Observation List
Get a list of Observation objects.
GET /api/v3/observations/?format=api&offset=3600
{ "count": 10256, "next": "https://api.catalogue.ceda.ac.uk/api/v3/observations/?format=api&limit=100&offset=3700", "previous": "https://api.catalogue.ceda.ac.uk/api/v3/observations/?format=api&limit=100&offset=3500", "results": [ { "ob_id": 19863, "uuid": "dcda86e1d52f44aaafcffb77b47ba1bb", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Jakobshavn Isbrae glacier, 2002-2010, v1.1 (June 2016 release)", "abstract": "This dataset contains a time series of ice velocities for the Jakobshavn Isbrae Glacier in Greenland between 2002-2010, which has been produced as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThis dataset consists of a time series of Ice velocity maps which have been generated from Image Swath mode images from the ASAR instrument on the ENVISAT satellite, with a 35 day repeat cycle. The data are supplied on a 500m polar stereographic grid. \r\n\r\nPlease note - this product was released on the Greenland Ice Sheets download page in June 2016, but an earlier product (also accidentally labelled v1.1) was available through the CCI Open Data Portal and the CEDA archive until 29th November 2016. Please now use the later v1.1 product.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-11-28T16:38:02.790311", "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI Greenland Ice Sheet project team and supplied to CEDA in the context of the ESA CCI Open Data Portal Project.", "removedDataReason": "", "keywords": "Greenland, Ice sheet, CCI, ESA", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2016-11-29T19:10:00", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1650, "bboxName": "Greenland",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": 26824, "dataPath": "/neodc/esacci/ice_sheets_greenland/data/greenland_ice_velocity/greenland_iv_jakobshavn_timeseries/v1.1/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 503986247, "numberOfFiles": 144, "fileFormat": "Data are in NetCDF and GeoTiff format" }, "timePeriod": { "ob_id": 5276, "startTime": "2002-11-10T00:00:00", "endTime": "2010-09-23T22:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "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": [ 12066, 13230, 13232, 50547, 50548, 53928, 63972, 79994 ], "vocabularyKeywords": [ { "ob_id": 10187, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" }, { "ob_id": 10666, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" } ], "identifier_set": [], "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": [ 75497, 76439, 76438, 104935, 105152, 105330, 76437, 75496 ], "onlineresource_set": [ 16031, 16032, 16795, 16033 ] }, { "ob_id": 19864, "uuid": "ec38bfab8ae64c8a8b9a8072c2765b9a", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity Time series for the Upernavik region, 1992-2010, v1.1 (June 2016 release)", "abstract": "This dataset contains a time series of ice velocities for the Upernavik region in Greenland between 1992-2010, and has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe data consists of an ice velocity time series derived from intensity-tracking of ERS-1/2, ASAR and PALSAR data acquired between 02-01-1992 and 22-08-2010. It provides components of the ice velocity and the magnitude of the velocity.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E). The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NOTHING(y) directions of the grid, and the vertical displacement (z), derived from a digital elevation model, is also provided. Please note that the previous versions of this product provided the horizontal velocities as true East and North velocities.\r\n\r\nBoth a single NetCDF file (including all measurements and annotation), and separate geotiff files with the velocity components are provided. The product was generated by GEUS. For further information please see the Product User Guide (v2.0).\r\n\r\nPlease note - this product was released on the Greenland Ice Sheets download page in June 2016, but an earlier product (also accidentally labelled v1.1) was available through the CCI Open Data Portal and the CEDA archive until 29th November 2016. Please now use the later v1.1 product.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-11-28T17:41:38.047720", "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI Greenland Ice Sheet project team and supplied to CEDA in the context of the ESA CCI Open Data Portal Project.", "removedDataReason": "", "keywords": "Greenland, Ice sheet, CCI, ESA", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2016-11-29T19:02:34", "doiPublishedTime": null, "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": 26826, "dataPath": "/neodc/esacci/ice_sheets_greenland/data/greenland_ice_velocity/greenland_iv_upernavik_timeseries/v1.1/", "oldDataPath": [ 20105 ], "storageLocation": "internal", "storageStatus": "online", "volume": 29480144, "numberOfFiles": 256, "fileFormat": "Data are in NetCDF and GeoTiff" }, "timePeriod": { "ob_id": 5275, "startTime": "1992-01-02T00:00:00", "endTime": "2010-08-22T22:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "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": [ 12066, 13204, 13205, 13206, 13207, 18431, 18432, 18433, 50547, 50548, 63972, 79994 ], "vocabularyKeywords": [ { "ob_id": 10187, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" }, { "ob_id": 10666, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" } ], "identifier_set": [], "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": [ 75498, 75499, 76435, 104915, 105131, 105309, 76436, 76434 ], "onlineresource_set": [ 16794, 16036, 16034, 16035 ] }, { "ob_id": 19865, "uuid": "e3a4bd4d857742c2922993722253f52b", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity Time Series of the Hagen Brae for 2015-2016 from Sentinel-1 data, v1.0", "abstract": "This dataset contains a time series of ice velocities for the Hagen Brae glacier in Greenland derived from Sentinel-1 SAR data acquired between 22/1/2015 and 1/6/2016. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-11-29T14:24:53.138528", "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI Greenland Ice Sheet project team and supplied to CEDA in the context of the ESA CCI Open Data Portal Project.", "removedDataReason": "", "keywords": "Greenland, Ice sheet, CCI, ESA", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2017-01-17T17:35:04", "doiPublishedTime": null, "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": 26846, "dataPath": "/neodc/esacci/ice_sheets_greenland/data/greenland_ice_velocity/greenland_iv_250m_s1_hagen/v1.0/", "oldDataPath": [ 20330 ], "storageLocation": "internal", "storageStatus": "online", "volume": 19194756, "numberOfFiles": 5, "fileFormat": "Data files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, "timePeriod": { "ob_id": 5328, "startTime": "2015-01-22T00:00:00", "endTime": "2016-06-01T22:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "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": [ 6023, 12066, 13230, 13232, 50547, 50548, 53927, 53928 ], "vocabularyKeywords": [ { "ob_id": 10187, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" }, { "ob_id": 10212, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/dataType/dtype_iv", "resolvedTerm": "ice sheet velocity" }, { "ob_id": 10619, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/dataType/dtype_iv", "resolvedTerm": "ice sheet velocity" }, { "ob_id": 10666, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" } ], "identifier_set": [], "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": [ 75500, 79017, 79016, 104937, 105154, 105332, 79015, 75501 ], "onlineresource_set": [ 16039, 16041, 16999, 17000, 16040 ] }, { "ob_id": 19866, "uuid": "ea4fefb0e791495fb80d6f571f055a6b", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity Time Series of the Upernavik Isstroem for 2014-2016 from Sentinel-1 data, v1.0", "abstract": "This dataset contains a time series of ice velocities for the Upernavik Isstroem glacier in Greenland, derived from Sentinel-1 SAR data acquired between October 2014 and June 2016. This dataset has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-11-29T14:21:54.870376", "updateFrequency": "notPlanned", "dataLineage": "Data were processed by the ESA CCI Greenland Ice Sheet project team and supplied to CEDA in the context of the ESA CCI Open Data Portal Project.", "removedDataReason": "", "keywords": "Greenland, Ice sheet, CCI, ESA", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2017-01-17T17:16:37", "doiPublishedTime": null, "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": 26836, "dataPath": "/neodc/esacci/ice_sheets_greenland/data/greenland_ice_velocity/greenland_iv_250m_s1_upernavik/v1.0/", "oldDataPath": [ 20328 ], "storageLocation": "internal", "storageStatus": "online", "volume": 101275280, "numberOfFiles": 5, "fileFormat": "Data files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, "timePeriod": { "ob_id": 5326, "startTime": "2014-10-09T23:00:00", "endTime": "2016-06-02T22:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "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": [ 6023, 12066, 13230, 13232, 50547, 50548, 53927, 53928 ], "vocabularyKeywords": [ { "ob_id": 10187, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" }, { "ob_id": 10212, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/dataType/dtype_iv", "resolvedTerm": "ice sheet velocity" }, { "ob_id": 10619, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/dataType/dtype_iv", "resolvedTerm": "ice sheet velocity" }, { "ob_id": 10666, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" } ], "identifier_set": [], "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": [ 75503, 75502, 79011, 79010, 104939, 105156, 105334, 79009 ], "onlineresource_set": [ 16048, 16046, 16995, 16996, 16047 ] }, { "ob_id": 19868, "uuid": "82e4ede59fe746ba810009d9a30e0153", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Ice Velocity Map Winter 2014-2015, v1.0", "abstract": "This dataset provides an ice velocity map for the whole Greenland ice-sheet for the winter of 2014-2015, derived from Sentinel-1 SAR data, as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E). The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid; the vertical displacement (z), derived from a digital elevation model, is also provided. 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The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid; the vertical displacement (z), derived from a digital elevation model, is also provided. 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It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. \r\n\r\nThis dataset consists of a time series of ice velocity with yearly sampling, derived from intensity tracking of PALSAR data acquired between 20-12-2016 and 17-03-2011. It provides components of the ice velocity and the magnitude of the velocity.\r\n\r\n The data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E). The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid; the vertical displacement (z), derived from a digital elevation model, is also provided. Please note that the previous versions of this product provided the horizontal velocities as true East and North velocities.\r\n\r\nBoth a single NetCDF file (including all measurements and annotation), and separate geotiff files with the velocity components are provided. The product was generated by GEUS. For further details, please consult the Product User Guide (v2.0)\r\n\r\nPlease note - this product was released on the Greenland Ice Sheets download page in June 2016, but an earlier product (also accidentally labelled v1.1) was available through the CCI Open Data Portal and the CEDA archive until 29th November 2016. Please now use the later v1.1 product.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-11-29T18:12:46.672938", "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI Greenland Ice Sheet project team and supplied to CEDA in the context of the ESA CCI Open Data Portal Project.", "removedDataReason": "", "keywords": "Greenland, Ice sheet, CCI, ESA", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2016-11-29T18:29:54", "doiPublishedTime": null, "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": 20104, "dataPath": "/neodc/esacci/ice_sheets_greenland/data/greenland_ice_velocity/greenland_margin_PALSAR_timeseries_2006_2011/v1.1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 98358325, "numberOfFiles": 19, "fileFormat": "Data are in NetCDF and GeoTiff format" }, "timePeriod": { "ob_id": 5271, "startTime": "2006-12-20T00:00:00", "endTime": "2011-03-17T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "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. 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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": [ 6023, 11952, 11953, 12066, 13204, 13205, 13206, 13207, 13228, 18431, 18432, 18433 ], "vocabularyKeywords": [ { "ob_id": 10666, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" }, { "ob_id": 10187, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" }, { "ob_id": 11111, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_palsar", "resolvedTerm": "PALSAR" }, { "ob_id": 10783, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_alos", "resolvedTerm": "ALOS" } ], "identifier_set": [], "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. 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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": [ 75516, 75517, 104938, 105155, 105333, 76443, 76442, 76441 ], "onlineresource_set": [ 16081, 16080, 16079, 16789, 26087 ] }, { "ob_id": 19878, "uuid": "0b23b3c771db4fff8958196432d978cb", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity data for the Greenland Margin from ERS-2 for winter 1995-1996, v1.1 (June 2016 release)", "abstract": "This dataset contains ice velocities for the Greenland margin for winter 1995-1996, which have been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. The data were derived from intensity-tracking of ERS-2 data acquired between 03-09-1995 and 29-03-1996. It provides components of the ice velocity and the magnitude of the velocity.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E). The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid; the vertical displacement (z), derived from a digital elevation model, is also provided. Please note that previous versions of this product provided the horizontal velocities as true East and North velocities.\r\n\r\nBoth a single NetCDF file (including all measurements and annotation), and separate geotiff files with the velocity components are provided. The product was generated by DTU Space - Microwaves and Remote Sensing. For further information please see the product user guide.\r\n\r\nPlease note - this product was released on the Greenland Ice Sheets download page in June 2016, but an earlier product (also accidentally labelled v1.1) was available through the CCI Open Data Portal and the CEDA archive until 29th November 2016. Please now use the later v1.1 product.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T13:14:10", "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI Greenland Ice Sheet project team and supplied to CEDA in the context of the ESA CCI Open Data Portal Project.", "removedDataReason": "", "keywords": "Greenland, Ice sheet, CCI, ESA", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2016-11-29T19:06:26", "doiPublishedTime": null, "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": 20106, "dataPath": "/neodc/esacci/ice_sheets_greenland/data/greenland_ice_velocity/greenland_margin_ERS2_1995_1996/v1.1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 69038097, "numberOfFiles": 8, "fileFormat": "Data are in NetCDF and GeoTiff format" }, "timePeriod": { "ob_id": 5270, "startTime": "1995-09-02T23:00:00", "endTime": "1996-03-29T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "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": [ 6023, 12066, 13204, 13205, 13206, 13207, 18431, 18432, 18433, 50547, 50548, 53927 ], "vocabularyKeywords": [ { "ob_id": 10666, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" }, { "ob_id": 10187, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" }, { "ob_id": 11047, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_amisar", "resolvedTerm": "AMI-SAR" }, { "ob_id": 10810, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_ers2", "resolvedTerm": "ERS-2" } ], "identifier_set": [], "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. 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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": [ 75518, 75519, 104949, 105167, 105345, 76430, 76429, 76428 ], "onlineresource_set": [ 16084, 16083, 16082, 16788, 26086 ] }, { "ob_id": 19879, "uuid": "2d0422ea3c4047d5829d5fbdabe0c156", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Gravimetric Mass Balance Gridded product, v1.1", "abstract": "This dataset provides gridded Gravimetric Mass Balance data for the Antarctic Ice Sheet. It has been produced in the framework of the Antarctic Ice Sheets Climate Change Initiative (CCI) project, under the lead of TU Dresden. \r\n\r\nThe ice sheet mass balance, i.e. the change in ice mass over time, is determined using the US-German satellite gravimetry mission GRACE (Gravity Recovery and Climate Experiment). The Antarctic Ice Sheet CCI GMB products are based on the monthly GRACE solutions ITSG-Grace2016 by Technische Universität Graz, and comprises a time series of mass change grids covering the entire ice sheet (GMB Gridded product), along side mass change time series for different drainage basins (GMB Basin Product). \r\n\r\nThe dataset described here covers version 1.1 of the Gridded product. Time series of gridded mass changes are provided in a polar-stereographic projection (EPSG:3031) with a grid resolution of 50 km x 50 km. The gridded changes are given in millimetre of equivalent water height (mm w.eq., or kg/m2). \r\n\r\nIf publishing results based on this dataset, please cite the following: Groh, A., & Horwath, M. (2016). The method of tailored sensitivity kernels for GRACE mass change estimates. Geophysical Research Abstracts, 18, EGU2016-12065\r\n\r\nInteractive data visualisation is available at: https://data1.geo.tu-dresden.de/ais_gmb/", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2017-06-05T16:33:43.078746", "updateFrequency": "notPlanned", "dataLineage": "Data were produced by TU Dresden in the context of the ESA CCI Antarctic Ice Sheet project team and are archived on https://data1.geo.tu-dresden.de/ais_gmb/. They have been supplied to CEDA in the context of the ESA CCI Open Data Portal Project.", "removedDataReason": "", "keywords": "Antarctic, Ice sheet, CCI, ESA", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2016-11-24T00:00:00", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1742, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": -62.0 }, "verticalExtent": null, "result_field": { "ob_id": 24696, "dataPath": "/neodc/esacci/ice_sheets_antarctica/data/gravimetric_mass_balance/gridded/v1.1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 34486436, "numberOfFiles": 4, "fileFormat": "Data are provided in netCDF, Ascii and GeoTiff formats" }, "timePeriod": { "ob_id": 6697, "startTime": "2002-07-31T23:00:00", "endTime": "2016-07-31T22:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2534, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 14, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_icesheets_antarctic_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 24700, "uuid": "fda6ad697b2c49f7882f70f954c44f92", "short_code": "proj", "title": "ESA Antarctic Ice Sheet Climate Change Initiative Project", "abstract": "The European Space Agency (ESA) Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci) project is part of ESA's Climate Change Initiative (CCI) programme to produce long term datasets of Essential Climate Variables (ECV's) derived from global satellite data.\r\n\r\nThe Antarctic Ice Sheet CCI aims to produce long term and reliable climate satellite data records required by the scientific user community. These datasets will improve understanding of present day change on the Antarctic Ice Sheet and provide data for models at a higher spatial and temporal resolution than is currently available, thereby improving estimates of future change. It is focusing on providing datasets of surface elevation changes, ice velocities, gravimetric mass balance and grounding line locations." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 12066, 52192, 52193, 67713, 67722, 67724, 67725, 67726, 67727 ], "vocabularyKeywords": [ { "ob_id": 10363, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/dataType/dtype_gmb", "resolvedTerm": "gravimetric mass balance" }, { "ob_id": 10617, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/dataType/dtype_gmb", "resolvedTerm": "gravimetric mass balance" }, { "ob_id": 10187, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" }, { "ob_id": 10666, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 24699, "uuid": "81fb84c4b00640b7a3acb58346497977", "short_code": "coll", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci) Dataset Collection", "abstract": "Collection of datasets from the European Space Agency's (ESA) Antarctic Ice Sheets Climate Change Initiative (CCI) project. This is producing long term and reliable climate data records from satellite data for a number of Essential Climate Variables (ECV's) for Antarctica. \r\n\r\nCurrent data products relate to Ice Velocities, Gravimetric Mass Balance, Grounding Line Locations and Surface Elevation Changes." } ], "responsiblepartyinfo_set": [ 101115, 101116, 101119, 105163, 105341, 101114, 111517, 111518, 101113, 101117, 101118 ], "onlineresource_set": [ 23262, 23263, 23271, 23253, 16085, 16086, 23264, 23265, 16087 ] }, { "ob_id": 19880, "uuid": "76ad6afa787d4c469122f0b472a988c0", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global ocean colour data products gridded on a sinusoidal projection (All Products), Version 2.0.", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 2.0 generated ocean colour products on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). \r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. 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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. 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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": [ 75542, 75543, 75544, 75545, 76553, 104951, 105169, 105347, 75546, 76579, 76605, 76631, 76657, 76683, 76709, 76735, 76761, 76787, 76813, 76839, 76865, 76891, 76917, 76943, 76969, 76995, 77021, 77047, 77073, 77099, 77125, 77151, 77177, 77203, 77229, 77255, 77281, 77307, 77333, 77359, 77385, 77411, 77437, 77463, 77489, 77515, 77541, 77567, 77593, 77619, 77645, 77671, 77697, 77723, 77749, 77775, 77801, 77827, 77853, 77879, 77905, 77931, 77957, 77983, 78009, 78035, 78061, 78087, 78113, 78139, 78165, 78191, 78217, 78243, 78269 ], "onlineresource_set": [ 16104, 16105, 16107, 16106, 16724 ] }, { "ob_id": 19884, "uuid": "b548475d0a5d4a2b8de40e7b1fa40d7a", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a sinusoidal projection, Version 2.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 2.0 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). 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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. 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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": [ 75567, 75569, 75565, 75566, 76551, 104945, 105162, 105340, 75570, 76577, 76603, 76629, 76655, 76681, 76707, 76733, 76759, 76785, 76811, 76837, 76863, 76889, 76915, 76941, 76967, 76993, 77019, 77045, 77071, 77097, 77123, 77149, 77175, 77201, 77227, 77253, 77279, 77305, 77331, 77357, 77383, 77409, 77435, 77461, 77487, 77513, 77539, 77565, 77591, 77617, 77643, 77669, 77695, 77721, 77747, 77773, 77799, 77825, 77851, 77877, 77903, 77929, 77955, 77981, 78007, 78033, 78059, 78085, 78111, 78137, 78163, 78189, 78215, 78241, 78267 ], "onlineresource_set": [ 16134, 16728, 16133, 16131, 16132 ] }, { "ob_id": 19888, "uuid": "a2cd1cefc5b84b86bbaa09bb3832e497", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global dataset of inherent optical properties (IOP) gridded on a geographic projection, Version 2.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 2.0 inherent optical properties (IOP) product (in mg/m3) on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). 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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. 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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. 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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. 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The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490 nm. Information on uncertainties is also provided.