters (submitted).", "creationDate": "2024-03-07T15:26:42.249234", "lastUpdatedDate": "2024-03-07T15:26:42", "latestDataUpdateTime": "2024-06-26T01:47:08", "updateFrequency": "notPlanned", "dataLineage": "Data were produced by Jonathan Carrivick and the Deplete and Retreat NERC Highlights project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "glaciers,ice caps,Andes,Little Ice Age", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-06-21T13:07:15", "doiPublishedTime": "2024-06-21T13:08:43", "removedDataTime": null, "geographicExtent": { "ob_id": 4162, "bboxName": "", "eastBoundLongitude": -65.0, "westBoundLongitude": -85.0, "southBoundLatitude": -60.0, "northBoundLatitude": 0.0 }, "verticalExtent": null, "result_field": { "ob_id": 42329, "dataPath": "/badc/deposited2024/Andes_GICs_LIA", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 81728184, "numberOfFiles": 9, "fileFormat": "Shape Files" }, "timePeriod": { "ob_id": 11580, "startTime": "1400-01-01T00:00:00", "endTime": "1850-12-31T00:00:00" }, "resultQuality": { "ob_id": 4540, "explanation": "please see accompanying paper for uncertainty analysis", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-03-07" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 43008, "uuid": "6d9b55418ae34e2da24ed56008d3dd13", "short_code": "comp", "title": "Computation for Andes glaciers and ice caps outlines during the Little Ice Age (LIA)", "abstract": "This computation took Randolph Glacier Inventory version 6 (RGI_v6) outlines and reshaped them to the extent interpreted to best represent the Little Ice Age (LIA). The output was shape files." }, "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": [ { "ob_id": 41534, "uuid": "2d8227dc429449e4887100bbf7513b8b", "short_code": "proj", "title": "Deplete and Retreat", "abstract": "This study is part of the Natural Environment Research Council (NERC) highlight topic grant ‘Deplete and Retreat: the future of Andean Water Towers’ (NE/X004031/1)." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [ 13141 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 202384, 202385, 202386, 202387, 202388, 202389, 202391, 204347 ], "onlineresource_set": [ 86548, 87893 ] }, { "ob_id": 41535, "uuid": "95aa41439d564756950f89921b6ef215", "title": "Deep-Time Model Intercomparison Project (DeepMIP) Eocene model data version 1.0", "abstract": "This dataset contains output from 35 climate model simulations of the warm early Eocene Climatic Optimum (EECO; ∼ 50 million years ago) and corresponding preindustrial reference experiments. The dataset combines global model output from nine coupled climate models (CESM1.2-CAM5, COSMOS-landveg-r2413, GFDL-CM2.1, HadCM3B-M2.1aN, HadCM3BL-M2.1aN, INM-CM4-8, IPSLCM5A2, MIROC4m and NorESM1-F) that have carried out coordinated simulations as part of the Deep-Time Model Intercomparison Project (DeepMIP). Climatological means and time series data of the respective last 100 model years for a total of 57 atmospheric and oceanic variables are standardised following the CMIP6 data request and CF metadata convention.", "creationDate": "2024-03-07T16:01:56.955369", "lastUpdatedDate": "2024-03-07T16:09:59", "latestDataUpdateTime": "2024-09-11T13:12:23", "updateFrequency": "notPlanned", "dataLineage": "Model simulations were performed by eight different modelling groups. Climatological means and time series data were centrally collected at the University Research Data Storage Facility (RDSF) at the University of Bristol. Final compilation and metadata creation for archiving at the Centre for Environmental Data Analysis (CEDA) was performed at the University of Bristol.", "removedDataReason": "", "keywords": "climate modelling,paleoclimate,Eocene,model intercomparison", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2024-06-14T12:00:34", "doiPublishedTime": "2024-06-14T12:00:15.274435", "removedDataTime": null, "geographicExtent": { "ob_id": 4163, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 42316, "dataPath": "/badc/cmip6/data/CMIP6Plus/DeepMIP/deepmip-eocene-p1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 180356199122, "numberOfFiles": 3625, "fileFormat": "Data are Net-CDF formatted" }, "timePeriod": { "ob_id": 11584, "startTime": "0001-01-01T00:00:00", "endTime": "9999-12-31T00:00:00" }, "resultQuality": { "ob_id": 4542, "explanation": "A consistent naming convention for variables, directories, and file names across all models is applied to simplify the comparison of different models and to allow a scripted analysis of the entire database. The list of output variables is a modified version of those proposed in the DeepMIP experimental design. Variable names, units and signs of fluxes follow the naming convention of the Coupled Model Intercomparison Project 6 (CMIP6) data request. Consistent standard names, long names and global attributes are added to the netCDF files following the Climate and Forecast metadata conventions (CF) in version 1.8. All netCDF file have been automatically tested for CF-compliance with the cf-checker utility (https://github.com/cedadev/cf-checker) A z-score for the global mean, minimum and maximum for each model and variable relative to the ensemble median is calcluated to identify outliers.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-03-07" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 42317, "uuid": "f42a371c84c243e291507a439138f548", "short_code": "comp", "title": "Model contributions to DeepMIP", "abstract": "35 climate model simulations were run from nine coupled climate models (CESM1.2-CAM5, COSMOS-landveg-r2413, GFDL-CM2.1, HadCM3B-M2.1aN, HadCM3BL-M2.1aN, INM-CM4-8, IPSLCM5A2, MIROC4m and NorESM1-F) that have carried out coordinated simulations as part of the Deep-Time Model Intercomparison Project (DeepMIP)." }, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [], "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": 41536, "uuid": "b63b07ce2d60490c94b583c09bcbe0cb", "short_code": "proj", "title": "DeepMIP: The Deep-Time Model Intercomparison Project", "abstract": "DeepMIP is an international effort to improve our understanding of Deep Time climates by conceiving, designing, carrying out, analysing, and disseminating coordinated model simulations and data syntheses. DeepMIP is part of the Paleoclimate Modelling Intercomparison Project (PMIP), which itself is affiliated to CMIP6. More information is available at https://www.deepmip.org." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6021, 6022, 6023, 6255, 9045, 22883, 24329, 50419, 50426, 50427, 50429, 50431, 50437, 50445, 50468, 50475, 50481, 50496, 50498, 50509, 50549, 50554, 50555, 50557, 50566, 50568, 50569, 50570, 50571, 50572, 50579, 50587, 50588, 50589, 50591, 50596, 50597, 50598, 50599, 50609, 50610, 50612, 50613, 50615, 52746, 52755, 52949, 52960, 52977, 54252, 54348, 54416, 54625, 54626, 54629, 57351, 57352, 60134, 60138, 60153, 60418, 60419, 61199, 61372, 61501, 62353, 62525, 62736, 63566, 63572, 64130, 68130, 69321, 71572, 71574, 71615, 71794, 75172, 75173, 75174, 75175, 75176, 75177, 75179, 75180, 75182, 75183, 75185, 75186, 75187, 75188, 75189, 75190, 75191, 75192, 75194, 75195, 75196, 75197, 89625, 89626, 89627, 89628, 89629, 89630, 89631, 89632, 89633 ], "vocabularyKeywords": [], "identifier_set": [ 13130 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 202395, 202396, 202397, 202398, 202399, 202400, 202418, 203923, 202419, 202420, 202421, 202422, 202423, 202424, 202425, 202426, 202427, 202428, 202429, 202430, 202431, 202432 ], "onlineresource_set": [ 86113, 86114, 86115, 86116 ] }, { "ob_id": 41546, "uuid": "1472ed9cd733446d954c71782c6a59c7", "title": "climate", "abstract": "This data set is involved from precipitation and temperature data for a station in Iran. After gathering data from large ensemble dataset of cesm2, averaging 100 models and then bias correcting them by multivariate bias correction method, results are presented for each year in winter season.", "creationDate": "2024-03-12T19:06:12.002288", "lastUpdatedDate": "2024-03-12T19:06:12.002294", "latestDataUpdateTime": "2024-03-12T19:06:12.002298", "updateFrequency": "notPlanned", "dataLineage": "This data set is precipitation and temperature data for a station in Iran. After gathering data from large ensemble dataset of cesm2, averaging 100 models and then bias correcting them by multivariate bias correction method, results are presented for each year in winter season.", "removedDataReason": "", "keywords": "cesm2_le", "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": 11585, "startTime": "1961-01-01T00:00:00", "endTime": "2099-12-31T00:00:00" }, "resultQuality": { "ob_id": 4543, "explanation": "", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-03-12" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [], "permissions": [], "projects": [], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 202438, 202439, 202440, 202441, 202442, 202443, 202444 ], "onlineresource_set": [] }, { "ob_id": 41547, "uuid": "300046500aeb4af080337ff86ae8e776", "title": "VISION: UKESM1 hourly modelled ozone for comparison to observations", "abstract": "Two UK Earth System Model (UKESM1) hindcasts have been performed in support of the Virtual Integration of Satellite and In-situ Observation Networks (VISION) project (NE/Z503393/1).\r\n\r\nData is provided as raw model output in Met Office PP (32-bit) format that can be read by the Iris (https://scitools-iris.readthedocs.io/en/stable/) or cf-python (https://ncas-cms.github.io/cf-python/) libraries.\r\n\r\nThis is global data at N96 L85 resolution (1.875 x 1.25, 85 model levels up to 85km). Simulations were performed on the Monsoon2 High Performance Computer (HPC).\r\n\r\nThe first dataset (Jan 1982 to May 2022) contains hourly ozone concentrations on the lowest model level (20m above the surface). \r\n\r\nThe second dataset (Jan 2010 to Dec 2020) contains hourly ozone concentrations and hourly Heaviside function on 37 fixed pressure levels. Data is only provided for days in which ozone was measured by the FAAM aircraft (for comparison purposes). \r\n\r\nOzone data is provided in mass mixing ratio (kg species/kg air).", "creationDate": "2024-03-15T16:26:05.458436", "lastUpdatedDate": "2024-03-15T16:58:12", "latestDataUpdateTime": "2025-01-18T03:18:59", "updateFrequency": "notPlanned", "dataLineage": "Data were produced using a dynamically-constrained version of UKESM1-StratTrop model deployed at NCAS-CAMBRIDGE and the output archived at CEDA", "removedDataReason": "", "keywords": "UKESM,ozone,hourly", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "pending", "dataPublishedTime": "2024-05-02T08:11:05", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 4164, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 41615, "dataPath": "/badc/vision/data/Vision_UKESM1_hourly_ozone", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 132012087023, "numberOfFiles": 15234, "fileFormat": "pp" }, "timePeriod": { "ob_id": 11594, "startTime": "1982-01-01T00:00:00", "endTime": "2022-05-31T00:00:00" }, "resultQuality": { "ob_id": 4544, "explanation": "These simulations have been developed over a number of years and had code reviews performed to ensure the coding standard used. All code developments have since been committed to the UM and UKCA trunks for use by the community.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-03-15" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 39993, "uuid": "ce22aec236b44835acdc9914fecb930a", "short_code": "comp", "title": "UKESM1 deployed on UK supercomputing platform MONSooN", "abstract": "UKESM1 Earth System Model described in Sellar et al. (2019) (DOI:10.1029/2019MS001739) at N96 horizontal resolution over global domain run on UK supercomputing platform MONSooN." }, "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": [ { "ob_id": 41548, "uuid": "4aee7be9a7aa43c7b29762fec72e3265", "short_code": "proj", "title": "VISION - Virtual Integration of Satellite and In-situ Observation Networks", "abstract": "This project will deliver a toolkit and novel visualisations that will allow for better integration of models and observations to enhance our confidence in future climate projections. It will also develop a digital twin to improve the operational flights of the FAAM Airborne Laboratory atmospheric research aircraft.\r\n\r\nThe aim is to improve the flight plans to better match the scientific aims and also to reduce the number of flights necessary to achieve those aims.\r\n\r\nIt will bring together a team of atmospheric modellers, scientists, software engineers and satellite experts to deliver a novel framework to reduce the carbon footprint of the UK research aircraft.\r\n\r\nThis project is funded by the Natural Environment Research Council (NERC), in partnership with the Met Office, as part of the Twinning Capability for the Natural Environment (TWINE) programme. \tNE/Z503393/1" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 86139, 86140, 86141 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 202445, 202446, 202447, 202448, 202449, 202450, 202451, 202892, 202452, 202453, 202454 ], "onlineresource_set": [ 86122, 86123 ] }, { "ob_id": 41549, "uuid": "8df2e81dbfc2499983aa87781fb3fd5a", "title": "VISION: Collated subset of FAAM ozone data 2010 to 2020", "abstract": "This is a subset extacted from the FAAM dataset containing ozone measurements made on board the FAAM aircraft using the TECO 49 UV photometric ozone instrument between 2010 and 2020. \r\nThis dataset was compiled to facilitate data access and integration for the Virtual Integration of Satellite and In-situ Observation Networks (VISION) project (NE/Z503393/1)\r\n\r\nData for all flights were extracted from the core FAAM data and new files were created which have the following advantages:\r\n- consistent variable names across the whole time period. \r\n- data points with missing coordinates, or ozone being flagged as inadequate, have been removed.\r\n- files are fully CF-compliant.\r\n- files contain geospatial coordinates and ozone\r\n- filenames contain flight date, unique flight identifier and name of the measurement campaign associated to the flight.\r\n\r\nThis dataset is a subset of the Facility for Airborne Atmospheric Measurements (FAAM) flights dataset collection https://catalogue.ceda.ac.uk/uuid/affe775e8d8890a4556aec5bc4e0b45c", "creationDate": "2024-03-15T17:46:34.287383", "lastUpdatedDate": "2024-03-15T17:55:46", "latestDataUpdateTime": "2025-01-18T03:19:00", "updateFrequency": "notPlanned", "dataLineage": "This dataset was processed from existing FAAM core data by the group at NCAS-CAMBRIDGE and the output archived at CEDA", "removedDataReason": "", "keywords": "FAAM,ozone,TECO 49 UV", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-06-04T12:47:36", "doiPublishedTime": "2024-06-04T12:48:03", "removedDataTime": null, "geographicExtent": { "ob_id": 4165, "bboxName": "", "eastBoundLongitude": 170.0, "westBoundLongitude": -155.0, "southBoundLatitude": -20.0, "northBoundLatitude": 85.0 }, "verticalExtent": null, "result_field": { "ob_id": 41631, "dataPath": "/badc/vision/data/Vision_FAAM_ozone_cf_compliant_2010_2020", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 293521898, "numberOfFiles": 553, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 11599, "startTime": "2010-01-12T00:00:00", "endTime": "2020-09-25T00:00:00" }, "resultQuality": { "ob_id": 4546, "explanation": "The quality of this dataset is the same as the quality of the core FAAM data that was used to produce it", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-03-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 41550, "uuid": "500d98dd82f94a78bf1f6c785097eb2e", "short_code": "acq", "title": "Acquisition for: FAAM ozone dataset 2010 to 2020", "abstract": "" }, "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": [ { "ob_id": 41548, "uuid": "4aee7be9a7aa43c7b29762fec72e3265", "short_code": "proj", "title": "VISION - Virtual Integration of Satellite and In-situ Observation Networks", "abstract": "This project will deliver a toolkit and novel visualisations that will allow for better integration of models and observations to enhance our confidence in future climate projections. It will also develop a digital twin to improve the operational flights of the FAAM Airborne Laboratory atmospheric research aircraft.\r\n\r\nThe aim is to improve the flight plans to better match the scientific aims and also to reduce the number of flights necessary to achieve those aims.\r\n\r\nIt will bring together a team of atmospheric modellers, scientists, software engineers and satellite experts to deliver a novel framework to reduce the carbon footprint of the UK research aircraft.\r\n\r\nThis project is funded by the Natural Environment Research Council (NERC), in partnership with the Met Office, as part of the Twinning Capability for the Natural Environment (TWINE) programme. \tNE/Z503393/1" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 50935, 75162, 75163, 75164, 75165, 75166, 75167, 75168, 75169, 75170, 75171 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 202456, 202457, 202458, 202459, 202460, 202461, 202464, 202893, 202465, 202467, 202468 ], "onlineresource_set": [] }, { "ob_id": 41552, "uuid": "a697ee6a3b314d4b866ec73d613369bb", "title": "C3S: Obs4MIPs format GOME-type Total Ozone Essential Climate Variable (GTO-ECV), Version 9.0", "abstract": "This dataset contains a time series of monthly averaged total ozone column data from nadir-viewing satellite sensors in Obs4MIPs format. It has been reformated from Version 9 of the GOME-type Total Ozone Essential Climate Variable (GTO-ECV) product, that has been generated as part of the European Union Copernicus Climate Change Service (C3S) ozone project. \r\n\r\nGTO-ECV is generated by combining measurements from several nadir-viewing satellite sensors (GOME/ERS-2, SCIAMACHY/Envisat, OMI/Aura, GOME-2/MetOp-A, GOME-2/MetOp-B, TROPOMI/Sentinel-5P, and GOME-2/MetOp-C) into one single cohesive record. The merging approach was developed in the framework of the European Space Agency’s Climate Change Initiative (ESA-CCI) ozone project.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2024-11-20T02:11:50", "updateFrequency": "notPlanned", "dataLineage": "The original GTO Version 9 product was generated as part of the European Union Copernicus Climate Change Service (C3S) ozone project. The merging approach was developed in the framework of the European Space Agency's Climate Change Initiative (ESA-CCI) ozone project.\r\n\r\nData were converted to Obs4MIPs format within the ESA CCI Climate Modellers User Group (CMUG) project.", "removedDataReason": "", "keywords": "ozone, C3S, CCI, obs4mips", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-11-19T15:45:02", "doiPublishedTime": "2024-11-19T16:48:23.621197", "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": 43234, "dataPath": "/neodc/obs4MIPs/DLR-BIRA/C3S-GTO-ECV-9-0/mon/toz/gn/v20231115/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 426995487, "numberOfFiles": 7, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 11601, "startTime": "1995-07-01T00:00:00", "endTime": "2022-04-30T23:59:59" }, "resultQuality": { "ob_id": 4569, "explanation": "See the linked documentation and Obs4MIPs tech note for further information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-06-11" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 41963, "uuid": "64e3991d2c444f8fb4bfe1139fcd546d", "short_code": "cmppr", "title": "Composite Process for: C3S: Obs4MIPs format GOME-type Total Ozone Essential Climate Variable (GTO-ECV), Version 9.0", "abstract": "The C3S: Obs4MIPs format GOME-type Total Ozone Essential Climate Variable (GTO-ECV), Version 9.0 dataset was generated by combining measurements from several nadir-viewing satellite sensors (GOME/ERS-2, SCIAMACHY/Envisat, OMI/Aura, GOME-2/MetOp-A, GOME-2/MetOp-B, TROPOMI/Sentinel-5P, and GOME-2/MetOp-C) into one single cohesive record. This was done using a merging approach developed in the framework of the European Space Agency's (ESA's) Climate Change Initiative Ozone project. Firstly, the separate pixel-based level-2 observation - produced by the GOME-type Direct FITting v4 retrieval algorithm (GODFIT) are converted into level-3 products per sensor i.e. daily and monthly averages on a regular grid of 1x1 degree in latitude and longitude. Before the individual level-3 data records are finally merged into one single product, adjustments are applied in order to minimize possible inter-sensor biases and/or temporal drifts. Due to its notable long-term stability one sensor (OMI/Aura) was selected to serve as a reference for the other instruments, which are then adjusted in terms of a correction that depends on latitude and time. A detailed description of the merging approach, the generation, and the geophysical validation of GTO-ECV is provided in Coldewey-Egbers et al. (2015, 2022), Garane et al. (2018) and Lambert et al. (2022)." }, "imageDetails": [ 111 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2640, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 100, "licenceURL": "https://creativecommons.org/licenses/by-nc-nd/4.0/", "licenceClassifications": [ { "ob_id": 6, "classification": "personal" }, { "ob_id": 4, "classification": "academic" }, { "ob_id": 5, "classification": "policy" } ] } } ], "projects": [], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6021, 6022, 6023, 50415, 50417, 50444, 60438 ], "vocabularyKeywords": [], "identifier_set": [ 13207 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 202476, 202478, 202479, 202480, 202481, 202482, 202483, 202491, 202492, 205649, 205650, 205651 ], "onlineresource_set": [ 86426, 86427, 86428, 88158 ] }, { "ob_id": 41553, "uuid": "62334c44979b4c62b763e0dff97cc923", "title": "Sea Surface Skin Temperature from SISTeR: QM2 Cruise 24, v2.5", "abstract": "Sea Surface Skin Temperature data from the SISTeR instrument (Scanning Infrared Sea surface Temperature Radiometer). This dataset contains SST data of the Mediterranean Sea, the North Sea, and the Atlantic Ocean measured by SISTeR on-board RMS Queen Mary 2 (QM2) between 15 July 2022 and 14 October 2022.\r\n\r\nThese data may be used freely, however we request they are not used as inputs to assimilated SST products, as the primary purpose of these data is for validation of such products.", "creationDate": "2024-03-28T12:04:55.215097", "lastUpdatedDate": "2025-02-26T12:34:17", "latestDataUpdateTime": "2024-03-28T12:04:55", "updateFrequency": "notPlanned", "dataLineage": "Measurements taken on the QM2 and processed with SISTeR processor version 2.5.1 to levels 2R and 3R as specified by the GHRSST recommended format.\r\n\r\nShip time and services were provided by Cunard Line.", "removedDataReason": "", "keywords": "SLSTR,Validation,RMS Queen Mary 2,SST", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2026-01-26T17:08:00", "doiPublishedTime": "2026-02-19T09:07:20.216297", "removedDataTime": null, "geographicExtent": { "ob_id": 4968, "bboxName": "", "eastBoundLongitude": 12.0, "westBoundLongitude": -75.0, "southBoundLatitude": 36.0, "northBoundLatitude": 63.0 }, "verticalExtent": null, "result_field": { "ob_id": 44498, "dataPath": "/neodc/ral_ship_sst/data/QM2/Cruise24/fv2.5/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 713396677, "numberOfFiles": 186, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 12128, "startTime": "2022-07-15T00:00:00", "endTime": "2022-10-14T00:00:00" }, "resultQuality": { "ob_id": 4650, "explanation": "Data files from this cruise have been assigned level 3: no problems with the data.", "passesTest": true, "resultTitle": "SISTeR", "date": "2025-01-31" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 41554, "uuid": "b8bd5c1633c94bdc8cce69586d2f9709", "short_code": "acq", "title": "Acquisition for: SISTeR: QM2 Cruise 24", "abstract": "Data were acquired by the SISTeR (Scanning Infrared Sea surface Temperature Radiometer) instrument on the RMS Queen Mary 2" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "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": 44841, "uuid": "9935ff7ff2444b9db90575d9d16fd4e0", "short_code": "proj", "title": "SISTeR: Scanning Infrared Sea surface Temperature Radiometer", "abstract": "The Scanning Infrared Sea surface Temperature Radiometer (SISTeR), developed at Rutherford Appleton Laboratory, is a self-calibrating filter radiometer for the in situ measurement of skin SST, that has been used to validate the radiometers ATSR-1, ATSR-2, AATSR and SLSTR which were on-board ERS-1, ERS-2 ENVISAT and Sentinel-3 respectively. 