\r\n\r\nThis dataset collection currently holds Version 1.0 data products, and later versions will be added in the future. Note, version 2.0 data products are now currently available directly from the Ocean Colour CCI team (see link in the documentation section)." }, { "ob_id": 20073, "uuid": "58268d53f02942fd9951bee50360b893", "short_code": "coll", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 2.0 Data", "abstract": "A collection of Version 2.0 datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI). The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490 nm. Information on uncertainties is also provided.\r\n\r\nThis dataset collection refers to the Version 2.0 data products held in the CEDA archive and available from ftp://anon-ftp.ceda.ac.uk/neodc/esacci/ocean_colour/data/v2-release . Links to the individual datasets that make up this collection are given in the record below. \r\n\r\nPlease note, this dataset has been superseded. Later version of the data are now available." }, { "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": [ 75596, 75597, 75598, 75599, 76558, 104964, 105188, 105364, 75600, 76584, 76610, 76636, 76662, 76688, 76714, 76740, 76766, 76792, 76818, 76844, 76870, 76896, 76922, 76948, 76974, 77000, 77026, 77052, 77078, 77104, 77130, 77156, 77182, 77208, 77234, 77260, 77286, 77312, 77338, 77364, 77390, 77416, 77442, 77468, 77494, 77520, 77546, 77572, 77598, 77624, 77650, 77676, 77702, 77728, 77754, 77780, 77806, 77832, 77858, 77884, 77910, 77936, 77962, 77988, 78014, 78040, 78066, 78092, 78118, 78144, 78170, 78196, 78222, 78248, 78274 ], "onlineresource_set": [ 16162, 16731, 16163, 16165, 16164 ] }, { "ob_id": 19893, "uuid": "49c2f1e23e6b4d7c8339bb1cf3bce2a2", "title": "__MUST_UPDATE__20160816091254__ Alouette I and Alouette II data", "abstract": "The Alouette I and II spacecraft mark Canada's first space program. 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We have three sets of ionospheric sounder data, each being specific to a certain location over the Earth. \r\nOver the solant, from 1962-10-12 to 1964-02-04. \r\nOver Woomera, from 1962-10-19 to 1964-12-11. \r\n\r\nAlouette II datum from the ionospheric sounder is available from 1967-03-21 to 1967-08-10. 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The purpose of Alouette 1 was to investigate the properties of the top of the ionosphere, and the dependence of those properties on geographical location, season, and time of day.\r\n\r\nAlouette 2 was a Canadian research satellite launched at 04:48 UTC on November 29, 1965 by a Thor Agena rocket with Explorer 31 from the Western test range at Vandenberg AFB in California. The Alouette 2 was built up from the identical backup satellite to Alouette 1. It had many more experiments and more sophisticated support systems than the earlier satellite. It lasted for 10 years, being terminated on August 1, 1975." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 75623, 75624, 75617, 75618, 75619, 75620, 75621, 75622 ], "onlineresource_set": [] }, { "ob_id": 19911, "uuid": "3c6d22dad7fb44dea4223319d2c37351", "title": "MEdium Resolution Imaging Spectrometer (MERIS): Level 1B reprocessed radiance product, Version 3", "abstract": "The Medium Resolution Imaging Spectrometer (MERIS) is one of the ten instruments on board the Envisat satellite launched on the 28th of February 2002 from Kourou (French Guyana) and operated by the European Space Agency (ESA). MERIS is a 68.5 deg field-of-view nadir-pointing imaging spectrometer which measures the solar radiation reflected by the Earth in 15 spectral bands (visible and near-infrared). It obtains a global coverage of the Earth in 3 days. Its main objective is to measure the sea colour and quantify the ocean chlorophyll content and sediment, thus providing information on the ocean carbon cycle and thermal regime. It is also used to derive the cloud top height, cloud optical thickness, aerosol and water vapour column. The ground spatial resolution of the instrument is 260 m x 290 m. Only reduced resolution data (1.04 km x 1.16 km) are archived at the NEODC.\r\n\r\nThis dataset contains version 3, Level 1B reprocessed radiances MERIS product.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2024-09-11T13:13:00", "updateFrequency": "notPlanned", "dataLineage": "Data acquired directly from European Space Agency (ESA) via a number of routes: File Transfer Protocol (FTP), Linear Tape-Open (LTO) tape transfer and Data Dissemination Service (DDS) link.", "removedDataReason": "", "keywords": "MERIS, Global Radiances, Sea Colour, Ocean Chlorophyll Content, Sediment, Cloud Parameters", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2024-03-21T10:15:46", "doiPublishedTime": null, "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": 19912, "dataPath": "/neodc/meris/data/l1b/reprocessing_v3", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 20561936133481, "numberOfFiles": 51873, "fileFormat": "Data are Envisat PDS formatted." }, "timePeriod": { "ob_id": 2381, "startTime": "2002-03-01T00:00:00", "endTime": "2012-04-08T22:59:59" }, "resultQuality": { "ob_id": 2211, "explanation": "Operational data", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-08-12" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 19916, "uuid": "14fcc49330334cb59f947afd24686e17", "short_code": "cmppr", "title": "Level 1B reprocessed radiance product, Version 3", "abstract": "This process is comprised of multiple procedures: 1. Acquisition: Acquisition Process for: Data from Envisat - MERIS at Envisat for the MEdium Resolution Imaging Spectrometer (MERIS) Project; \r\n2. Computation: deployed on Envisat; \r\n" }, "imageDetails": [ 115 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2554, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "meris", "label": "restricted: meris group", "licence": { "ob_id": 26, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/meris.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" }, { "ob_id": 7, "classification": "specific" }, { "ob_id": 4, "classification": "academic" } ] } } ], "projects": [ { "ob_id": 8341, "uuid": "07f1e9f7ff781cc38ed6b3c1555050ef", "short_code": "proj", "title": "MEdium Resolution Imaging Spectrometer (MERIS)", "abstract": "The Medium Resolution Imaging Spectrometer (MERIS) is one of the ten instruments on board the Envisat satellite launched on the 28th of February 2002 from Kourou (French Guyana) and operated by the European Space Agency (ESA). MERIS is a 68.5 deg field-of-view nadir-pointing imaging spectrometer which measures the solar radiation reflected by the Earth in 15 spectral bands (visible and near-infrared). It obtains a global coverage of the Earth in 3 days. Its main objective is to measure the sea colour and quantify the ocean chlorophyll content and sediment, thus providing information on the ocean carbon cycle and thermal regime. It is also used to derive the cloud top height, cloud optical thickness, aerosol and water vapour column. The ground spatial resolution of the instrument is 260 m x 290 m. Only reduced resolution data (1.04 km x 1.16 km) are archived at the NEODC." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 22345, 22346, 23084, 23420, 25397, 25844, 25845, 25846, 25853, 25855, 25879, 25885, 25902, 25913, 25922, 25930, 25936, 25983, 25985, 25994, 26107, 26117, 26118, 26119, 26120, 26121, 26122, 26123 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 8338, "uuid": "f26559a9daeae9e6740811d3b3113716", "short_code": "coll", "title": "MEdium Resolution Imaging Spectrometer (MERIS) on-board the European Space Agency (ESA) Envisat Satellite: Global Radiances, Sea Colour, Ocean Chlorophyll Content, Sediment and Cloud Parameters", "abstract": "The Medium Resolution Imaging Spectrometer (MERIS) is one of the ten instruments on board the Envisat satellite launched on the 28th of February 2002 from Kourou (French Guyana) and operated by the European Space Agency (ESA). MERIS is a 68.5 deg field-of-view nadir-pointing imaging spectrometer which measures the solar radiation reflected by the Earth in 15 spectral bands (visible and near-infrared). It obtains a global coverage of the Earth in 3 days. Its main objective is to measure the sea colour and quantify the ocean chlorophyll content and sediment, thus providing information on the ocean carbon cycle and thermal regime. It is also used to derive the cloud top height, cloud optical thickness, aerosol and water vapour column. The ground spatial resolution of the instrument is 260 m x 290 m. Only reduced resolution data (1.04 km x 1.16 km) are archived at the NEODC. \r\n\r\nThis dataset collection contains Level 1B radiances and Level 2 retrieved parameters products from 2002-2012." }, { "ob_id": 30129, "uuid": "3b0630c7fa264164868d4da5c9f90bed", "short_code": "coll", "title": "National Centre for Earth Observation (NCEO) Third Party Data", "abstract": "The National Centre for Earth Observation (NCEO) Third Party data contains a broad range remotely sensed data acquired by satellite for use by the Earth Observation Scientific community supported by NCEO. The Centre for Environmental Data Analysis (CEDA) has archived and provides access to extensive Earth observation datasets under strict licensing conditions. Please see the individual dataset records for conditions of use." } ], "responsiblepartyinfo_set": [ 75697, 75698, 75696, 75691, 75692, 75694, 75695, 75693 ], "onlineresource_set": [ 16178 ] }, { "ob_id": 19918, "uuid": "3fa1bf857a2b41c49284037c859b549d", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): ERS-2/ GOME Level 3 Tropospheric Tropical Ozone 1995-2011 V2.0", "abstract": "This dataset is a gridded 320x40km2 product with a temporal resolution of 3 days across the equator. \r\n\r\nThe data is calculated on a convective cloud differential (CCD) algorithm and averaged whereby only the position of the central coordinate is considered. \r\nThe tropospheric column can then be calculated by the difference between the stratospheric column and the total column. The stratospheric column being estimated as above the high reaching convective clouds (cloud cover >0.8 and >8km in height). To reduce the error above the clouds from up draught of tropospheric pollution a clean reference region 70°E to 170°W representitive of the latitude band. \r\n\r\nFor the Total column only cloud free observations are considered (<10%). This method assumes the stratospheric ozone is constant throughout each month and for one latitude band limit the CCD algorithm to the tropics (20°S to 20°N).", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": null, "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI Ozone project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "ESA, Ozone, CCI", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": null, "timePeriod": { "ob_id": 5226, "startTime": "1995-01-01T00:00:00", "endTime": "2011-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 2749, "uuid": "8f94a3a46f61435e8c247dfe2b92c580", "short_code": "acq", "title": "Acquisition Process for: Data from Global Ozone Monitoring Experiment (GOME) at European Remote Sensing satellite 2 (ERS-2) for the European Space Agency (ESA)", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Global Ozone Monitoring Experiment (GOME); PLATFORMS: European Remote Sensing satellite 2 (ERS-2); " }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 95 ], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 14147, "uuid": "10b36f5715274b1d985c569501ceed68", "short_code": "proj", "title": "ESA Ozone Climate Change Initiative Project", "abstract": "The European Space Agency Ozone Climate Change Initiative (Ozone CCI) project is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs). \r\nOzone_cci aims at generating new high-quality satellite data sets that are essential to assess the fate of atmospheric ozone and better understand its link with anthropogenic activities." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 30129, "uuid": "3b0630c7fa264164868d4da5c9f90bed", "short_code": "coll", "title": "National Centre for Earth Observation (NCEO) Third Party Data", "abstract": "The National Centre for Earth Observation (NCEO) Third Party data contains a broad range remotely sensed data acquired by satellite for use by the Earth Observation Scientific community supported by NCEO. The Centre for Environmental Data Analysis (CEDA) has archived and provides access to extensive Earth observation datasets under strict licensing conditions. Please see the individual dataset records for conditions of use." } ], "responsiblepartyinfo_set": [ 75701, 75700, 75702, 75705, 141969, 141970, 141971, 75704, 75703 ], "onlineresource_set": [ 16181, 16183, 16180, 16182 ] }, { "ob_id": 19919, "uuid": "2dabd18dc23c4e89ab615172f34fb1b9", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): ENVISAT/ SCIAMACHY Level 3 Tropospheric Tropical Ozone 2002-2012 V2.0", "abstract": "This dataset is a gridded 60x30km2 product with a temporal resolution of 6 days across the equator. \r\n\r\nThe data is calculated on a convective cloud differential (CCD) algorithm and averaged whereby only the position of the central coordinate is considered. \r\nThe tropospheric column can then be calculated by the difference between the stratospheric column and the total column. The stratospheric column being estimated as above the high reaching convective clouds (cloud cover >0.8 and >8km in height). To reduce the error above the clouds from up draught of tropospheric pollution a clean reference region 70°E to 170°W representitive of the latitude band. \r\n\r\nFor the Total column only cloud free observations are considered (<10%). This method assumes the stratospheric ozone is constant throughout each month and for one latitude band limit the CCD algorithm to the tropics (20°S to 20°N).\r\n\r\nSCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY) is\r\na multi-channel UV-Vis-NIR spectrometer launched on the ENVISAT platform in 2002. Its\r\nprimary mission objective is the global monitoring of trace gases in the troposphere and in the\r\nstratosphere. The solar radiation transmitted, backscattered and reflected from the atmosphere is\r\nrecorded at medium resolution (0.2 nm to 1.5 nm) over the range 240 nm to 1700 nm, and in\r\nselected regions between 2.0 µm and 2.4 µm. SCIAMACHY is particular since it has three\r\ndifferent viewing geometries: nadir, limb, and sun/moon occultation, which yield total column\r\nvalues as well as distribution profiles in the stratosphere and upper troposphere. In this project\r\nboth nadir and limb measurements are used in Channels 1, 2 and 3. In nadir view, used for ozone\r\ntotal column and vertical profile retrievals, the ground pixel size for channels 2-3 is 30x60 km2\r\ni.e. a resolution intermediate between GOME and OMI. The swath width of SCIAMACHY at\r\nnadir is similar to GOME (960 km), however due to the alternate nadir and limb mode operation,\r\nglobal coverage is only obtained in approximately 6 days. In limb view, ozone number density\r\nprofiles are derived in the stratosphere by exploiting the Hartley and Chappuis spectral\r\nabsorption bands in channels 1 and 3. SCIAMACHY data are available from July 2002 till April\r\n2012 when communication with ENVISAT was lost.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": null, "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI Ozone project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "ESA, Ozone, CCI", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": null, "timePeriod": { "ob_id": 5227, "startTime": "2002-01-01T00:00:00", "endTime": "2012-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 8036, "uuid": "fa6a8b1a91cf4a4cb78ac3aa64fd2659", "short_code": "acq", "title": "Acquisition Process for: SCIAMACHY Level 2 vertical columns of trace gases products", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Envisat - SCIAMACHY; PLATFORMS: Envisat; " }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 95 ], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 14147, "uuid": "10b36f5715274b1d985c569501ceed68", "short_code": "proj", "title": "ESA Ozone Climate Change Initiative Project", "abstract": "The European Space Agency Ozone Climate Change Initiative (Ozone CCI) project is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs). \r\nOzone_cci aims at generating new high-quality satellite data sets that are essential to assess the fate of atmospheric ozone and better understand its link with anthropogenic activities." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 75708, 75706, 75707, 75711, 141978, 141979, 141980, 75710, 75709 ], "onlineresource_set": [ 16186, 16185, 16187, 16184 ] }, { "ob_id": 19920, "uuid": "f534a463b0d24b14ad7e5f8fe649c66c", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): METOP-A/GOME-A Level 3 Tropospheric Tropical Ozone 2007-2014 V2.0", "abstract": "This dataset is a gridded 80x40km2 product with a temporal resolution of daily across the equator. \r\n\r\nThe data is calculated on a convective cloud differential (CCD) algorithm and averaged whereby only the position of the central coordinate is considered. \r\nThe tropospheric column can then be calculated by the difference between the stratospheric column and the total column. The stratospheric column being estimated as above the high reaching convective clouds (cloud cover >0.8 and >8km in height). To reduce the error above the clouds from up draught of tropospheric pollution a clean reference region 70°E to 170°W representitive of the latitude band. \r\n\r\nFor the Total column only cloud free observations are considered (<10%). This method assumes the stratospheric ozone is constant throughout each month and for one latitude band limit the CCD algorithm to the tropics (20°S to 20°N).\r\n\r\nGOME-2 is on-board the EUMETSAT satellite MetOp-A which was launched in October 2006.\r\nBuild on a design almost identical to GOME, it covers the same spectral range as its predecessor\r\nbut with an improved spatial resolution. The nominal ground-pixel size is 80 x 40 km2 with a\r\nglobal coverage in almost one day (swath of 1920 km). GOME-2 continues the measurement\r\nseries started with GOME, and in this project it is therefore used to retrieve total columns and\r\nvertical distributions of ozone. Data are available since January 2007 on an operational basis. A\r\nsecond GOME-2 instrument has been launched in 2012 on the METOP-B platform, and a third\r\none will be launched at the end of the decade on METOP-C.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": null, "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI Ozone project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "ESA, Ozone, CCI", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": null, "timePeriod": { "ob_id": 5228, "startTime": "2007-01-01T00:00:00", "endTime": "2014-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 8210, "uuid": "eec8d2e5b2f14fd7b69e8f209b23ac4a", "short_code": "acq", "title": "Acquisition Process for: Data from GOME-2 at Metop-A for the Eumetsat Polar System Project", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: GOME-2; PLATFORMS: Metop-A; " }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 95 ], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 14147, "uuid": "10b36f5715274b1d985c569501ceed68", "short_code": "proj", "title": "ESA Ozone Climate Change Initiative Project", "abstract": "The European Space Agency Ozone Climate Change Initiative (Ozone CCI) project is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs). \r\nOzone_cci aims at generating new high-quality satellite data sets that are essential to assess the fate of atmospheric ozone and better understand its link with anthropogenic activities." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 30129, "uuid": "3b0630c7fa264164868d4da5c9f90bed", "short_code": "coll", "title": "National Centre for Earth Observation (NCEO) Third Party Data", "abstract": "The National Centre for Earth Observation (NCEO) Third Party data contains a broad range remotely sensed data acquired by satellite for use by the Earth Observation Scientific community supported by NCEO. The Centre for Environmental Data Analysis (CEDA) has archived and provides access to extensive Earth observation datasets under strict licensing conditions. Please see the individual dataset records for conditions of use." } ], "responsiblepartyinfo_set": [ 75713, 75714, 75712, 75717, 141972, 141973, 141974, 75716, 75715 ], "onlineresource_set": [ 16190, 16191, 16189, 16188 ] }, { "ob_id": 19923, "uuid": "a1bcaef6eeec446b9226479c9e8e2948", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): METOP-A/GOME-A Level 3 Tropospheric Tropical Ozone 2013-2014 V2.0", "abstract": "This dataset is a gridded 80x40km2 product with a temporal resolution of daily across the equator. \r\n\r\nThe data is calculated on a convective cloud differential (CCD) algorithm and averaged whereby only the position of the central coordinate is considered. \r\nThe tropospheric column can then be calculated by the difference between the stratospheric column and the total column. The stratospheric column being estimated as above the high reaching convective clouds (cloud cover >0.8 and >8km in height). To reduce the error above the clouds from up draught of tropospheric pollution a clean reference region 70°E to 170°W representitive of the latitude band. \r\n\r\nFor the Total column only cloud free observations are considered (<10%). This method assumes the stratospheric ozone is constant throughout each month and for one latitude band limit the CCD algorithm to the tropics (20°S to 20°N).\r\n\r\nGOME-2 is on-board the EUMETSAT satellite MetOp-A which was launched in October 2006.\r\nBuild on a design almost identical to GOME, it covers the same spectral range as its predecessor\r\nbut with an improved spatial resolution. The nominal ground-pixel size is 80 x 40 km2 with a\r\nglobal coverage in almost one day (swath of 1920 km). GOME-2 continues the measurement\r\nseries started with GOME, and in this project it is therefore used to retrieve total columns and\r\nvertical distributions of ozone. Data are available since January 2007 on an operational basis. A\r\nsecond GOME-2 instrument has been launched in 2012 on the METOP-B platform, and a third\r\none will be launched at the end of the decade on METOP-C.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": null, "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI Ozone project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "ESA, Ozone, CCI", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": null, "timePeriod": { "ob_id": 5228, "startTime": "2007-01-01T00:00:00", "endTime": "2014-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 8210, "uuid": "eec8d2e5b2f14fd7b69e8f209b23ac4a", "short_code": "acq", "title": "Acquisition Process for: Data from GOME-2 at Metop-A for the Eumetsat Polar System Project", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: GOME-2; PLATFORMS: Metop-A; " }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 95 ], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 14147, "uuid": "10b36f5715274b1d985c569501ceed68", "short_code": "proj", "title": "ESA Ozone Climate Change Initiative Project", "abstract": "The European Space Agency Ozone Climate Change Initiative (Ozone CCI) project is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs). \r\nOzone_cci aims at generating new high-quality satellite data sets that are essential to assess the fate of atmospheric ozone and better understand its link with anthropogenic activities." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 30129, "uuid": "3b0630c7fa264164868d4da5c9f90bed", "short_code": "coll", "title": "National Centre for Earth Observation (NCEO) Third Party Data", "abstract": "The National Centre for Earth Observation (NCEO) Third Party data contains a broad range remotely sensed data acquired by satellite for use by the Earth Observation Scientific community supported by NCEO. The Centre for Environmental Data Analysis (CEDA) has archived and provides access to extensive Earth observation datasets under strict licensing conditions. Please see the individual dataset records for conditions of use." } ], "responsiblepartyinfo_set": [ 75737, 75740, 75735, 75736, 141975, 141976, 141977, 75739, 75738 ], "onlineresource_set": [ 16193, 16192, 16194, 16195 ] }, { "ob_id": 19924, "uuid": "897b63a5f0244523b3d41461d4422886", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): AURA/OMI Level 3 Tropospheric Tropical Ozone 2004-2014 V2.0", "abstract": "The data is calculated on a convective cloud differential (CCD) algorithm and averaged whereby only the position of the central coordinate is considered. \r\nThe tropospheric column can then be calculated by the difference between the stratospheric column and the total column. The stratospheric column being estimated as above the high reaching convective clouds (cloud cover >0.8 and >8km in height). To reduce the error above the clouds from up draught of tropospheric pollution a clean reference region 70°E to 170°W representitive of the latitude band. \r\n\r\nFor the Total column only cloud free observations are considered (<10%). This method assumes the stratospheric ozone is constant throughout each month and for one latitude band limit the CCD algorithm to the tropics (20°S to 20°N).\r\n\r\nThe Ozone Monitoring Instrument (OMI) is a nadir viewing imaging spectrograph that measures\r\nthe solar radiation backscattered by the Earth's atmosphere and surface over the entire\r\nwavelength range from 270 to 500 nm with a spectral resolution of about 0.5 nm. OMI was\r\nlaunched on-board the NASA satellite AURA in July 2004. In comparison to the GOME and\r\nSCIAMACHY sensors, OMI is characterized by a larger swath width of 2600 km, which enables\r\nmeasurements with a daily global coverage at all latitudes. The nominal OMI pixel size of 13 × \r\n6 Product Specification Document\r\nIssue: 4.6 – Date of issue: 3/11/2015\r\nReference: Ozone_cci_ PSD_4.6\r\nPage 8 of 45\r\n24 km2 at nadir is also significantly smaller. The small pixel size enables OMI to look in between\r\nthe clouds, which is important for retrieving tropospheric information. The light entering the\r\ntelescope is also depolarised using a scrambler, which avoids polarization-related artefacts. OMI data are\r\navailable since 2004 and the instrument is still operational, however in 2007 OMI started to\r\nexperience the so-called row anomaly which reduces the amount of useful measurements, despite\r\ncorrection algorithms being implemented in the level-1 processing chain. In the project, the OMI\r\ninstrument is used for ozone profile retrievals. OMI total ozone data are also used for\r\nintercomparison and validation with total ozone data products developed from the GOME,\r\nSCIAMACHY and GOME-2 sensors", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": null, "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI Ozone project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "ESA, Ozone, CCI", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": null, "timePeriod": { "ob_id": 5229, "startTime": "2004-01-01T00:00:00", "endTime": "2014-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 4120, "uuid": "01e607294d4343c8a89d09f41e505a3a", "short_code": "acq", "title": "Acquisition Process for: OMI on EOS-AURA (2004-present)", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Ozone Monitoring instrument (OMI); PLATFORMS: EOS-AURA; " }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 95 ], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 14147, "uuid": "10b36f5715274b1d985c569501ceed68", "short_code": "proj", "title": "ESA Ozone Climate Change Initiative Project", "abstract": "The European Space Agency Ozone Climate Change Initiative (Ozone CCI) project is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs). \r\nOzone_cci aims at generating new high-quality satellite data sets that are essential to assess the fate of atmospheric ozone and better understand its link with anthropogenic activities." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 75746, 75741, 141981, 141982, 141983, 75745, 75742, 75743, 75744 ], "onlineresource_set": [ 16197, 16196, 16198, 16199 ] }, { "ob_id": 19925, "uuid": "35b956ceb80b48ca953f310951146832", "title": "BUNIAACIC: Manchester atmospheric cloud condensation nuclei measurements", "abstract": "The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1)\r\n\r\nThis project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon.\r\n\r\nThis dataset contains cloud condensation nuclei measurements.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-10-18T10:34:43", "updateFrequency": "notPlanned", "dataLineage": "Data collected by project team and sent to CEDA", "removedDataReason": "", "keywords": "BUNIAACIC, Brazil, CCN, chemistry, pollution", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2017-09-07T13:09:04", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1651, "bboxName": "Pristine, Brazil", "eastBoundLongitude": -60.209289, "westBoundLongitude": -60.209289, "southBoundLatitude": -2.594541, "northBoundLatitude": -2.594541 }, "verticalExtent": null, "result_field": { "ob_id": 20064, "dataPath": "/badc/buniaac/data/man-ccn", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1712168, "numberOfFiles": 2, "fileFormat": "Data are NASA Ames formatted" }, "timePeriod": { "ob_id": 5253, "startTime": "2013-07-08T23:00:00", "endTime": "2013-07-27T23:00:00" }, "resultQuality": { "ob_id": 3067, "explanation": "Data provided by project group", "passesTest": true, "resultTitle": "BUNIAACIC project data", "date": "2016-10-17" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 19931, "uuid": "f2888d717f454ab1834355ba337f443a", "short_code": "acq", "title": "BUNIAACIC: Atmospheric cloud condensation nuclei measurements", "abstract": "BUNIAACIC: Atmospheric cloud condensation nuclei measurements" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 18 ], "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": 19921, "uuid": "039fa6aef65d4adf96f064188bbf7a00", "short_code": "proj", "title": "Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC)", "abstract": "The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1)\r\n\r\nThis project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon. \r\n\r\nA network of Brazilian and UK atmospheric researchers were established to scope potential collaborative opportunities by exploiting and extending the infrastructural framework of the FAPESP AEROCLIMA Thematic Grant. 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A pump-priming pilot scale intensive deployment of the CAS container laboratory with additional particulate measurement instrumentation were used to i) validate the long-term measurements, ii) quantitatively interpret the impacts of aerosol composition on physical properties of climate relevance in the context of the long-term variability, iii) act as a focal measurement suite around which a broader consortium-scale activity can be developed. \r\n\r\nA strategy for the medium and longer term collaborative efforts were developed based on the initial scoping study and consultation throughout the UK research community. This strategy was consolidated into a White Paper outlining the Brazil-UK collaborative opportunities and recommended participation of UK groups in Amazonian atmospheric research." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 52353 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 19922, "uuid": "314b6cc4d99a4bb79f79c7879ad2ef7f", "short_code": "coll", "title": "Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC)", "abstract": "The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1)\r\n\r\nThis project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon.\r\n\r\nThis dataset collection contains atmospheric composition measurements." } ], "responsiblepartyinfo_set": [ 75754, 75757, 75756, 75758, 75760, 75761, 75755, 75759, 76329 ], "onlineresource_set": [] }, { "ob_id": 19926, "uuid": "dd00b044449040f2be311b1fe6dd9350", "title": "ESA Ozone Climate Change Initiative (Ozone CCI):ENVISAT/SCIAMACHY Limb Nadir Tropospheric Columns Level 3 Tropospheric Tropical Ozone 2002-2012 V2.0", "abstract": "The data is calculated on a convective cloud differential (CCD) algorithm and averaged whereby only the position of the central coordinate is considered. \r\nThe tropospheric column can then be calculated by the difference between the stratospheric column and the total column. The stratospheric column being estimated as above the high reaching convective clouds (cloud cover >0.8 and >8km in height). To reduce the error above the clouds from up draught of tropospheric pollution a clean reference region 70°E to 170°W representitive of the latitude band. \r\n\r\nFor the Total column only cloud free observations are considered (<10%). This method assumes the stratospheric ozone is constant throughout each month and for one latitude band limit the CCD algorithm to the tropics (20°S to 20°N).\r\n\r\nSCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY) is\r\na multi-channel UV-Vis-NIR spectrometer launched on the ENVISAT platform in 2002. Its\r\nprimary mission objective is the global monitoring of trace gases in the troposphere and in the\r\nstratosphere. The solar radiation transmitted, backscattered and reflected from the atmosphere is\r\nrecorded at medium resolution (0.2 nm to 1.5 nm) over the range 240 nm to 1700 nm, and in\r\nselected regions between 2.0 µm and 2.4 µm. SCIAMACHY is particular since it has three\r\ndifferent viewing geometries: nadir, limb, and sun/moon occultation, which yield total column\r\nvalues as well as distribution profiles in the stratosphere and upper troposphere. In this project\r\nboth nadir and limb measurements are used in Channels 1, 2 and 3. In nadir view, used for ozone\r\ntotal column and vertical profile retrievals, the ground pixel size for channels 2-3 is 30x60 km2, \r\ni.e. a resolution intermediate between GOME and OMI. The swath width of SCIAMACHY at\r\nnadir is similar to GOME (960 km), however due to the alternate nadir and limb mode operation,\r\nglobal coverage is only obtained in approximately 6 days. In limb view, ozone number density\r\nprofiles are derived in the stratosphere by exploiting the Hartley and Chappuis spectral\r\nabsorption bands in channels 1 and 3. SCIAMACHY data are available from July 2002 till April\r\n2012 when communication with ENVISAT was lost.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": null, "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI Ozone project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "ESA, Ozone, CCI", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": null, "timePeriod": { "ob_id": 5230, "startTime": "2002-01-01T00:00:00", "endTime": "2012-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 8036, "uuid": "fa6a8b1a91cf4a4cb78ac3aa64fd2659", "short_code": "acq", "title": "Acquisition Process for: SCIAMACHY Level 2 vertical columns of trace gases products", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Envisat - SCIAMACHY; 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A pump-priming pilot scale intensive deployment of the CAS container laboratory with additional particulate measurement instrumentation were used to i) validate the long-term measurements, ii) quantitatively interpret the impacts of aerosol composition on physical properties of climate relevance in the context of the long-term variability, iii) act as a focal measurement suite around which a broader consortium-scale activity can be developed. \r\n\r\nA strategy for the medium and longer term collaborative efforts were developed based on the initial scoping study and consultation throughout the UK research community. This strategy was consolidated into a White Paper outlining the Brazil-UK collaborative opportunities and recommended participation of UK groups in Amazonian atmospheric research." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 52353 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 19922, "uuid": "314b6cc4d99a4bb79f79c7879ad2ef7f", "short_code": "coll", "title": "Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC)", "abstract": "The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1)\r\n\r\nThis project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon.\r\n\r\nThis dataset collection contains atmospheric composition measurements." } ], "responsiblepartyinfo_set": [ 75777, 75773, 76326, 75771, 75776, 75774, 75775, 75772, 75770 ], "onlineresource_set": [] }, { "ob_id": 19929, "uuid": "6aa09380a1e04f8c99adea8602394caa", "title": "BUNIAACIC: Aerosol Chemical Speciation Monitor - Universidade de Sao Paulo (USP-ACSM)", "abstract": "The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1)\r\n\r\nThis project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon.\r\n\r\nThis dataset contains measurements from the Aerodyne Aerosol Chemical Speciation Monitor\r\noperated by Universidade de Sao Paulo (USP-ACSM)", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-10-18T10:35:26", "updateFrequency": "notPlanned", "dataLineage": "Data collected by project team and sent to CEDA", "removedDataReason": "", "keywords": "BUNIAACIC, Brazil, CCN, chemistry, pollution", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2017-09-07T13:08:16", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1651, "bboxName": "Pristine, Brazil", "eastBoundLongitude": -60.209289, "westBoundLongitude": -60.209289, "southBoundLatitude": -2.594541, "northBoundLatitude": -2.594541 }, "verticalExtent": null, "result_field": { "ob_id": 20065, "dataPath": "/badc/buniaac/data/usp-acsm", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 12414, "numberOfFiles": 2, "fileFormat": "Data are NASA Ames formatted" }, "timePeriod": { "ob_id": 5249, "startTime": "2013-07-13T23:00:00", "endTime": "2013-07-23T23:00:00" }, "resultQuality": { "ob_id": 3067, "explanation": "Data provided by project group", "passesTest": true, "resultTitle": "BUNIAACIC project data", "date": "2016-10-17" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 19934, "uuid": "3215638d2db24cbcbad3fb1a25efcbe9", "short_code": "acq", "title": "BUNIAACIC: USP-ACSM Aerosol Chemical Speciation Monitor measurements", "abstract": "Measurements of concentrations of organics, nitrate, sulphate, ammonium and chloride aerosols by the Universidade de Sao Paulo - Aerodyne Aerosol Chemical Speciation Monitor for the BUNIAAC project\r\n" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 18 ], "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": 19921, "uuid": "039fa6aef65d4adf96f064188bbf7a00", "short_code": "proj", "title": "Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC)", "abstract": "The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1)\r\n\r\nThis project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon. \r\n\r\nA network of Brazilian and UK atmospheric researchers were established to scope potential collaborative opportunities by exploiting and extending the infrastructural framework of the FAPESP AEROCLIMA Thematic Grant. An early secondment of CAS staff to São Paulo followed by a broad kick-off workshop were used to initiate the scoping study. Potential UK activities at various stages of development were drawn into a broader strategy of International collaboration and opportunities for further consortium scale activities were developed. A UK office for collaboration on Amazonian atmospheric research was established at the University of Manchester. \r\n\r\nThe long-term particulate monitoring programme within AEROCLIMA was expanded to include online aerosol composition measurements at the pristine rainforest site. Secondment of São Paulo staff to CAS ensured adequate training was provided in the operation of the instrumentation, data analysis and quality control. A pump-priming pilot scale intensive deployment of the CAS container laboratory with additional particulate measurement instrumentation were used to i) validate the long-term measurements, ii) quantitatively interpret the impacts of aerosol composition on physical properties of climate relevance in the context of the long-term variability, iii) act as a focal measurement suite around which a broader consortium-scale activity can be developed. \r\n\r\nA strategy for the medium and longer term collaborative efforts were developed based on the initial scoping study and consultation throughout the UK research community. This strategy was consolidated into a White Paper outlining the Brazil-UK collaborative opportunities and recommended participation of UK groups in Amazonian atmospheric research." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 52353 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 19922, "uuid": "314b6cc4d99a4bb79f79c7879ad2ef7f", "short_code": "coll", "title": "Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC)", "abstract": "The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1)\r\n\r\nThis project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon.\r\n\r\nThis dataset collection contains atmospheric composition measurements." } ], "responsiblepartyinfo_set": [ 75785, 75779, 75778, 75784, 75782, 75783, 75781, 75780 ], "onlineresource_set": [] }, { "ob_id": 19977, "uuid": "ac5efde71dc14234959488fd780430a9", "title": "Environmental Baseline Project: Air quality measurements from Kirby Misperton", "abstract": "This dataset contains air quality measurements: atmospheric ozone, NOx and particulate matter, for the Kirby Misperton site.\r\n\r\nBritish Geological Survey (BGS), the universities of Birmingham, Bristol, Liverpool, Manchester and York and partners from Public Health England (PHE) and the Department for Business, Energy and Industrial Strategy (BEIS), are conducting an independent environmental baseline monitoring programme near Kirby Misperton, North Yorkshire and Little Plumpton, Lancashire. These are areas where planning permission has been granted for hydraulic fracturing.\r\n\r\nThe monitoring allows the characterisation of the environmental baseline before any hydraulic fracturing and gas exploration or production takes place in the event that planning permission is granted. The investigations are independent of any monitoring carried out by the industry or the regulators, and information collected from the programme will be made freely available to the public. \r\n\r\n-----------------------------------------------------------------------------------------------\r\nIf you use these data, please note the requirement to acknowledge use.\r\n\r\nUse of data and information from the project:\r\n\"Science-based environmental baseline monitoring associated with shale gas development in the Vale of Pickering, Yorkshire (including supplementary air quality monitoring in Lancashire)\", led by the British Geological Survey\r\n\r\nPermission for reproduction of data accessed from the CEDA website is granted subject to inclusion of the following acknowledgement:\r\n\"These data were produced by the Universities of Manchester and York (National Centre for Atmospheric Science) in a collaboration with the British Geological Survey and partners from the Universities of Birmingham, Bristol and Liverpool and Public Health England, undertaking a project grant-funded by the Department for Energy & Climate Change (DECC), 2015-2016. \"\r\n----------------------------------------------------------------------------------------------------------", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-04-15T09:45:05.280971", "updateFrequency": "", "dataLineage": "Data collected by the project team and supplied to the Centre of Environmental Data Analysis (CEDA) for archiving.", "removedDataReason": "", "keywords": "ozone, PM10, PM2.5, NOx, air quality", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2016-09-28T10:52:28", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1637, "bboxName": "Kirby Misperton (UK)", "eastBoundLongitude": -0.818, "westBoundLongitude": -0.818, "southBoundLatitude": 54.2, "northBoundLatitude": 54.2 }, "verticalExtent": null, "result_field": { "ob_id": 19974, "dataPath": "/badc/env-baseline/data/kirby-misperton/aq", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 193578979, "numberOfFiles": 58, "fileFormat": "Data are NASA Ames formatted" }, "timePeriod": { "ob_id": 5231, "startTime": "2016-01-13T00:00:00", "endTime": "2020-05-31T23:59:59" }, "resultQuality": { "ob_id": 3061, "explanation": "Research data from Environmental baseline project NASA Ames 1001 compliant", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2016-09-27" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 19976, "uuid": "f1b245e0aed042b5a1d3be1b8456ebbb", "short_code": "acq", "title": "Air Quality data at Kirby Misperton", "abstract": "Air Quality data at Kirby Misperton for the Environmental Baseline Project" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2589, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 52, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ebl.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 19625, "uuid": "62fe80946b06412a97fea19c8e9c1910", "short_code": "proj", "title": "Environmental baseline monitoring in the Vale of Pickering and Lancashire", "abstract": "British Geological Survey (BGS), the Universities of Birmingham, Bristol, Liverpool, Manchester and York and partners from Public Health England (PHE) and the Department of Energy and Climate Change (DECC), are conducting an independent environmental baseline monitoring programme in the Vale of Pickering, North Yorkshire. This is the area where North Yorkshire County Council has granted planning permission to Third Energy to hydraulically fracture one of their wells.\r\n\r\nThe monitoring allows the characterisation of the environmental baseline before any hydraulic fracturing and gas exploration or production takes place in the event that planning permission is granted. The investigations are independent of any monitoring carried out by the industry or the regulators, and information collected from the programme will be made freely available to the public. \r\n\r\nThe monitoring in and around the Vale of Pickering and Lancashire includes:\r\n\r\n water quality (groundwater and surface water)\r\n seismicity\r\n ground motion\r\n air quality\r\n radon\r\n soil gas" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 25394, 61313 ], "vocabularyKeywords": [], "identifier_set": [ 9000 ], "observationcollection_set": [ { "ob_id": 19978, "uuid": "17381cd841ba46aca622307cdcf95da7", "short_code": "coll", "title": "Environmental Baseline Project: Air quality, greenhouse gas, Volatile Organic Compounds (VOCs) and surface meteorological measurements from Kirby Misperton and Little Plumpton", "abstract": "This dataset collection contains air quality, greenhouse gas, Volatile Organic Compounds (VOCs) and surface meteorological measurements for the Kirby Misperton site and Little Plumpton.\r\n\r\nBritish Geological Survey (BGS), the universities of Birmingham, Bristol, Liverpool, Manchester and York and partners from Public Health England (PHE) and the Department for Business, Energy and Industrial Strategy (BEIS), are conducting an independent environmental baseline monitoring programme near Kirby Misperton, North Yorkshire and Little Plumpton, Lancashire. These are areas where planning permission has been granted for hydraulic fracturing.\r\n\r\nThe monitoring allows the characterisation of the environmental baseline before any hydraulic fracturing and gas exploration or production takes place in the event that planning permission is granted. The investigations are independent of any monitoring carried out by the industry or the regulators, and information collected from the programme will be made freely available to the public." } ], "responsiblepartyinfo_set": [ 75957, 75960, 75959, 75958, 75956, 75955, 75954, 75953, 75950, 76167 ], "onlineresource_set": [ 16257 ] }, { "ob_id": 19979, "uuid": "fde8e875d45346bcb533641f44531268", "title": "Gridded global surface measurements of nitric ozone, nitrogen dioxide, carbon monoxide and isoprene metrics data (1980-2015) - version 1.0", "abstract": "This dataset represents a collation of surface measurements of nitric oxide (NO), nitrogen dioxide (NO2), carbon monoxide (CO) and isoprene (C5H8) from publicly available data sets (of hourly, daily and monthly resolutions), for the aim of improved evaluation of surface ozone in global atmospheric chemistry models.\r\n\r\nMeasurements begin in 1980 running through to 2015. The data comes in a range of formats, with a plethora of associated data quality issues, requiring substantial cleaning before being able to be utilised for model assessment. 