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These flow projections are for a historical and future period spanning 1st December 1980 to 30th November 2080 and reflect scenarios of change in both climate and artificial (anthropogenic) influences (abstractions and discharges).\r\nThe historical and future projections are available in two formats: \r\n(i) 1 km × 1 km gridded daily mean river flows (m3s-1) for two spatial regions: Natural river flows across Great Britain, and Artificially influenced river flows across England\r\n(ii) Time series of daily flows for 626 catchments across England\r\nThe climate projections consist of an ensemble of bias-corrected UKCP18 Regional Climate Model (RCM) output. A further 4 hydrological connectivity datasets provide flow directions, upstream areas and coastal/gauged locations. Further details are provided in a linked Data Document.\r\n\r\n Three future scenarios of artificial influences are considered: \r\n(a) Sustainability (SUS), \r\n(b) Business as usual (BAU) and \r\n(c) Economic Growth (EG). \r\n\r\nThe dataset is an output from the CS-NOW project (Climate services for a Net Zero resilient world - GOV.UK (www.gov.uk)) commissioned by the UK Department for Energy Security and Net Zero (DESNZ). Publication of these data is also supported by the Natural Environment Research Council award number NE/X019063/1 as part of the Hydro-JULES programme delivering National Capability.", "creationDate": "2024-04-03T18:35:43.817926", "lastUpdatedDate": "2024-10-31T22:38:05", "latestDataUpdateTime": "2025-02-12T09:09:07", "updateFrequency": "notPlanned", "dataLineage": "This dataset comprise an ensemble of natural and artificially influenced (AI) estimates of daily mean river flows (m3s-1). 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Measurements are taken at 2 second intervals and the ascents extend to heights of approximately 20-30 km.\r\n\r\nThe archive has around 10 stations with data from the 1990's, generally with either 2 or 4 ascents per day from each station until around 2020 where routine observations decrease to 1 a day from 6 main sites with additional ascents as required.\r\n\r\nAdditionally, data from Aberporth, obtained to support observations at the MST Radar, Aberystwyth, are also available from April 1990 - April 2000 with at least one ascent a day and then as required operationally thereafter.\r\n\r\nFor details of sites see station record details linked to each dataset within this collection." } ], "responsiblepartyinfo_set": [ 202531, 202536, 202530, 202532, 202533, 202534, 202535, 202537 ], "onlineresource_set": [] }, { "ob_id": 41557, "uuid": "8ff82957cd414b74ac3550f5109b2ff7", "title": "Met Office South Uist station high resolution radiosonde data v2", "abstract": "Met Office high resolution (2 second) radiosonde data from the South Uist station from 1999 to present. 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Measurements are taken at 2 second intervals and the ascents extend to heights of approximately 20-30 km.\r\n\r\nThe archive has around 10 stations with data from the 1990's, generally with either 2 or 4 ascents per day from each station until around 2020 where routine observations decrease to 1 a day from 6 main sites with additional ascents as required.\r\n\r\nAdditionally, data from Aberporth, obtained to support observations at the MST Radar, Aberystwyth, are also available from April 1990 - April 2000 with at least one ascent a day and then as required operationally thereafter.\r\n\r\nFor details of sites see station record details linked to each dataset within this collection." } ], "responsiblepartyinfo_set": [ 202603, 202605, 202606, 202604, 202607, 202608, 202609, 202610 ], "onlineresource_set": [] }, { "ob_id": 41588, "uuid": "a1e5dd132fad4e129669e71adeed1ab1", "title": "UK 1.5km NWP meteorological data for Met Office NAME dispersion model (Mk4: Jul 2017 - current)", "abstract": "This dataset contains Numerical Weather Prediction (NWP) meteorological data produced by the operational UKV (United Kingdom Variable-resolution) configuration of the Met Office Unified Model. 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The dataset includes time in UTC, pressure, temperature, relative humidity, wind speed and direction, rainfall rate, shortwave downwelling flux and duration of sunshine, along other technical parameters, such as the time adjustment from GPS signal.\r\nThe data are operationally used as part of the Harwell TCCON data processing.\r\nContact information can be found in the metadata file 'harwell_weather_metadata'.", "creationDate": "2024-04-18T12:58:54.202804", "lastUpdatedDate": "2024-04-18T12:55:17", "latestDataUpdateTime": "2024-04-18T12:55:17", "updateFrequency": "", "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "pressure, relative humidity, temperature, wind speed, wind direction, rainfall, downwelling flux, sunshine, UTC time", "publicationState": "preview", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 914, "bboxName": "Harwell", "eastBoundLongitude": -1.293, "westBoundLongitude": -1.293, "southBoundLatitude": 51.597, "northBoundLatitude": 51.597 }, "verticalExtent": null, "result_field": null, "timePeriod": null, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 41609, "uuid": "452764d8e30f446fa05bd6859caa7f13", "short_code": "acq", "title": "Acquisition for meteorological data from the TCCON site at Harwell, Oxfordshire (UK).", "abstract": "Instruments and Platform pairings for Meteorological data from the TCCON site at Harwell, Oxfordshire (UK)." }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 226 ], "discoveryKeywords": [], "permissions": [], "projects": [], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 41060, "uuid": "efd6f7f45fc34189b6fbb7164b6d7255", "short_code": "coll", "title": "Total Carbon Column Observing Network (TCCON): TCCON data from Harwell, Oxfordshire (UK)", "abstract": "This repository contains TCCON data specific to the Harwell (UK) site. It contains both public top-level (Level 2) data, that have passed quality control, and the associated intermediate instrumental (Level 1) data for users wishing to run an independent column retrieval processor. Corresponding environmental (e.g. meteorological, geophysical) data recorded at the Harwell site are also provided.\r\n\r\nThe current Data Use Policy is available at https://tcconwiki.caltech.edu/Network_Policy/Data_Use_Policy\r\nSee project page for more details." } ], "responsiblepartyinfo_set": [ 202740, 202741, 202742, 202743, 202744, 202745, 202746, 202747, 202748, 202749 ], "onlineresource_set": [] }, { "ob_id": 41601, "uuid": "5725de8c7e934a05b978ff2b93e4438f", "title": "HadCM3Q PRECIS data generated for the QUMP (Quantifying Uncertainty in Model Predictions) Project using IPCC's SRES A1B future emissions scenario.", "abstract": "This PRESCIS dataset (Providing REgional Climates for Impacts Studies) is output data from the HadCM3Q GCM ensemble, which used the SRES A1B scenario (see the Special Report on Emissions Scenarios (SRES) www.ipcc.ch/pdf/special-reports/spm/sres-en.pdf) spanning December 1949 to November 2099. The data are split up according to their runid and then by their stash code. \r\n\r\nThe Quantifying Uncertainty in Model Predictions (QUMP) research theme aims to provide probabilistic predictions of future climate. These are based on large ensembles of simulations of equilibrium and time-dependent change, carried out by perturbing poorly constrained parameters controlling key physical and biogeochemical processes in the HadCM3 coupled ocean-atmosphere global climate model. Further ensembles of regional climate simulations at high resolution, driven by boundary conditions obtained from the HadCM3 ensemble, allow the specification of probabilistic predictions at spatial scales suitable for climate impact studies. These experiments allow quantification of the effects of earth system modelling uncertainties and internal climate variability on feedbacks likely to exert a significant influence on twenty-first century regional climate. \r\n \r\nThe diagnostics are either on the horizontal 'pressure grid' or the horizontal 'wind grid'. For the 'wind grid' an Arakawa B grid layout is used, in which wind variables are offset from all other variables (said to be on the 'pressure grid') by half a grid box in both directions. The 'wind grid' has the same number of points in the east-west direction as the 'pressure grid', but one less in the north-south direction.\r\n\r\nSome files are available as monthly means and some are available as daily means. \r\n\r\nEach daily mean file contains 360 fields (one field per day for a year in the 360 day calendar used by HadCM3Q). Each monthly mean tarball contains files with one field (one field for a month covering the span of December 1949 to November 2099).\r\n\r\nTables of information about the runids and stash codes can be found in the PRECIS_Data_Readme stored alongside the fileset.", "creationDate": "2023-11-08T14:39:29.343320", "lastUpdatedDate": "2023-11-08T14:39:29", "latestDataUpdateTime": "2024-09-11T13:12:29", "updateFrequency": "notPlanned", "dataLineage": "Data from the UK Met Office Hadley Centre. 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These data cover various time periods, but for the climate change experimenst are typically over the range 1989-2100 and contains all atmospheric fields derived from the HadCM3 model, at various time resolutions." } ], "responsiblepartyinfo_set": [ 202750, 202751, 202752, 202753, 202754, 202755, 202756, 202757, 202758 ], "onlineresource_set": [ 86172, 86169, 86170, 86171 ] }, { "ob_id": 41610, "uuid": "5b1caf9095d7412282f5ba6b558034e3", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE product, Version 09.1", "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 v09.1 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 2023-12-31. 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": "2024-10-16T02:03:28", "updateFrequency": "", "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": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-10-03T15:36:13", "doiPublishedTime": "2024-10-15T10:36:28", "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": 43058, "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/ACTIVE/v09.1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 8813892699, "numberOfFiles": 11838, "fileFormat": "The data are provided in netCDF format." }, "timePeriod": { "ob_id": 11808, "startTime": "1991-08-05T00:00:00", "endTime": "2023-12-31T23:59:59" }, "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": 43035, "uuid": "fbf9614e6168457580911dec3d77911b", "short_code": "cmppr", "title": "ESA Soil Moisture Climate Change Initiative: Retrieval of Soil Moisture using Active sensors for version 09.1 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": 2577, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 99, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_soilmoisture_terms_and_conditions_v2.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, 62501, 62745 ], "vocabularyKeywords": [], "identifier_set": [ 13193 ], "observationcollection_set": [ { "ob_id": 41613, "uuid": "779f116d0477439db1874592add5848c", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 09.1 data collection", "abstract": "Soil Moisture data (version 09.1) 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 2023-12-31 and the ACTIVE product covering 1991-08-05 to 2023-12-31. 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": [ 202771, 202772, 202773, 202766, 202767, 202768, 202769, 202770, 202774, 202775, 202776, 202777, 202778, 202779, 202780, 202781, 202782, 202783, 202784, 204501 ], "onlineresource_set": [ 88076, 88077, 88078, 86177, 86178, 86179, 86180, 86181, 86183, 86182 ] }, { "ob_id": 41611, "uuid": "ca55ac11fc814b0d95e68a34a10539c1", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE product, Version 09.1", "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 v09.1 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 2023-12-31. 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": "2024-10-16T02:03:32", "updateFrequency": "", "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": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-10-03T15:36:27", "doiPublishedTime": "2024-10-15T10:37:28", "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": 43059, "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/PASSIVE/v09.1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 21329380118, "numberOfFiles": 16499, "fileFormat": "The data are provided in netCDF format." }, "timePeriod": { "ob_id": 11809, "startTime": "1978-11-01T00:00:00", "endTime": "2023-12-31T23:59:59" }, "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": 43040, "uuid": "eabded7ffd304865b4de708dc83ffe6a", "short_code": "cmppr", "title": "ESA Soil Moisture Climate Change Initiative: Retrieval of Soil Moisture using Passive sensors for version 09.1 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": 2577, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 99, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_soilmoisture_terms_and_conditions_v2.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, 62501, 62745 ], "vocabularyKeywords": [], "identifier_set": [ 13194 ], "observationcollection_set": [ { "ob_id": 41613, "uuid": "779f116d0477439db1874592add5848c", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 09.1 data collection", "abstract": "Soil Moisture data (version 09.1) 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 2023-12-31 and the ACTIVE product covering 1991-08-05 to 2023-12-31. 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": [ 202791, 202792, 202793, 202786, 202787, 202788, 202789, 202790, 202794, 202795, 202796, 202797, 202798, 202799, 202800, 202801, 202802, 202803, 202804, 204502 ], "onlineresource_set": [ 88079, 88080, 88081, 86194, 86189, 86190, 86191, 86192, 86193, 86195 ] }, { "ob_id": 41612, "uuid": "0e346e1e1e164ac99c60098848537a29", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED product, Version 09.1", "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 v09.1 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 2023-12-31. 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": "2024-10-16T02:03:30", "updateFrequency": "", "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": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-10-03T15:36:37", "doiPublishedTime": "2024-10-15T10:37:36", "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": 43060, "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/COMBINED/v09.1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 23286634661, "numberOfFiles": 16498, "fileFormat": "The data are provided in netCDF format." }, "timePeriod": { "ob_id": 11810, "startTime": "1978-11-01T00:00:00", "endTime": "2023-12-31T23:59:59" }, "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": 43041, "uuid": "44d1c75234a04a9a9569e0bad8d82c33", "short_code": "cmppr", "title": "ESA Soil Moisture Climate Change Initiative: Retrieval of Soil Moisture using combined active and passive sensors for version 09.1 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": 2577, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 99, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_soilmoisture_terms_and_conditions_v2.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, 62501, 62745 ], "vocabularyKeywords": [], "identifier_set": [ 13195 ], "observationcollection_set": [ { "ob_id": 41613, "uuid": "779f116d0477439db1874592add5848c", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 09.1 data collection", "abstract": "Soil Moisture data (version 09.1) 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 2023-12-31 and the ACTIVE product covering 1991-08-05 to 2023-12-31. 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": [ 202813, 202806, 202807, 202808, 202809, 202810, 202811, 202812, 202814, 202815, 202816, 202817, 202818, 202819, 202820, 202821, 202822, 202823, 202824, 204503 ], "onlineresource_set": [ 88082, 88083, 88084, 86204, 86202, 86199, 86200, 86203, 86201, 86207 ] }, { "ob_id": 41614, "uuid": "85c7d97c5d104a32989b13abc3f8ea5d", "title": "Elevation change grids of Greenland's periphery for the years 1978, 1981, 1985 and 1987", "abstract": "This dataset contains elevation change grids (Digital Elevation Models (DEMs) of Difference) for Greenland's periphery subtracting the AeroDEM (Korsgaard et al., 2016) elevation data from the ArcticDEM (Porter et al., 2023). Four timestamps are available given the four nominal years for AeroDEM acquisition (1978, 1981, 1985, 1987).\r\n\r\nThe .tif files are the first order filtered DoDs (DEM of Difference) of the entire periphery prior to subsequent empiracle rule filtering and clipping to peripheral ice cap and glacier ablation areas.\r\n\r\nKorsgaard, N.J., Nuth, C., Khan, S.A., Kjeldsen, K.K., Bjørk, A.A., Schomacker, A. and Kjær, K.H., 2016. Digital elevation model and orthophotographs of Greenland based on aerial photographs from 1978–1987. Scientific Data, 3(1), pp.1-15.\r\n\r\nPorter, Claire, et al., 2023, “ArcticDEM, Version 4.1”, https://doi.org/10.7910/DVN/3VDC4W, Harvard Dataverse, V1", "creationDate": "2024-04-24T13:24:34.503094", "lastUpdatedDate": "2024-04-24T13:24:34", "latestDataUpdateTime": "2024-05-22T01:45:48", "updateFrequency": "notPlanned", "dataLineage": "ArcticDEM mosaic accessed and exported from Google Earth Engine at 2m and resampled (bilinear) to 30m\r\nAeroDEM data downloaded from NCEI site and resampled to 30m resolution Bilinear) https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.nodc:0145405 \r\n\r\nCoregistration conducted using the DEMcoreg python scripts of David Shean https://github.com/dshean/demcoreg", "removedDataReason": "", "keywords": "Elevation,DEM of Difference,Greenland,PGIC", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "pending", "dataPublishedTime": "2024-05-21T09:26:44", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 4390, "bboxName": "", "eastBoundLongitude": 11.0, "westBoundLongitude": -74.0, "southBoundLatitude": 59.0, "northBoundLatitude": 84.0 }, "verticalExtent": null, "result_field": { "ob_id": 41669, "dataPath": "/badc/deposited2024/Greenland_peripheral_DH_grids", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1348705691, "numberOfFiles": 5, "fileFormat": ".tif" }, "timePeriod": { "ob_id": 11650, "startTime": "1978-06-01T00:00:00", "endTime": "1987-12-31T00:00:00" }, "resultQuality": { "ob_id": 4560, "explanation": "", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-04-24" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 41673, "uuid": "a95bed741dd3456db375a0234ceaf4f1", "short_code": "comp", "title": "Computation for elevation change grids of Greenland's periphery for the years 1978, 1981, 1985 and 1987.", "abstract": "ArcticDEM mosaic accessed and exported from Google Earth Engine at 2m and resampled (bilinear) to 30m\r\nAeroDEM data downloaded from NCEI site and resampled to 30m resolution Bilinear) https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.nodc:0145405 \r\n\r\nCoregistration conducted using the DEMcoreg python scripts of David Shean https://github.com/dshean/demcoreg" }, "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": [ { "ob_id": 41663, "uuid": "0c92aaa948fc4cb7a66b641bb587f48e", "short_code": "proj", "title": "NE/L002574/ NERC Funded PhD by Michael Grimes at Uni of Leeds", "abstract": "This work was conducted as part of a NERC funded PhD project at the University of Leeds (Grant NE/L002574/1)" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 202846, 202847, 202848, 202849, 202850, 202851, 202852, 203052, 202853, 202854, 202855 ], "onlineresource_set": [] }, { "ob_id": 41617, "uuid": "4aac4f8ba15f43e59eb81756b464c9fb", "title": "A global climatology of sting-jet cyclones: TRACK files and Sting-Jet Precursor Cut-Outs", "abstract": "This dataset contains:\r\n(1) extra-tropical cyclone tracks generated by the \"TRACK\" storm tracking algorithm (Hodges 1994, 1995, 1999) applied the European Centre for Medium-Range Weather Forecasts ERA5 reanalysis product,\r\n(2) cyclone 'cutouts' holding storm-centred gridded data used by the sting-jet precursor (SJP) algorithm (Martinez-Alvarado et al., 2013), and\r\n(3) output diagnostics from the SJP algorithm.\r\n\r\nThe directories contain data for seasons October-March (Northern Hemisphere) and April-September (Southern Hemisphere) during 1979-2022. TRACK uses 850 hPa relative vorticity filtered to T42 spectral resolution to find storm candidates and only tracks lasting >=1day and tracking >=500km are considered. The 10% strongest tracks also exhibiting a warm seclusion are archived in the \"storm_data\" directory for each season, except for the single season October-March 2011/2012 for which all North Atlantic tracks are also included in \"storm_data_alltracks\" directory.\r\n\r\nFull descriptions of each data type are given in:\r\n(1) readme-tracks.txt\r\n(2) readme-cutouts.txt\r\n(3) readme-sjp-outputs.txt\r\n\r\nFor full details of the storm selection and SJP analysis, see Gray et al: A global climatology of sting-jet extratropical cyclones (doi.org/10.5194/egusphere-2024-1413).\r\n\r\nSee online resources on this record for referenced items.", "creationDate": "2024-04-26T12:02:27.410888", "lastUpdatedDate": "2024-07-23T16:13:49", "latestDataUpdateTime": "2024-10-23T02:09:11", "updateFrequency": "notPlanned", "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "Sting Jet, ERA5, Extra-tropical cyclone", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-10-22T11:23:21", "doiPublishedTime": "2024-10-22T11:34:13", "removedDataTime": null, "geographicExtent": { "ob_id": 4392, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -80.0, "northBoundLatitude": 80.0 }, "verticalExtent": null, "result_field": { "ob_id": 43201, "dataPath": "/badc/deposited2024/sjclim/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 660617190430, "numberOfFiles": 11814, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 11822, "startTime": "1979-01-01T00:00:00", "endTime": "2022-12-31T23:59:59" }, "resultQuality": { "ob_id": 4588, "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": "Standard CEDA Data Quality Statement", "date": "2024-07-31" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 2 ], "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": 41618, "uuid": "5131f7491ddb4b9793047b8793e32eee", "short_code": "proj", "title": "A global climatology of sting-jet cyclones", "abstract": "The aim of this project is to generate the first global climatology of sting-jets in intense mid-latitude cyclones. Current climatologies are restricted to the North Atlantic-European region and yet there are no physical reasons why sting jets should not exist in other regions. This climatology will reveal the presence and frequency of sting jets over the southern hemisphere, North Pacific, and North Atlantic oceans, extending into continental Europe." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 50340, 50559, 53939, 54879, 55257, 55258, 56766, 62353, 70293, 73987, 75139, 75140, 75141, 75142, 75143, 75144, 75145, 75146, 75147, 75148, 75149, 75150, 75151, 75152, 75153, 75154, 75155, 75156, 75157, 75158, 75159 ], "vocabularyKeywords": [], "identifier_set": [ 13203 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 202856, 202857, 202858, 202859, 202860, 202861, 202862, 205473, 202863, 205474, 202864, 202865 ], "onlineresource_set": [ 88062, 88063, 88064, 88065, 88144 ] }, { "ob_id": 41620, "uuid": "02e1b18071ad45a19b4d3e8adafa2817", "title": "ESA Biomass Climate Change Initiative (Biomass_cci): Global datasets of forest above-ground biomass for the years 2010, 2015, 2016, 2017, 2018, 2019, 2020 and 2021, v5", "abstract": "This dataset comprises estimates of forest above-ground biomass for the years 2010, 2015, 2016, 2017, 2018, 2019, 2020 and 2021. They are derived from a combination of Earth observation data, depending on the year, from the Copernicus Sentinel-1 mission, Envisat’s ASAR (Advanced Synthetic Aperture Radar) instrument and JAXA’s (Japan Aerospace Exploration Agency) Advanced Land Observing Satellite (ALOS-1 and ALOS-2), along with additional information from Earth observation sources. The data has been produced as part of the European Space Agency's (ESA's) Climate Change Initiative (CCI) programme by the Biomass CCI team. \r\n\r\nThis release of the data is version 5. Compared to version 4, version 5 consists of an update of the three maps of AGB (aboveground biomass) for the years 2010, 2017, 2018, 2019, 2020 and new AGB maps for 2015, 2016 and 2021. New AGB change maps have been created for consecutive years (2015-2016, 2016-2017 and 2020-2021), alongside an update of change maps for years 2010-2020, 2017-2018, 2018-2019 and 2019-2020, and for a decadal interval (2020-2010). The pool of remote sensing data now includes multi-temporal observations at L-band for all biomes and for all years. The AGB maps rely on revised allometries which are now based on a longer record of spaceborne LiDAR data from the GEDI and ICESat-2 missions. Temporal information is now implemented in the retrieval algorithm to preserve biomass dynamics as expressed in the remote sensing data. Biases between 2010 and more recent years have been reduced.\r\n\r\nThe data products consist of two (2) global layers that include estimates of:\r\n1) above ground biomass (AGB, unit: tons/ha i.e., Mg/ha) (raster dataset). This is defined as the mass, expressed as oven-dry weight of the woody parts (stem, bark, branches and twigs) of all living trees excluding stump and roots\r\n2) per-pixel estimates of above-ground biomass uncertainty expressed as the standard deviation in Mg/ha (raster dataset)\r\n\r\nAdditionally provided in this version release are new aggregated data products. These aggregated products of the AGB and AGB change data layers are available at coarser resolutions (1, 10, 25 and 50km).\r\n\r\nIn addition, files describing the AGB change between two consecutive years (i.e., 2015-2016, 2016-2017, 2018-2017, 2019-2018, 2019-2020, 2020-2021) and over a decade (2020-2010) are provided (labelled as 2015_2016, 2016_2017, 2017_2018, 2018_2019, 2019_2020 and 2020_2010). Each AGB change product consists of two sets of maps: the standard deviation of the AGB change and a quality flag of the AGB change. Note that the change itself can be simply computed as the difference between two AGB maps, so is not provided directly.\r\n\r\n\r\nData are provided in both netcdf and geotiff format.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2024-09-11T13:12:27", "updateFrequency": "notPlanned", "dataLineage": "Data was created by the Biomass CCI team.", "removedDataReason": "", "keywords": "ESA, CCI, Biomass", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-06-06T14:08:37", "doiPublishedTime": "2024-08-22T16:16:41", "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": 41779, "dataPath": "/neodc/esacci/biomass/data/agb/maps/v5.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 664510290791, "numberOfFiles": 8798, "fileFormat": "Data are netCDF and geotiff formatted." }, "timePeriod": { "ob_id": 11655, "startTime": "2010-01-01T00:00:00", "endTime": "2021-12-31T23:59:59" }, "resultQuality": { "ob_id": 3355, "explanation": "For information on the quality of the data see the documentation and website for the Biomass CCI", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-11-28" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 41622, "uuid": "c5a516b7e8584ebb9c2e46604c580676", "short_code": "cmppr", "title": "CCI Biomass v5.0", "abstract": "CCI Biomass" }, "imageDetails": [ 111 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2542, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 20, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_biomass_terms_and_conditions_v2.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 29954, "uuid": "748552f369494506bc790c8a51854c38", "short_code": "proj", "title": "ESA CCI Biomass Climate Change Initiative (CCI)", "abstract": "The primary science objective ESA’s Climate Change Initiative + Biomass project is to provide global maps of above-ground biomass (Mg ha-1) with these being capable of supporting quantification of biomass change. The mapping aims to achieve 500 m to 1 km spatial resolution with a relative error of less than 20 % where AGB exceeds 50 Mg ha-1. Although this resolution is finer than required for current climate modelling, it will allow more refined information to be inferred (e.g. forest age structure and the disturbance regime) that is relevant for climate and has the potential to be exploited by carbon cycle and climate models as they develop." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6021, 6022, 6023, 66280, 66281, 66282, 66283, 66285, 66286, 66287, 75116, 75117, 75118, 75119, 75120, 75121 ], "vocabularyKeywords": [], "identifier_set": [ 13175 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 202869, 202871, 202872, 202873, 202874, 202875, 202876, 202877, 202870, 202878 ], "onlineresource_set": [ 86220, 86221, 86222, 87930 ] }, { "ob_id": 41632, "uuid": "23acd3f409e6420daff30c1dab874c1b", "title": "ATSR-1: Average Surface Temperature (AST) Product (AT1_AR__2P), v3.0.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) Average Surface Temperature (AST) Product. These data are the Level 2 spatially averaged geophysical product derived from Level 1B product and auxiliary data. This data is from the 3rd reprocessing and tagged v3.0.1\r\n\r\nThere are two types of averages provided: 10 arcminute cells and 30 arcminute cells. All cells are present regardless of the surface type. Hence, the sea (land) cells would also have the land (sea) records even though these would be empty. Cells containing coastlines will have both valid land and sea records; the land (sea) record only contains averages from the land (sea) pixels. The third reprocessing was done to implement the updated algorithms, processors, and auxiliary files.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2023-05-23T09:15:57", "latestDataUpdateTime": "2024-05-31T01:45:27", "updateFrequency": "notPlanned", "dataLineage": "The data were acquired by the European Space Agency's (ESA) ERS-1 satellite, and the NERC Earth Observation Data Centre (NEODC) mirrored the data for UK users. 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From these data surface level turbulence was derived." }, "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": [ { "ob_id": 643, "uuid": "8254273ca7985d4c3d447aa8cf317488", "short_code": "proj", "title": "Greenland Flow Distortion EXperiment (GFDex)", "abstract": "The Greenland Flow Distortion experiment (GFDex) is an international fieldwork and modelling-based project to investigate the role that Greenland plays in distorting atmospheric flow over and around it: affecting local and remote weather systems and, via air-sea interaction processes, the coupled climate system." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 640, "uuid": "77a24c3705599d03825ce9005a8610f8", "short_code": "coll", "title": "Greenland Flow Distortion EXperiment (GFDex): In-situ Observations of High-impact Weather Systems and Their Associated Air-sea Fluxes in the Coastal Seas of Greenland", "abstract": "The Greenland Flow Distortion EXperiment, based in Keflavik, Iceland, took place during February 2007. Its aim was to improve the understanding and ability to predict interactions between the atmospheric circulation and the topography of Greenland, both locally and downstream over Western Europe. Hitherto rare in situ observations of high-impact weather systems and their associated air-sea fluxes in the coastal seas of Greenland, were obtained and will be used to improve the numerical modelling and prediction of these weather systems, and thus improve the quality of the atmospheric forcing fields that are essential for accurate atmosphere-ocean coupling and the thermohaline circulation. These measurements will also be used to improve the numerical modelling and prediction of high-impact weather systems over Europe through the use of targeted observations upstream in sensitive areas of the flow.\r\n\r\nThis project investigates the role of Greenland in defining the structure and the predictability of both local and downstream weather systems, through a programme of aircraft-based observation and numerical modelling. The Greenland Flow Distortion Experiment (GFDex) will provide some of the first detailed in situ observations of the intense atmospheric forcing events that are thought to be important in modifying the ocean in this area (but are presently poorly understood): namely tip jets, barrier winds and mesoscale cyclones. Tip jets form at the southern tip of Greenland, at Cape Farewell, through the forcing of flow over and around the topography. Barrier winds occur when the large-scale flow is piled up against the southeast coast of Greenland, forcing winds parallel to the coast. While located off this southeast coast is an area of frequent mesoscale cyclogenesis. GFDex will also investigate Greenlands role in atmospheric flow predictability by carrying out upstream observations that are targeted at investigating the sensitivity of the downstream flow to the details of the upstream flow and at improving subsequent forecasts over Europe. Greenlands flow distortion can trigger large-scale atmospheric Rossby waves which influence weather systems thousands of kilometres away and several days later. These waves are by nature predictable, so by adapting our observing strategy to target specific areas, improvements in subsequent forecasts over the United Kingdom are possible.\r\n\r\nNumerical modelling experiments after the field campaign will be used to assess any improvements from the additional targeted observations. While further numerical modelling studies of the high impact local weather systems will be evaluated and refined using the aircraft-based observations. This will increase our understanding of these systems and, through comparisons with other observations and data sets, provide accurate fields of air-sea heat and moisture fluxes for driving ocean and climate models." } ], "responsiblepartyinfo_set": [ 202968, 202969, 202970, 202971, 202972, 202973, 202974, 202975, 203433, 202977 ], "onlineresource_set": [] }, { "ob_id": 41659, "uuid": "83ba8d0333ba4ccd99c9d3df3096df24", "title": "Surface level turbulence derived from FAAM and MASIN flight measurements for the Aerosol Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) project", "abstract": "This dataset contains surface layer turbulent fluxes and meteorological variables derived from instruments on board the Facility for Airborne Atmospheric Measurement (FAAM) and Meteorological Airborne Science Instrumentation (MASIN) instrumentation measurements onboard the British Antarctic Survey (BAS) Twin Otter aircraft. These data were based on measurements made during the Aerosol Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) project.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-02-12T09:13:57", "updateFrequency": "notPlanned", "dataLineage": "These data were produced by the project team and the output data were then supplied to CEDA for archiving.", "removedDataReason": "", "keywords": "ACCACIA, FAAM, MASIN, turbulence", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-06-06T13:56:20", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1991, "bboxName": "ACCACIA-masin", "eastBoundLongitude": 29.2, "westBoundLongitude": -1.0, "southBoundLatitude": 75.0, "northBoundLatitude": 82.0 }, "verticalExtent": null, "result_field": { "ob_id": 41780, "dataPath": "/badc/accacia/data/turbulence_SL", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 238799, "numberOfFiles": 3, "fileFormat": "plain text" }, "timePeriod": { "ob_id": 11661, "startTime": "2013-03-23T00:00:00", "endTime": "2013-03-31T23:59:59" }, "resultQuality": { "ob_id": 3959, "explanation": "No quality information available. Data are as provided by the project team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2022-06-06" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 43422, "uuid": "05658e71d42241fbadb8613f6165f1c8", "short_code": "cmppr", "title": "Composite process for Surface level turbulence derived from aircraft measurements for the Aerosol Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) project", "abstract": "Core measurements were made on board the FAAM BAe-146 and BAS MASIN aircraft during flights for the Greenland Flow Aerosol Cloud Coupling and Climate Interactions in the Arctic (ACCACIA) project. From these data surface level turbulence was derived." }, "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": [ { "ob_id": 12286, "uuid": "e0e2261d155848fab84b1169aeb2be80", "short_code": "proj", "title": "Aerosol Cloud Coupling and Climate Interactions in the Arctic (ACCACIA)", "abstract": "ACCACIA was a £3M NERC-funded consortium project in collaboration with the Universities of Manchester, York, and East Anglia, and the British Antarctic Survey, along with the Met Office and project partners in the US and Europe. ACCACIA aimed to improve our understanding of aerosol-cloud interactions in the Arctic, and the potential changes and feedbacks that may result from decreasing Arctic sea ice cover in the future. In situ measurements have been made during two field campaigns utilising ship-based measurements of surface aerosol sources and airborne measurements of aerosol and cloud microphysical properties, boundary layer dynamics, and radiative forcing. The observations have been complemented by modelling studies on a range of scales: from explicit aerosol and cloud microphysics process modelling, through large eddy simulation and mesoscale models, up to global climate models." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 202979, 202980, 202981, 202982, 202983, 202984, 202985, 202986, 202988, 202987 ], "onlineresource_set": [] }, { "ob_id": 41662, "uuid": "667a2328d2b04f02b653569975f53f55", "title": "Greenland 1980 and 2010s landcover grids from Landsat 5 and Landsat 8", "abstract": "This dataset consists of two landcover grids representing Greenland in the late 1980s and late 2010s, utilising Landsat 5 Thematic Mapper Top-Of-Atmosphere (TM TOA) and Landsat 8 Operational Land Imager Top-Of-Atmosphere (OLI TOA) imagery respectively. \r\nThe data creation involved rigorous preprocessing and image classification methodologies, detailed extensively in the paper by Grimes, M., Carrivick, J.L., Smith, M.W., et al. (2024), \"Land cover changes across Greenland dominated by a doubling of vegetation in three decades,\" Sci Rep, 14, 3120. DOI: 10.1038/s41598-024-52124-1. The full methodology is also discussed in the supplementary material of the publication.\r\n\r\nThe resultant .tif grids are in integer format with values from 1 to 9 representing landcover class:\r\n1 - Bad data/Cloud/Shadow\r\n2 - Snow and Ice\r\n3 - Wet ice and meltwater\r\n4 - Freshwater\r\n5 - Coarse sediment\r\n6 - Fine-grained sediment\r\n7 - Bedrock\r\n8 - Tundra vegetation\r\n9 - Dense/wet vegetation\r\nThe tif grids were produced using Google Earth Engine. All summer Landsat imagery was filtered by metadata, followed by topographical correction, resulting in a best-pixel mosaic for Greenland's periphery. Band ratios (NDSI, NDVI, NDWI) were computed and stacked with visible, NIR, and SWIR bands. A principal component analysis was conducted, retaining the first six principal components as bands, which were subsequently classified using a K-means clusterer and refined with a supervised random-forest classifier and a slope threshold was applied to discriminate shadows from dark water bodies more effective.\r\nThis dataset was generated through a NERC-funded PhD project at the University of Leeds (Grant NE/L002574/1).", "creationDate": "2024-05-14T19:04:00.671080", "lastUpdatedDate": "2024-05-14T19:05:48", "latestDataUpdateTime": "2024-06-14T01:54:20", "updateFrequency": "notPlanned", "dataLineage": "The data creation involved rigorous preprocessing and image classification methodologies and the full methodology is discussed in the supplementary material of the publication Grimes, M., Carrivick, J.L., Smith, M.W., et al. (2024), \"Land cover changes across Greenland dominated by a doubling of vegetation in three decades,\" Sci Rep, 14, 3120. DOI: 10.1038/s41598-024-52124-1.\r\nBriefly, the tif grids were produced using Google Earth Engine. All summer Landsat imagery was filtered by metadata, followed by topographical correction, resulting in a best-pixel mosaic for Greenland's periphery. Band ratios (NDSI, NDVI, NDWI) were computed and stacked with visible, NIR, and SWIR bands. A principal component analysis was conducted, retaining the first six principal components as bands, which were subsequently classified using a K-means clusterer and refined with a supervised random-forest classifier and a slope threshold was applied to discriminate shadows from dark water bodies more effective.", "removedDataReason": "", "keywords": "landcover,classification,greenland,climate", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-06-13T15:43:14", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 4396, "bboxName": "", "eastBoundLongitude": -10.0, "westBoundLongitude": -76.0, "southBoundLatitude": 59.0, "northBoundLatitude": 84.0 }, "verticalExtent": null, "result_field": { "ob_id": 42318, "dataPath": "/badc/deposited2024/Greenland_Landcover_Grids/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 924202091, "numberOfFiles": 3, "fileFormat": "TIF files" }, "timePeriod": { "ob_id": 11665, "startTime": "1986-07-01T00:00:00", "endTime": "2019-09-30T00:00:00" }, "resultQuality": { "ob_id": 4562, "explanation": "", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-05-14" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 42320, "uuid": "55d1b73f6663431fb256622f40a9ede5", "short_code": "cmppr", "title": "Composite process for Greenland 1980 and 2010s landcover grids from Landsat 5 and Landsat 8", "abstract": "The data creation involved rigorous preprocessing and image classification methodologies and the full methodology is discussed in the supplementary material of the publication Grimes, M., Carrivick, J.L., Smith, M.W., et al. (2024), \"Land cover changes across Greenland dominated by a doubling of vegetation in three decades,\" Sci Rep, 14, 3120. DOI: 10.1038/s41598-024-52124-1.\r\nBriefly, the tif grids were produced using Google Earth Engine. All summer Landsat imagery was filtered by metadata, followed by topographical correction, resulting in a best-pixel mosaic for Greenland's periphery. Band ratios (NDSI, NDVI, NDWI) were computed and stacked with visible, NIR, and SWIR bands. A principal component analysis was conducted, retaining the first six principal components as bands, which were subsequently classified using a K-means clusterer and refined with a supervised random-forest classifier and a slope threshold was applied to discriminate shadows from dark water bodies more effective." }, "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": [ { "ob_id": 41663, "uuid": "0c92aaa948fc4cb7a66b641bb587f48e", "short_code": "proj", "title": "NE/L002574/ NERC Funded PhD by Michael Grimes at Uni of Leeds", "abstract": "This work was conducted as part of a NERC funded PhD project at the University of Leeds (Grant NE/L002574/1)" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 203011, 203012, 203013, 203014, 203015, 203016, 203018, 203927, 203019, 203020, 203021 ], "onlineresource_set": [ 86293 ] }, { "ob_id": 41670, "uuid": "81567bfb789e4ec4ae30cdd3772f8242", "title": "OpenCLIM - Catchment Flow Metrics", "abstract": "This dataset contains flood, drought, and flow metrics calculated as part of the OpenCLIM (Open CLimate Impacts Modelling framework) project. All metrics have been calculated for 698 UK catchments from timeseries of daily river flow simulated by the hydrological models SHETRAN and HBV by teams from Newcastle University and the University of East Anglia respectively for historical and future periods. All analysis code is available on GitHub (https://github.com/OpenCLIM/OpenCLIM-SHETRAN_Flow_Analysis).\r\n\r\nClimate change simulations were driven by bias corrected UKCP18 data from 01/12/1980 to 30/11/2080. Datasets from all 12 regional climate models (RCMs) were used and are presented separately. Flow metrics are given for 698 catchments in the UK at catchment outlets/gauge locations: https://nrfa.ceh.ac.uk/data/search. These data can be used for the continued analysis of climate impacts and for comparison with future studies.\r\n\r\nFile naming convention: Project_Data_Model_ClimateDriver_ScenarioNumber_ScenarioNote_Metric.csv\r\n\r\nScenario notes:\r\nSc01: Land use was taken from baseline Urban Development Model (UDM) setups with no Natural Flood Management (NFM) adaptations applied. \r\nSc02 & Sc06: Land use was taken from baseline UDM setups with NFM max/moderate adaptations applied. \r\nSc03: Land use was taken from storylined UDM setups (2050 and 2080) for SSPs 2 and 4. No NFM adaptations were applied. For SHETRAN, only catchments with UDM changes relative to the baseline simulations or the previous UDM year were simulated.\r\n\r\nFurther information, including descriptions of the urban development model (UDM) and natural flood management (NFM) setups, is provided in the supplementary README.txt alongside the data.\r\n\r\nUKCP18 - UK Climate Projections 2018 (UKCP18) is a climate analysis tool that forms part of the Met Office Hadley Centre Climate Programme.", "creationDate": "2024-05-16T15:30:53.263019", "lastUpdatedDate": "2024-05-16T15:33:10", "latestDataUpdateTime": "2024-09-11T13:12:31", "updateFrequency": "notPlanned", "dataLineage": "Hydrological models were run for 698 catchments in the UK by teams at Newcastle university (SHETRAN) and University of East Anglia (HBV) as part of the OpenCLIM project. These models generated river flows for historical and climate change simulations from which these metrics have been calculated.", "removedDataReason": "", "keywords": "SHETRAN,HBV,OpenCLIM,UDM,UKCP18", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-07-26T13:20:34", "doiPublishedTime": "2024-07-26T13:20:50.693127", "removedDataTime": null, "geographicExtent": { "ob_id": 4398, "bboxName": "", "eastBoundLongitude": 2.0, "westBoundLongitude": -8.0, "southBoundLatitude": 50.0, "northBoundLatitude": 60.0 }, "verticalExtent": null, "result_field": { "ob_id": 42341, "dataPath": "/badc/deposited2024/OpenCLIM_CatchmentFlowMetrics/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 165172087, "numberOfFiles": 338, "fileFormat": "Data are BADC-CSV formatted." }, "timePeriod": { "ob_id": 11677, "startTime": "1980-12-01T00:00:00", "endTime": "2080-12-30T00:00:00" }, "resultQuality": { "ob_id": 4563, "explanation": "Only catchments that scored Nash Sutcliffe Efficiencies greater than equal to 0.7 are included in the analysis.