1,033,463,750 measurements from 16,996 sites are processed through numerous data quality checks, resulting in 76,413,458 observations from 1607 sites of appropriate quality (with the majority of excluded observations due to urban influence). Observations are heavily weighted towards North America and Europe, with generally sparse coverage over the rest of the globe (with the exception of CO). See documentation for more details. \r\n\r\nData is provided as multiple globally gridded output files, each consisting of a series of metrics designed to reflect the distributions of the observed ozone precursor species, allowing fair and easy comparison with global models. Metrics include the moments of the distribution (i.e. mean, temporal standard deviation, skewness and kurtosis) and percentiles. A total of 80 different netCDF-4 files are produced, with metrics calculated in multiple temporal (monthly and annual) and spatial configurations (8 different resolutions), for each different species. \r\n\r\nThe format of the output netCDF-4 files is designed to be consistent with the related dataset which compiled surface ozone observations (v2.7).", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2017-05-17T16:55:38.447462", "updateFrequency": "notPlanned", "dataLineage": "Data were processed by the authors and delivered to CEDA for archiving. See associated documentation for more details.", "removedDataReason": "", "keywords": "Nitric Oxide, Nitrogen Dioxide, Carbon Monoxide, Isoprene, NO, NO2, CO, C5H8, Surface, Chemistry", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "various grid resolutions", "status": "completed", "dataPublishedTime": "2017-06-12T09:37:10", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 24691, "dataPath": "/badc/proc-earth-model/data/other-metrics/v1.0", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 43958560677, "numberOfFiles": 81, "fileFormat": "NetCDF4" }, "timePeriod": { "ob_id": 5232, "startTime": "1980-01-01T00:00:00", "endTime": "2015-12-31T23:59:59" }, "resultQuality": { "ob_id": 3086, "explanation": "Please see documentation for details of data quality", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2017-06-12" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 2 ], "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": 12368, "uuid": "0a5fb98570a0459fb326deb173f50b2f", "short_code": "proj", "title": "Process Based Earth System Model (ESM) Evaluation", "abstract": "This project was funded by the Natural Environment Research Council (NERC) with the grant reference - NE/K016008/1 - led by Professor Mathew Evans (University of York).\r\n\r\nClimate change and air pollution are two of the biggest challenges facing humanity today. Ozone and particulate matter are pollutants that are particularly harmful to human health. Recent studies have suggested that in the UK alone they cause 50,000 extra deaths and result in a financial burden of 8-22 billion pounds per year. Both ozone and particulate matter also play an important role in climate change. Ozone absorbs infra-red radiation resulting in a warming of the climate. Particles scatter and absorb incoming solar radiation and alter the properties of clouds. This results in complex interactions with the Earth's climate, with some types of aerosol pollution warming climate whereas others cool climate. Future air quality depends both on changes to emissions of pollutants and to changes in climate. Furthermore, a warming climate can result in worsened air pollution, which in turn can drive additional warming, meaning that complex feedbacks are possible between air pollution and climate.\r\n\r\nTo help understand these complex interactions and feedbacks scientists have developed Earth System Models that include a description of the important physical and biogeochemical processes. These models are increasingly being used by policy makers to make predictions about future air quality and climate and to guide policy decisions. It is therefore important that the models are rigorously tested. \r\n\r\nThis testing involves using detailed observations of atmospheric composition that have been made over the past few decades at locations around the world. Most model evaluation to date has involved testing whether the models simulate current average concentrations of atmospheric pollutants. Whilst this is a useful and necessary first step in model evaluation it does not test whether the model accurately simulates the change in concentration of a pollutant under changing emissions or changing climate. For example, does the model capture the real-world change in concentrations of a pollutant given a particular change in emission or under a future climate change scenario? This is particularly important as these predictions under-pin policy recommendations for air quality abatement. \r\n\r\nThis project synthesised long-term (multi-decadal) observations of ozone and particulate matter and their atmospheric precursors. They used these observations to explore trends and variability that have been observed over the past few decades. A model-observation framework was developed that can be used to evaluate how well models simulate observed variability and trends. The project tested state-of-the-art Earth System Models using existing model output from model intercomparison exercises. Finally, they explored the model processes that are driving simulated variability and trends.\r\n\r\nThe results inform the scientific community as to the fidelity of Earth System Models. This project helped to improve our models and give us more confidence in our predictions.\r\n\r\nThe overall objective of this project was to develop and implement a framework capable of evaluating the sensitivity of atmospheric composition simulated by ESMs to changing climate and emissions. \r\n\r\nOur scientific objectives were to:\r\n\r\nO1. Develop observationally-based metrics and relationships with which to evaluate variability and trends in atmospheric composition and its drivers in ESMs. \r\n\r\nO2. Understand the sensitivity of observed and simulated atmospheric composition to environmental drivers.\r\n\r\nO3. Quantify the ability of ESMs to capture observed temporal variability and trends in atmospheric composition.\r\n\r\nO4. Improve our understanding of the processes driving observed variability in atmospheric composition." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 25851, 50416, 50542, 50543, 55923, 55924, 55925, 55926, 55927, 55928, 55929, 55930, 55931, 55932 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12398, "uuid": "5af3f51efc1d46c88d35be217b20fad3", "short_code": "coll", "title": "Process Based Earth System Model Evaluation: Gridded Global Surface Ozone Metrics and Precursor species data collection for Atmospheric Chemistry Model Evaluation", "abstract": "This dataset collection presents a global surface ozone compilation for long-term trends and ESM (Earth System Model) evaluation.\r\n\r\nThe project (Process Based Earth System Model Evaluation) brought together all publicly available surface ozone observations from online databases from the modern era to build a consistent dataset for the evaluation of chemical transport and chemistry-climate (Earth System) models for projects such as the Chemistry-Climate Model Initiative (CCMI) and Aer-Chem-MIP. \r\n\r\nFrom a total dataset of approximately 6600 sites and 500 million hourly observations from 1971-2015, approximately 2200 sites and 200 million hourly observations pass screening as high-quality sites in regional background locations that are appropriate for use in global model evaluation. There was generally good data volume in the datasets since the start of air quality monitoring networks in 1990 through to 2013. Ozone observations are biased heavily toward North America and Europe with sparse coverage over the rest of the globe. \r\n\r\nThis dataset collection was made available for the purposes of model evaluation as a set of gridded metrics intended to describe the distribution of ozone concentrations on monthly and annual timescales. This collection currently holds version 2.4 data only, but future versions may follow." } ], "responsiblepartyinfo_set": [ 75978, 101216, 75981, 75980, 75979, 75977, 75976, 75975, 101071 ], "onlineresource_set": [ 16259, 16261, 16260 ] }, { "ob_id": 19981, "uuid": "d864a8a9776f4b46af29a292fcf4556c", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Merged SCIAMACHY and GOSAT Level 3 gridded atmospheric column-average carbon dioxide (XCO2) product in Obs4MIPs format", "abstract": "This dataset contains satellite-derived atmospheric column-average dry-air mole fractions of carbon dioxide (XCO2), and is a Level 3 gridded product in Obs4MIPs format. It has been derived by the Greenhouse Gases CCI (GHG_cci) project as part of the European Space Agency's (ESA's) Climate Change Initiative (CCI) programme, and has been obtained from an ensemble of individual Level 2 (i.e. swath) XCO2 products, retrieved from the satellite sensors SCIAMACHY / ENVISAT and TANSO-FTS / GOSAT. The versions of the Level 2 GHG_cci data products used as input for this product are those of the GHG_cci \"Climate Research Data Package No. 3\" (CRDP#3).\r\n\r\nThis Level 3 Obs4MIPs XCO2 product has been specifically generated for comparisons with climate model output in the context of the CMIP5/CMIP6/IPCC experiments.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-07-26T08:32:50.293229", "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI GHG project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "CCI, GHG, Obs4MIPS, carbon dioxide, ESA", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2016-10-10T09:05:31", "doiPublishedTime": "2016-10-10T09:05:34", "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": 19982, "dataPath": "/neodc/esacci/ghg/data/obs4mips/crdp_3/CO2/v100/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 10461113, "numberOfFiles": 2, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 5241, "startTime": "2003-01-01T00:00:00", "endTime": "2014-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2564, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 34, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_ghg_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13295, "uuid": "f0c66ffa30514d2daee821286a014b16", "short_code": "proj", "title": "ESA Greenhouse Gases Climate Change Initiative Project", "abstract": "The European Space Agency Greenhouse Gases Climate Change Initiative (GHG CCI) project is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs)\r\n\r\nCarbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases (GHGs) and a focus of international research activities related to a better understanding of the carbon cycle (see, for example, the Global Carbon Project (GCP)).\r\n \r\nWithin the GHG-CCI project the focus is on satellite data. Satellite observations combined with modelling can add important missing global information on regional CO2 and CH4 (surface) sources and sinks required for better climate prediction. The GHG CCI project started on the 1st September 2010." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6023, 18945, 18946, 18947, 18948, 18949, 50416, 50559, 50561, 91317 ], "vocabularyKeywords": [ { "ob_id": 10130, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org28", "resolvedTerm": "Institute of Environmental Physics" }, { "ob_id": 10139, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org61", "resolvedTerm": "University of Bremen" } ], "identifier_set": [ 9001 ], "observationcollection_set": [ { "ob_id": 12808, "uuid": "0508f3dd991144aa80346007a415fb07", "short_code": "coll", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci) dataset collection", "abstract": "The Greenhouse Gases Climate Change Initiative (GHG_cci) data products are near-surface-sensitive dry-air column-averaged mole fractions (mixing ratios) of methane (CH4) and carbon dioxide (CO2), created as part of the European Space Agency's (ESA) Greenhouses Gases Essential Climate Variable (ECV) CCI project. Denoted XCO2 (in ppmv) and XCH4 (in ppbv), the products have been retrieved from the SCIAMACHY instrument on ENVISAT and TANSO-FTS onboard GOSAT, using ECV Core Algorithms (ECAs). Other satellite instruments such as IASI, MIPAS and ACE-FTS have also been used to provide constraints for upper layers, with their corresponding retrieval algorithms referred to as Additional Constraints Algorithms (ACAs). The GHG data products are typically updated annually, the corresponding datasets being called Climate Research Data Packages (CRDP). \r\n\r\nThe products have each been generated from individual sensors, a single merged product not having yet been created \"combining\" the products from different sensors to cover the entire available satellite time series. One merged product has however been generated using the EMMA algorithm, covering a limited time period. This EMMA product is mainly used as a comparison tool for products generated using individual algorithms, making up the collection of products used by EMMA. \r\n\r\nTypically the same product (e.g. XCO2 from GOSAT) has been generated using different retrieval algorithms. A baseline algorithm has been used to generate one recommended baseline product, for users unsure which product to choose. Other products are called alternative products. However an alternative product's quality may equal that of the corresponding baseline product. It typically depends upon the application for which a product is required, which product is best to use as methods involved in producing them typically have varying strength and weaknesses. \r\n\r\nFor further information on the products, such as details on the SCIAMACHY and TANSO instruments, the algorithms used to generate the data and the data's format, please see the Product Specification Document (PSD) in the documentation section." } ], "responsiblepartyinfo_set": [ 193396, 193395, 76185, 76182, 76183, 76192, 76184, 76181, 76180, 76193, 76230, 76231, 76232, 76233, 76234, 76235, 76236, 76237, 76238 ], "onlineresource_set": [ 16601, 16733 ] }, { "ob_id": 19985, "uuid": "a9f4876560234ded84ac87eb9d4853c6", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Surface Elevation Change from Cryosat-2, v2.0", "abstract": "This data set is part of the ESA Greenland Ice sheet CCI project. The data set provides surface elevation changes (SEC) for the Greenland Ice sheet derived from Cryosat 2 satellite radar altimetry, for the time period between 2010 and 2015.\r\n \r\nThe surface elevation change data are provided as 2-year means (2011-2012, 2012-2013, 2013-2014 and 2014-2015), and a five-year mean is also provided (2011-2015), along with their associated errors. Data are provided in both NetCDF and gridded ASCII format, as well as png plots.\r\n\r\nThe algorithm used to devive the product is described in the paper “Implications of changing scattering properties on the Greenland ice sheet volume change from Cryosat-2 altimetry” by S.B. Simonsen and L.S. 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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": [ 6023, 12066, 13230, 13232, 50547, 50548, 53927, 53928 ], "vocabularyKeywords": [ { "ob_id": 10187, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" }, { "ob_id": 10212, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/dataType/dtype_iv", "resolvedTerm": "ice sheet velocity" }, { "ob_id": 10619, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/dataType/dtype_iv", "resolvedTerm": "ice sheet velocity" }, { "ob_id": 10666, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" } ], "identifier_set": [], "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": [ 79004, 79003, 105350, 105174, 104954, 79005, 76007, 76006 ], "onlineresource_set": [ 16286, 16288, 16991, 16992, 16287 ] }, { "ob_id": 19997, "uuid": "0899444452c740cc8cdc65e86fb301c7", "title": "MINERVA: North-West European shelf seas marine climate projections data: spatial two-dimensional 30-year mean climatology ensemble members", "abstract": "These climate projections for the North-West European Shelf Seas update the shelf seas component of UKCP09 Marine Report (Lowe et al, 2009) and were funded by the MINERVA project.\r\n\r\nThis dataset contains three ensemble exemplars for model output based on the QUMP (Quantifying Uncertainties in Model Projections) ensemble of HadCM3 (Hadley Centre Coupled Model version 3) runs downscaled with the POLCOMS (Proudman Oceanographic Laboratory Coastal Ocean Modelling System) under SRES A1B (Special Report on Emissons Scenarios - A1B business-as-usual with medium emissions) conditions, from 1952-2098 for which 30-year means anomalies have been calculated from monthly mean data for each of the 12 months. \r\n\r\nA Perturbed Physics Ensemble (PPE) of HadCM3 has been downscaled with the shelf seas model POLCOMS. Each of the 11 ensemble members has been downscaled as transient simulations (from 1952-2098) under the SRES A1B emissions scenario. The PPE (QUMP) was designed to span the range of uncertainty associated with model parameter uncertainty in the atmosphere of the driving global climate model. POLCOMS was run at 12 km resolution, with 32 vertical levels using s-coordinates over the NW European Shelf Seas domain (-18.3 to 14 degrees East, 43 to 63.56 degrees North). Monthly statistics of the model results were recorded. \r\nFurther details can be found in Tinker et al (2015).\r\n", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T02:54:01", "updateFrequency": "notPlanned", "dataLineage": "A Perturbed Physics Ensemble (PPE) of the Atmosphere-Ocean General Circulation Model (AO-GCM, or GCM) HadCM3 is downscaled by the shelf seas model POLCOMS. Monthly mean (and time-step minimum, maximum and variance) 3D (temperature, salinity, u- and v- components of currents) and 2D (surface elevation) fields were saved and the following variables were calculated: \r\n SST: Sea Surface Temperature – surface model layer\r\n\tSSS: Sea Surface Salinity – surface model layer\r\n\tNBT: Near-Bed Temperature – bottom model layer\r\n\tNBS: Near-Bed Salinity – bottom model layer\r\n\tDFT: Difference between SST and NBT – surface model layer minus bottom model layer\r\n\tDFS: Difference between SSS and NBS – surface model layer minus bottom model layer\r\n\tPEA: Potential Energy Anomaly (a measure of stratification).\r\n\tMLD: Mixed Layer Depth", "removedDataReason": "", "keywords": "MINERVA, UKCP, Marine Climate, Climate Projection, Uncertainty, Climate Downscaling, Shelf Seas, Temperature, SST, Salinity, Stratification, Sea Surface Temperature", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "12 km", "status": "completed", "dataPublishedTime": "2016-09-05T11:00:00", "doiPublishedTime": "2016-09-20T09:10:54", "removedDataTime": null, "geographicExtent": { "ob_id": 537, "bboxName": "NW European Shelf Seas", "eastBoundLongitude": 13.0, "westBoundLongitude": -18.33, "southBoundLatitude": 43.0, "northBoundLatitude": 63.56 }, "verticalExtent": null, "result_field": { "ob_id": 19998, "dataPath": "/badc/ukcp09/data/marine/minerva/dataset_1/ens_members", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 269051361, "numberOfFiles": 289, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 3335, "startTime": "1960-01-01T00:00:00", "endTime": "2098-12-31T23:59:00" }, "resultQuality": { "ob_id": 1, "explanation": "See dataset associated documentation", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2012-08-15" }, "validTimePeriod": { "ob_id": 3334, "startTime": "1960-01-01T00:00:00", "endTime": "2098-12-31T23:59:00" }, "procedureAcquisition": null, "procedureComputation": { "ob_id": 19988, "uuid": "42283041b306455cb05955abb7d8b95f", "short_code": "comp", "title": "MINERVA: North-West European shelf seas marine climate projection simulations", "abstract": "A Perturbed Physics Ensemble (PPE) of the Atmosphere-Ocean General Circulation Model (AO-GCM, or GCM) HadCM3 is downscaled by the shelf seas model POLCOMS. Each ensemble member is run as a transient experiment, from 1952-2098, under the SRES (Nakicenovic et al. 2000) business-as-usual, medium emission scenario A1B. This work extends that of Holt et al. (2010), released as UKCP09 (Lowe et al. 2009).\r\nHadCM3 (Gordon et al. 2000; Pope et al. 2000) is a CMIP3 model (third phase of the Coupled Model Intercomparison Project). 30 parameters within the HadCM3 atmosphere were perturbed within an expert-specified range to explore the uncertainty in Climate Sensitivity (Collins et al. 2011). 16 parameter-sets were selected that spanned the full range of Climate Sensitivity whilst still validating against present day. These, with the standard parameter set, formed a 17-member global PPE. \r\nThe atmosphere of each ensemble member was downscaled with the regional version of HadCM3, HadRM3 (Jones et al. 2004), with equivalent parameter perturbations. One parameter perturbation, common to 6 HadRM3 ensemble members, did not validate, and so was excluded from the rest of the work.\r\nThe atmospheric run-off fields from HadRM3 were used to drive the river routing model TRIP (Oki and Sud 1998; Oki et al. 1999) to provide river forcings.\r\nPOLCOMS (Proudman Oceanographic Laboratory Coastal Ocean Modelling System) (Holt and James 2001) downscaled each of the 11 member from the HadRM3 PPE. Atmospheric forcings were taken from HadRM3, lateral ocean forcings were taken from the HadCM3 ocean, and riverine forcings were taken from TRIP. The Baltic was treated as a climatological river, with a seasonal cycle of temperature, salinity and volume flux that did not change through time, or across the ensemble. This is a limitation of the study, and has implications downstream (in the Skagerrak, Kattegat and in the Norwegian Trench)." }, "procedureCompositeProcess": null, "imageDetails": [], "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": 12372, "uuid": "045cf918f7084c568f90d76f3f6d95c0", "short_code": "proj", "title": "MINERVA: North-West European Shelf Seas Marine Climate Projections", "abstract": "Climate projections for the North-West European Shelf Seas. An update to the shelf seas component of UKCP09 Marine Report (Lowe et al, 2009) funded by the MINERVA project.\r\n\r\n" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 11392, 25900, 55933, 55934, 55935, 55936, 55937, 55938, 55939, 55940, 55941, 55942, 55943, 55944, 55945, 55946, 55947, 55948, 55949, 55950, 55951, 78889, 78890 ], "vocabularyKeywords": [], "identifier_set": [ 8996 ], "observationcollection_set": [ { "ob_id": 12371, "uuid": "9eba512621144dbaacda1ddb470f885b", "short_code": "coll", "title": "MINERVA: Update to the UKCP09 Marine Report North-West European Shelf Seas Marine Climate Projections", "abstract": "An update to the shelf seas component of UKCP09 Marine Report (Lowe et al. 2009) funded by the Minerva Project. \r\nA Perturbed Physics Ensemble (PPE) of HadCM3 has been downscaled with the shelf seas model POLCOMS. Each of the 11 ensemble members have been downscaled as transient simulations (from 1952-2098) under the SRES A1B emissions scenario. The PPE (QUMP: Quantifying Uncertainty in Model Projections) was designed to span the range of uncertainty associated with model parameter uncertainty in the atmosphere of the driving global climate model. POLCOMS was run at a 12km resolution, with 32 vertical levels using s-coordinates. Monthly statistics of the model results were recorded. \r\n" } ], "responsiblepartyinfo_set": [ 76024, 76019, 76026, 76025, 76023, 76022, 76021, 76020, 76018, 76027 ], "onlineresource_set": [ 16310, 16311, 16312, 16313, 16314, 16315, 16316, 94842 ] }, { "ob_id": 20007, "uuid": "4f6b1b7bde0645d18bf8ce30e9326280", "title": "Landsat 5 (LS5) Thematic Mapper data from the Landsat Campaign", "abstract": "Landsat 5 carries both the TM (thematic mapper) and the MSS (multi-spectral scanner) sensors, though routine collection of MSS data was terminated in late 1992. The satellites orbit at an altitude of 705 km and provide a 16-day, 233-orbit cycle with a swath overlap that varies from 7 percent at the Equator to nearly 84 percent at 81 degrees north or south latitude. Landsat data is widely used in many fields including geology, agriculture, resource management, climate analysis etc. The Landsat program is jointly managed by the National Aeronautics and Space Administration (NASA) and the US Geological Survey (USGS). The NERC Earth Observation Data Centre (NEODC) now also holds the data.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-09-14T09:46:26", "updateFrequency": "asNeeded", "dataLineage": "THIS IS REQUIRED!", "removedDataReason": "", "keywords": "", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": null, "timePeriod": { "ob_id": 5234, "startTime": "1984-03-01T00:00:00", "endTime": null }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 8583, "uuid": "058a467ead8f4acc9736fb3f77a423ee", "short_code": "cmppr", "title": "Composite Process for: Data from Thematic Mapper (LS5) at Landsat5 for the Landsat Campaign", "abstract": "This process is comprised of multiple procedures: 1. Acquisition: Acquisition Process for: Data from Thematic Mapper (LS5) at Landsat5 for the Landsat Campaign; \n2. Computation: DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on Landsat5; \n" }, "imageDetails": [], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 8334, "uuid": "4e5dea57e8f01c2824b2169683822b56", "short_code": "proj", "title": "Landsat", "abstract": "Landsat satellites have been collecting images of the Earth's surface for more than thirty years. NASA launched the first Landsat satellite in 1972, and the most recent one, Landsat 8, in 2013. Instruments onboard the satellites have acquired millions of images of the Earth. These images provide a unique resource for people who work in agriculture, geology, forestry, regional planning, education, mapping, and global change research." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 30129, "uuid": "3b0630c7fa264164868d4da5c9f90bed", "short_code": "coll", "title": "National Centre for Earth Observation (NCEO) Third Party Data", "abstract": "The National Centre for Earth Observation (NCEO) Third Party data contains a broad range remotely sensed data acquired by satellite for use by the Earth Observation Scientific community supported by NCEO. The Centre for Environmental Data Analysis (CEDA) has archived and provides access to extensive Earth observation datasets under strict licensing conditions. Please see the individual dataset records for conditions of use." } ], "responsiblepartyinfo_set": [ 76034, 76038, 76037, 76036, 76035, 76033, 76032, 76031 ], "onlineresource_set": [ 16580 ] }, { "ob_id": 20008, "uuid": "194b93eebfc64f249b5f539bc8f0c802", "title": "SPECS - MOHC-GloSea5 model output prepared for SPECS horizlResImpact (1996-2009)", "abstract": "This dataset includes the Met Office GloSea5 model output prepared for SPECS horizlResImpact (1996-2009). These data were prepared by the Met Office Hadley Centre, as part of the SPECS project. \r\n \r\nModel id is GloSea5 (GloSea5: HadGEM3-AO (GC2); atmosphere: UM (GA6.0) ; ocean: NEMO (v3.4, ORCA0.25) ; coupler: OASIS3 (v3.3); sea ice: CICE), frequency is daily and monthly. \r\n\r\nDaily Atmospheric variables are:\r\npr psl rls rlut tas tasmax tasmin\r\n\r\nMonthly atmos variables:\r\npr psl ta tas zg\r\n\r\nMonthly seaIce variables:\r\nsic sit snd\r\n\r\nOcean variables:\r\nso thetao tos uo vo", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-04-30T22:52:24", "updateFrequency": "notPlanned", "dataLineage": "Data were supplied by SPECS participants to CEDA for archiving in 2016. Data was checked for compliance with CF standards and SPECS requirements.", "removedDataReason": "", "keywords": "specs, MOHC, GloSea5, climate, model", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2016-09-19T11:16:47", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 528, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 20009, "dataPath": "/badc/specs/data/SPECS/output/MOHC/GloSea5/horizlResImpact", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 952161330016, "numberOfFiles": 36709, "fileFormat": "The data are provided in NetCDF format." }, "timePeriod": { "ob_id": 5235, "startTime": "1996-04-24T23:00:00", "endTime": "2009-11-09T23:59:59" }, "resultQuality": { "ob_id": 3049, "explanation": " ", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2016-09-16" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 153 ], "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": 12970, "uuid": "c9b4b1fcab734987bcbfb36437734ca7", "short_code": "proj", "title": "Seasonal-to-decadal climate Prediction for the improvement of European Climate Services (SPECS)", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nThe improved understanding and seamless predictions will offer better estimates of the future frequency of high-impact, extreme climatic events and of the prediction uncertainty. New services to convey climate information and its quality will be used.\r\n\r\nSPECS will be, among other things, the glue to coalesce the outcome of previous research efforts that hardly took climate prediction into account. It will ensure interoperability so as to easily incorporate their application in an operational context, provide the basis for improving the capacity of European policy making, industry and society to adapt to near-future climate variations and a coordinated response to some of the GFCS components.\r\n\r\nThis project is funded by the Seventh Framework Programme (FP7) of the European Commission (GA 308378)." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6023, 12334, 12335, 12336, 12571, 18924, 18925, 50426, 50427, 50475, 50496, 50566, 50569, 50603, 50608, 50623, 50624, 52741, 52761, 53094, 53095, 53096, 53097, 53098, 53099, 53100, 53101, 53102, 53103, 53104, 53105, 53106, 53107, 53108, 53109, 53110, 53111, 53112, 53113, 55976, 55977, 55981, 55982 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 6086, "uuid": "2d9c5f2cc621fb9bc0062356851b31b9", "short_code": "coll", "title": "SPECS: Seasonal-to-decadal climate prediction model outputs", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nA core set of common experiments has been defined, to which most forecast systems will contribute. Another set of coordinated experiments, tier 1, includes the experiments that one or more forecast systems are planning to run. \r\n\r\nA standard seasonal experimental set up will consist of ten-member ensembles, with two start dates per year (first of May and November) over the 1981-2012 period and seven-month forecast length. \r\n\r\nThe standard decadal experimental set up consists in five-member ensembles, starting on the first of November (or some time close to that date) of the years 1960, 1963, 1965, 1968, 1970, 1973, 1975, 1978, 1980, 1983, 1985, 1988, 1990, 1993, 1995, 1998, 2000, 2003, 2005, 2008, 2010, 2013, with a five-year forecast length. \r\n\r\nA description of the main experiments, with the minimum contribution in terms of start dates, forecast length and ensemble size follows: \r\n1 - Assessment of the impact of soil-moisture initial conditions (seasonal): contributing EC-Earth, IFS/NEMO (ECMWF), CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG);\r\n2 - Assessment of the impact of sea-ice initialization (interannual); contributing EC-Earth (IC3), IPSL-CM5, CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG)\r\n3 - Assessment of impact of increased horizontal resolution (seasonal and decadal); contributing CNRM-CM5 (CERFACS, decadal; MeteoF, seasonal), EC-Earth (IC3, seasonal; KNMI and SMHI, decadal), MPI-ESM (MPG, seasonal and decadal), IPSL-CM5 (decadal), UM (seasonal and decadal); \r\n4 - Assessment of impact of an improved stratosphere (seasonal and decadal) including interannually-varying ozone; contributing EC-Earth (KNMI seasonal with ozone; SMHI decadal), IFS/NEMO (ECMWF, seasonal), CNRM-CM5 (MeteoF, seasonal), UM (seasonal, decadal);\r\n5 - Assessment of impact of additional start dates (decadal); contributing EC-Earth (KNMI, SMHI), MPI-ESM (MPG), IPSL-CM5.\r\n\r\nSPECS research has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under SPECS project (grant agreement n° 308378)." } ], "responsiblepartyinfo_set": [ 76045, 76043, 76047, 76046, 76040, 76039, 76049, 76041, 76042, 76044, 76048, 169546 ], "onlineresource_set": [] }, { "ob_id": 20013, "uuid": "1625829014d640d8ae2b9286e3bb8978", "title": "SPECS - MOHC-GloSea5 model output prepared for SPECS seaIceInit (1996-2009)", "abstract": "This dataset includes the Met Office GloSea5 model output prepared for SPECS seaIceInit (1996-2009). These data were prepared by the Met Office Hadley Centre, as part of the SPECS project. \r\n \r\nModel id is GloSea5 (GloSea5: HadGEM3 v3.0 (2014); atmosphere: UM (GA3.0) ; ocean: NEMO (v2, ORCA0.25) ; coupler: OASIS3 (v3.3); sea ice: CICE), frequency is daily and monthly. \r\n\r\nDaily Atmospheric variables are:\r\npr psl rls rlut tas tasmax tasmin\r\n\r\nMonthly atmos variables:\r\npr psl ta tas zg\r\n\r\nMonthly seaIce variables:\r\nsic sit snd\r\n\r\nOcean variables:\r\nso thetao tos uo vo\r\n\r\n\r\n", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-04-22T07:07:13", "updateFrequency": "notPlanned", "dataLineage": "Data were supplied by SPECS participants to CEDA for archiving in 2015. Data was checked for compliance with CF standards and SPECS requirements.", "removedDataReason": "", "keywords": "specs, MOHC, GloSea5, climate, model", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2016-09-27T12:16:32", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 528, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 20014, "dataPath": "/badc/specs/data/SPECS/output/MOHC/GloSea5/seaIceInit", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 687463587127, "numberOfFiles": 31501, "fileFormat": "The data are provided in a CF compliant NetCDF format." }, "timePeriod": { "ob_id": 5240, "startTime": "1996-04-24T23:00:00", "endTime": "2009-05-09T22:59:59" }, "resultQuality": { "ob_id": 3060, "explanation": " ", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2016-09-27" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 153 ], "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": 12970, "uuid": "c9b4b1fcab734987bcbfb36437734ca7", "short_code": "proj", "title": "Seasonal-to-decadal climate Prediction for the improvement of European Climate Services (SPECS)", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nThe improved understanding and seamless predictions will offer better estimates of the future frequency of high-impact, extreme climatic events and of the prediction uncertainty. New services to convey climate information and its quality will be used.\r\n\r\nSPECS will be, among other things, the glue to coalesce the outcome of previous research efforts that hardly took climate prediction into account. It will ensure interoperability so as to easily incorporate their application in an operational context, provide the basis for improving the capacity of European policy making, industry and society to adapt to near-future climate variations and a coordinated response to some of the GFCS components.\r\n\r\nThis project is funded by the Seventh Framework Programme (FP7) of the European Commission (GA 308378)." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6023, 12334, 12335, 12336, 12571, 50426, 50427, 50475, 50496, 50498, 50566, 50569, 50603, 50608, 50623, 50624, 52741, 53094, 53095, 53096, 53097, 53098, 53099, 53100, 53101, 53102, 53103, 53104, 53105, 53106, 53107, 53108, 53109, 53110, 53111, 53112, 53113, 55976, 55977 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 6086, "uuid": "2d9c5f2cc621fb9bc0062356851b31b9", "short_code": "coll", "title": "SPECS: Seasonal-to-decadal climate prediction model outputs", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nA core set of common experiments has been defined, to which most forecast systems will contribute. Another set of coordinated experiments, tier 1, includes the experiments that one or more forecast systems are planning to run. \r\n\r\nA standard seasonal experimental set up will consist of ten-member ensembles, with two start dates per year (first of May and November) over the 1981-2012 period and seven-month forecast length. \r\n\r\nThe standard decadal experimental set up consists in five-member ensembles, starting on the first of November (or some time close to that date) of the years 1960, 1963, 1965, 1968, 1970, 1973, 1975, 1978, 1980, 1983, 1985, 1988, 1990, 1993, 1995, 1998, 2000, 2003, 2005, 2008, 2010, 2013, with a five-year forecast length. \r\n\r\nA description of the main experiments, with the minimum contribution in terms of start dates, forecast length and ensemble size follows: \r\n1 - Assessment of the impact of soil-moisture initial conditions (seasonal): contributing EC-Earth, IFS/NEMO (ECMWF), CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG);\r\n2 - Assessment of the impact of sea-ice initialization (interannual); contributing EC-Earth (IC3), IPSL-CM5, CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG)\r\n3 - Assessment of impact of increased horizontal resolution (seasonal and decadal); contributing CNRM-CM5 (CERFACS, decadal; MeteoF, seasonal), EC-Earth (IC3, seasonal; KNMI and SMHI, decadal), MPI-ESM (MPG, seasonal and decadal), IPSL-CM5 (decadal), UM (seasonal and decadal); \r\n4 - Assessment of impact of an improved stratosphere (seasonal and decadal) including interannually-varying ozone; contributing EC-Earth (KNMI seasonal with ozone; SMHI decadal), IFS/NEMO (ECMWF, seasonal), CNRM-CM5 (MeteoF, seasonal), UM (seasonal, decadal);\r\n5 - Assessment of impact of additional start dates (decadal); contributing EC-Earth (KNMI, SMHI), MPI-ESM (MPG), IPSL-CM5.\r\n\r\nSPECS research has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under SPECS project (grant agreement n° 308378)." } ], "responsiblepartyinfo_set": [ 76069, 76065, 76100, 76099, 76073, 76072, 76066, 76098, 76067, 76068, 76071 ], "onlineresource_set": [] }, { "ob_id": 20015, "uuid": "96de05733b5d464885da0e1495626f7f", "title": "Sentinel 1B C-band Synthetic Aperture Radar (SAR): Interferometric Wide (IW) mode Single Look Complex (SLC) Level 1 data, Instrument Processing Facility (IPF) v2", "abstract": "This dataset contains Interferometric Wide swath (IW) Single Look Complex (SLC) C-band Synthetic Aperture Radar (SAR) data from the European Space Agency (ESA) Sentinel 1B satellite. Sentinel 1B was lanched on 25th April 2016 and provides continuous all-weather, day and night imaging radar data. The IW mode is the main operational mode. The IW mode supports single (HH or VV) and dual (HH+HV or VV+VH) polarisation. \r\n\r\nThe IW SLC product contains one image per sub-swath, per polarisation channel, for a total of three or six images. Each sub-swath image consists of a series of bursts, where each burst was processed as a separate SLC image. The individually focused complex burst images are included, in azimuth-time order, into a single sub-swath image, with black-fill demarcation in between\r\n\r\nUnlike SM and WV SLC products, which are sampled at the natural pixel spacing, the images for all bursts in all sub-swaths of an IW SLC product are re-sampled to a common pixel spacing grid in range and azimuth. The resampling to a common grid eliminates the need for further interpolation in case, in later processing stages, the bursts are merged to create a contiguous ground range, detected image.\r\n\r\n\r\nThese data are available via CEDA to any registered user.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-04-15T02:00:16", "updateFrequency": "asNeeded", "dataLineage": "Data collected and prepared by European Space Agency (ESA). Downloaded from the Collaborative Hub for use by the UK scientific community.", "removedDataReason": "", "keywords": "Sentinel, radar, Synthetic Aperture Radar, SAR, Interferometric Wide, IW, Single Look Complex, SLC", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2016-09-08T23:00:00", "doiPublishedTime": null, "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": 20031, "dataPath": "/neodc/sentinel1b/data/IW/L1_SLC/IPF_v2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1439933488233013, "numberOfFiles": 1692978, "fileFormat": "Image data files are in a binary format. Quicklook images are in png format. Manifest files with relevant metadata are in SAFE format." }, "timePeriod": { "ob_id": 9007, "startTime": "2016-08-20T00:00:00", "endTime": "2019-06-26T23:59:59" }, "resultQuality": { "ob_id": 3004, "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": "2014-09-28" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 20019, "uuid": "4f2cbf03e45046e2b1b8cd27c89b5b3c", "short_code": "cmppr", "title": "Composite Process for: Level 1 data from the Sentinel 1B C-band Synthetic Aperture Radar (SAR) Interferometric Wide (IW), Instrument Processing Facility (IPF) v2", "abstract": "Composite process for Level 1 data from the C-band Synthetic Aperture Radar (SAR) deployed on Sentinel 1B. This consists of the Acquisition process for raw radar data from the Sentinel 1 SAR and the computation component to produce processed Level 1 radar data." }, "imageDetails": [ 148 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2586, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 49, "licenceURL": "https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 12321, "uuid": "7896ea1117dc4fa9bb95485ca9b1c6be", "short_code": "proj", "title": "Copernicus Programme", "abstract": "Copernicus, formerly known as the Global Monitoring for Environment and Security (GMES) programme, is headed by the European Commission (EC) in partnership with the European Space Agency (ESA). Within the Copernicus Space Component, ESA is developing a series of Sentinel satellite missions. Data from the Sentinel missions, as well as from Contributing Missions from other space agencies, are made freely available through a unified ground segment. Each Sentinel mission is comprised of a constallation of two or more satellites to fulfil the timeliness and reliability requirements of the Copernicus Services environmental monitoring and civil security activities. As well as operational and monitoring capabilities, the Sentinel missions will provide a wealth of Earth Observation data for scientific exploitation. The Sentinel 1 mission provides all weather, day and night radar imagery with scientific applications in sea-ice measurements, biomass observations and earthquake analysis. Sentinel 2 is a high resolution imaging mission to provide imagery of vegetation, soil and water cover, inland waterways and coastal areas. Sentinel 3 is a multi-instrument mission to measure sea-surface topography, sea- and land-surface temperature, ocean colour and land colour with high-end accuracy and reliability. Sentinel 4 is devoted to atmospheric monitoring and will be flown on a Meteosat Third Generation-Sounder (MTG-S) satellite in geostationary orbit. Sentinel 5 will monitor the atmosphere from polar orbit on board a MetOp Second Generation satellite. The Sentinel 5 precursor satellite mission is being developed to reduce data gaps between Envisat, in particular the Sciamachy instrument, and the launch of Sentinel 5. The Sentinel 5 mission will be dedicated to atmospheric monitoring. Sentinel 6 carries a radar altimeter to measure global sea-surface height, primarily for operational oceanography and for climate studies." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 22593, 22849 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 20016, "uuid": "356ae234d1ad4681a2dd2c599f21883c", "short_code": "coll", "title": "Sentinel 1B: C-band Synthetic Aperture Radar (SAR) data", "abstract": "This dataset collection contains radar data from the C-band Synthetic Aperture Radar (SAR) on the European Space Agency (ESA) Sentinel 1B satellite. Sentinel 1B was launched on 25th April 2016 and provides continuous all-weather, day and night imaging radar data. Three acquisition modes are available: Stripmap (SM), Interferometric Wide swath (IW), and Extra Wide swath (EW). The main operational mode is IW. The EW mode is primarily used for wide area coastal monitoring. The SM mode is only used on special request for extraordinary events such as emergency management. The SM, IW and EW modes are available in single (HH or VV) and dual (HH+HV or VV+VH) polarisation. The C-band Synthetic Aperture Radar images the Earth with enhanced frequency and revisit times obtaining full Earth coverage every two weeks. Timeliness and reliability is optimized for emergency response and operational applications with Europes’s coastal zones and shipping routes being monitored on a daily basis. The data has a wide range of scientific applications including sea-ice monitoring, imaging of forests and investigation into the carbon cycle, and the analysis of earthquakes. Data are provided by the European Space Agency (ESA) and are made available via CEDA to any registered scientific user in the UK." }, { "ob_id": 30129, "uuid": "3b0630c7fa264164868d4da5c9f90bed", "short_code": "coll", "title": "National Centre for Earth Observation (NCEO) Third Party Data", "abstract": "The National Centre for Earth Observation (NCEO) Third Party data contains a broad range remotely sensed data acquired by satellite for use by the Earth Observation Scientific community supported by NCEO. The Centre for Environmental Data Analysis (CEDA) has archived and provides access to extensive Earth observation datasets under strict licensing conditions. Please see the individual dataset records for conditions of use." } ], "responsiblepartyinfo_set": [ 146221, 76080, 76078, 105173, 76079, 76076, 76075, 76077, 76081, 76074, 146278 ], "onlineresource_set": [ 16583, 23918, 16585, 25334, 16586 ] }, { "ob_id": 20020, "uuid": "030067cfcb664bc0a6edd0542f801135", "title": "SPECS - MOHC-DePreSys3 model output prepared for SPECS decadal (1960-2005)", "abstract": "This dataset includes the Met Office DePreSys model output prepared for SPECS decadal (1960-2005). These data were prepared by the Met Office Hadley Centre, as part of the SPECS project. \r\n \r\nModel id is DePreSys3 (DePreSys3: HadGEM3-GC2 N216; atmosphere: UM (GA5.0) ; ocean: NEMO (v3.4, ORCA0.25) ; coupler: OASIS3 (v3.3); sea ice: CICE), frequency is daily and monthly. \r\n\r\nDaily Atmospheric variables are:\r\npr psl tas\r\n\r\nMonthly atmos variables:\r\nhfls hfss mrso pr psl rls rlut rsdt rss rsut ta tas ua va zg\r\n\r\nMonthly seaIce variables:\r\nsic sit \r\n\r\nOcean variables:\r\ntos", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-06-24T15:43:56.171591", "updateFrequency": "notPlanned", "dataLineage": "Data were supplied by SPECS participants to CEDA for archiving in 2015. Data was checked for compliance with CF standards and SPECS requirements.", "removedDataReason": "", "keywords": "specs, MOHC, DePreSys3, climate, model", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2016-09-29T11:39:28", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 528, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 26545, "dataPath": "/badc/specs/data/SPECS/output/MOHC/DePreSys3/decadal", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 589201933710, "numberOfFiles": 152442, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 3575, "startTime": "1992-04-24T23:00:00", "endTime": "2009-05-08T23:00:00" }, "resultQuality": { "ob_id": 3056, "explanation": " ", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2016-09-23" }, "validTimePeriod": { "ob_id": 5236, "startTime": "1960-11-01T00:00:00", "endTime": "2005-11-01T23:59:59" }, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 153 ], "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": 12970, "uuid": "c9b4b1fcab734987bcbfb36437734ca7", "short_code": "proj", "title": "Seasonal-to-decadal climate Prediction for the improvement of European Climate Services (SPECS)", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nThe improved understanding and seamless predictions will offer better estimates of the future frequency of high-impact, extreme climatic events and of the prediction uncertainty. New services to convey climate information and its quality will be used.\r\n\r\nSPECS will be, among other things, the glue to coalesce the outcome of previous research efforts that hardly took climate prediction into account. It will ensure interoperability so as to easily incorporate their application in an operational context, provide the basis for improving the capacity of European policy making, industry and society to adapt to near-future climate variations and a coordinated response to some of the GFCS components.\r\n\r\nThis project is funded by the Seventh Framework Programme (FP7) of the European Commission (GA 308378)." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6023, 12334, 12335, 12336, 19039, 19043, 50426, 50429, 50431, 50475, 50496, 50498, 50554, 50555, 50566, 50591, 50596, 50623, 50624, 52741, 52748, 53094, 53095, 53105, 53107, 53109, 53112, 53133, 53134, 55976, 55977, 55978, 55979, 55980 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 6086, "uuid": "2d9c5f2cc621fb9bc0062356851b31b9", "short_code": "coll", "title": "SPECS: Seasonal-to-decadal climate prediction model outputs", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nA core set of common experiments has been defined, to which most forecast systems will contribute. Another set of coordinated experiments, tier 1, includes the experiments that one or more forecast systems are planning to run. \r\n\r\nA standard seasonal experimental set up will consist of ten-member ensembles, with two start dates per year (first of May and November) over the 1981-2012 period and seven-month forecast length. \r\n\r\nThe standard decadal experimental set up consists in five-member ensembles, starting on the first of November (or some time close to that date) of the years 1960, 1963, 1965, 1968, 1970, 1973, 1975, 1978, 1980, 1983, 1985, 1988, 1990, 1993, 1995, 1998, 2000, 2003, 2005, 2008, 2010, 2013, with a five-year forecast length. \r\n\r\nA description of the main experiments, with the minimum contribution in terms of start dates, forecast length and ensemble size follows: \r\n1 - Assessment of the impact of soil-moisture initial conditions (seasonal): contributing EC-Earth, IFS/NEMO (ECMWF), CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG);\r\n2 - Assessment of the impact of sea-ice initialization (interannual); contributing EC-Earth (IC3), IPSL-CM5, CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG)\r\n3 - Assessment of impact of increased horizontal resolution (seasonal and decadal); contributing CNRM-CM5 (CERFACS, decadal; MeteoF, seasonal), EC-Earth (IC3, seasonal; KNMI and SMHI, decadal), MPI-ESM (MPG, seasonal and decadal), IPSL-CM5 (decadal), UM (seasonal and decadal); \r\n4 - Assessment of impact of an improved stratosphere (seasonal and decadal) including interannually-varying ozone; contributing EC-Earth (KNMI seasonal with ozone; SMHI decadal), IFS/NEMO (ECMWF, seasonal), CNRM-CM5 (MeteoF, seasonal), UM (seasonal, decadal);\r\n5 - Assessment of impact of additional start dates (decadal); contributing EC-Earth (KNMI, SMHI), MPI-ESM (MPG), IPSL-CM5.\r\n\r\nSPECS research has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under SPECS project (grant agreement n° 308378)." } ], "responsiblepartyinfo_set": [ 76109, 76101, 76108, 76107, 76105, 76104, 76102, 76103, 76106, 76110, 76111 ], "onlineresource_set": [] }, { "ob_id": 20021, "uuid": "c2a5a9351cf64dd3837ad68944086333", "title": "SPECS - MPI-ESM-LR model output prepared for SPECS seaIceInit (1991-2012)", "abstract": "This dataset includes the MPI-ESM-LR model output prepared for SPECS seaIceInit (1991-2012). These data were prepared by the Max Planck Institute for Meteorology (MPI-M), as part of the SPECS project. \r\n \r\nModel id is MPI-ESM-LR (MPI-ESM-LR 2013; atmosphere: ECHAM6 v6.1.0.0 (REV: 2595), T63L47; land: JSBACH (REV: v2.01); ocean: MPIOM (REV: 3151) marine biogeochemistry HAMOCC included, GR15L40; sea ice (REV: 3151): . Frequency is daily and monthly. \r\n\r\nDaily Atmospheric variables are:\r\nclt hfls hfss mrso pr prc psl rlds rlut rsds tas uas vas\r\n\r\nMonthly atmos variables:\r\nhus pr psl ta tas ua va zg\r\n\r\nMonthly ocean variables:\r\nmlotst tos\r\n\r\nMonthly land variables:\r\nmrro mrso\r\n", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-03-03T16:38:34.891787", "updateFrequency": "notPlanned", "dataLineage": "Data were supplied by SPECS participants to CEDA for archiving in 2015. Data was checked for compliance with CF standards and SPECS requirements.", "removedDataReason": "", "keywords": "specs, MPI-ESM, climate, model", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2016-09-27T13:59:39", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 528, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 20023, "dataPath": "/badc/specs/data/SPECS/output/MPI-M/MPI-ESM-LR/seaIceInit", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 261440189621, "numberOfFiles": 47307, "fileFormat": "The data are provided in a CF-compliant NetCDF format." }, "timePeriod": { "ob_id": 5238, "startTime": "1991-04-30T23:00:00", "endTime": "2012-05-01T22:59:59" }, "resultQuality": { "ob_id": 3059, "explanation": " ", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2016-09-23" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 153 ], "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": 12970, "uuid": "c9b4b1fcab734987bcbfb36437734ca7", "short_code": "proj", "title": "Seasonal-to-decadal climate Prediction for the improvement of European Climate Services (SPECS)", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nThe improved understanding and seamless predictions will offer better estimates of the future frequency of high-impact, extreme climatic events and of the prediction uncertainty. New services to convey climate information and its quality will be used.\r\n\r\nSPECS will be, among other things, the glue to coalesce the outcome of previous research efforts that hardly took climate prediction into account. It will ensure interoperability so as to easily incorporate their application in an operational context, provide the basis for improving the capacity of European policy making, industry and society to adapt to near-future climate variations and a coordinated response to some of the GFCS components.\r\n\r\nThis project is funded by the Seventh Framework Programme (FP7) of the European Commission (GA 308378)." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6021, 6022, 6023, 6255, 11044, 11045, 50426, 50427, 50429, 50431, 50475, 50496, 50498, 50559, 50561, 50566, 50568, 50569, 50579, 50589, 50591, 50592, 50596, 50598, 52741, 52747, 52748, 53094, 53107, 53108, 53109, 53113, 53128, 53129, 53130, 53131, 53143, 54228, 54265, 54796, 54797, 54798, 54799, 79918, 82362 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 6086, "uuid": "2d9c5f2cc621fb9bc0062356851b31b9", "short_code": "coll", "title": "SPECS: Seasonal-to-decadal climate prediction model outputs", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nA core set of common experiments has been defined, to which most forecast systems will contribute. Another set of coordinated experiments, tier 1, includes the experiments that one or more forecast systems are planning to run. \r\n\r\nA standard seasonal experimental set up will consist of ten-member ensembles, with two start dates per year (first of May and November) over the 1981-2012 period and seven-month forecast length. \r\n\r\nThe standard decadal experimental set up consists in five-member ensembles, starting on the first of November (or some time close to that date) of the years 1960, 1963, 1965, 1968, 1970, 1973, 1975, 1978, 1980, 1983, 1985, 1988, 1990, 1993, 1995, 1998, 2000, 2003, 2005, 2008, 2010, 2013, with a five-year forecast length. \r\n\r\nA description of the main experiments, with the minimum contribution in terms of start dates, forecast length and ensemble size follows: \r\n1 - Assessment of the impact of soil-moisture initial conditions (seasonal): contributing EC-Earth, IFS/NEMO (ECMWF), CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG);\r\n2 - Assessment of the impact of sea-ice initialization (interannual); contributing EC-Earth (IC3), IPSL-CM5, CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG)\r\n3 - Assessment of impact of increased horizontal resolution (seasonal and decadal); contributing CNRM-CM5 (CERFACS, decadal; MeteoF, seasonal), EC-Earth (IC3, seasonal; KNMI and SMHI, decadal), MPI-ESM (MPG, seasonal and decadal), IPSL-CM5 (decadal), UM (seasonal and decadal); \r\n4 - Assessment of impact of an improved stratosphere (seasonal and decadal) including interannually-varying ozone; contributing EC-Earth (KNMI seasonal with ozone; SMHI decadal), IFS/NEMO (ECMWF, seasonal), CNRM-CM5 (MeteoF, seasonal), UM (seasonal, decadal);\r\n5 - Assessment of impact of additional start dates (decadal); contributing EC-Earth (KNMI, SMHI), MPI-ESM (MPG), IPSL-CM5.\r\n\r\nSPECS research has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under SPECS project (grant agreement n° 308378)." } ], "responsiblepartyinfo_set": [ 76116, 76117, 76113, 76132, 76131, 76130, 76120, 76119, 76114, 76112, 76118, 76129, 76115 ], "onlineresource_set": [] }, { "ob_id": 20022, "uuid": "275dfa6961464bfdada866b156f2605a", "title": "Sentinel 1B C-band Synthetic Aperture Radar (SAR): Extra Wide (EW) mode Ground Range Detected (GRD) Medium Resolution (MR) Level 1 data", "abstract": "This dataset contains Extra Wide swath (EW) Ground Range Detected (GRD) Medium Resolution (MR) C-band Synthetic Aperture Radar (SAR) data from the European Space Agency (ESA) Sentinel 1B satellite. Sentinel 1A was launched on 25th April 2016 and provides continuous all-weather, day and night imaging radar data. The EW mode is primarily used for wide-area coastal monitoring. The EW mode supports single (HH or VV) and dual (HH+HV or VV+VH) polarisation. These data are available via CEDA to any registered user in the UK.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2020-05-29T20:30:41", "updateFrequency": "asNeeded", "dataLineage": "Data collected and prepared by European Space Agency (ESA). Downloaded from the Collaborative Hub for use by the UK scientific community.", "removedDataReason": "", "keywords": "Sentinel, radar, Synthetic Aperture Radar, SAR, Extra Wide, EW, Ground Range Detected, GRD", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2022-10-26T14:02:18", "doiPublishedTime": null, "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": 20032, "dataPath": "/neodc/sentinel1b/data/EW/L1_GRD/m/IPF_v2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 12543638216111, "numberOfFiles": 240826, "fileFormat": "Image data files are in a binary format. Quicklook images are in png format. 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This consists of the Acquisition process for raw radar data from the Sentinel 1 SAR and the computation component to produce processed Level 1 radar data." }, "imageDetails": [ 148 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2586, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 49, "licenceURL": "https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 12321, "uuid": "7896ea1117dc4fa9bb95485ca9b1c6be", "short_code": "proj", "title": "Copernicus Programme", "abstract": "Copernicus, formerly known as the Global Monitoring for Environment and Security (GMES) programme, is headed by the European Commission (EC) in partnership with the European Space Agency (ESA). Within the Copernicus Space Component, ESA is developing a series of Sentinel satellite missions. Data from the Sentinel missions, as well as from Contributing Missions from other space agencies, are made freely available through a unified ground segment. Each Sentinel mission is comprised of a constallation of two or more satellites to fulfil the timeliness and reliability requirements of the Copernicus Services environmental monitoring and civil security activities. As well as operational and monitoring capabilities, the Sentinel missions will provide a wealth of Earth Observation data for scientific exploitation. The Sentinel 1 mission provides all weather, day and night radar imagery with scientific applications in sea-ice measurements, biomass observations and earthquake analysis. Sentinel 2 is a high resolution imaging mission to provide imagery of vegetation, soil and water cover, inland waterways and coastal areas. Sentinel 3 is a multi-instrument mission to measure sea-surface topography, sea- and land-surface temperature, ocean colour and land colour with high-end accuracy and reliability. Sentinel 4 is devoted to atmospheric monitoring and will be flown on a Meteosat Third Generation-Sounder (MTG-S) satellite in geostationary orbit. Sentinel 5 will monitor the atmosphere from polar orbit on board a MetOp Second Generation satellite. The Sentinel 5 precursor satellite mission is being developed to reduce data gaps between Envisat, in particular the Sciamachy instrument, and the launch of Sentinel 5. The Sentinel 5 mission will be dedicated to atmospheric monitoring. Sentinel 6 carries a radar altimeter to measure global sea-surface height, primarily for operational oceanography and for climate studies." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 25947, 25995 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 20016, "uuid": "356ae234d1ad4681a2dd2c599f21883c", "short_code": "coll", "title": "Sentinel 1B: C-band Synthetic Aperture Radar (SAR) data", "abstract": "This dataset collection contains radar data from the C-band Synthetic Aperture Radar (SAR) on the European Space Agency (ESA) Sentinel 1B satellite. Sentinel 1B was launched on 25th April 2016 and provides continuous all-weather, day and night imaging radar data. Three acquisition modes are available: Stripmap (SM), Interferometric Wide swath (IW), and Extra Wide swath (EW). The main operational mode is IW. The EW mode is primarily used for wide area coastal monitoring. The SM mode is only used on special request for extraordinary events such as emergency management. The SM, IW and EW modes are available in single (HH or VV) and dual (HH+HV or VV+VH) polarisation. The C-band Synthetic Aperture Radar images the Earth with enhanced frequency and revisit times obtaining full Earth coverage every two weeks. Timeliness and reliability is optimized for emergency response and operational applications with Europes’s coastal zones and shipping routes being monitored on a daily basis. The data has a wide range of scientific applications including sea-ice monitoring, imaging of forests and investigation into the carbon cycle, and the analysis of earthquakes. Data are provided by the European Space Agency (ESA) and are made available via CEDA to any registered scientific user in the UK." }, { "ob_id": 30129, "uuid": "3b0630c7fa264164868d4da5c9f90bed", "short_code": "coll", "title": "National Centre for Earth Observation (NCEO) Third Party Data", "abstract": "The National Centre for Earth Observation (NCEO) Third Party data contains a broad range remotely sensed data acquired by satellite for use by the Earth Observation Scientific community supported by NCEO. The Centre for Environmental Data Analysis (CEDA) has archived and provides access to extensive Earth observation datasets under strict licensing conditions. Please see the individual dataset records for conditions of use." } ], "responsiblepartyinfo_set": [ 146223, 76126, 76121, 76127, 76125, 143591, 76123, 76122, 76128, 76124, 146224 ], "onlineresource_set": [ 16591, 16592, 23914, 16593 ] }, { "ob_id": 20024, "uuid": "74cc15faa27b4e86acb8f54c4e704dcd", "title": "SPECS - MPI-ESM-LR model output prepared for SPECS soilMoistureInit (1981-2012)", "abstract": "This dataset includes the MPI-ESM-LR model output prepared for SPECS soilMoistureInit (1981-2012). These data were prepared by the Max Planck Institute for Meteorology (MPI-M), as part of the SPECS project. \r\n \r\nModel id is MPI-ESM-LR (MPI-ESM-LR 2015; atmosphere: ECHAM6 v6.3.01p2 (REV: 3904), T63L47; land: JSBACH (REV: 3904); ocean: MPIOM v1.6.1p1 (REV: 3753) marine biogeochemistry HAMOCC included, GR15L40; sea ice (REV: 3753). Frequency is daily and monthly. \r\n\r\nDaily Atmospheric variables are:\r\nclt hfls hfss mrso pr prc psl rlds rlut rsds tas uas vas\r\n\r\nMonthly atmos variables:\r\nhus pr psl ta tas ua va zg\r\n\r\nMonthly ocean variables:\r\nmlotst tos\r\n\r\nMonthly land variables:\r\nmrro mrso\r\n", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-01-22T03:04:15", "updateFrequency": "notPlanned", "dataLineage": "Data were supplied by SPECS participants to CEDA for archiving in 2015. Data was checked for compliance with CF standards and SPECS requirements.", "removedDataReason": "", "keywords": "specs, MPI-ESM, climate, model", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2016-09-27T13:59:56", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 528, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 20026, "dataPath": "/badc/specs/data/SPECS/output/MPI-M/MPI-ESM-LR/soilMoistureInit", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1002907213309, "numberOfFiles": 179201, "fileFormat": "The data are provided in a CF-compliant NetCDF format." }, "timePeriod": { "ob_id": 5239, "startTime": "1901-01-01T00:00:00", "endTime": "2015-12-31T23:59:59" }, "resultQuality": { "ob_id": 3058, "explanation": " Data have been quality controlled by CEDA, including internal metadata consistency for SPECS data is complete and that data are CF-compliant.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2016-09-23" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 153 ], "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": 12970, "uuid": "c9b4b1fcab734987bcbfb36437734ca7", "short_code": "proj", "title": "Seasonal-to-decadal climate Prediction for the improvement of European Climate Services (SPECS)", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nThe improved understanding and seamless predictions will offer better estimates of the future frequency of high-impact, extreme climatic events and of the prediction uncertainty. New services to convey climate information and its quality will be used.\r\n\r\nSPECS will be, among other things, the glue to coalesce the outcome of previous research efforts that hardly took climate prediction into account. It will ensure interoperability so as to easily incorporate their application in an operational context, provide the basis for improving the capacity of European policy making, industry and society to adapt to near-future climate variations and a coordinated response to some of the GFCS components.\r\n\r\nThis project is funded by the Seventh Framework Programme (FP7) of the European Commission (GA 308378)." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6021, 6022, 6023, 6255, 11044, 11045, 50426, 50427, 50429, 50431, 50475, 50496, 50498, 50559, 50561, 50566, 50568, 50569, 50579, 50589, 50591, 50596, 50598, 52741, 52747, 52748, 53094, 53095, 53107, 53108, 53109, 53113, 53128, 53129, 53130, 53131, 53143, 54228, 54265, 54796, 54797, 54798, 54799 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 6086, "uuid": "2d9c5f2cc621fb9bc0062356851b31b9", "short_code": "coll", "title": "SPECS: Seasonal-to-decadal climate prediction model outputs", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nA core set of common experiments has been defined, to which most forecast systems will contribute. Another set of coordinated experiments, tier 1, includes the experiments that one or more forecast systems are planning to run. \r\n\r\nA standard seasonal experimental set up will consist of ten-member ensembles, with two start dates per year (first of May and November) over the 1981-2012 period and seven-month forecast length. \r\n\r\nThe standard decadal experimental set up consists in five-member ensembles, starting on the first of November (or some time close to that date) of the years 1960, 1963, 1965, 1968, 1970, 1973, 1975, 1978, 1980, 1983, 1985, 1988, 1990, 1993, 1995, 1998, 2000, 2003, 2005, 2008, 2010, 2013, with a five-year forecast length. \r\n\r\nA description of the main experiments, with the minimum contribution in terms of start dates, forecast length and ensemble size follows: \r\n1 - Assessment of the impact of soil-moisture initial conditions (seasonal): contributing EC-Earth, IFS/NEMO (ECMWF), CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG);\r\n2 - Assessment of the impact of sea-ice initialization (interannual); contributing EC-Earth (IC3), IPSL-CM5, CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG)\r\n3 - Assessment of impact of increased horizontal resolution (seasonal and decadal); contributing CNRM-CM5 (CERFACS, decadal; MeteoF, seasonal), EC-Earth (IC3, seasonal; KNMI and SMHI, decadal), MPI-ESM (MPG, seasonal and decadal), IPSL-CM5 (decadal), UM (seasonal and decadal); \r\n4 - Assessment of impact of an improved stratosphere (seasonal and decadal) including interannually-varying ozone; contributing EC-Earth (KNMI seasonal with ozone; SMHI decadal), IFS/NEMO (ECMWF, seasonal), CNRM-CM5 (MeteoF, seasonal), UM (seasonal, decadal);\r\n5 - Assessment of impact of additional start dates (decadal); contributing EC-Earth (KNMI, SMHI), MPI-ESM (MPG), IPSL-CM5.\r\n\r\nSPECS research has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under SPECS project (grant agreement n° 308378)." } ], "responsiblepartyinfo_set": [ 76142, 76143, 76145, 76140, 76139, 76138, 76137, 76135, 76134, 76133, 76144, 76136, 76141 ], "onlineresource_set": [] }, { "ob_id": 20025, "uuid": "ac7ade0c3a7b4444867e7e46959ee385", "title": "Sentinel 1B C-band Synthetic Aperture Radar (SAR): Interferometric Wide (IW) mode Ground Range Detected (GRD) High Resolution (HR) Level 1 data", "abstract": "This dataset contains Interferometric Wide swath (IW) Ground Range Detected (GRD) High Resolution (HR) C-band Synthetic Aperture Radar (SAR) data from the European Space Agency (ESA) Sentinel 1B satellite. Sentinel 1B was launched on 25th April 2016 and provides continuous all-weather, day and night imaging radar data. The IW mode is the main operational mode. The IW mode supports single (HH or VV) and dual (HH+HV or VV+VH) polarisation. These data are available via CEDA to any registered user.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2022-07-16T12:03:54", "updateFrequency": "asNeeded", "dataLineage": "Data collected and prepared by European Space Agency (ESA). Downloaded from the Collaborative Hub for use by the UK scientific community.", "removedDataReason": "", "keywords": "Sentinel, radar, Synthetic Aperture Radar, SAR, Interferometric Wide, IW, Ground Range Detected, GRD", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2016-09-26T23:00:00", "doiPublishedTime": null, "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": 20033, "dataPath": "/neodc/sentinel1b/data/IW/L1_GRD/h/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 104584916166009, "numberOfFiles": 621960, "fileFormat": "Image data files are in a binary format. Quicklook images are in png format. Manifest files with relevant metadata are in SAFE format." }, "timePeriod": { "ob_id": 3588, "startTime": "2015-01-21T00:00:00", "endTime": null }, "resultQuality": { "ob_id": 3004, "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": "2014-09-28" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 20019, "uuid": "4f2cbf03e45046e2b1b8cd27c89b5b3c", "short_code": "cmppr", "title": "Composite Process for: Level 1 data from the Sentinel 1B C-band Synthetic Aperture Radar (SAR) Interferometric Wide (IW), Instrument Processing Facility (IPF) v2", "abstract": "Composite process for Level 1 data from the C-band Synthetic Aperture Radar (SAR) deployed on Sentinel 1B. This consists of the Acquisition process for raw radar data from the Sentinel 1 SAR and the computation component to produce processed Level 1 radar data." }, "imageDetails": [ 148 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2586, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 49, "licenceURL": "https://sentinel.esa.int/documents/247904/690755/Sentinel_Data_Legal_Notice", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 12321, "uuid": "7896ea1117dc4fa9bb95485ca9b1c6be", "short_code": "proj", "title": "Copernicus Programme", "abstract": "Copernicus, formerly known as the Global Monitoring for Environment and Security (GMES) programme, is headed by the European Commission (EC) in partnership with the European Space Agency (ESA). Within the Copernicus Space Component, ESA is developing a series of Sentinel satellite missions. Data from the Sentinel missions, as well as from Contributing Missions from other space agencies, are made freely available through a unified ground segment. Each Sentinel mission is comprised of a constallation of two or more satellites to fulfil the timeliness and reliability requirements of the Copernicus Services environmental monitoring and civil security activities. As well as operational and monitoring capabilities, the Sentinel missions will provide a wealth of Earth Observation data for scientific exploitation. The Sentinel 1 mission provides all weather, day and night radar imagery with scientific applications in sea-ice measurements, biomass observations and earthquake analysis. Sentinel 2 is a high resolution imaging mission to provide imagery of vegetation, soil and water cover, inland waterways and coastal areas. Sentinel 3 is a multi-instrument mission to measure sea-surface topography, sea- and land-surface temperature, ocean colour and land colour with high-end accuracy and reliability. Sentinel 4 is devoted to atmospheric monitoring and will be flown on a Meteosat Third Generation-Sounder (MTG-S) satellite in geostationary orbit. Sentinel 5 will monitor the atmosphere from polar orbit on board a MetOp Second Generation satellite. The Sentinel 5 precursor satellite mission is being developed to reduce data gaps between Envisat, in particular the Sciamachy instrument, and the launch of Sentinel 5. The Sentinel 5 mission will be dedicated to atmospheric monitoring. Sentinel 6 carries a radar altimeter to measure global sea-surface height, primarily for operational oceanography and for climate studies." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 25947, 25995 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 20016, "uuid": "356ae234d1ad4681a2dd2c599f21883c", "short_code": "coll", "title": "Sentinel 1B: C-band Synthetic Aperture Radar (SAR) data", "abstract": "This dataset collection contains radar data from the C-band Synthetic Aperture Radar (SAR) on the European Space Agency (ESA) Sentinel 1B satellite. Sentinel 1B was launched on 25th April 2016 and provides continuous all-weather, day and night imaging radar data. Three acquisition modes are available: Stripmap (SM), Interferometric Wide swath (IW), and Extra Wide swath (EW). The main operational mode is IW. The EW mode is primarily used for wide area coastal monitoring. The SM mode is only used on special request for extraordinary events such as emergency management. The SM, IW and EW modes are available in single (HH or VV) and dual (HH+HV or VV+VH) polarisation. The C-band Synthetic Aperture Radar images the Earth with enhanced frequency and revisit times obtaining full Earth coverage every two weeks. Timeliness and reliability is optimized for emergency response and operational applications with Europes’s coastal zones and shipping routes being monitored on a daily basis. The data has a wide range of scientific applications including sea-ice monitoring, imaging of forests and investigation into the carbon cycle, and the analysis of earthquakes. Data are provided by the European Space Agency (ESA) and are made available via CEDA to any registered scientific user in the UK." }, { "ob_id": 30129, "uuid": "3b0630c7fa264164868d4da5c9f90bed", "short_code": "coll", "title": "National Centre for Earth Observation (NCEO) Third Party Data", "abstract": "The National Centre for Earth Observation (NCEO) Third Party data contains a broad range remotely sensed data acquired by satellite for use by the Earth Observation Scientific community supported by NCEO. The Centre for Environmental Data Analysis (CEDA) has archived and provides access to extensive Earth observation datasets under strict licensing conditions. Please see the individual dataset records for conditions of use." } ], "responsiblepartyinfo_set": [ 146222, 76149, 76152, 105172, 76146, 76151, 76148, 76147, 76150, 76153, 146279 ], "onlineresource_set": [ 16596, 16597, 16598, 23915, 25353 ] }, { "ob_id": 20027, "uuid": "3b680883c88b4bfb9e80542ed5b3f1e8", "title": "Environmental Baseline Project: Surface meteorological measurements from Kirby Misperton", "abstract": "This dataset contains wind speed and direction, pressure, temperature and humidity measurements for the Kirby Misperton site.