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-05-16" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 43043, "uuid": "dbc82a13416647ffba38688918acf3dd", "short_code": "comp", "title": "Catchment metrics were calculated from daily flow datasets from two hydrological models: SHETRAN and HBV.", "abstract": "Catchment metrics were calculated from daily flow datasets from two hydrological models: SHETRAN and HBV. Both models were developed using historical data and then driven using bias corrected Met Office UKCP18 datasets to simulate river flows under climate change scenarios. Two different land use changes were applied: (1) natural flood management (provided by Sayers and Partners) and (2) storylined urban development (Provided by the Urban Development Model team at Newcastle University)." }, "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": [ { "ob_id": 41636, "uuid": "0b29cfe8f7194c1280876abf2474b8bf", "short_code": "proj", "title": "Open CLimate IMpacts modelling framework (OpenCLIM)", "abstract": "OpenCLIM, the Open Climate Impacts Modelling framework, is an integrated assessment framework that brings together models to explore potential future impacts of climate change and selected potential adaptation options. Covering hazards such as heat, drought and flooding, and sectors such as biodiversity and agriculture, the framework allows a consistent cross-sectoral approach to exploring adaptation options. Using UKCP18 and down-scaled SSP (Shared Socio-economic Pathways) both future climate and population growth are considered in the analysis. Where possible as well as data outputs and models, much of the framework is open, with it developed and deployed on the DAFNI platform." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [ 13157 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 203053, 203054, 203055, 203056, 203057, 203058, 203059, 204117 ], "onlineresource_set": [ 86297, 86546, 86656, 86657, 86660 ] }, { "ob_id": 41672, "uuid": "a2e1601a29004c13849be5e84594f37a", "title": "OpenCLIM: Catchment Discharges", "abstract": "This dataset contains simulated river flow discharges from the SHETRAN and HBV hydrological models used in the OpenCLIM (Open CLimate Impacts Modelling framework) project. All values are daily flows (i.e. flow at midnight on the given day) in cumecs. Flows are given for 698 catchments in the UK at catchment outlets/gauge locations: https://nrfa.ceh.ac.uk/data/search. These data can be used for the continued analysis of climate impacts and for comparison with future studies.\r\n\r\nHistorical simulations were driven by CHESS/GEAR (Great Britain) and HADUK-Grid (Northern Ireland) datasets from 01/01/1980 to 31/12/2010 (described below).\r\nClimate change simulations were driven by bias corrected UKCP18 data from from 01/12/1980 to 30/11/2080. \r\n\r\nFile naming convention: Project_Data_Model_ClimateDriver_ScenarioNumber_ScenarioNote_RCMNumber.csv\r\n\r\nScenario notes:\r\nSc01: Land use was taken from baseline Urban Development Model (UDM) setups with no Natural Flood Management (NFM) applied.\r\nSc02 & Sc06: Land use was taken from baseline UDM setups with maximum/moderate NFM were applied (increased woodland and storage). \r\nSc03: Land use was taken from storylined UDM setups (2050 and 2080) for SSPs 2 and 4. No NFM adaptations were applied. Only those (GB) catchments that have UDM changes relative to the baseline simulations or the previous UDM year are simulated.\r\n'RCM' refers to the UKCP18 Regional Climate Model time series that was used in the simulation.\r\n\r\nFurther information, including descriptions of the urban development model (UDM) and natural flood management (NFM) setups, is provided in the supplementary README.txt alongside the data.\r\n\r\nInput datasets:\r\nCHESS - The Climate hydrology and ecology research support system (CHESS) provides high-resolution gridded datasets for environmental research. These datasets include data for driving land surface models and hydrological models, as well as model output.\r\nGEAR - The Centre for Ecology & Hydrology – Gridded Estimates of Areal Rainfall (CEH-GEAR) data set was developed to provide reliable 1 km gridded estimates of daily and monthly rainfall for Great Britain (GB) and Northern Ireland (NI) from 1890 onwards. The data set was primarily required to support hydrological modelling.\r\nHadUK-Grid - HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations by the Met Office. \r\nUKCP18 - UK Climate Projections 2018 (UKCP18) is a climate analysis tool that forms part of the Met Office Hadley Centre Climate Programme.", "creationDate": "2024-05-16T15:45:26.688723", "lastUpdatedDate": "2024-05-16T15:50:00", "latestDataUpdateTime": "2024-09-11T13:12:32", "updateFrequency": "notPlanned", "dataLineage": "Hydrological models were run for 698 catchments in the UK by teams at Newcastle university (SHETRAN) and University of East Anglia (HBV) as part of the OpenCLIM project.", "removedDataReason": "", "keywords": "SHETRAN,HBV,OpenCLIM,UKCP18,UDM,Discharge", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-07-26T13:10:29", "doiPublishedTime": "2024-07-26T13:11:00", "removedDataTime": null, "geographicExtent": { "ob_id": 4399, "bboxName": "", "eastBoundLongitude": 2.0, "westBoundLongitude": -8.0, "southBoundLatitude": 50.0, "northBoundLatitude": 60.0 }, "verticalExtent": null, "result_field": { "ob_id": 41757, "dataPath": "/badc/deposited2024/OpenCLIM_CatchmentDischarges/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 15477974649, "numberOfFiles": 171, "fileFormat": "BADC-CSV" }, "timePeriod": { "ob_id": 11680, "startTime": "1980-01-01T00:00:00", "endTime": "2080-11-30T00:00:00" }, "resultQuality": { "ob_id": 4565, "explanation": "All catchment models were calibrated and validated against historical flows. Only those with Nash Sutcliffe Efficiencies greater than equal to 0.7 were included in subsequent analysis.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-05-16" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 43044, "uuid": "75ca674d027d47b887190d55e9302408", "short_code": "comp", "title": "Daily flows were simulated by two hydrological models: SHETRAN and HBV", "abstract": "Daily flows were simulated by two hydrological models: SHETRAN and HBV. Both models were developed using historical data and then driven using bias corrected Met Office UKCP18 datasets to simulate river flows under climate change scenarios. Two different land use changes were applied: (1) natural flood management (provided by Sayers and Partners) and (2) storylined urban development (Provided by the Urban Development Model team at Newcastle University)." }, "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": [ { "ob_id": 41636, "uuid": "0b29cfe8f7194c1280876abf2474b8bf", "short_code": "proj", "title": "Open CLimate IMpacts modelling framework (OpenCLIM)", "abstract": "OpenCLIM, the Open Climate Impacts Modelling framework, is an integrated assessment framework that brings together models to explore potential future impacts of climate change and selected potential adaptation options. Covering hazards such as heat, drought and flooding, and sectors such as biodiversity and agriculture, the framework allows a consistent cross-sectoral approach to exploring adaptation options. Using UKCP18 and down-scaled SSP (Shared Socio-economic Pathways) both future climate and population growth are considered in the analysis. Where possible as well as data outputs and models, much of the framework is open, with it developed and deployed on the DAFNI platform." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [ 13156 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 203061, 203062, 203063, 203064, 203065, 203066, 203067, 204485, 203068 ], "onlineresource_set": [ 86638, 86653, 86659, 86655 ] }, { "ob_id": 41674, "uuid": "235e3307338c4168816871a314eada4f", "title": "ECMWF SEAS5 seasonal forecast output - case study of summer 2022", "abstract": "This dataset contains the output of three fully coupled seasonal forecast experiments performed as a case study of summer 2022, using the same model setup as ECWMF seasonal forecast system 5 (SEAS5), as presented in the paper Patterson, M., Befort, D., O'Reilly, C., Weisheimer, A. \"The ECMWF SEAS5 seasonal forecast of the hot and dry European summer of 2022\" Quarterly Journal of the Royal Meteorological Society, https://doi.org/10.1002/qj.4851\r\n\r\nThe three experiments are:\r\n1) CONTROL\r\nA coupled hindcast ensemble with perturbed initial conditions for the 2022 summer, identical to the operational hindcast with the start date 1st May, but for 200 members rather than 51.\r\n2) ATMOS-IC-2022\r\nSimilar to the CONTROL with 2022 initial conditions for the atmosphere and land surface and 2022 concentrations of carbon dioxide, but with ocean initial conditions taken from a year in 1981-2021. Five perturbed initial condition states taken for each year hence, 41 x 5 = 205 members.\r\n3) OCEAN-IC-2022\r\nSimilar to CONTROL with 2022 initial conditions for the ocean, but with initial atmosphere, land surface and carbon dioxide conditions taken from a year in 1981-2021. Like ATMOS-IC-2022, 41 x 5 = 205 members.\r\n\r\nThe OCEAN-IC-2022 experiments were performed by taking the setup for hindcasts 1981-2021 and swapping the ocean initial conditions for 2022. The time dimension therefore corresponds to the time of the base hindcast taken from 1981-2021. Conversely, the ATMOS-IC-2022 were performed by running the 2022 hindcast and swapping the ocean initial conditions for other years. The time dimension for ATMOS-IC-2022 therefore is identical for all members. Hindcasts are all started on 1st May and run for four months.\r\n\r\nThe data stored is monthly-mean output from the experiments with the following directory structure\r\nfor variables on pressure levels:\r\n[experiment_name]/pl/[experiment_name]_[ensemble_member_number]_pl_[level]hPa.nc\r\n\r\nand for those on a single level or at the surface:\r\n[experiment_name]/sfc/[experiment_name]_[ensemble_member_number]_sfc.nc\r\n\r\nThe files each contain multiple variables. Variables on pressure levels are stored at 700hPa,500hPa and 250hPa levels.\r\n\r\nPressure level variables stored are:\r\nu (zonal wind), v (meridional wind), t (air temperature), z (geopotential), q (specific humidity)\r\n\r\nSurface variables stored are:\r\nsst (sea surface temperature), swvl1 (Volumetric soil water layer 1), swvl2 (Volumetric soil water layer 2), swvl3 (Volumetric soil water layer 3), swvl4 (Volumetric soil water layer 4), msl (air pressure at mean sea level), t2m (2m temperature), tprate (mean total precipitation rate).", "creationDate": "2024-05-21T13:33:22.673925", "lastUpdatedDate": "2024-05-21T13:33:22", "latestDataUpdateTime": "2024-06-06T01:46:11", "updateFrequency": "notPlanned", "dataLineage": "The data were produced using the same model setup as ECWMF seasonal forecast system 5 (SEAS5) on the ECMWF ATOS system. Data were produced by the project team before archival at CEDA.", "removedDataReason": "", "keywords": "Seasonal forecasts,Climate prediction,Climate modelling,Europe", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-06-05T09:56:16", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 4400, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 41687, "dataPath": "/badc/deposited2024/Seasonal_forecasts_of_JJA_2022/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 30100841472, "numberOfFiles": 2442, "fileFormat": "Contact support@ceda.ac.uk for file format information." }, "timePeriod": { "ob_id": 11681, "startTime": "2022-05-01T00:00:00", "endTime": "2022-08-31T00:00:00" }, "resultQuality": { "ob_id": 4566, "explanation": "", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-05-21" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 41676, "uuid": "09f4596ecbfc40bf8380b2825ceb0a26", "short_code": "comp", "title": "ECMWF IFS cycle 43r1", "abstract": "" }, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "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": 41675, "uuid": "f735448787f54f5b874689736dc6fe45", "short_code": "proj", "title": "Drivers of the successful 2022 European summer seasonal ECMWF forecast", "abstract": "The 2022 European summer season was marked by extremely high temperatures over southern and western areas of Europe resulting in severe wildfires, heat-related deaths and general disruption to western European societies. The associated circulation patterns were relatively well captured by the European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecast system 5, in spite of generally low skill in the summer. This project performed a case study of this seasonal forecast to examine the drivers and windows of forecast opportunity." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 50542, 50543, 62645, 68854, 68861, 69027, 69029, 69030, 69031, 69032, 69039, 75130, 75131, 75132, 75133, 75134, 75135, 75136, 75137, 75138 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 203074, 203075, 203080, 203071, 203072, 203073, 203076, 203432, 203082, 203081, 203083 ], "onlineresource_set": [ 87960 ] }, { "ob_id": 41677, "uuid": "628e62282f1b4efdb3328a1632c9a37d", "title": "FAAM C274 ACAO flight: Airborne atmospheric measurements from instruments on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from instrument suites on board the FAAM BAE-146 aircraft collected for Arctic Cold Air Outbreak (ACAO) project. Flight C274 took place on 21st March 2022 over northern Sweden.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": null, "updateFrequency": "asNeeded", "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": "ACAO, FAAM, airborne, atmospheric measurments", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2024-05-21T14:20:37", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 4401, "bboxName": "FAAM C274", "eastBoundLongitude": 21.123774, "westBoundLongitude": 8.182301, "southBoundLatitude": 67.817566, "northBoundLatitude": 72.16289 }, "verticalExtent": null, "result_field": null, "timePeriod": { "ob_id": 11682, "startTime": "2022-03-21T10:22:47", "endTime": "2022-03-21T13:29:57" }, "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": 41678, "uuid": "6f2ec2e7bbe14dd7bb8929e8b119eaf6", "short_code": "acq", "title": "FAAM Flight C274 Acquisition", "abstract": "FAAM Flight C274 Acquisition" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 8 ], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 36908, "uuid": "01021a90c0c2481c909bdb145cb72398", "short_code": "proj", "title": "Arctic Cold Air Outbreak (ACAO) - FAAM Aircraft Project", "abstract": "The Arctic Cold Air Outbreak (ACAO) airborne field campaign was undertaken by the Met Office using the FAAM BAe-146 aircraft in March 2022 operating out of Kiruna, Sweden. \r\n\r\nIn addition to the Met Office, scientists from the Universities of Manchester and Leeds participated in the campaign to make novel in-situ airborne measurements of the evolution of cold-air outbreaks (CAOs), in terms of the meteorology, atmospheric composition and clouds, from the Marginal Ice Zone (MIZ) to Scandinavia.\r\n\r\nRepresenting the processes important for the formation and evolution of these mixed-phase clouds in models is extremely challenging, yet acutely important for the radiation budget of mid- and high-latitude clouds. Close co-ordination between ACAO flights and four other research aircraft that are scheduled to operate in the region at the same time, with complimentary scientific objectives, facilitated a unique opportunity to collect a more comprehensive dataset. This will be used to evaluate and develop improvements to the representation of mixed-phase clouds in the Unified Model that is used by the Met Office for operational Numerical Weather Prediction and climate simulations." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 36911, "uuid": "ee96bac7c6e747c3b74ff952634ff2d7", "short_code": "coll", "title": "ACAO: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for Arctic Cold Air Outbreak Project (ACAO). The ACAO campaign took place in March 2022 based out of Kiruna in Sweden and included flights C271 to C282 inclusive.\r\n\r\nThe campaign by scientists from the Met Office and Universities of Manchester and Leeds was to make novel in-situ airborne measurements of the evolution of cold-air outbreaks (CAOs), in terms of the meteorology, atmospheric composition and clouds, from the Marginal Ice Zone (MIZ) to Scandinavia." }, { "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": [ 203088, 203089, 203090, 203091, 203092, 203093, 203094, 203095, 203096 ], "onlineresource_set": [ 86298, 86299 ] }, { "ob_id": 41682, "uuid": "91b93025d23d4074b03c4df6f2366d5d", "title": "FAAM C367 CCREST-M 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 CCREST-M FAAM Aircraft Project project.", "creationDate": "2024-05-21T16:42:53.882771", "lastUpdatedDate": "2024-05-21T16:42:53.882787", "latestDataUpdateTime": "2024-11-05T14:16:02", "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": "CCREST-M, FAAM, airborne, atmospheric measurments", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2024-03-18T17:15:36", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 4402, "bboxName": "", "eastBoundLongitude": -0.46035805, "westBoundLongitude": -2.5160203, "southBoundLatitude": 50.854877, "northBoundLatitude": 52.267662 }, "verticalExtent": null, "result_field": { "ob_id": 41681, "dataPath": "/badc/faam/data/2024/c367-feb-06", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1622843428, "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": 11683, "startTime": "2024-02-06T12:25:46", "endTime": "2024-02-06T17:29:18" }, "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": 41684, "uuid": "915c870bf4c54417ad38852a1ab07a1e", "short_code": "acq", "title": "FAAM Flight C367 Acquisition", "abstract": "FAAM Flight C367 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": 41680, "uuid": "d339aef874594e5e9cd22161e9efb9a1", "short_code": "proj", "title": "Characterising CiRrus and icE cloud acrosS the spectrTrum (CCREST-M)", "abstract": "The Characterising CiRrus and icE cloud acrosS the spectrTrum (CCREST-M) project utilised the FAAM aircraft. The project aims to reduce uncertainty associated with the representation of cirrus and ice cloud radiative properties with anticipated benefits from NWP through to climate timescales. Central to achieving these goals is the collection and analysis of a novel ground and airborne observational dataset, combining both active (radar, lidar) and passive radiative measurements of ice clouds from across the electromagnetic spectrum with comprehensive up-to-date in-situ cloud microphysics observations over the full range of particle sizes" } ], "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, 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, 60213, 60214, 60215, 60216, 60217, 60218, 60219, 60220, 60221, 60222, 60223, 60224, 60225, 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, 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, 72012, 74162, 74163, 74164, 74165, 74166, 74167, 74168, 74169, 74171 ], "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": 41683, "uuid": "07cdd23c7b57433fbb0634c53e777d6b", "short_code": "coll", "title": "CCREST-M: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for CCREST-M FAAM Aircraft Project." } ], "responsiblepartyinfo_set": [ 203106, 203107, 203108, 203109, 203110, 203111, 203112, 203113, 203114, 203115 ], "onlineresource_set": [ 86302, 86303 ] }, { "ob_id": 41692, "uuid": "8125cb15feac49a5aee5e14d1b66c9aa", "title": "Hydro-PE CHESS-SCAPE: Potential evapotranspiration derived from CHESS-SCAPE 1980-2080", "abstract": "Gridded potential evapotranspiration derived from CHESS-SCAPE: Future projections of meteorological variables at 1 km resolution for the United Kingdom 1980-2080 derived from UK Climate Projections 2018. This dataset contains two variables: daily total potential evapotranspiration (PET; kg m-2 d-1) and daily total potential evapotranspiration with interception correction (PETI; kg m-2 d-1). This dataset contains four different realisations of future climate for each of four different representative concentration pathway scenarios (RCP2.6, RCP4.5, RCP6.0 and RCP8.5), both with and without bias correction. The data are provided in gridded netCDF files at 1 km resolution aligned to the Ordnance Survey / British National Grid. There is one file for each variable for each month of the daily data. Also provided are monthly, seasonal and annual means, for which there is one file for each variable for each time. The projections use a 360-day calendar, where each month is 30 days long.", "creationDate": "2024-05-28T15:21:12.607631", "lastUpdatedDate": "2024-05-28T15:59:23", "latestDataUpdateTime": "2024-05-28T15:21:12", "updateFrequency": "notPlanned", "dataLineage": "This dataset was derived from CHESS-SCAPE (https://dx.doi.org/10.5285/8194b416cbee482b89e0dfbe17c5786c) The PET was calculated using the Penman-Monteith equation parameterised for a well-watered grass surface. The PETI was calculated as PET with a correction added for interception by a grass canopy on days with non-zero precipitation. The units kg m-2 d-1 are equivalent to mm d-1. This dataset has been developed for use for hydrological modelling in the United Kingdom, it was calculated using an adaptation of the Hydro-PE method (Robinson, et al., 2023). In particular, the PETI is intended to be consistent with the Met Office Rainfall and Evaporation Calculation System (MORECS v2.0) observation-based historical potential evapotranspiration. As such, where the PET and PETI calculations have been parameterised, parameterisations from the MORECS v2.0 documentation have been used (https://digital.nmla.metoffice.gov.uk/IO_9d68dec6-8ad2-420b-a971-806f7a6987d8)", "removedDataReason": "", "keywords": "evaporation,evapotranspiration,potential evaporation,potential evapotranspiration,interception", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "withdrawn", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 4411, "bboxName": "", "eastBoundLongitude": 2.50059, "westBoundLongitude": -9.014131, "southBoundLatitude": 49.76619, "northBoundLatitude": 59.39968 }, "verticalExtent": null, "result_field": null, "timePeriod": { "ob_id": 11694, "startTime": "1980-12-01T00:00:00", "endTime": "2080-11-30T00:00:00" }, "resultQuality": { "ob_id": 4567, "explanation": "", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-05-28" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 33173, "uuid": "f4efc3cd88914cb0a957f7cffe7f894e", "short_code": "proj", "title": "UK Status, Change and Projections of the Environment (UK-SCAPE)", "abstract": "Significant environmental challenges have been created by pressures on land use, air and soil quality, water and food security, and biodiversity. The UK-SCAPE programme will undertake research and provide national-scale data and models designed to deliver new integrated understanding of the environment to tackle those challenges. It will improve our understanding of the consequences of interventions in the UK landscape and allow researchers to answer high-level questions relating to the environment." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 203137, 203138, 203139, 203140, 203141, 203142, 203159, 203160, 203161, 203162, 203163, 203164, 203165, 203166, 203167 ], "onlineresource_set": [ 86315, 86316, 86317, 86318 ] }, { "ob_id": 41694, "uuid": "c188ae131147468cbb26fcdab903e74d", "title": "FAAM C368 CCREST-M 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 Characterising CiRrus and icE cloud acrosS the spectrTrum (CCREST-M) project. 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These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2023.\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 2023. 