\r\n\r\nBritish Geological Survey (BGS), the universities of Birmingham, Bristol, Liverpool, Manchester and York and partners from Public Health England (PHE) and the Department for Business, Energy and Industrial Strategy (BEIS), are conducting an independent environmental baseline monitoring programme near Kirby Misperton, North Yorkshire and Little Plumpton, Lancashire. These are areas where planning permission has been granted for hydraulic fracturing.\r\n\r\nThe monitoring allows the characterisation of the environmental baseline before any hydraulic fracturing and gas exploration or production takes place in the event that planning permission is granted. 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This is the area where North Yorkshire County Council has granted planning permission to Third Energy to hydraulically fracture one of their wells.\r\n\r\nThe monitoring allows the characterisation of the environmental baseline before any hydraulic fracturing and gas exploration or production takes place in the event that planning permission is granted. The investigations are independent of any monitoring carried out by the industry or the regulators, and information collected from the programme will be made freely available to the public. \r\n\r\nThe monitoring in and around the Vale of Pickering and Lancashire includes:\r\n\r\n water quality (groundwater and surface water)\r\n seismicity\r\n ground motion\r\n air quality\r\n radon\r\n soil gas" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 21769, 52651 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 19978, "uuid": "17381cd841ba46aca622307cdcf95da7", "short_code": "coll", "title": "Environmental Baseline Project: Air quality, greenhouse gas, Volatile Organic Compounds (VOCs) and surface meteorological measurements from Kirby Misperton and Little Plumpton", "abstract": "This dataset collection contains air quality, greenhouse gas, Volatile Organic Compounds (VOCs) and surface meteorological measurements for the Kirby Misperton site and Little Plumpton.\r\n\r\nBritish Geological Survey (BGS), the universities of Birmingham, Bristol, Liverpool, Manchester and York and partners from Public Health England (PHE) and the Department for Business, Energy and Industrial Strategy (BEIS), are conducting an independent environmental baseline monitoring programme near Kirby Misperton, North Yorkshire and Little Plumpton, Lancashire. 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Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19730101-20131231_v1-0-2-2013f.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep up to date with 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 HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-10-10T09:37:05.831192", "updateFrequency": "notPlanned", "dataLineage": "HadISD the global sub-daily station dataset is produced by the Met Office Hadley Centre. It is based on the ISD dataset from NOAA's NCDC. HadISD has been passed to the BADC for archiving and distribution.", "removedDataReason": "", "keywords": "HadISD, cloud data", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2016-10-11T09:19:31", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 20038, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISD/subdaily/HadISDTable/r1/v1-0-2-2013f", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 7727928098, "numberOfFiles": 6104, "fileFormat": "The data are provided in NetCDF format." }, "timePeriod": { "ob_id": 9611, "startTime": "1973-01-01T00:00:00", "endTime": "2013-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 3862, "uuid": "c8a8c946e63a421987db316acb8384f1", "short_code": "comp", "title": "HadISD station data processing performed at the Met Office Hadley Centre", "abstract": "The HadISD station data were produced by the Met Office Hadley Centre. Individual station data within the ISD were selected to be merged to form composite stations using a hierarchical scoring system. Then stations were selected on the basis of their length of record and reporting frequency. A final set of 6103 stations were passed through a suite of automated quality control tests designed to remove bad data whilst keeping the extremes. None of the ISD flags were used in this process. The QC tests focussed on the temperature, dewpoint temperature and sea-level pressure variables, although some were applied to the wind speed and direction and cloud data. The data files also contain other variables which were pulled through from the raw ISD record, but have had no QC applied (e.g. cloud base and precipitation depth). Some final filtering was performed to select those stations which in our opinion are most useful for climate studies. Note: These data have not yet been homogenised and so trend fitting should be undertaken with caution. The homogeneity has been assessed and results are available from the Met Office Hadley Centre HadISD website (http://www.metoffice.gov.uk/hadobs/hadisd/) For further details see: Dunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Climate of the Past and Dunn, R. J. H., et al. (2014), Pairwise Homogeneity Assessment of HadISD, Climate of the Past, 10, 1501-1522 (see Docs for links to publications)." }, "procedureCompositeProcess": null, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "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": [ 1050, 12419, 12420, 12421, 12422, 12423, 12424, 12425, 12427, 12428, 12429, 12430, 12432, 12433, 12434, 12435, 12436, 12437, 12438, 25956 ], "vocabularyKeywords": [ { "ob_id": 6525, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0023/", "resolvedTerm": "air_temperature" }, { "ob_id": 6923, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0747/", "resolvedTerm": "cloud_base_altitude" }, { "ob_id": 6524, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0723/", "resolvedTerm": "dew_point_temperature" }, { "ob_id": 6555, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0036/", "resolvedTerm": "wind_from_direction" }, { "ob_id": 6573, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0039/", "resolvedTerm": "wind_speed_of_gust" }, { "ob_id": 6570, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0745/", "resolvedTerm": "cloud_area_fraction" }, { "ob_id": 8128, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0569/", "resolvedTerm": "lwe_thickness_of_precipitation_amount" }, { "ob_id": 6556, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0038/", "resolvedTerm": "wind_speed" }, { "ob_id": 6568, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0022/", "resolvedTerm": "air_pressure_at_sea_level" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 13521, "uuid": "f579035b3c954475922e4b13705a7669", "short_code": "coll", "title": "HadISD: global sub-daily station data for climate extremes", "abstract": "HadISD is a station based dataset comprising 6103 stations covering 1973-present. These stations are a subset of the stations available in the Integrated Surface Database (ISD), and are ones selected to be those most useful for climate studies (long records and high reporting frequency). Individual stations within the ISD were composited when it was appropriate to do so to improve the coverage.\r\n \r\nHadISD is a multi-variate dataset, where the following fields are available: temperature, dewpoint temperature, sea-level pressure, wind speed, wind direction and cloud data (total, low, mid and high levels). These variables are all quality controlled using an automatic suite of tests, the code for which is available on request. The QC tests were designed to remove bad data whilst keeping true extremes. A number of other variables are also carried through to the final NetCDF files, but have not been quality controlled (e.g. precipitation period, precipitation depth, sunshine duration)." } ], "responsiblepartyinfo_set": [ 76227, 108760, 76220, 76225, 76224, 76222, 76221, 76219, 76218, 76226, 76223, 168102, 168103, 76229, 76228, 168104 ], "onlineresource_set": [ 16824, 16825, 16631, 16629, 16632, 16633, 16630 ] }, { "ob_id": 20041, "uuid": "c1b593ad0a9945e18fa8d975908f19f0", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2015, v2.0.0.2015p", "abstract": "This is version 2.0.0.2015p of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data that extends HadISD v1.0.4.2015p to span 1931-2015 and includes an increase in the number of stations and an updated methodology. \r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20151231_v2-0-0-2015p.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep up to date with 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 HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2019-05-20T12:59:56", "updateFrequency": "notPlanned", "dataLineage": "HadISD the global sub-daily station dataset was produced by the Met Office Hadley Centre. It was derived from the Integrated Surface Dataset (ISD) from NOAA's National Climatic Data Center (NCDC). HadISD has been passed to the BADC for archiving and distribution.", "removedDataReason": "", "keywords": "HadISD, cloud data", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2016-10-19T07:55:00", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 20042, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISD/subdaily/HadISDTable/r1/v2-0-0-2015p", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 31881886594, "numberOfFiles": 7693, "fileFormat": "The data are provided in NetCDF format." }, "timePeriod": { "ob_id": 5246, "startTime": "1931-01-01T00:00:00", "endTime": "2015-12-31T23:59:59" }, "resultQuality": { "ob_id": 3066, "explanation": "CF-Compliant NetCDF, see documentation for quality control processes used to produce these data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2016-10-10" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 20043, "uuid": "32eff53af32442d1a347da2cc45bb9db", "short_code": "comp", "title": "HadISD station data processing performed at the Met Office Hadley Centre", "abstract": "The HadISD station data were produced by the Met Office Hadley Centre. Individual station data within the ISD were selected selected on the basis of their length of record and reporting frequency. A merging algorithm using their location, elevation and station name identified candidates suitable to combine together. All stations were passed through a suite of automated quality control tests designed to remove bad data whilst keeping the extremes. None of the ISD flags were used in this process. The QC tests focussed on the temperature, dewpoint temperature and sea-level pressure variables, although some were applied to the wind speed and direction and cloud data. The data files also contain other variables which were pulled through from the raw ISD record, but have had no QC applied (e.g. cloud base and precipitation depth). \r\n\r\nNotes:\r\n1. These data have not yet been homogenised and so trend fitting should be undertaken with caution. The homogeneity has been assessed and results are available from the Met Office Hadley Centre HadISD website: http://www.metoffice.gov.uk/hadobs/hadisd/. \r\n2. A long-standing bug (affecting versions v2.0.2_2017p through to v3.3.0.2022f), was discovered in autumn 2023 whereby the neighbour checks (and associated [un]flagging for some other tests) were not being implemented. This was corrected for the later version v3.4.0.2023f to HadISD. For more details see the posts on the HadISD blog: https://hadisd.blogspot.com/2023/10/bug-in-buddy-checks.html & https://hadisd.blogspot.com/2024/01/hadisd-v3402023f-future-look.html(v2.0.2_2017p through to v3.3.0.2022f), and as noted this has been fixed for v3.4.02023f.\r\n\r\n\r\nFor further details see: \r\nDunn, R. J. H., et al., (2016), Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geoscientific Instrumentation, Methods and Data Systems, and Dunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations\r\nfrom 1973-2011, Climate of the Past.\r\nDunn, R. J. H., et al. (2014), Pairwise Homogeneity Assessment of HadISD, Climate of the Past, 10, 1501-1522 (see Docs for links to publications)." }, "procedureCompositeProcess": null, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "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": [ 12419, 12420, 12421, 12436, 18926, 18927, 18928, 18929, 18930, 18931, 18932, 18933, 18934, 18935, 18936, 18937, 18938, 18939, 18940, 18942, 18943, 25956 ], "vocabularyKeywords": [ { "ob_id": 6555, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0036/", "resolvedTerm": "wind_from_direction" }, { "ob_id": 6568, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0022/", "resolvedTerm": "air_pressure_at_sea_level" }, { "ob_id": 6525, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0023/", "resolvedTerm": "air_temperature" }, { "ob_id": 8128, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0569/", "resolvedTerm": "lwe_thickness_of_precipitation_amount" }, { "ob_id": 6573, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0039/", "resolvedTerm": "wind_speed_of_gust" }, { "ob_id": 6524, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0723/", "resolvedTerm": "dew_point_temperature" }, { "ob_id": 6923, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0747/", "resolvedTerm": "cloud_base_altitude" }, { "ob_id": 6570, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0745/", "resolvedTerm": "cloud_area_fraction" }, { "ob_id": 6556, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/P07/current/CFSN0038/", "resolvedTerm": "wind_speed" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 13521, "uuid": "f579035b3c954475922e4b13705a7669", "short_code": "coll", "title": "HadISD: global sub-daily station data for climate extremes", "abstract": "HadISD is a station based dataset comprising 6103 stations covering 1973-present. These stations are a subset of the stations available in the Integrated Surface Database (ISD), and are ones selected to be those most useful for climate studies (long records and high reporting frequency). Individual stations within the ISD were composited when it was appropriate to do so to improve the coverage.\r\n \r\nHadISD is a multi-variate dataset, where the following fields are available: temperature, dewpoint temperature, sea-level pressure, wind speed, wind direction and cloud data (total, low, mid and high levels). These variables are all quality controlled using an automatic suite of tests, the code for which is available on request. The QC tests were designed to remove bad data whilst keeping true extremes. A number of other variables are also carried through to the final NetCDF files, but have not been quality controlled (e.g. precipitation period, precipitation depth, sunshine duration)." } ], "responsiblepartyinfo_set": [ 76257, 108763, 76250, 76255, 76254, 76252, 76251, 76249, 76248, 76253, 76259, 168105, 168106, 168107 ], "onlineresource_set": [ 16634, 16635, 16638, 16636, 16643, 16637, 16818, 16819 ] }, { "ob_id": 20044, "uuid": "a38c710ef63c4e8c9a295501f1122dbf", "title": "CRU CY3.24: Climatic Research Unit (CRU) Year-by-Year Variation of Selected Climate Variables by CountrY (CY) version 3.24 (Jan. 1901 - Dec. 2015)", "abstract": "The CRU CY version 3.24 dataset consists of country averages at a monthly, seasonal and annual frequency, for ten climate variables, including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and Potential Evapo-transpiration. \r\n\r\nThis dataset was produced in 2016 by the Climatic Research Unit (CRU) at the University of East Anglia. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nSpatial averages are calculated using area-weighted means. CRU CY3.24 is derived directly from the CRU TS3.24 dataset. CRU CY version 3.24 spans the period 1901-2015 for 289 countries.\r\n\r\nTo understand the CRU-CY3.24 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS3.24. It is therefore recommended that all users read the Harris et al, 2014 paper listed in the online documentation on this record.\r\n\r\nCRU CY data are available for download to all CEDA users.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-06-24T11:17:01", "updateFrequency": "notPlanned", "dataLineage": "CRU CY is derived directly from the CRU TS dataset, and version numbering is matched between the two datasets. Thus, the first official version of CRU CY was v3.21 as it is based on CRU TS v3.21.\r\n\r\nCRU CY 3.24 data files supplied to CEDA for long term archival by CRU in October 2016.\r\n\r\nThe CRU CY 3.24 data were withdrawn in January 2017 due to known issues with the data.", "removedDataReason": "", "keywords": "CRU, CRU CY, climate", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "0.5x0.5 degree grid", "status": "withdrawn", "dataPublishedTime": "2017-01-30T08:16:51", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 513, "bboxName": "CRU High Resolution Grid", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -60.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 32765, "dataPath": "/badc/cru/data/cru_cy/cru_cy_3.24/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2026, "numberOfFiles": 2, "fileFormat": "The CRU CY data are provided as text files with the extension \".per\", most text editors will open these files. See the linked file formats guide for more information." }, "timePeriod": { "ob_id": 5281, "startTime": "1901-01-01T00:00:00", "endTime": "2015-12-31T23:59:59" }, "resultQuality": { "ob_id": 3077, "explanation": "CRU CY 3.24 has been withdrawn due to data quality issues and is replaced by CRU CY 3.24.01", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2017-02-14" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 6676, "uuid": "f300abf12b80415594ab776280307a31", "short_code": "comp", "title": "UEA Climatic Research Unit (CRU) High Resolution gridding software deployed on UEA Climatic Research Unit (CRU) computer system", "abstract": "This computation involved: UEA Climatic Research Unit (CRU) High Resolution gridding software deployed on UEA Climatic Research Unit (CRU) computer system. For details about the production of CRU TS and CRU CY datasets, please refer to Harris et al. (2014) - see link below." }, "procedureCompositeProcess": null, "imageDetails": [ 103 ], "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": 6672, "uuid": "b6c783922d1ce68c4293d90caede5bb9", "short_code": "proj", "title": "UEA Climatic Research Unit (CRU) Gridded Datasets production project", "abstract": "The Climatic Research Unit at the University of East Anglia is producing various resolution gridded datasets.\r\nSome of those datasets are stored at CEDA-BADC." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 6889, "uuid": "116aed45b5f0d15ddc3b0e753837e8c9", "short_code": "coll", "title": "Climatic Research Unit (CRU): Year-by-Year Variation of Selected Climate Variables by CountrY (CY) v3", "abstract": "The CRU CY datasets consists of country averages at a monthly, seasonal and annual frequency, for ten climate variables in 289 countries. Spatial averages are calculated using area-weighted means. Variables include cloud cover (cld), diurnal temperature range (dtr), frost day frequency (frs), precipitation (pre), daily mean temperature (tmp), monthly average daily maximum (tmx) and minimum (tmn) temperature, vapour pressure (vap), Potential Evapo-transpiration (pet) and wet day frequency (wet). The CRU CY datasets produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nSpatial averages are calculated using area-weighted means. CRU CY is derived directly from the CRU TS dataset and version numbering is matched between the two datasets. Thus, the first official version of CRU CY is v3.21, as it is based on CRU TS v3.21 (1901-2012) and the latest version of CRU-CY is v3.26 based on CRU TS v3.26 (1901-2017) for 289 countries. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nTo understand the CRU-CY dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS. It is therefore recommended that all users read the paper referenced below (Harris et al, 2014)." } ], "responsiblepartyinfo_set": [ 76271, 79048, 76275, 76274, 76270, 76269, 76268, 76267, 76272, 76273, 79049, 168506, 168507 ], "onlineresource_set": [ 16649, 16650, 23708, 16651 ] }, { "ob_id": 20046, "uuid": "492c792f417c452db1a5946b9c3bc5fe", "title": "CRU TS3.24: Climatic Research Unit (CRU) Time-Series (TS) Version 3.24 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2015)", "abstract": "The gridded CRU TS (time-series) 3.24 data are month-by-month variations in climate over the period 1901-2015, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nCRU TS 3.24 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period Jan. 1901 - Dec. 2015.\r\n\r\nCRU TS 3.24 data were produced using the same methodology as for the 3.21 datasets. In addition to updating the dataset with 2015 data, some new stations have been added for TMP and PRE only. Known issues predating this release remain.\r\n\r\nThe CRU TS 3.24 data are monthly gridded fields based on monthly observational data, which are calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and netcdf data files both contain monthly mean values for the various parameters.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies.\r\n\r\nNote, these data were found to be in error and a new version, v3.24.01, should be used instead.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": null, "updateFrequency": "notPlanned", "dataLineage": "CRU TS 3.00 data files acquired directly from CRU in 2007. CRU provided the BADC with software to generate the CRU datasets in 2010, and this was used to produce CRU TS 3.10 at the BADC in early 2011.\r\n\r\nIn July 2012, systematic errors were discovered in the CRUTS v3.10 process. The effect was, in some cases, to reduce the gridded values for PRE and therefore WET. Values of FRS were found to be unrealistic in some areas due to the algorithms used for synthetic generation. The files (pre, frs and wet) were immediately removed from BADC. The corrected run for precipitation, based on the v3.10 precipitation station data, was generated as a direct replacement and given the version number 3.10.01. There were no corrected runs produced for wet and frs.\r\n\r\nCRU TS 3.20 was produced in December 2012.\r\nIn March 2013, CRU TS observation databases for TMP and PRE variables were provided by CRU. Others are in preparation. In july 2013, two errors were found in the PRE and WET variables of CRU TS v3.20. These have been repaired in CRU TS v3.21. Details of the errors found are available in the Release Notes in the archive.\r\n\r\nCRU TS 3.21 was provided to CEDA for archival in July 2013 by CRU.\r\n\r\nCRU TS 3.22 was provided to CEDA for archival in July 2014 by CRU.\r\n\r\nCRU TS 3.23 was provided to CEDA in October 2015 by CRU. This is the latest version available, superseding all previous data versions (which are available to allow user comparisons).\r\n\r\nCRU TS 3.24 was provided to CEDA for archival in July 2016. This is the latest version available, superseding all previous data versions (which are available to allow user comparisons).", "removedDataReason": "Data has been withdrawn by the data provider due to known errors in the gridded output. Please see https://crudata.uea.ac.uk/cru/data/hrg/Known_Problems_CRU_TS_3.24.txt for further details", "keywords": "CRU,TS, atmosphere, earth science, climate", "publicationState": "removed", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "0.5x0.5 degree grid", "status": "obsolete", "dataPublishedTime": "2017-01-25T10:36:36", "doiPublishedTime": null, "removedDataTime": "2017-01-25T00:00:00", "geographicExtent": { "ob_id": 513, "bboxName": "CRU High Resolution Grid", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -60.