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": "2024-06-19T01:48:51", "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": "completed", "dataPublishedTime": "2024-06-14T09:25:45", "doiPublishedTime": "2024-06-14T10:12:02", "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": 41773, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISDH-blend/mon/HadISDHTable/r1/v1-5-0-2023f", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 177232280, "numberOfFiles": 8, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 11715, "startTime": "1973-01-01T00:00:00", "endTime": "2023-12-31T23:59:59" }, "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": [ 13128 ], "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": [ 203475, 203476, 203477, 203478, 203479, 203480, 203481, 203482, 203483, 203485, 203484, 203486, 203487, 203488, 203489, 203490, 203491, 203492, 203493 ], "onlineresource_set": [ 86371, 86372, 86373, 86374, 86375, 86376, 86377, 86378, 86379, 86380, 86381, 86382, 86383 ] }, { "ob_id": 41767, "uuid": "0a36ca390a5844578905780ed4c78ded", "title": "HadISDH.extremes: gridded global monthly land surface wet bulb and dry bulb temperature extremes index data version 1.1.0.2023f", "abstract": "This is the HadISDH.extremes 1.1.0.2023f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.extremes is a near-global gridded monthly land surface extremes index climate monitoring product. It is created from in situ sub-daily observations of wet bulb (converted from dew point temperature) and dry bulb temperature from weather stations. The observations have been quality controlled at the hourly level with strict temporal completeness thresholds applied at daily, monthly, annual, climatological and whole period scales to minimise biases. Gridbox months are assessed for inhomogeneity and scores provided (see Homogeneity Score Document in Docs). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2023.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for 27 different heat extremes indices based on the ET-SCI (Expert Team on Sector-Specific Climate Indices) framework. These indices capture a range of moderate to severe extremes. They utilise the daily maximum and minimum values of sub-daily dry bulb and wet bulb temperature observations. Note that these will most likely underestimate the true extremes even when hourly data are available. The data are designed for assessing large scale features over long time scales, ideally using the anomaly fields as these are less affected by sampling biases. Users are advised to cross-compare with national datasets other supporting evidence when assessing small scale localised features.\r\n\r\nThis version is the first with annual updates envisaged. An update record will be maintained in the Docs section.\r\n\r\nHadISD.3.4.0.2023f is the basis of HadISDH.extremes.\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, 2023: HadISDH.extremes Part 1: a gridded wet bulb temperature extremes index product for climate monitoring. Advances in Atmospheric Sciences, 40, 1952–1967, doi: 10.1007/s00376-023-2347-8. https://link.springer.com/article/10.1007/s00376-023-2347-8\r\n\r\nWillett, K. 2023: HadISDH.extremes Part 2: exploring humid heat extremes using wet bulb temperature indices. Advances in Atmospheric Sciences, 40, 1968–1985, doi: 10.1007/s00376-023-2348-7. https://link.springer.com/article/10.1007/s00376-023-2348-7\r\n\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\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", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2024-07-21T01:45:35", "updateFrequency": "notPlanned", "dataLineage": "HadISDH.extremes is a global land surface (~2 m) humid and dry heat extremes index dataset and is produced by the Met Office Hadley Centre through the Met Office Climate Science for Service Partnership (CSSP) China project. It is based on the quality controlled sub-daily HadISD from the Met Office Hadley Centre which is in turn based on the ISD dataset from NOAA's NCEI. It is passed to the BADC for archiving and distribution.", "removedDataReason": "", "keywords": "HadISDH, humidity, surface, land, gridded, station, heat, extremes index, air temperature, wet bulb temperature, in-situ", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-06-18T09:43:24", "doiPublishedTime": "2024-07-12T13:53:39", "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": 41772, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISDH-extremes/mon/HadISDHTable/r1/v1-1-0-2023f", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 218313636, "numberOfFiles": 33, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 11131, "startTime": "1973-01-01T00:00:00", "endTime": "2022-12-31T23:59:59" }, "resultQuality": { "ob_id": 4310, "explanation": "The sub-daily observations have been quality controlled and data completeness thresholds are applied at the daily, monthly, annual, climatological and whole record level. Each gridbox month is given a score relating to likely inhomogeneity which can be used to filter the dataset to reduce the influence of large inhomogeneity.", "passesTest": true, "resultTitle": "HadISDH.extremes QC statement", "date": "2023-06-12" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 40170, "uuid": "62c89c91587c4bc9adcf20b2fe7677fd", "short_code": "comp", "title": "HadISDH.extremes: gridded global monthly land surface wet bulb and dry bulb temperature extremes index dataset produced by the Met Office Hadley Centre", "abstract": "HadISDH.extremes utilises simultaneous sub-daily dry bulb and wet bulb temperature (calculated from dry bulb and dew point temperature) data from over 4000 quality controlled HadISD stations that have sufficiently long records. After checking for sufficient completeness at the daily, monthly, annual, climatological and whole record scale, monthly indices are created from the maximum and minimum of the available daily values. Note that these likely underestimate the true extremes. Climatological averages are calculated over 1991-2020 and monthly climate anomalies obtained. These anomalies (in addition to climatological mean and standard deviation, actual values) 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. Each gridbox month has an associated homogeneity score obtained from the homogenisation information from HadISDH.landT and HadISDH.landTw. Users can filter the data to remove those gridboxes likely affected by large inhomogeneity. While unlikely to be perfect, this process does help remove large errors from the data an improve robustness of long-term climate monitoring. For greater detail please see: \r\n\r\n\r\n\r\nWillett, K, 2023: HadISDH.extremes Part 1: a gridded wet bulb temperature extremes index product for climate monitoring. Advances in Atmospheric Sciences, 40, 1952–1967, doi: 10.1007/s00376-023-2347-8. https://link.springer.com/article/10.1007/s00376-023-2347-8. \r\n\r\nWillett, K. 2023: HadISDH.extremes Part 2: exploring humid heat extremes using wet bulb temperature indices. Advances in Atmospheric Sciences, 40, 1968–1985, doi: 10.1007/s00376-023-2348-7. https://link.springer.com/article/10.1007/s00376-023-2348-7.\r\n\r\nSee the documentation links in the online resources section of this record for 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": [ 56886, 56887, 56888, 56889, 56891, 56892, 56893, 56894, 56895, 60438, 66085, 66086, 66087, 66088, 66089, 66090, 66091, 66092, 66093, 66094, 66095, 66096, 66097, 66098, 66099, 66100, 66101, 66102, 66103, 66104, 66105, 66106, 66107, 66108, 66109, 66110, 66111, 66112, 66113, 66114, 66115, 66116, 66117, 66118, 66119, 66120, 66121, 66122, 66123, 66127, 66128, 66129, 66130, 66131, 66132, 66133, 66134, 66135, 66136, 66137, 66138, 66139, 66140, 66141, 66142, 66143, 66144, 66145, 66146, 66147, 66148, 66149, 66150, 66160, 66161, 66162, 66163, 66164, 66165, 66166, 66168, 66169, 66171, 66172, 66173, 66174, 66175, 66176, 66177, 66178, 73614, 73615, 73616, 73617, 73618, 73619, 73620, 73621, 73622, 73623, 73624, 73625, 73626, 73627, 73628, 73629, 73630, 73631, 73632, 73633, 73634, 73635, 73636, 73637, 73638, 73639, 73640, 73641, 73642 ], "vocabularyKeywords": [], "identifier_set": [ 13146 ], "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": [ 203502, 203494, 203495, 203496, 203497, 203498, 203499, 203500, 203501, 203503 ], "onlineresource_set": [ 86384, 86393, 86385, 86386, 86387, 86388, 86389, 86390, 86391, 86392, 86417 ] }, { "ob_id": 41768, "uuid": "c844fc58615a422aa2e7d2fc8bd8cccf", "title": "HadISDH.land: gridded global monthly land surface humidity data version 4.6.0.2023f", "abstract": "This is the HadISDH.land 4.6.0.2023f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.land is a near-global gridded monthly mean land surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from weather stations. The observations have been quality controlled and homogenised. 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 31/12/2023. \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 2023. 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\nAs in previous years, the annual scrape of NOAAs Integrated Surface Dataset for HadISD.3.4.0.2023f, which is the basis of HadISDH.land, has pulled through some historical changes to stations. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data.\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., 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": "2024-09-11T13:12:37", "updateFrequency": "notPlanned", "dataLineage": "HadISDH.land is a global land surface (~2 m) humidity dataset and is produced by the Met Office Hadley Centre in collaboration with Maynooth University, NOAA NCEI, NPL and CRU. It is based on the quality controlled sub-daily HadISD from the Met Office Hadley Centre which is in turn based on the ISD dataset from NOAA's NCEI. It is passed to CEDA for archiving and distribution.", "removedDataReason": "", "keywords": "HadISDH, humidity, surface, land, 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": "completed", "dataPublishedTime": "2024-06-14T10:17:42", "doiPublishedTime": "2024-06-14T10:32:06", "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": 41770, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISDH/mon/HadISDHTable/r1/v4-6-0-2023f", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 97531658, "numberOfFiles": 8, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 11714, "startTime": "1973-01-01T00:00:00", "endTime": "2023-12-31T23:59:59" }, "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": 13526, "uuid": "02d903686bc9471a866e6b0d7c19f727", "short_code": "comp", "title": "HadISDH.land: gridded global land surface humidity dataset produced by the Met Office Hadley Centre", "abstract": "HadISDH.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. \r\n\r\nMonthly 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. See Docs 'HadISDH.land process diagram'.\r\n\r\nStation measurement, climatological and homogeneity adjustment uncertainties are estimated for each month. Climatological averages are calculated (the climatological period is dependent on product version) 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:\r\nWillett, 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\nand\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": 2561, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 32, "licenceURL": "http://www.nationalarchives.gov.uk/doc/non-commercial-government-licence/version/2/", "licenceClassifications": [ { "ob_id": 6, "classification": "personal" }, { "ob_id": 4, "classification": "academic" }, { "ob_id": 5, "classification": "policy" } ] } } ], "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": [ 56886, 56887, 56888, 56889, 56890, 56891, 56892, 56893, 56894, 56895, 56898, 56899, 56900, 60438, 66183, 66184, 66185, 66187, 66189, 66192, 73574, 73575, 73576, 73577, 73578, 73579, 73580, 73581, 73582, 73583, 73584, 73585, 73586, 73587, 73588, 73589, 73590, 73591, 73592, 73593, 73594, 73595, 73596, 73597, 73598, 73599 ], "vocabularyKeywords": [], "identifier_set": [ 13129 ], "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": [ 203510, 203504, 203505, 203511, 203506, 203507, 203512, 203508, 203509, 203514, 203513, 203515, 203516, 203517, 203518, 203519, 203520 ], "onlineresource_set": [ 86399, 86402, 86395, 86400, 86396, 86397, 86398, 86405, 86401, 86403, 86404 ] }, { "ob_id": 41769, "uuid": "2fdc37a517b54376ba19d5c7432457d5", "title": "HadISDH.marine: gridded global monthly ocean surface humidity data version 1.6.0.2023f", "abstract": "This is the HadISDH.marine 1.6.0.2023f 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 31/12/2023.\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 2023. 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": "2024-06-19T01:48:52", "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": "completed", "dataPublishedTime": "2024-06-14T09:35:08", "doiPublishedTime": "2024-06-14T10:02:31.986527", "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": 41771, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISDH-marine/mon/HadISDHTable/r1/v1-6-0-2023f", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 252296273, "numberOfFiles": 8, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 11713, "startTime": "1973-01-01T00:00:00", "endTime": "2023-12-31T23:59:59" }, "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": [ 13127 ], "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": [ 203523, 203521, 203522, 203524, 203525, 203526, 203527, 203528, 203529, 203532, 203531, 203530, 203533, 203534 ], "onlineresource_set": [ 86406, 86407, 86408, 86409, 86410, 86411, 86412, 86413, 86416 ] }, { "ob_id": 41959, "uuid": "89c654c2e4a74ce5a494b69753d8291e", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Mass flow rate ice discharge (MFID) for Greenland from CCI IV, CCI SEC, and BedMachine v2.0", "abstract": "Mass flow rate ice discharge (MFID) for Greenland ice sheet sectors. This data set is part of the ESA Greenland Ice sheet CCI project. \r\n\r\nIt provides the following CSV files: \r\n- Mass flow rate ice discharge. Units are Gt yr^{-1}.\r\n- Mass flow rate ice discharge uncertainty. Units are Gt yr^{-1}.\r\n- Coverage for each sector at each timestamp. Unitless [0 to 1].\r\n\r\nIce discharge is calculated from the CCI Ice Velocity (IV) product, the CCI Surface Elevation Change (SEC) product (where it overlaps with the ice discharge gates), and ice thickness from BedMachine. Ice discharge gates are placed 10 km upstream from all marine terminating glacier termini that have baseline velocities of more than 150 m/yr. Results are summed by Zwally et al. (2012) sectors.\r\n\r\nThe methods, including description of \"coverage\", are described in Mankoff et al. 2020.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2024-10-19T02:00:54", "updateFrequency": "notPlanned", "dataLineage": "Ice discharge is calculated from the CCI Ice Velocity (IV) product, the CCI Surface Elevation Change (SEC) product (where it overlaps with the ice discharge gates), and ice thickness from BedMachine. Ice discharge gates are placed 10 km upstream from all marine terminating glacier termini that have baseline velocities of more than 150 m/yr. Results are summed by Zwally et al. (2012) sectors. The methods, including description of \"coverage\", are described in Mankoff et al. (2020; DOI: 10.5194/essd-12-1367-2020)", "removedDataReason": "", "keywords": "Greenland, Ice sheet, CCI, ESA", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2024-10-16T08:19:51", "doiPublishedTime": "2024-10-18T13:25:04.526350", "removedDataTime": null, "geographicExtent": { "ob_id": 1650, "bboxName": "Greenland", "eastBoundLongitude": -10.0, "westBoundLongitude": -80.0, "southBoundLatitude": 60.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 43145, "dataPath": "/neodc/esacci/ice_sheets_greenland/data/greenland_mass_flow_rate_ice_discharge/v2.0", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 384289, "numberOfFiles": 8, "fileFormat": "csv, png, txt" }, "timePeriod": { "ob_id": 11863, "startTime": "2014-10-01T00:00:00", "endTime": "2021-04-01T22:59:59" }, "resultQuality": { "ob_id": 3240, "explanation": "As provided by the CCI Greenland Ice Sheets team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-02-05" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 43144, "uuid": "b2ea0c5a99f849728e1b7640ade097a6", "short_code": "comp", "title": "Mass flow rate ice discharge (MFID) derived by the ESA Greenland Ice Sheets Climate Change Initiative project, v2.0", "abstract": "Ice discharge is calculated from the CCI Ice Velocity (IV) product, the CCI Surface Elevation Change (SEC) product (where it overlaps with the ice discharge gates), and ice thickness from BedMachine. Ice discharge gates are placed 10 km upstream from all marine terminating glacier termini that have baseline velocities of more than 150 m/yr. Results are summed by Zwally et al. (2012) sectors. The methods, including description of \"coverage\", are described in Mankoff et al. 2020. \r\n\r\nFor further details see the documentation." }, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2553, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 25, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_icesheets_greenland_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 14317, "uuid": "362f66a7e09a4a59be2a40af6b41d0a6", "short_code": "proj", "title": "ESA Greenland Ice Sheet Climate Change Initiative Project", "abstract": "The Greenland Ice Sheet CCI project aims to maximize the impact of ESA satellite data on climate research, by analysing data from ESA Earth Observation missions such as ERS, Envisat, CryoSat, GRACE and the new Sentinel series of satellites. Over the last decade, the Greenland Ice Sheet has shown rapid change, characterized by rapid thinning along the margins, accelerating outlet glaciers, and overall increasing mass loss. The state of the Greenland Ice Sheet is of global importance, and has consequently been included in the ESA CCI Programme as a monitored Essential Climate Variable (ECV).\r\n\r\nThe project is producing data products of the following five parameters, which are important in characterizing the Greenland Ice Sheet as an Essential Climate Variable: Surface Elevation Change (SEC) gridded data from radar altimetry; Ice Velocity (IV) gridded data from synthetic aperture radar interferometry and feature tracking; Calving Front Location (CFL) time series of marine-terminating glaciers; Grounding Line Location (GLL) time series of marine-terminating glaciers; Gravimetry Mass Balance (GMB) maps and time series." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [ 13202 ], "observationcollection_set": [ { "ob_id": 14316, "uuid": "394464f9c39445d3b6445d8e305841d7", "short_code": "coll", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland Ice Sheet CCI) Dataset Collection", "abstract": "The Greenland Ice Sheet CCI project aims to maximize the impact of ESA satellite data on climate research, by analysing data from ESA Earth Observation missions such as ERS, Envisat, CryoSat, GRACE and the new Sentinel series of satellites. Over the last decade, the Greenland Ice Sheet has shown rapid change, characterized by rapid thinning along the margins, accelerating outlet glaciers, and overall increasing mass loss. The state of the Greenland Ice Sheet is of global importance, and has consequently been included in the ESA CCI Programme as a monitored Essential Climate Variable (ECV).\r\n\r\nThe project is producing data products of the following five parameters, which are important in characterizing the Greenland Ice Sheet as an Essential Climate Variable: Surface Elevation Change (SEC) gridded data from radar altimetry; Ice Velocity (IV) gridded data from synthetic aperture radar interferometry and feature tracking; Calving Front Location (CFL) time series of marine-terminating glaciers; Grounding Line Location (GLL) time series of marine-terminating glaciers; Gravimetry Mass Balance (GMB) maps and time series." } ], "responsiblepartyinfo_set": [ 203892, 203893, 203895, 203896, 203897, 203898, 203899, 203894, 203900, 203901 ], "onlineresource_set": [ 86423, 86418, 86419, 86420, 86421, 86422, 87895, 87896 ] }, { "ob_id": 42321, "uuid": "c22d0b462321447882d2d1367cc77d3c", "title": "HadUK-Grid Gridded Climate Observations on a 60km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The dataset at 60 km resolution is derived from the associated 1 km x 1 km resolution to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-01-10T01:56:20", "updateFrequency": "notPlanned", "dataLineage": "Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.", "removedDataReason": "", "keywords": "Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-07-18T11:21:38", "doiPublishedTime": "2024-07-18T13:11:04", "removedDataTime": null, "geographicExtent": { "ob_id": 2305, "bboxName": "HadUK-Grid area", "eastBoundLongitude": 4.59, "westBoundLongitude": -12.61, "southBoundLatitude": 48.83, "northBoundLatitude": 60.57 }, "verticalExtent": null, "result_field": { "ob_id": 43078, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.0.ceda/60km", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 336410037, "numberOfFiles": 6505, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 11726, "startTime": "1836-01-01T00:00:00", "endTime": "2023-12-31T23:59:59" }, "resultQuality": { "ob_id": 3946, "explanation": "Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.", "passesTest": true, "resultTitle": "HadUK-Grid v1.1 Data Quality Statement", "date": "2022-05-13" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26870, "uuid": "b1b352825f5548a8bf0639afe335f5ae", "short_code": "comp", "title": "HadUK-Grid gridded climate observations methodology", "abstract": "The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography." }, "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": 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": [ 6023, 11484, 11485, 11486, 50516, 50517, 51186, 51187, 51188, 51189, 51193, 51195, 51196, 51197, 51200, 54990, 54991, 54992, 54994, 54997, 62352, 62353, 62354, 62355, 62356, 64067 ], "vocabularyKeywords": [], "identifier_set": [ 13149 ], "observationcollection_set": [ { "ob_id": 26862, "uuid": "4dc8450d889a491ebb20e724debe2dfb", "short_code": "coll", "title": "HadUK-Grid gridded and regional average climate observations for the UK", "abstract": "This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.1.ceda, released in June 2025 and containing data up to the end of 2024. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home) The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised." } ], "responsiblepartyinfo_set": [ 203928, 203929, 203930, 203931, 203932, 203933, 203934, 203937, 203936, 203938, 203939, 203940, 203941, 204600 ], "onlineresource_set": [ 86439, 86442, 86443, 86440, 86441 ] }, { "ob_id": 42322, "uuid": "5ba67d62cdc249a3bc5b1c38b339beb3", "title": "HadUK-Grid Gridded Climate Observations on a 5km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The dataset at 5 km resolution is derived from the associated 1 km x 1 km resolution to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-06-27T01:57:39", "updateFrequency": "notPlanned", "dataLineage": "Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.", "removedDataReason": "", "keywords": "Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2024-07-18T11:17:21", "doiPublishedTime": "2024-07-18T13:10:42", "removedDataTime": null, "geographicExtent": { "ob_id": 2305, "bboxName": "HadUK-Grid area", "eastBoundLongitude": 4.59, "westBoundLongitude": -12.61, "southBoundLatitude": 48.83, "northBoundLatitude": 60.57 }, "verticalExtent": null, "result_field": { "ob_id": 43074, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.0.ceda/5km", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 14705927716, "numberOfFiles": 6505, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 11727, "startTime": "1836-01-01T00:00:00", "endTime": "2023-12-31T23:59:59" }, "resultQuality": { "ob_id": 3946, "explanation": "Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.", "passesTest": true, "resultTitle": "HadUK-Grid v1.1 Data Quality Statement", "date": "2022-05-13" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26870, "uuid": "b1b352825f5548a8bf0639afe335f5ae", "short_code": "comp", "title": "HadUK-Grid gridded climate observations methodology", "abstract": "The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography." }, "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": 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": [ 6023, 11484, 11485, 11486, 50516, 50517, 51186, 51187, 51188, 51189, 51193, 51195, 51196, 51197, 51200, 54990, 54991, 54992, 54994, 54997, 62352, 62353, 62354, 62355, 62356, 64067 ], "vocabularyKeywords": [], "identifier_set": [ 13148 ], "observationcollection_set": [ { "ob_id": 26862, "uuid": "4dc8450d889a491ebb20e724debe2dfb", "short_code": "coll", "title": "HadUK-Grid gridded and regional average climate observations for the UK", "abstract": "This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.1.ceda, released in June 2025 and containing data up to the end of 2024. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home) The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised." } ], "responsiblepartyinfo_set": [ 203942, 203943, 203944, 203945, 203946, 203947, 203948, 203949, 203950, 203951, 203952, 203953, 203954, 203955, 204599 ], "onlineresource_set": [ 95077, 86446, 86447, 86448, 86444, 86445 ] }, { "ob_id": 42323, "uuid": "18ddbb686be549bfadfecbe0c673f405", "title": "HadUK-Grid Gridded Climate Observations on a 25km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The dataset at 25 km resolution is derived from the associated 1 km x 1 km resolution to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-06-27T01:57:39", "updateFrequency": "notPlanned", "dataLineage": "Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.", "removedDataReason": "", "keywords": "Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2024-07-18T11:25:19", "doiPublishedTime": "2024-07-18T13:11:21", "removedDataTime": null, "geographicExtent": { "ob_id": 2305, "bboxName": "HadUK-Grid area", "eastBoundLongitude": 4.59, "westBoundLongitude": -12.61, "southBoundLatitude": 48.83, "northBoundLatitude": 60.57 }, "verticalExtent": null, "result_field": { "ob_id": 43077, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.0.ceda/25km", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 889161020, "numberOfFiles": 6505, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 11728, "startTime": "1836-01-01T00:00:00", "endTime": "2023-12-31T23:59:59" }, "resultQuality": { "ob_id": 3946, "explanation": "Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.", "passesTest": true, "resultTitle": "HadUK-Grid v1.1 Data Quality Statement", "date": "2022-05-13" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26870, "uuid": "b1b352825f5548a8bf0639afe335f5ae", "short_code": "comp", "title": "HadUK-Grid gridded climate observations methodology", "abstract": "The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography." }, "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": 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": [ 6023, 11484, 11485, 11486, 50516, 50517, 51186, 51187, 51188, 51189, 51193, 51195, 51196, 51197, 51200, 54990, 54991, 54992, 54994, 54997, 62352, 62353, 62354, 62355, 62356, 64067 ], "vocabularyKeywords": [], "identifier_set": [ 13150 ], "observationcollection_set": [ { "ob_id": 26862, "uuid": "4dc8450d889a491ebb20e724debe2dfb", "short_code": "coll", "title": "HadUK-Grid gridded and regional average climate observations for the UK", "abstract": "This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.1.ceda, released in June 2025 and containing data up to the end of 2024. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home) The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised." } ], "responsiblepartyinfo_set": [ 203957, 203958, 203959, 203960, 203961, 203962, 203963, 203956, 203964, 203965, 203966, 203967, 203968, 203969, 204598 ], "onlineresource_set": [ 86451, 86449, 86450, 86452, 86453 ] }, { "ob_id": 42324, "uuid": "b963ead70580451aa7455782224479d5", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-01-10T01:56:19", "updateFrequency": "notPlanned", "dataLineage": "Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.", "removedDataReason": "", "keywords": "Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-07-18T12:25:15", "doiPublishedTime": "2024-07-18T13:11:51", "removedDataTime": null, "geographicExtent": { "ob_id": 2305, "bboxName": "HadUK-Grid area", "eastBoundLongitude": 4.59, "westBoundLongitude": -12.61, "southBoundLatitude": 48.83, "northBoundLatitude": 60.57 }, "verticalExtent": null, "result_field": { "ob_id": 43072, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.0.ceda/1km", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 324702016098, "numberOfFiles": 6505, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 11729, "startTime": "1836-01-01T00:00:00", "endTime": "2023-12-31T23:59:59" }, "resultQuality": { "ob_id": 3946, "explanation": "Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.", "passesTest": true, "resultTitle": "HadUK-Grid v1.1 Data Quality Statement", "date": "2022-05-13" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26870, "uuid": "b1b352825f5548a8bf0639afe335f5ae", "short_code": "comp", "title": "HadUK-Grid gridded climate observations methodology", "abstract": "The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography." }, "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": 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": [ 6023, 11484, 11485, 11486, 50516, 50517, 51186, 51187, 51188, 51189, 51193, 51195, 51196, 51197, 51200, 54990, 54991, 54992, 54994, 54997, 62352, 62353, 62354, 62355, 62356, 64067 ], "vocabularyKeywords": [], "identifier_set": [ 13152 ], "observationcollection_set": [ { "ob_id": 26862, "uuid": "4dc8450d889a491ebb20e724debe2dfb", "short_code": "coll", "title": "HadUK-Grid gridded and regional average climate observations for the UK", "abstract": "This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.1.ceda, released in June 2025 and containing data up to the end of 2024. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home) The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised." } ], "responsiblepartyinfo_set": [ 203970, 203971, 203972, 203973, 203974, 203975, 203976, 203977, 203978, 203979, 203980, 203981, 203982, 203983, 204597 ], "onlineresource_set": [ 86456, 86454, 86455, 86457, 86458 ] }, { "ob_id": 42325, "uuid": "5a248096468640a6bfb0dfda8b018ac5", "title": "HadUK-Grid Gridded Climate Observations on a 12km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The dataset at 12 km resolution is derived from the associated 1 km x 1 km resolution to allow for comparison to data from climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation). \r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-06-27T01:57:38", "updateFrequency": "notPlanned", "dataLineage": "Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.", "removedDataReason": "", "keywords": "Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2024-07-18T11:30:16", "doiPublishedTime": "2024-07-18T13:11:38", "removedDataTime": null, "geographicExtent": { "ob_id": 2305, "bboxName": "HadUK-Grid area", "eastBoundLongitude": 4.59, "westBoundLongitude": -12.61, "southBoundLatitude": 48.83, "northBoundLatitude": 60.57 }, "verticalExtent": null, "result_field": { "ob_id": 43075, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.0.ceda/12km", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2859928948, "numberOfFiles": 6505, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 11730, "startTime": "1836-01-01T00:00:00", "endTime": "2023-12-31T23:59:59" }, "resultQuality": { "ob_id": 3946, "explanation": "Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.", "passesTest": true, "resultTitle": "HadUK-Grid v1.1 Data Quality Statement", "date": "2022-05-13" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26870, "uuid": "b1b352825f5548a8bf0639afe335f5ae", "short_code": "comp", "title": "HadUK-Grid gridded climate observations methodology", "abstract": "The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography." }, "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": 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": [ 6023, 11484, 11485, 11486, 50516, 50517, 51186, 51187, 51188, 51189, 51193, 51195, 51196, 51197, 51200, 54990, 54991, 54992, 54994, 54997, 62352, 62353, 62354, 62355, 62356, 64067 ], "vocabularyKeywords": [], "identifier_set": [ 13151 ], "observationcollection_set": [ { "ob_id": 26862, "uuid": "4dc8450d889a491ebb20e724debe2dfb", "short_code": "coll", "title": "HadUK-Grid gridded and regional average climate observations for the UK", "abstract": "This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.1.ceda, released in June 2025 and containing data up to the end of 2024. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home) The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised." } ], "responsiblepartyinfo_set": [ 203984, 203985, 203986, 203987, 203988, 203989, 203990, 203991, 203994, 203993, 203992, 203995, 203996, 203997, 204596 ], "onlineresource_set": [ 86459, 86460, 86461, 86462, 86463 ] }, { "ob_id": 42326, "uuid": "b1282951f38947da93c0b0db31bb8419", "title": "HadUK-Grid Climate Observations by UK river basins, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. These data at 1 km resolution have been averaged across a set of discrete geographies defining UK river basins consistent with data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-01-10T01:56:21", "updateFrequency": "notPlanned", "dataLineage": "Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.", "removedDataReason": "", "keywords": "Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-07-18T12:51:51", "doiPublishedTime": "2024-07-18T13:12:24", "removedDataTime": null, "geographicExtent": { "ob_id": 2308, "bboxName": "", "eastBoundLongitude": 1.76, "westBoundLongitude": -8.84, "southBoundLatitude": 49.86, "northBoundLatitude": 60.86 }, "verticalExtent": null, "result_field": { "ob_id": 43073, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.0.ceda/river", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 24969594, "numberOfFiles": 163, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 11731, "startTime": "1836-01-01T00:00:00", "endTime": "2023-12-31T23:59:59" }, "resultQuality": { "ob_id": 3946, "explanation": "Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.", "passesTest": true, "resultTitle": "HadUK-Grid v1.1 Data Quality Statement", "date": "2022-05-13" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26870, "uuid": "b1b352825f5548a8bf0639afe335f5ae", "short_code": "comp", "title": "HadUK-Grid gridded climate observations methodology", "abstract": "The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography." }, "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": 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": [ 6023, 50511, 50516, 50517, 51193, 51195, 51196, 51197, 51200, 54990, 54992, 54994, 61135, 62352, 62353, 62354, 62357, 64067 ], "vocabularyKeywords": [], "identifier_set": [ 13154 ], "observationcollection_set": [ { "ob_id": 26862, "uuid": "4dc8450d889a491ebb20e724debe2dfb", "short_code": "coll", "title": "HadUK-Grid gridded and regional average climate observations for the UK", "abstract": "This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.1.ceda, released in June 2025 and containing data up to the end of 2024. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home) The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised." } ], "responsiblepartyinfo_set": [ 203998, 203999, 204000, 204001, 204002, 204003, 204004, 204005, 204008, 204007, 204006, 204009, 204010, 204011, 204595 ], "onlineresource_set": [ 86464, 86465, 86466, 86467, 86468 ] }, { "ob_id": 42327, "uuid": "a508838f92c74005a26b9277eae59a7c", "title": "HadUK-Grid Climate Observations by UK countries, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. These data at 1 km resolution have been averaged across a set of discrete geographies defining UK countries consistent with data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n\r\n * Added data for calendar year 2023\r\n \r\n* Added newly digitised data for monthly sunshine 1910-1918\r\n\r\n * Added Rainfall Rescue version 2 doi:10.5281/zenodo.7554242\r\n\r\n * Updated shapefiles used for production of area average statistics https://github.com/ukcp-data/ukcp-spatial-files\r\n\r\n * Updated controlled vocabulary for metadata assignment https://github.com/ukcp-data/UKCP18_CVs\r\n\r\n * Updated assignment of timepoint for some periods so that the datetime is the middle of the period (e.g. season) rather than a fixed offset from the period start.\r\n\r\n * Updated ordering of regions within regional values files. Alphabetical ordering.\r\n\r\n * Files use netcdf level 4 compression using gzip https://www.unidata.ucar.edu/blogs/developer/entry/netcdf_compression\r\n\r\n* Net changes to the input station data used to generate this dataset:\r\n\r\n- Total of 125601744 observations\r\n\r\n- 122621050 (97.6%) unchanged\r\n\r\n- 26700 (0.02%) modified for this version\r\n\r\n- 2953994 (2.35%) added in this version\r\n\r\n- 16315 (0.01%) deleted from this version\r\n\r\n* Changes to monthly rainfall 1836-1960\r\n\r\n- Total of 4823973 observations\r\n\r\n- 3315657 (68.7%) unchanged\r\n\r\n- 21029 (0.4%) modified for this version\r\n\r\n- 1487287 (30.8%) added in this version\r\n\r\n- 11155 (0.2%) deleted from this version\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-01-10T01:56:20", "updateFrequency": "notPlanned", "dataLineage": "Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.", "removedDataReason": "", "keywords": "Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-07-18T13:00:46", "doiPublishedTime": "2024-07-18T13:12:39", "removedDataTime": null, "geographicExtent": { "ob_id": 2309, "bboxName": "", "eastBoundLongitude": 1.76, "westBoundLongitude": -8.18, "southBoundLatitude": 49.16, "northBoundLatitude": 60.86 }, "verticalExtent": null, "result_field": { "ob_id": 43089, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.0.ceda/country", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 12786131, "numberOfFiles": 163, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 11732, "startTime": "1836-01-01T00:00:00", "endTime": "2023-12-31T23:59:59" }, "resultQuality": { "ob_id": 3946, "explanation": "Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.", "passesTest": true, "resultTitle": "HadUK-Grid v1.1 Data Quality Statement", "date": "2022-05-13" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26870, "uuid": "b1b352825f5548a8bf0639afe335f5ae", "short_code": "comp", "title": "HadUK-Grid gridded climate observations methodology", "abstract": "The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography." }, "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": 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": [ 6023, 50511, 50517, 51193, 51195, 51196, 51197, 51200, 54990, 54991, 54992, 54994, 54997, 60895, 61135, 62352, 62353, 62354, 62355, 62356, 64067 ], "vocabularyKeywords": [], "identifier_set": [ 13155 ], "observationcollection_set": [ { "ob_id": 26862, "uuid": "4dc8450d889a491ebb20e724debe2dfb", "short_code": "coll", "title": "HadUK-Grid gridded and regional average climate observations for the UK", "abstract": "This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.1.ceda, released in June 2025 and containing data up to the end of 2024. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home) The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised." } ], "responsiblepartyinfo_set": [ 204015, 204019, 204016, 204012, 204013, 204014, 204017, 204018, 204021, 204020, 204022, 204023, 204024, 204025, 204594 ], "onlineresource_set": [ 86471, 86469, 86470, 86472, 86473 ] }, { "ob_id": 42328, "uuid": "8a51496be92b4e9488954c7c0199f3f9", "title": "HadUK-Grid Climate Observations by Administrative Regions over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. These data at 1 km resolution have been averaged across a set of discrete geographies defining UK administrative regions consistent with data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023 but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-01-10T01:54:12", "updateFrequency": "notPlanned", "dataLineage": "Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.", "removedDataReason": "", "keywords": "Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-09-10T11:31:39", "doiPublishedTime": "2024-07-18T13:12:08", "removedDataTime": null, "geographicExtent": { "ob_id": 2307, "bboxName": "", "eastBoundLongitude": 1.76, "westBoundLongitude": -8.18, "southBoundLatitude": 49.86, "northBoundLatitude": 60.86 }, "verticalExtent": null, "result_field": { "ob_id": 43076, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.0.ceda/region", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 19207679, "numberOfFiles": 163, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 11819, "startTime": "1836-01-01T00:00:00", "endTime": "2023-12-31T23:59:59" }, "resultQuality": { "ob_id": 3946, "explanation": "Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.", "passesTest": true, "resultTitle": "HadUK-Grid v1.1 Data Quality Statement", "date": "2022-05-13" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26870, "uuid": "b1b352825f5548a8bf0639afe335f5ae", "short_code": "comp", "title": "HadUK-Grid gridded climate observations methodology", "abstract": "The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography." }, "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": 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": [ 6023, 50511, 50517, 51193, 51195, 51197, 51200, 54990, 54991, 54992, 54997, 61135, 62352, 62353, 62354, 62355, 62356, 62358 ], "vocabularyKeywords": [], "identifier_set": [ 13153 ], "observationcollection_set": [ { "ob_id": 26862, "uuid": "4dc8450d889a491ebb20e724debe2dfb", "short_code": "coll", "title": "HadUK-Grid gridded and regional average climate observations for the UK", "abstract": "This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.1.ceda, released in June 2025 and containing data up to the end of 2024. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home) The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised." } ], "responsiblepartyinfo_set": [ 204026, 204027, 204028, 204029, 204030, 204031, 204032, 204033, 204036, 204035, 204034, 204037, 204038, 204039, 204593 ], "onlineresource_set": [ 88172, 86477, 86478, 86474, 86475, 86476 ] }, { "ob_id": 42330, "uuid": "a6bb3e8def544b5790d4b05a6f37f901", "title": "MIDAS Open: UK soil temperature data, v202407", "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 2023.\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 2023.\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": "2025-07-16T01:54:15", "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": "2024-08-06T14:34:26", "doiPublishedTime": "2024-08-06T14:34:42", "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": 43103, "dataPath": "/badc/ukmo-midas-open/data/uk-soil-temperature-obs/dataset-version-202407/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 4264701373, "numberOfFiles": 23948, "fileFormat": "Data are BADC-CSV formatted." }, "timePeriod": { "ob_id": 11831, "startTime": "1900-01-01T09:00:00", "endTime": "2023-12-31T23:59:59" }, "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": [ { "ob_id": 1138, "name": "NDGO0003" } ], "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": [ 13164 ], "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": [ 204040, 204041, 204042, 204043, 204044, 204045, 204046, 204047, 204048 ], "onlineresource_set": [ 86481, 86479, 86480, 86482, 86483, 86484, 86486, 86485, 87873 ] }, { "ob_id": 42331, "uuid": "91cb9985a6c2453d99084bde4ff5f314", "title": "MIDAS Open: UK mean wind data, v202407", "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 2023.\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 2023.\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": "2025-07-16T01:54:14", "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": "2024-08-06T14:51:27", "doiPublishedTime": "2024-08-06T14:52:16", "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": 43104, "dataPath": "/badc/ukmo-midas-open/data/uk-mean-wind-obs/dataset-version-202407/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 8861087248, "numberOfFiles": 15324, "fileFormat": "Data are BADC-CSV formatted." }, "timePeriod": { "ob_id": 11828, "startTime": "1949-01-01T00:00:00", "endTime": "2023-12-31T23:59:59" }, "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. 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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 ], "vocabularyKeywords": [], "identifier_set": [ 13166 ], "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": [ 204049, 204050, 204051, 204052, 204053, 204054, 204055, 204056, 204057 ], "onlineresource_set": [ 86487, 86490, 86489, 86491, 86492, 86493, 86488, 86494, 87870 ] }, { "ob_id": 42332, "uuid": "c50776e4903942cdb329589da70b83fe", "title": "MIDAS Open: UK hourly weather observation data, v202407", "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 2023.\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 2023.\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": "2025-07-16T01:54:13", "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": "2024-08-06T14:42:09", "doiPublishedTime": "2024-08-06T14:43:14", "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": 43105, "dataPath": "/badc/ukmo-midas-open/data/uk-hourly-weather-obs/dataset-version-202407/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 34099134895, "numberOfFiles": 53148, "fileFormat": "Data are BADC-CSV formatted." }, "timePeriod": { "ob_id": 11829, "startTime": "1875-01-01T09:00:00", "endTime": "2023-12-31T23:59:59" }, "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. 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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": [ 13165 ], "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. 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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. 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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 2023.\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 2023.\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": "2025-07-16T01:54:15", "updateFrequency": "notPlanned", "dataLineage": "Data collated by the Met Office and archived in the Met Office's MIDAS database. 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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": [ { "ob_id": 1138, "name": "NDGO0003" } ], "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": [ 13161 ], "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. 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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 2023.\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": "2025-07-16T01:54:15", "updateFrequency": "notPlanned", "dataLineage": "Data collated by the Met Office and archived in the Met Office's MIDAS database. 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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": [ 13163 ], "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. 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These include the addition of data for calendar year 2023.\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": "2025-07-16T01:55:20", "updateFrequency": "notPlanned", "dataLineage": "Data collated by the Met Office and archived in the Met Office's MIDAS database. 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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. 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The relative humidity (from WRF) and the chemical composition (from EMEP4UK) were then used to calculate the water mass associated with the components of PM2.5 using the method by Snider et al. 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The Weather Research Forecast (WRF) model was used as the main meteorological driver (https://www2.mmm.ucar.edu/wrf/users/).\r\nModel website: http://www.emep4uk.ceh.ac.uk/" }, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 43010, "uuid": "a2fe61d9744c4c83a00ac85b09bae0ee", "short_code": "proj", "title": "Quantification of Utility of Atmospheric Network Technologies (QUANT)", "abstract": "" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 45670, "uuid": "824c0c058de442ab885431eba938dc03", "short_code": "coll", "title": "NCAS archive of Air quality measurements from Manchester, Birmingham and London air quality supersites", "abstract": "This collection contains maeasurements of air quality parameters from a suite of instruments deployed at 3 urban supesites located in Manchester, Birmingham and London Honor Oak Park.\r\n\r\nMore details to follow." } ], "responsiblepartyinfo_set": [ 204348, 204349, 204350, 204351, 204352, 204353, 204354, 204355, 204356, 204357 ], "onlineresource_set": [ 86552, 86553, 86554 ] }, { "ob_id": 43020, "uuid": "a66447dd099c4320b67c2a8f9458b27a", "title": "Daily model outputs from coupled ocean-biogeochemistry model with passive tracers released from the location of the MV X-Press Pearl accident location 2021.", "abstract": "This dataset contains outputs from two sets of simulations from an ocean-biogeochemistry (NEMO v.4.0.4 - ERSEM) model over the Sri Lanka region. In both simulations, the model is forced with ERA5 atmosphere, and a Nucleus for European Modelling of the Ocean (NEMO) dataset (ocean only, 3 year run) as lateral ocean boundary and initial conditions. Passive tracers (urea - organic nitrogen) are released from the region of the MV X-Press Pearl accident (approximately 7.0546N, 79.7589E). Both simulations last three months each. The outputs are stored in daily averaged grid-u, grid-v, grid-w, grid-t, and tracer variable files. For one set of these simulations, 1100T of passive tracers (urea, organic nitrogen compound) are released at different rates - over 1 day, 7 days, and 15 days. The start date of the release is 25/05/2021. These simulation start and end on: 01/05/2021 - 31/07/2021. In the other set of simulations, the release rate is over 1 day, but the date of the release is shifted from the 25th May to 25th of January, 25th February, 25th July, 25th September and 25th October (2021). These simulations start and end respectively on: 01/01/2021 - 31/03/2021; 01/02/2021 - 30/04/2021; 01/07/2021-31/09/2021; 01/09/21 - 30/11/2021; 01/10/2021 - 31/12/2021. The model configuration is named SRIL34. A complementary dataset with the hourly averaged release of tracers is also public. The outputs were generated under the Climate Linked Atlantic Sector Science (CLASS) and the South Asian Nitrogen Hub (SANH; NE/S009019/1) projects.", "creationDate": "2024-06-21T15:28:52.360065", "lastUpdatedDate": "2024-06-21T15:28:52", "latestDataUpdateTime": "2024-06-21T15:28:52", "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. 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In both simulations, the model is forced with ERA5 atmosphere, and a Nucleus for European Modelling of the Ocean (NEMO) dataset (ocean only, 3 year run) as lateral ocean boundary and initial conditions. Passive tracers (urea - organic nitrogen) are released from the region of the MV X-Press Pearl accident (approximately 7.0546N, 79.7589E). The outputs are stored in monthly files on grid-u, grid-v, grid-w, grid-t, and tracer variables containing hourly averages. For these simulations, 1100T of passive tracers (urea, organic nitrogen compound) are released at different rates - over 1 hour and over 6 hours. The start date of the release is 25th of May 2021. These simulation start and end on: 01/05/2021 - 30/06/2021. A complementary dataset with daily release of tracers is also public. The model configuration is named SRIL34. The outputs were generated under the Climate Linked Atlantic Sector Science (CLASS) and the South Asian Nitrogen Hub (SANH; NE/S009019/1) projects.", "creationDate": "2024-06-21T15:36:04.126308", "lastUpdatedDate": "2024-06-21T15:36:04", "latestDataUpdateTime": "2024-06-21T15:36:04", "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": "oceans", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-05-21T13:46:16", "doiPublishedTime": "2024-05-21T13:46:16", "removedDataTime": null, "geographicExtent": { "ob_id": 4567, "bboxName": "", "eastBoundLongitude": 83.5557, "westBoundLongitude": 77.275, "southBoundLatitude": 4.4932, "northBoundLatitude": 11.765 }, "verticalExtent": null, "result_field": { "ob_id": 43021, "dataPath": "/bodc/pol240043", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 0, "numberOfFiles": 0, "fileFormat": "NetCDF, text" }, "timePeriod": { "ob_id": 11805, "startTime": "2021-05-01T00:00:00", "endTime": "2021-06-30T23:59:59" }, "resultQuality": { "ob_id": 4576, "explanation": "The data are provided as-is with no quality control undertaken by the British Oceanographic Data Centre (BODC). 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The model is at 1/60 degree resolution, based on General Bathymetric Chart of the Oceans (GEBCO) bathymetry. It is forced with Copernicus Marine Environment Monitoring Service (CMEMS), GLOBAL_MULTIYEAR_PHY_001_030-TDS, derived ocean boundary conditions and ERA5 atmosphere. The data are daily averages saved in monthly grid-t, grid-u, and grid-v files. The model configuration is named SRIL34, and was part of the X-Press Pearl Disaster Nitrogen Modelling project. The outputs were generated under the Climate Linked Atlantic Sector Science (CLASS) and the South Asian Nitrogen Hub (SANH; NE/S009019/1) projects.", "creationDate": "2024-06-21T15:36:40.767603", "lastUpdatedDate": "2024-06-21T15:36:40", "latestDataUpdateTime": "2024-06-21T15:36:40", "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": "oceans", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-05-21T13:43:27", "doiPublishedTime": "2024-05-21T13:43:27", "removedDataTime": null, "geographicExtent": { "ob_id": 4567, "bboxName": "", "eastBoundLongitude": 83.5557, "westBoundLongitude": 77.275, "southBoundLatitude": 4.4932, "northBoundLatitude": 11.765 }, "verticalExtent": null, "result_field": { "ob_id": 43023, "dataPath": "/bodc/pol240044", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 0, "numberOfFiles": 0, "fileFormat": "NetCDF, text" }, "timePeriod": { "ob_id": 11806, "startTime": "2019-01-01T00:00:00", "endTime": "2021-11-30T23:59:59" }, "resultQuality": { "ob_id": 4577, "explanation": "The data are provided as-is with no quality control undertaken by the British Oceanographic Data Centre (BODC). 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The simulations model an idealised coast (19.75 km alongshore by 9 km cross-shore) and river (width 250 m by length 50 km) with constant discharge of water (1280 m3 s-1) and sediment (128 kg s-1), and with various combinations of significant wave height (up to 2 m) and tidal range (up to 6 m). They represent either 36 or 72 years of morphological development, starting from January 1, 2022. The simulations were generated using the open source model Delft3D. The data outputs were designed to explore the potential limiting effects of wave height and tidal range on delta formation. The results demonstrate that large enough combinations of these processes may prevent deltas from forming. Also included in the dataset are input files necessary to run the model code, and animations showing various processes over time in addition to bathymetry. The outputs were generated under the Natural Environment Research Council (NERC) Envision Doctoral Training Partnership (grant number: NE/S007423/1).", "creationDate": "2024-06-21T16:22:48.062563", "lastUpdatedDate": "2024-06-21T16:21:33", "latestDataUpdateTime": "2024-06-26T01:47:13", "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": "oceans, geoscientificInformation", "publicationState": "citable", "nonGeographicFlag": true, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-06-07T17:57:24", "doiPublishedTime": "2024-06-07T17:57:24", "removedDataTime": null, "geographicExtent": null, "verticalExtent": null, "result_field": { "ob_id": 43025, "dataPath": "/bodc/nfe240101", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2633969823121, "numberOfFiles": 10847, "fileFormat": null }, "timePeriod": { "ob_id": 11807, "startTime": "2022-01-01T00:00:00", "endTime": "2094-01-01T23:59:59" }, "resultQuality": { "ob_id": 4578, "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": "2024-06-21" }, "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": [ 13145 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 204430, 204431, 204427, 204428, 204429, 204433, 204434, 204436, 204432, 204435, 204437, 204438 ], "onlineresource_set": [] }, { "ob_id": 43029, "uuid": "8ea2c697ee53430a84825384bfdcf06a", "title": "ForestScan Project : Terrestrial Laser Scanning (TLS) of FBRMS-02: Station d’Etudes des Gorilles et Chimpanzés, Lopé National Park, Gabon 1ha plot LPG-01, June to July 2022", "abstract": "Terrestrial laser scanning (TLS) was conducted at three ForestScan 1ha (100m x 100m) Forest Biomass Reference Measurement Site (FBRMS) plots in Gabon from June to July 2022 by Cecilia Chavana-Bryant using a Riegl VZ-400i scanner. Data collection assistance was provided by Heddy O. Milamizokou Napo, Luna Soenens, Virginie Daelemans and Löic Makaga, data processing assistance was provided by Mr Peter Vines. This data collection was part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates.\r\n\r\nScans were acquired using chain sampling at 121 locations along a 10m Cartesian grid to ensure sufficient data overlap to produce high-quality point clouds for all ForestScan 1ha FBRMS plots. Due to the scanner's 100° field of view, capturing a complete sample of the scene at each scan location required two scans -an upright scan and a tilt scan. Upright scans are odd-numbered while tilt scans are even-numbered. The first scan at each plot is collected at the southwest corner, i.e. scan position 0,0 (unless something impedes it, e.g. stream, large tree fall, etc. or if the plot is oriented differently). To facilitate scan registration, five retro-reflective targets were located between scan positions with all tilt scans along the first sampling line were oriented towards the same sampling position along the next sampling line and tilt scans at the ends of sampling lines (i.e. tilt scans along plot edges) were oriented towards the inside of the plot. This aids scan registration as it allows tilt scans to capture the previous scan location within its field of view. A total of 242 scans were collected at each plot.\r\n\r\nThe Riegl operating and processing software RiSCAN PRO version 2.14.1 was used to generate a plot-level point cloud, scans were coarse registered using the shared retro-reflective targets located between consecutive scan positions. Coarse registration was then fine-tuned using Multi Station Adjustment 2 (MSA2).\r\n\r\nData for each of the four FBRMS plots is found within plot directories: LPG-01, OKO-01, OKO-02 and OKO-03. Plot directories contain a main project directory (named using the starting date of data collection, e.g. 2022-06-24_LPG-01.PROJ) with nine data subdirectories and a tile_index.dat file as shown in the archived document /neodc/forestscan/data/gabon/lope/TLS_lope_2022/LPG-01/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets.", "creationDate": "2024-06-25T16:52:47.574995", "lastUpdatedDate": "2024-06-25T16:52:04", "latestDataUpdateTime": "2025-03-29T01:54:33", "updateFrequency": "", "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "ForestScan project, GEO-TREES, BIOMASS mission, European Space Agency (ESA), Earth Observation (EO) calibration/validation, Terrestrial LiDAR Scanning (TLS), Unpiloted Aerial Vehicle LiDAR Scanning (UAV-LS), Aerial LiDAR Scanning (ALS), Digital twins, Above Ground Biomass (AGB) estimates, Carbon estimates, Forest structure, Tree segmentation, 3D tree structure, Field protocols", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2025-03-27T13:56:11", "doiPublishedTime": "2025-03-28T16:55:07.867984", "removedDataTime": null, "geographicExtent": { "ob_id": 2371, "bboxName": "TLS - LPG-01 Gabon\tOgooué-Ivindo Lopé Na", "eastBoundLongitude": 11.573, "westBoundLongitude": 11.573, "southBoundLatitude": -0.175, "northBoundLatitude": -0.175 }, "verticalExtent": null, "result_field": { "ob_id": 43562, "dataPath": "/neodc/forestscan/data/gabon/lope/TLS_lope_2022/LPG-01/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1066178163790, "numberOfFiles": 424132, "fileFormat": "Terrestrial LiDAR scanner data in csv, point cloud and Riegl Proprietary raw data format. Details of formats and data structure can be found in the archive document /neodc/forestscan/data/gabon/lope/TLS_lope_2022/LPG-01/ForestScan_example_data_directory_structure.pdf which details the data structure shared by all FBRSM plot TLS datasets. Further explanation of the files and their origin can also be found in the process computation section." }, "timePeriod": { "ob_id": 12108, "startTime": "2022-06-24T00:00:00", "endTime": "2022-07-03T00:00:00" }, "resultQuality": { "ob_id": 4671, "explanation": "Data quality control conducted by UCL ForestScan project team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2025-02-25" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 43565, "uuid": "c384fdd708e44dc29371d30ba2ace0a7", "short_code": "cmppr", "title": "Terrestrial laser scan composite process for ForestScan Plots in Gabon", "abstract": "Terrestrial laser scan composite process for ForestScan Plots in Gabon" }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "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": 40337, "uuid": "3da9f666e3ea4bb3af9cca064f05d3af", "short_code": "proj", "title": "ForestScan Project: a unique multiscale dataset of tropical forest structure across 3 continents including terrestrial, UAV and airborne LiDAR and in-situ forest census data", "abstract": "The ForestScan project was conceived to evaluate new technologies for characterizing forest structure and biomass at Forest Biomass Reference Measurement Sites (FBRMS). It is closely aligned with other international initiatives, particularly the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration & Validation (WGCV) AGB cal/val protocols, and is part of GEO-TREES, an international consortium dedicated to establishing a global network of Forest Biomass Reference Measurement Sites (FBRMS) to support EO and encourage investment in relevant field-based observations and science. ForestScan is the first demonstration of what can be achieved more broadly under GEO-TREES, which would significantly expand and enhance the use of E-derived AGB estimates.\r\n\r\nWe present data from the ForestScan project, a unique multiscale dataset of tropical forest 3D structural measurements, including terrestrial laser scanning (TLS), unpiloted aerial vehicle LiDAR scanning (UAV-LS), airborne LiDAR scanning (ALS), and in-situ tree census and ancillary data. These data are critical for the calibration and validation of earth observation (EO) estimates of forest biomass, as well as providing broader insights into tropical forest structure.\r\n\r\nData are presented for three FBRMS: FBRMS-01: Paracou, French Guiana; FBRMS-02: Lopé, Gabon; and FBRMS-03: Kabili-Sepilok, Malaysia. Field data for each site include new 3D LiDAR measurements combined with plot tree census and ancillary data, at a multi-hectare scale. Not all data types were collected at all sites, reflecting the practical challenges of field data collection. We also provide detailed data collection protocols and recommendations for TLS, UAV-LS, and plot census measurements for each site, along with requirements for ancillary data to enable integration with ALS data (where possible) and upscaling to EO estimates. We outline the requirements and challenges for field data collection for each data type and discuss the practical considerations for establishing new FBRMS or upgrading existing sites to FBRMS standard, including insights into the associated costs and benefits.\r\n\r\nThe ForestScan Project was funded under ESA contract: 4000126857/20/NL/AI" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [ 13284 ], "observationcollection_set": [ { "ob_id": 40623, "uuid": "88a8620229014e0ebacf0606b302112d", "short_code": "coll", "title": "ForestScan Collection", "abstract": "This collection is part of the European Space Agency (ESA) funded ForestScan project designed to improve the use of new Earth Observation (EO) estimates of above ground biomass (AGB) by providing TLS-, unmanned airborne vehicles (UAV-LS)- and airborne (ALS) LiDAR scanning-derived AGB and tree census data to compare to allometric and EO-derived estimates. The collection contains a multiscale dataset of tropical forest 3D structural measurements, including terrestrial laser scanning (TLS), unoccupied aerial vehicle LiDAR scanning (UAV-LS), airborne laser scanning (ALS), and in-situ tree census and ancillary data. ForestScan was conceived to evaluate new technologies for characterising forest structure and biomass at Forest Biomass Reference Measurement Sites (FBRMS). These data are critical for the calibration and validation of earth observation (EO) estimates of forest biomass, as well as providing broader insights into tropical forest structure.\r\n\r\nData are presented for the first three Forest Biomass Research Monitoring Sites in Paracou Research Station in French Guiana; Station d'Etudes des Gorilles et Chimpanzes, Lopé National Park in Gabon; and Kabili-Sepilok Forest Reserve, Malaysia. Field data for each site include new 3D LiDAR measurements combined with plot tree census and ancillary data, unmanned aerial vehicle-based laser scanning (UAV-LS) and airborne laser scanning (ALS) where possible, at a multi-hectare scale. Not all data types were collected at all sites, reflecting the practical challenges of field data collection.\r\n\r\nWe also provide detailed field data collection protocols for TLS, UAV-LS, and ALS measurements for each site, along with requirements for ancillary data to enable integration with ALS data (where possible) and upscaling to EO estimates.\r\n\r\nThe ForestScan project is closely aligned with other international initiatives, particularly the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration & Validation (WGCV) AGB cal/val protocols, and GEO-TREES, a new Group on Earth Observations (GEO) initiative aimed at establishing a network of FBRM sites. ForestScan is the first demonstration of what could be achieved more broadly under GEO-TREES, which would significantly expand and enhance the use of EO-derived AGB estimates" }, { "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": [ 204451, 204452, 204453, 204454, 204455, 204456, 208003, 208006, 208004, 208005, 208455, 208456, 208457, 208458, 208459, 208460, 208461, 208462, 208463, 208464, 208465, 208466, 208469, 208470, 208471, 208472, 208474, 208475, 208476, 208477, 208478, 208473, 208486, 208481, 208482, 208488, 208483, 208489, 208490, 208484, 208479, 208468, 208467, 208485, 208487, 208491, 208492 ], "onlineresource_set": [ 94272 ] }, { "ob_id": 43052, "uuid": "5e48b31e413b480792e4156191b654f4", "title": "FAMOUS-Glimmer simulations with interactive North American and Greenland ice sheets (21ka and 140ka)", "abstract": "This dataset contains model inputs and outputs from ensembles of simulations and sensitivity tests performed by FAMOUS-Glimmer of the Last Glacial Maximum (LGM; 21 kilo annum before present (ka BP)) and the Penultimate Glacial Maximum (PGM; 140 ka BP), as used in the publication Patterson et al., 2024 (https://doi.org/10.5194/cp-2024-10) These data were used to help understand the difference between the North American Ice Sheet at the last two glacial maxima, explore the sensitivity of the ice sheet to uncertain model parameters and understand the role of orbit, greenhouse gases and initial conditions on the final ice sheet configurations. The output of 62 ensemble members varying climate and ice sheet model parameters for each of the LGM and PGM are included as well as the results of 8 sensitivity tests using one set of parameters but varying the initial ice sheets and climates. These simulations were created using the atmospheric general circulation model FAMOUS coupled to the Glimmer ice sheet model under LGM and PGM climate boundary conditions, including greenhouse gas concentrations and orbital parameters outlined in the PMIP4 protocols (Kageyama et al., 2017 and Menviel et al., 2019).\r\n\r\nThe model inputs include ancillary files of the prescribed sea surface temperature and sea ice fields and climate model boundary conditions, netCDF files of the ice sheet model initial condition as well as the model configuration file and updated model modifications. The outputs consist of netCDF files of monthly climate model variables from ‘Not Ruled Out Yet’ ensemble simulations, ice sheet model output from the final timestep of all ensemble simulations (including ice sheet thickness, topography, surface mass balance and velocity) and final ice sheet thickness from the sensitivity tests. Also included are excel spreadsheets of the time series of total ice volumes for all ensemble members and the list of parameter combinations used for each. The climate model data has global coverage on a 7.5x5 degree lat/lon grid. The ice sheet model data covers North America and Greenland on a Lambert Azimuthal Equal Area projection at 40x40km resolution. Each simulation was run for ~1000 climate model years, with the ice sheet model running at 10x acceleration, giving ~10,000 years of ice sheet model output.", "creationDate": "2024-07-01T09:39:18.908609", "lastUpdatedDate": "2024-07-01T09:39:18", "latestDataUpdateTime": "2025-03-20T01:54:05", "updateFrequency": "notPlanned", "dataLineage": "Data were generated using the FAMOUS atmosphere model coupled to the Glimmer ice sheet model. The Glimmer model output data every 10 years over the 10000 ice sheet year simulations in a netCDF file and the final timestep of the 4 variables (thickness, topography, velocity and surface mass balance) was extracted. FAMOUS output a data field every month over the 1000 climate year simulations which were converted to netCDF format and concatenated into timeseries data. The data were then archived at CEDA.", "removedDataReason": "", "keywords": "Last Glacial Maximum, Penultimate Glacial Maximum, Ensemble, Uncertainty Quantification, FAMOUS-Ice, Glimmer", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "pending", "dataPublishedTime": "2024-07-18T08:51:18", "doiPublishedTime": "2024-07-18T10:52:43.833171", "removedDataTime": null, "geographicExtent": { "ob_id": 4568, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 43062, "dataPath": "/badc/deposited2024/Famous-Glimmer_data/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 138407167187, "numberOfFiles": 551, "fileFormat": "net-CDF" }, "timePeriod": { "ob_id": 11811, "startTime": "0001-01-01T00:00:00", "endTime": "9999-12-31T00:00:00" }, "resultQuality": { "ob_id": 4579, "explanation": "", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-07-01" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32054, "uuid": "826fe398a5784c478a845c1fc2efbb7f", "short_code": "comp", "title": "FAMOUS-ice-Glimmer model", "abstract": "Glimmer is a dynamical ice sheet model coupled to an atmosphere general circulation model of low resolution (FAMOUS-ice AGCM (FAst Met Office/UK Universities Simulator)), based on version 4.5 of the UK MetOffice Unified Model." }, "procedureCompositeProcess": null, "imageDetails": [], "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": 43091, "uuid": "dd58a4ee01034315b2c3e21e30c633d0", "short_code": "proj", "title": "Modelling output from the SMB-Gen project: Constraining projections of ice sheet instabilities and future sea level rise", "abstract": "This collection of data is an archive of the key model output from the UKRI Future Leaders Fellowship project \"SMB-Gen Constraining projections of Ice Sheet instabilities and future sea level rise\". The project aim is to constrain future projections of ice sheet instabilities using information from the geological past through the development of novel Bayesian uncertainty quantification tools and their application to modelling past, present and future ice sheet changes using complex coupled climate-ice sheet modelling. This collection of data contains inputs and output from coupled climate-ice sheet simulations of the Quaternary run with the FAMOUS-ice model in which Northern Hemisphere ice sheets are interactively simulated with either the low complexity Glimmer ice sheet model or the more complex BISICLES marine ice sheet model." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 1322, 1323, 1324, 3064, 3143, 3574, 3576, 3695, 3697, 51582, 51583, 52470, 55449, 55622, 56965, 62190, 67226, 67728, 69151, 69157, 69161, 69170, 69172, 74174, 74175, 74176, 74177, 74178, 74179, 74180, 74181, 74182, 74183, 74184, 74185, 74186, 74187, 74188, 74189, 74190, 74191, 74192, 74193, 74194, 74195, 74196, 74197, 74198, 74199, 74200, 74201, 74202, 74203, 74204, 74205, 74206, 74207, 74208, 74209, 74210, 74211, 74212, 74213, 74214, 74215, 74216, 74217, 74218, 74219, 74220, 74221, 74222, 74223, 74224, 74225, 74226, 74227, 74228, 74229, 74230, 74231, 74232, 74233, 74234, 74235, 74236, 74237, 74238, 74239, 74240, 74241, 74242, 74243, 74244, 74245, 74246, 74247, 74248, 74249, 74250, 74251, 74252, 74253, 74254, 74255, 74256, 74257, 74258, 74259, 74260, 74261, 74262, 74263, 74264, 74265, 74266, 74267, 74268, 74269, 74270, 74271, 74272, 74273, 74274, 74275, 74276, 74277, 74278, 74279, 74280, 74281, 74282, 74283, 74284, 74285, 74286, 74287, 74288, 74289, 74290, 74291, 74292 ], "vocabularyKeywords": [], "identifier_set": [ 13147 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 204486, 204487, 204488, 204489, 204490, 204491, 204492, 204543, 204493, 204494, 204495, 204496, 204497, 204498, 204499, 204500 ], "onlineresource_set": [ 86593, 86594, 86595, 88143 ] }, { "ob_id": 43054, "uuid": "a798f69cb13e4c219e735f96a7c33faa", "title": "OpenCLIM - Urban Flood Impacts : 1km gridded outputs for five GB cities", "abstract": "This dataset contains output datasets from the OpenCLIM_UrbanFlood Workflow. These runs were part of the NERC funded OpenCLIM (Open CLimate IMpacts modelling framework) project. This data can be used for the continued analysis of climate impacts and for comparison with future studies.\r\n\r\nThe data has been generated using the OpenCLIM_UrbanFlood workflow available on DAFNI (https://www.dafni.ac.uk/) and focuses on the cities of Newcastle, Norwich, Bath, Inverness and Swansea. The workflow was run for five cities across GB to analyse changes in flood risk for a large range of urban and climate futures. The workflow uses output datasets from the Urban Development Model (described below) to generate future urban landscapes. \r\n\r\nA second model transformed the population density data into new urban form maps including building footprints. Passed through the 2-D hydrodynamic model CityCAT, a range of future storm events with varying intensities were modelled to capture changes in flow and water depths across the domain. Damages incurred as a result of flood waters were calculated and aggregated to the 1km grid level along with the number of commercial and residential buildings affected. The code for each model in the workflow is available within the OpenCLIM GitHub repository (linked in Related Documents).\r\n\r\nThe Urban Development Model (Newcastle University) presents plausible realisations of future urban change. These are initiated from the 2017 Ordnance Survey urban-rural land use ('UDMbaseline') and projected into the future using attractors and constraints based on the UK's Shared Socio-ecconomic Pathways (SSPs).", "creationDate": "2024-07-03T14:11:12.544657", "lastUpdatedDate": "2024-07-03T14:11:12", "latestDataUpdateTime": "2024-09-11T13:12:49", "updateFrequency": "notPlanned", "dataLineage": "Five cities across GB were modelled using the OpenCLIM_UrbanFlood Workflow. Models in the workflow include the Urban Development Model, which generates new urban form based on projected population / density change, and the CityCAT model, a high resolution, 2-D flood model. The workflow generates maps of urban flood risk for a wide range of future scenarios.", "removedDataReason": "", "keywords": "CityCAT,Urban Flooding,OpenCLIM,Urban Form,Climate Change", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-08-19T15:47:52", "doiPublishedTime": "2024-08-28T12:39:07", "removedDataTime": null, "geographicExtent": { "ob_id": 4569, "bboxName": "", "eastBoundLongitude": 2.0, "westBoundLongitude": -8.0, "southBoundLatitude": 50.0, "northBoundLatitude": 60.0 }, "verticalExtent": null, "result_field": { "ob_id": 43126, "dataPath": "/badc/deposited2024/OpenCLIM_UrbanFlood_Model/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 21107940992, "numberOfFiles": 894, "fileFormat": "Files are BADC-CSV and TIFF formatted" }, "timePeriod": { "ob_id": 11813, "startTime": "2020-01-01T00:00:00", "endTime": "2080-12-03T00:00:00" }, "resultQuality": { "ob_id": 4581, "explanation": "", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2024-07-03" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 43055, "uuid": "56788876eb1a439d9937166ae2c59867", "short_code": "comp", "title": "CityCAT - City Catchment Analysis Tool", "abstract": "The City Catchment Analysis Tool (CityCAT) is a 2-D hydrodynamic flood model, that models complex free-surface flow over a domain, capturing permeable and impermeable surfaces and obstacles to flow such as buildings and other man-made features.\r\n\r\nGlenis, V., Kutija, V., & Kilsby, C. G. (2018). A fully hydrodynamic urban flood modelling system representing buildings, green space and interventions. Environmental Modelling & Software, 109, 272-292. https://doi.org/10.1016/j.envsoft.2018.07.018" }, "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": [ { "ob_id": 41636, "uuid": "0b29cfe8f7194c1280876abf2474b8bf", "short_code": "proj", "title": "Open CLimate IMpacts modelling framework (OpenCLIM)", "abstract": "OpenCLIM, the Open Climate Impacts Modelling framework, is an integrated assessment framework that brings together models to explore potential future impacts of climate change and selected potential adaptation options. Covering hazards such as heat, drought and flooding, and sectors such as biodiversity and agriculture, the framework allows a consistent cross-sectoral approach to exploring adaptation options. Using UKCP18 and down-scaled SSP (Shared Socio-economic Pathways) both future climate and population growth are considered in the analysis. Where possible as well as data outputs and models, much of the framework is open, with it developed and deployed on the DAFNI platform." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 85575, 85576, 85577, 85578, 85579, 85580, 85581, 85582, 85583, 85584, 85585 ], "vocabularyKeywords": [], "identifier_set": [ 13179 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 204506, 204507, 204508, 204509, 204510, 204511, 204513, 204759 ], "onlineresource_set": [ 87857, 87858, 86658, 86661 ] }, { "ob_id": 43056, "uuid": "7c95469ae2b7454cb389fc18ff5ce26b", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the ACTIVE, PASSIVE and COMBINED products, Version 09.1", "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 v09.1 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": "2024-10-16T02:05:17", "updateFrequency": "", "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": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-10-03T15:36:47", "doiPublishedTime": "2024-10-15T10:37:43", "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": 43057, "dataPath": "/neodc/esacci/soil_moisture/data/ancillary/v09.1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1751588, "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": 2577, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 99, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_soilmoisture_terms_and_conditions_v2.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, 63534, 63535, 63536, 75127, 75128, 75129 ], "vocabularyKeywords": [], "identifier_set": [ 13196 ], "observationcollection_set": [ { "ob_id": 41613, "uuid": "779f116d0477439db1874592add5848c", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 09.1 data collection", "abstract": "Soil Moisture data (version 09.1) 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 2023-12-31 and the ACTIVE product covering 1991-08-05 to 2023-12-31. 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": [ 204515, 204516, 204517, 204518, 204519, 204520, 204521, 204522, 204523, 204524, 204525, 204526, 204527, 204528, 204529, 204530, 204531, 204532, 204533, 204535 ], "onlineresource_set": [ 88085, 88086, 88087, 86580, 86581, 86582, 86583, 86584, 86585, 86586 ] }, { "ob_id": 43087, "uuid": "a784eeb9287b43bcb63ccae59e6af82e", "title": "EOCIS: Daily land surface temperature from SLSTR (Sea and Land Surface Temperature Radiometer) on Sentinel 3A, level 3 collated (L3C) global product, version 4.00", "abstract": "This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel 3A. Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.\r\n\r\nDaytime and night-time temperatures are provided in separate files corresponding to the morning and evening Sentinel-3A equator crossing times which are 10:00 and 22:00 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class.\r\n\r\nThe dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. SLSTRA achieves full Earth coverage in 1 day so the daily files have gaps where the surface is not covered by the satellite swath during day or night on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.\r\n\r\nDataset coverage starts on 1st May 2016 and continues until 31st December 2024. There are minor interruptions (1-10 days) during satellite/instrument maintenance periods or instrument anomalies.\r\n\r\nThe dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain.\r\n\r\nThe dataset was produced as part of the UK Earth Observation Climate Information Service (EOCIS) and is based on development funded under ESA CCI with additional funding from NCEO. The EOCIS dataset includes and continues the CCI v4 CDR (currently under development).", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-01-22T09:06:45", "updateFrequency": "notPlanned", "dataLineage": "The data record has been produced by the University of Leicester as part of the UK Earth Observation Climate Information Service (EOCIS) project and is based on development funded under ESA CCI with additional funding from NCEO. 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EOCIS was announced by the government in November 2022, and formally launched in March 2023. It is funded currently until March 2025. \r\n\r\nEOCIS is a collaboration led by the National Centre for Earth Observation, and involving over a dozen research organisations. EOCIS addresses 12 categories of global and regional essential climate variables, which are the following:\r\n- Sea surface temperature\r\n- Ocean reflectance\r\n- Fire occurrence and emissions\r\n- Aerosol and particulate\r\n- Cloud-aerosol-radiation\r\n- Methane\r\n- Land surface temperature\r\n- Water vapour, ozone\r\n- Arctic: ice sheet mass and sea ice\r\n- Eurasia: surface methane\r\n- Africa: soil water balance\r\n- Antarctic: ice sheet mass and ice velocity\r\n\r\nEOCIS is also creating new climate data at high resolution for the UK specifically. This includes both rapid-response information for climate-linked events (fire early warning and urban flood mapping) and longer term climate data linked to human and ecosystem health and landscape greenhouse gas emissions." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 62778, 62779, 62780, 62781, 62790, 62791, 62792, 66303, 66305, 66307, 66308, 66310, 66311, 66312, 66751, 66753, 66754, 75122, 75123, 75124, 75125, 75126 ], "vocabularyKeywords": [], "identifier_set": [ 13228 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 204570, 204571, 204572, 204573, 204574, 204575, 204576, 204577, 206520, 206521, 204578, 204580 ], "onlineresource_set": [ 88245, 88323 ] }, { "ob_id": 43088, "uuid": "fc0bc3d5887d441296091a8025f8f45d", "title": "EOCIS: Daily land Surface Temperature from SLSTR (Sea and Land Surface Temperature Radiometer) on Sentinel 3B, level 3 collated (L3C) global product , version 4.00", "abstract": "This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Sea and Land Surface Temperature Radiometer (SLSTR) on Sentinel 3B. Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.\r\n\r\nDaytime and night-time temperatures are provided in separate files corresponding to the morning and evening Sentinel 3B equator crossing times which are 10:00 and 22:00 local solar time. Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and solar geometry angles, a quality flag, and land cover class.\r\n\r\nThe dataset coverage is global over the land surface. LSTs are provided on a global equal angle grid at a resolution of 0.01° longitude and 0.01° latitude. SLSTRB achieves full Earth coverage in 1 day so the daily files have gaps where the surface is not covered by the satellite swath during day or night on that day. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.\r\n\r\nDataset coverage starts on 17th November 2018 and continues until 31st December 2024. There are minor interruptions (1-10 days) during satellite/instrument maintenance periods or instrument anomalies.\r\n\r\nThe dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain.\r\n\r\nThe dataset was produced as part of the UK Earth Observation Climate Information Service (EOCIS) and is based on development funded under ESA CCI with additional funding from NCEO. The EOCIS dataset includes and continues the CCI v4 CDR (currently under development).", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-01-20T16:47:59", "updateFrequency": "notPlanned", "dataLineage": "The data record has been produced by the University of Leicester as part of the UK Earth Observation Climate Information Service (EOCIS) project and is based on development funded under ESA CCI with additional funding from NCEO. The EOCIS dataset includes and continues the CCI v4 CDR (currently under development).", "removedDataReason": "", "keywords": "land surface temperature, EOCIS, SLSTR", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2025-01-23T11:45:51", "doiPublishedTime": "2025-01-23T12:11:10.025867", "removedDataTime": null, "geographicExtent": { "ob_id": 2896, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 43351, "dataPath": "/neodc/eocis/data/global_and_regional/land_surface_temperature/SENTINEL3B_SLSTR/L3C/0.01/v4.00/daily/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2291469072425, "numberOfFiles": 4395, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 11994, "startTime": "2018-11-17T00:00:00", "endTime": "2024-12-31T23:59:59" }, "resultQuality": { "ob_id": 4634, "explanation": "Data are as provided by the data producer. 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Remote Sensing, 16, 3403. https://doi.org/10.3390/rs16183403" }, "imageDetails": [], "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": 43216, "uuid": "8bffaba46c4a4b8c82e4be2c91c637b9", "short_code": "proj", "title": "Earth Observation Climate Information Service (EOCIS)", "abstract": "The UK Earth Observation Climate Information Service exploits the observations available from environmental sensors orbiting in space to create climate data records and climate information. EOCIS was announced by the government in November 2022, and formally launched in March 2023. It is funded currently until March 2025. \r\n\r\nEOCIS is a collaboration led by the National Centre for Earth Observation, and involving over a dozen research organisations. EOCIS addresses 12 categories of global and regional essential climate variables, which are the following:\r\n- Sea surface temperature\r\n- Ocean reflectance\r\n- Fire occurrence and emissions\r\n- Aerosol and particulate\r\n- Cloud-aerosol-radiation\r\n- Methane\r\n- Land surface temperature\r\n- Water vapour, ozone\r\n- Arctic: ice sheet mass and sea ice\r\n- Eurasia: surface methane\r\n- Africa: soil water balance\r\n- Antarctic: ice sheet mass and ice velocity\r\n\r\nEOCIS is also creating new climate data at high resolution for the UK specifically. This includes both rapid-response information for climate-linked events (fire early warning and urban flood mapping) and longer term climate data linked to human and ecosystem health and landscape greenhouse gas emissions." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 62778, 62779, 62780, 62781, 62790, 62791, 62792, 66303, 66305, 66307, 66308, 66310, 66311, 66312, 66751, 66753, 66754, 75122, 75123, 75124, 75125, 75126 ], "vocabularyKeywords": [], "identifier_set": [ 13227 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 204581, 204582, 204583, 204584, 204585, 204586, 204587, 204588, 206528, 206529, 204589, 204591 ], "onlineresource_set": [ 88246, 88326 ] }, { "ob_id": 43090, "uuid": "bf535053562141c6bb7ad831f5998d77", "title": "ESA Biomass Climate Change Initiative (Biomass_cci): Global datasets of forest above-ground biomass for the years 2010, 2015, 2016, 2017, 2018, 2019, 2020 and 2021, v5.01", "abstract": "This dataset comprises estimates of forest above-ground biomass for the years 2010, 2015, 2016, 2017, 2018, 2019, 2020 and 2021. They are derived from a combination of Earth observation data, depending on the year, from the Copernicus Sentinel-1 mission, Envisat’s ASAR (Advanced Synthetic Aperture Radar) instrument and JAXA’s (Japan Aerospace Exploration Agency) Advanced Land Observing Satellite (ALOS-1 and ALOS-2), along with additional information from Earth observation sources. The data has been produced as part of the European Space Agency's (ESA's) Climate Change Initiative (CCI) programme by the Biomass CCI team. \r\n\r\nThis release of the data is version 5. Compared to version 4, version 5 consists of an update of the three maps of AGB (aboveground biomass) for the years 2010, 2017, 2018, 2019, 2020 and new AGB maps for 2015, 2016 and 2021. New AGB change maps have been created for consecutive years (2015-2016, 2016-2017 and 2020-2021), alongside an update of change maps for years 2010-2020, 2017-2018, 2018-2019 and 2019-2020, and for a decadal interval (2020-2010). The pool of remote sensing data now includes multi-temporal observations at L-band for all biomes and for all years. The AGB maps rely on revised allometries which are now based on a longer record of spaceborne LiDAR data from the GEDI and ICESat-2 missions. Temporal information is now implemented in the retrieval algorithm to preserve biomass dynamics as expressed in the remote sensing data. Biases between 2010 and more recent years have been reduced.\r\n\r\nThe data products consist of two (2) global layers that include estimates of:\r\n1) above ground biomass (AGB, unit: tons/ha i.e., Mg/ha) (raster dataset). This is defined as the mass, expressed as oven-dry weight of the woody parts (stem, bark, branches and twigs) of all living trees excluding stump and roots\r\n2) per-pixel estimates of above-ground biomass uncertainty expressed as the standard deviation in Mg/ha (raster dataset)\r\n\r\nAdditionally provided in this version release are new aggregated data products. These aggregated products of the AGB and AGB change data layers are available at coarser resolutions (1, 10, 25 and 50km).\r\n\r\nIn addition, files describing the AGB change between two consecutive years (i.e., 2015-2016, 2016-2017, 2018-2017, 2019-2018, 2019-2020, 2020-2021) and over a decade (2020-2010) are provided (labelled as 2015_2016, 2016_2017, 2017_2018, 2018_2019, 2019_2020 and 2020_2010). Each AGB change product consists of two sets of maps: the standard deviation of the AGB change and a quality flag of the AGB change. Note that the change itself can be simply computed as the difference between two AGB maps, so is not provided directly.\r\n\r\n\r\nData are provided in both netcdf and geotiff format.\r\n\r\nThis version represents an update of v5.0 which was missing a number of tiles covering islands on the Pacific and Indian Ocean and one tile covering Scandinavia north of 70 deg latitude.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2024-09-11T13:12:55", "updateFrequency": "notPlanned", "dataLineage": "Data was created by the Biomass CCI team.\r\n\r\nThis version represents an update of v5.0 which was missing a number of tiles covering islands on the Pacific and Indian Ocean and one tile covering Scandinavia north of 70 deg latitude.", "removedDataReason": "", "keywords": "ESA, CCI, Biomass", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-07-29T13:22:41", "doiPublishedTime": "2024-08-22T16:15:08", "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": 43092, "dataPath": "/neodc/esacci/biomass/data/agb/maps/v5.01/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 663753419014, "numberOfFiles": 8978, "fileFormat": "Data are netCDF and geotiff formatted." }, "timePeriod": { "ob_id": 11655, "startTime": "2010-01-01T00:00:00", "endTime": "2021-12-31T23:59:59" }, "resultQuality": { "ob_id": 3355, "explanation": "For information on the quality of the data see the documentation and website for the Biomass CCI", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-11-28" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 41622, "uuid": "c5a516b7e8584ebb9c2e46604c580676", "short_code": "cmppr", "title": "CCI Biomass v5.0", "abstract": "CCI Biomass" }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1140, "name": "ESACCI" } ], "permissions": [ { "ob_id": 2542, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 20, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_biomass_terms_and_conditions_v2.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 29954, "uuid": "748552f369494506bc790c8a51854c38", "short_code": "proj", "title": "ESA CCI Biomass Climate Change Initiative (CCI)", "abstract": "The primary science objective ESA’s Climate Change Initiative + Biomass project is to provide global maps of above-ground biomass (Mg ha-1) with these being capable of supporting quantification of biomass change. The mapping aims to achieve 500 m to 1 km spatial resolution with a relative error of less than 20 % where AGB exceeds 50 Mg ha-1. Although this resolution is finer than required for current climate modelling, it will allow more refined information to be inferred (e.g. forest age structure and the disturbance regime) that is relevant for climate and has the potential to be exploited by carbon cycle and climate models as they develop." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6021, 6022, 6023, 66280, 66281, 66282, 66283, 66285, 66286, 66287, 75116, 75117, 75118, 75119, 75120, 75121 ], "vocabularyKeywords": [], "identifier_set": [ 13174 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 204602, 204603, 204604, 204605, 204606, 204607, 204608, 204609, 204610, 204612 ], "onlineresource_set": [ 86650, 86651, 86652, 87931 ] } ] }