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 20047, "dataPath": "https://crudata.uea.ac.uk/cru/data/hrg/Known_Problems_CRU_TS_3.24.txt", "oldDataPath": [], "storageLocation": "external", "storageStatus": "offline", "volume": 0, "numberOfFiles": 0, "fileFormat": "NetCDF and ASCII" }, "timePeriod": { "ob_id": 5283, "startTime": "1901-01-01T00:00:00", "endTime": "2015-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 6676, "uuid": "f300abf12b80415594ab776280307a31", "short_code": "comp", "title": "UEA Climatic Research Unit (CRU) High Resolution gridding software deployed on UEA Climatic Research Unit (CRU) computer system", "abstract": "This computation involved: UEA Climatic Research Unit (CRU) High Resolution gridding software deployed on UEA Climatic Research Unit (CRU) computer system. For details about the production of CRU TS and CRU CY datasets, please refer to Harris et al. (2014) - see link below." }, "procedureCompositeProcess": null, "imageDetails": [ 103 ], "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": 6672, "uuid": "b6c783922d1ce68c4293d90caede5bb9", "short_code": "proj", "title": "UEA Climatic Research Unit (CRU) Gridded Datasets production project", "abstract": "The Climatic Research Unit at the University of East Anglia is producing various resolution gridded datasets.\r\nSome of those datasets are stored at CEDA-BADC." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 21919, 21935, 21948, 21962, 21974, 21978, 25388, 25397, 25845, 25879, 25882, 25911, 25957, 25978, 25979 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 6669, "uuid": "3f8944800cc48e1cbc29a5ee12d8542d", "short_code": "coll", "title": "Climatic Research Unit (CRU): Time-series (TS) datasets of variations in climate with variations in other phenomena v3", "abstract": "Time-series (TS) datasets are month-by-month variation in climate over the last century or so as produced by the Climatic Research Unit (CRU) at the University of East Anglia. These are calculated on high-resolution (0.5x0.5 degree) grids, which are based on an archive of monthly mean temperatures provided by more than 4000 weather stations distributed around the world. They allow variations in climate to be studied, and include variables such as cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum temperature, vapour pressure, Potential Evapo-transpiration and wet day frequency.\r\n\r\nAt present, the BADC holds the latest Time Series data generated by CRU for the period 1901-2017. Those are available as CRU TS 3.26 data. The BADC also holds the preliminary CRU TS3.00 datasets for the period 1901-2006 as well as the subsequent CRU TS 3.10, 3.20, 3.21, 3.22, 3.23, 3.24 and CRU TS 3.25 datasets for the period 1901-2016.\r\n\r\nThe CRU TS data are monthly gridded fields based on daily values -hence the ASCII and netcdf files both contain monthly mean values for the various parameters." } ], "responsiblepartyinfo_set": [ 191950, 76283, 76281, 76286, 76285, 76280, 76279, 76278, 76282, 79047, 76287, 76284, 79046, 168504, 168505 ], "onlineresource_set": [ 16653, 16655, 16654, 23707 ] }, { "ob_id": 20048, "uuid": "3c3ecba47fdc41f8bbf2e2e9194a3598", "title": "Chilbolton Facility for Atmospheric and Radio Research (CFARR): cloud camera imagery from Sparsholt College, Hampshire (1996-1997)", "abstract": "Sky images collected by a JVC KYF55-BE digital camera over Sparsholt College, Hampshire. The data were collected from 5th of July 1996 to end of 1997 before the camera was relocated to the main Chilbolton Observatory, Hampshire.\r\n\r\nSee the linked instrument details record (under the Process information) for subsequent data from this instrument.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2008-10-01T16:42:18", "updateFrequency": "notPlanned", "dataLineage": "Data were prepared by Chilbolton Facility for Atmospheric and Radio Research (CFARR) staff prior to submission to BADC for archiving.", "removedDataReason": "", "keywords": "CFARR, cloud camera", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "1996-07-05T06:50:00", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 59, "bboxName": "Chilbolton", "eastBoundLongitude": -1.427, "westBoundLongitude": -1.427, "southBoundLatitude": 51.145, "northBoundLatitude": 51.145 }, "verticalExtent": null, "result_field": { "ob_id": 20049, "dataPath": "/badc/chilbolton/data/cloud-camera_sparsholt", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 14860255307, "numberOfFiles": 78015, "fileFormat": "Image files are GIF formatted" }, "timePeriod": { "ob_id": 965, "startTime": "1996-07-04T23:00:00", "endTime": null }, "resultQuality": { "ob_id": 853, "explanation": "Data are checked by CFARR staff prior to submission to BADC", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-09-21" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 20050, "uuid": "150509e9e06e4233b77de9b566bfdd0f", "short_code": "acq", "title": "Acquisition Process for: Chilbolton Facility for Atmospheric and Radio Research (CFARR) Cloud Camera deployed at Sparsholt College, 1996-1997", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Chilbolton Facility for Atmospheric and Radio Research (CFARR) Cloud Camera; PLATFORMS: Chilbolton Facility for Atmospheric and Radio Research (CFARR), UK; " }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 50 ], "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": 3464, "uuid": "493185a4f967ee2a34516d9c5da9331e", "short_code": "proj", "title": "Chilbolton Facility for Atmospheric and Radio Research (CFARR)", "abstract": "The STFC facility at Chilbolton, Hampshire (51.1445N, 1.4270W) is the site of several observation systems for meteorological studies. The main system is the 3 GHz Doppler radar (CAMRa). A supporting 94 GHz radar (Galileo) has been located close to the main dish to allow dual frequency studies of precipitating particles. The system is complemented by a 905 nm Vaisala CT75K lidar, a 355nm UV Raman Lidar, multiple raingauge and meteorological sensors. This dataset also holds attenuation time-series data from vertically polarised links from South Wonston to Sparsholt. Sparsholt meteorological sensor and raingauge data is also archived. Cloud camera data from the Chilbolton site is available for examining weather patterns." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 13200, 21919, 22450 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 3461, "uuid": "7cbc3fc19bfa037a48ba4cba4b93544d", "short_code": "coll", "title": "Chilbolton Facility for Atmospheric and Radio Research (CFARR): surface, radar and lidar measurements (1998-present)", "abstract": "Data from observations made using Chilbolton Facility for Atmospheric and Radio Research (CFARR).The Science and Technology Facilities Council (STFC) facility at Chilbolton Observatory, Hampshire (51.1445N, 1.4270W) is the home of many observation systems for meteorological and atmospheric science research. There are 4 radar systems designed to study precipitation, clouds and clear air, of which the largest is the 3 GHz Doppler radar (CAMRa) on the 25 m dish. There are also 4 lidar systems providing data on elastic backscattering, Doppler velocity, water vapour profiles and depolarisation. A wide range of meteorological and multiple raingauge data are available from both Chilbolton and the nearby Sparsholt field site. There is a wide range of radiometers at the site: microwave (for water vapour and liquid water measurements) and downwelling infra-red and visible detectors for radiation budget measurements. This dataset holds attenuation time-series data from vertically polarised 5 km links from South Wonston to Sparsholt. Cloud camera data from the Chilbolton site are available to provide visual information on weather conditions.\r\n\r\nCFARR is funded by the Natural Environment Research Council (NERC) and is owned and operated by the Space Science and Technology Department of the STFC." } ], "responsiblepartyinfo_set": [ 76291, 76297, 76296, 76295, 76294, 76293, 76292, 76290, 76298, 76299, 76300, 76301 ], "onlineresource_set": [ 16687, 16688 ] }, { "ob_id": 20051, "uuid": "f55f5649110b4b98b3d5177d8ff2eac9", "title": "Chilbolton Facility for Atmospheric and Radio Research (CFARR): cloud camera 2 imagery from Chilbolton, Hampshire (2016-present)", "abstract": "Sky images collected by a sky camera replacing the earlier JVC KYF55-BE digital camera deployed at the Chilbolton Observatory, Hampshire. These differ from the previous camera imagery by the use of a fish-eye lens to give complete sky imagery. These images have been captured from mid-2016 to the present.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-09-30T10:21:27", "updateFrequency": "continual", "dataLineage": "Data are prepared by Chilbolton Facility for Atmospheric and Radio Research (CFARR) staff prior to submission to CEDA for archiving.", "removedDataReason": "", "keywords": "CFARR, cloud camera", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2016-10-17T12:48:52", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 59, "bboxName": "Chilbolton", "eastBoundLongitude": -1.427, "westBoundLongitude": -1.427, "southBoundLatitude": 51.145, "northBoundLatitude": 51.145 }, "verticalExtent": null, "result_field": { "ob_id": 20052, "dataPath": "/badc/chilbolton/data/cloud-camera-2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 530708496, "numberOfFiles": 289, "fileFormat": "Image files are Jpeg formatted" }, "timePeriod": { "ob_id": 965, "startTime": "1996-07-04T23:00:00", "endTime": null }, "resultQuality": { "ob_id": 853, "explanation": "Data are checked by CFARR staff prior to submission to BADC", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-09-21" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 20054, "uuid": "49ee31d83c0c443b88c7673b1161ee71", "short_code": "acq", "title": "Acquisition Process for: Chilbolton Facility for Atmospheric and Radio Research (CFARR) Cloud Camera 2 Data", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Chilbolton Facility for Atmospheric and Radio Research (CFARR) Cloud Camera; PLATFORMS: Chilbolton Facility for Atmospheric and Radio Research (CFARR), UK; " }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 50 ], "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": 3464, "uuid": "493185a4f967ee2a34516d9c5da9331e", "short_code": "proj", "title": "Chilbolton Facility for Atmospheric and Radio Research (CFARR)", "abstract": "The STFC facility at Chilbolton, Hampshire (51.1445N, 1.4270W) is the site of several observation systems for meteorological studies. The main system is the 3 GHz Doppler radar (CAMRa). A supporting 94 GHz radar (Galileo) has been located close to the main dish to allow dual frequency studies of precipitating particles. The system is complemented by a 905 nm Vaisala CT75K lidar, a 355nm UV Raman Lidar, multiple raingauge and meteorological sensors. This dataset also holds attenuation time-series data from vertically polarised links from South Wonston to Sparsholt. Sparsholt meteorological sensor and raingauge data is also archived. Cloud camera data from the Chilbolton site is available for examining weather patterns." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 13200, 21919, 22450 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 3461, "uuid": "7cbc3fc19bfa037a48ba4cba4b93544d", "short_code": "coll", "title": "Chilbolton Facility for Atmospheric and Radio Research (CFARR): surface, radar and lidar measurements (1998-present)", "abstract": "Data from observations made using Chilbolton Facility for Atmospheric and Radio Research (CFARR).The Science and Technology Facilities Council (STFC) facility at Chilbolton Observatory, Hampshire (51.1445N, 1.4270W) is the home of many observation systems for meteorological and atmospheric science research. There are 4 radar systems designed to study precipitation, clouds and clear air, of which the largest is the 3 GHz Doppler radar (CAMRa) on the 25 m dish. There are also 4 lidar systems providing data on elastic backscattering, Doppler velocity, water vapour profiles and depolarisation. A wide range of meteorological and multiple raingauge data are available from both Chilbolton and the nearby Sparsholt field site. There is a wide range of radiometers at the site: microwave (for water vapour and liquid water measurements) and downwelling infra-red and visible detectors for radiation budget measurements. This dataset holds attenuation time-series data from vertically polarised 5 km links from South Wonston to Sparsholt. Cloud camera data from the Chilbolton site are available to provide visual information on weather conditions.\r\n\r\nCFARR is funded by the Natural Environment Research Council (NERC) and is owned and operated by the Space Science and Technology Department of the STFC." } ], "responsiblepartyinfo_set": [ 76305, 76311, 76310, 76304, 76309, 76308, 76307, 76306, 76312, 76313, 76314, 76315 ], "onlineresource_set": [ 16689, 16690 ] }, { "ob_id": 20057, "uuid": "f054a8b0fac649f78e87baef1db89cde", "title": "BUNIAACIC: Manchester UV-LIF spectrometer data (fluorine and chlorine number concentration and particle size distribution) (MAN-WIBS3M)", "abstract": "The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1)\r\n\r\nThis project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon. \r\n\r\nThis dataset contains measurements from the Manchester UV-LIF spectrometer data (fluorine and chlorine number concentration and particle size distribution) processed with \"MUTANT data processing toolkit (MAN-WIBS3M)", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-10-18T10:35:06", "updateFrequency": "notPlanned", "dataLineage": "Data collected by project team and sent to CEDA", "removedDataReason": "", "keywords": "BUNIAACIC, Brazil, chemistry, pollution", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2017-09-07T13:08:07", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1651, "bboxName": "Pristine, Brazil", "eastBoundLongitude": -60.209289, "westBoundLongitude": -60.209289, "southBoundLatitude": -2.594541, "northBoundLatitude": -2.594541 }, "verticalExtent": null, "result_field": { "ob_id": 20058, "dataPath": "/badc/buniaac/data/man-wibs3m", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1718382, "numberOfFiles": 2, "fileFormat": "Data are netCDF formatted" }, "timePeriod": { "ob_id": 5248, "startTime": "2013-07-02T23:00:00", "endTime": "2013-07-30T23:00:00" }, "resultQuality": { "ob_id": 3067, "explanation": "Data provided by project group", "passesTest": true, "resultTitle": "BUNIAACIC project data", "date": "2016-10-17" }, "validTimePeriod": { "ob_id": 5248, "startTime": "2013-07-02T23:00:00", "endTime": "2013-07-30T23:00:00" }, "procedureAcquisition": { "ob_id": 20059, "uuid": "b793af59a69042099b0ca12d48001298", "short_code": "acq", "title": "BUNIAACIC: WIBS3M Manchester UV-LIF spectrometer data processed with MUTANT toolbox", "abstract": "Measurements of number concentrations and particle size distribution of fluoprine ad chlorine by the Manchester UV-LIF spectrometer for the BUNIAAC project\r\n" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 18 ], "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": 19921, "uuid": "039fa6aef65d4adf96f064188bbf7a00", "short_code": "proj", "title": "Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC)", "abstract": "The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1)\r\n\r\nThis project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon. \r\n\r\nA network of Brazilian and UK atmospheric researchers were established to scope potential collaborative opportunities by exploiting and extending the infrastructural framework of the FAPESP AEROCLIMA Thematic Grant. An early secondment of CAS staff to São Paulo followed by a broad kick-off workshop were used to initiate the scoping study. Potential UK activities at various stages of development were drawn into a broader strategy of International collaboration and opportunities for further consortium scale activities were developed. A UK office for collaboration on Amazonian atmospheric research was established at the University of Manchester. \r\n\r\nThe long-term particulate monitoring programme within AEROCLIMA was expanded to include online aerosol composition measurements at the pristine rainforest site. Secondment of São Paulo staff to CAS ensured adequate training was provided in the operation of the instrumentation, data analysis and quality control. A pump-priming pilot scale intensive deployment of the CAS container laboratory with additional particulate measurement instrumentation were used to i) validate the long-term measurements, ii) quantitatively interpret the impacts of aerosol composition on physical properties of climate relevance in the context of the long-term variability, iii) act as a focal measurement suite around which a broader consortium-scale activity can be developed. \r\n\r\nA strategy for the medium and longer term collaborative efforts were developed based on the initial scoping study and consultation throughout the UK research community. This strategy was consolidated into a White Paper outlining the Brazil-UK collaborative opportunities and recommended participation of UK groups in Amazonian atmospheric research." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 55956, 55957, 55958, 55959, 55960, 55961, 55962, 55963, 55964, 55965, 55966, 55967, 55968, 55969, 55970, 55971, 55972, 55973, 55974, 55975 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 19922, "uuid": "314b6cc4d99a4bb79f79c7879ad2ef7f", "short_code": "coll", "title": "Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC)", "abstract": "The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1)\r\n\r\nThis project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon.\r\n\r\nThis dataset collection contains atmospheric composition measurements." } ], "responsiblepartyinfo_set": [ 76338, 76331, 76334, 76332, 76333, 76335, 76336, 76337, 76341 ], "onlineresource_set": [] }, { "ob_id": 20060, "uuid": "59c40940887b4c3f98158c2f8ed7fb10", "title": "BUNIAACIC: Pollution episode flags", "abstract": "The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1)\r\n\r\nThis project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon.\r\n\r\nThis dataset contains flags to indicate pollution episodes during the BUNIAACIC deployment.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-10-18T10:35:15", "updateFrequency": "notPlanned", "dataLineage": "Data collected by project group and provided to CEDA", "removedDataReason": "", "keywords": "BUNIAACIC, Brazil, chemistry, pollution", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2017-09-07T13:07:48", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1651, "bboxName": "Pristine, Brazil", "eastBoundLongitude": -60.209289, "westBoundLongitude": -60.209289, "southBoundLatitude": -2.594541, "northBoundLatitude": -2.594541 }, "verticalExtent": null, "result_field": { "ob_id": 20061, "dataPath": "/badc/buniaac/data/pollution-flags", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 42962, "numberOfFiles": 2, "fileFormat": "Data are NASA Ames formatted" }, "timePeriod": { "ob_id": 5250, "startTime": "2013-06-30T23:00:00", "endTime": "2013-07-30T23:00:00" }, "resultQuality": { "ob_id": 3067, "explanation": "Data provided by project group", "passesTest": true, "resultTitle": "BUNIAACIC project data", "date": "2016-10-17" }, "validTimePeriod": { "ob_id": 5247, "startTime": "2013-06-30T23:00:00", "endTime": "2013-07-30T23:00:00" }, "procedureAcquisition": { "ob_id": 20062, "uuid": "fd0320a970fd4afab3445cf6b90f7094", "short_code": "acq", "title": "BUNIAACIC pollution flags", "abstract": "BUNIAACIC pollution flags" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 18 ], "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": 19921, "uuid": "039fa6aef65d4adf96f064188bbf7a00", "short_code": "proj", "title": "Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC)", "abstract": "The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1)\r\n\r\nThis project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon. \r\n\r\nA network of Brazilian and UK atmospheric researchers were established to scope potential collaborative opportunities by exploiting and extending the infrastructural framework of the FAPESP AEROCLIMA Thematic Grant. 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A pump-priming pilot scale intensive deployment of the CAS container laboratory with additional particulate measurement instrumentation were used to i) validate the long-term measurements, ii) quantitatively interpret the impacts of aerosol composition on physical properties of climate relevance in the context of the long-term variability, iii) act as a focal measurement suite around which a broader consortium-scale activity can be developed. \r\n\r\nA strategy for the medium and longer term collaborative efforts were developed based on the initial scoping study and consultation throughout the UK research community. This strategy was consolidated into a White Paper outlining the Brazil-UK collaborative opportunities and recommended participation of UK groups in Amazonian atmospheric research." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 52353 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 19922, "uuid": "314b6cc4d99a4bb79f79c7879ad2ef7f", "short_code": "coll", "title": "Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC)", "abstract": "The Brazil-UK Network for Investigation of Amazonian Atmospheric Composition and Impacts on Climate (BUNIAACIC) collaboration was a NERC (Natural Environment Research Council) funded project (NE/I030178/1)\r\n\r\nThis project aimed to develop a coherent strategy for UK studies of atmospheric composition and impacts in the Amazon.\r\n\r\nThis dataset collection contains atmospheric composition measurements." } ], "responsiblepartyinfo_set": [ 76347, 76349, 76348, 76343, 76346, 76344, 76345, 76342, 76350 ], "onlineresource_set": [] }, { "ob_id": 20072, "uuid": "3451b0d7a2f2439d8f1926041ddf8b4c", "title": "GloCAEM: Atmospheric electricity measurements at University of Reading", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill at the University of Reading.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2025-07-18T15:40:07", "updateFrequency": "irregular", "dataLineage": "Data collected by project team and sent to CEDA", "removedDataReason": "", "keywords": "GloCAEM, GEC, electric potential, electric field", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2018-08-01T15:17:38", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 894, "bboxName": "University of Reading", "eastBoundLongitude": -0.9456, "westBoundLongitude": -0.9456, "southBoundLatitude": 51.4419, "northBoundLatitude": 51.4419 }, "verticalExtent": null, "result_field": { "ob_id": 20069, "dataPath": "/badc/glocaem/data/reading/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 14745602753, "numberOfFiles": 13934, "fileFormat": "Data are BADC-CSV formatted" }, "timePeriod": { "ob_id": 6753, "startTime": "2007-01-01T00:00:00", "endTime": null }, "resultQuality": { "ob_id": 3068, "explanation": "Data provided by project group", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2016-10-18" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 20071, "uuid": "dd2c819d09bf421f9c5e4907b25802ba", "short_code": "acq", "title": "GLOCaeM potential gradient - Reading", "abstract": "Measurements of atmospheric electric potential gradient made at Reading for the Glocaem project" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2546, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 8, "licenceURL": "http://creativecommons.org/licenses/by/4.0/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 20068, "uuid": "6ee6e0a3f57c4ca79e8cbc0daaafe76f", "short_code": "proj", "title": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM)", "abstract": "It is well established that Earth has a \"Global atmospheric Electric Circuit\" (GEC), through which charge separation in thunderstorms sustains large scale current flow around the planet. The GEC generates an atmospheric electric field which is present globally, and is typically 100V/m near the surface in fair weather conditions. Measurements of electric field have been shown to include information about global thunderstorm activity, local aerosol concentrations and cloud cover, as well as changes in the space weather environment. Recent work has also suggested that atmospheric electrical changes may be effective as earthquake precursors, as well as being sensitive to release of radioactivity, as evidenced by the Fukushima disaster in 2011. \r\n\r\nThe global nature of the GEC means that in order that truly global signals are considered in understanding the processes within the circuit, many validating measurements must be made at different locations around the world. To date, no genuinely global network of FW atmospheric electricity measurements has ever existed, therefore, given the growing number of groups now involved in atmospheric electricity monitoring, such a proposal is timely. \r\n\r\nThis project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 19002, 32398, 32399, 32400, 32401, 32402, 32403, 32404, 32405, 32406, 32407, 32408, 32409, 32410, 32411, 32412, 32413, 32414, 32415, 32416, 32417, 32418 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 24981, "uuid": "bffd0262439a4ecb8fadf0134c4a4a41", "short_code": "coll", "title": "GloCAEM: Atmospheric electric potential gradient measurements", "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset collection contains measurements of atmospheric electricity and electric potential gradient made using a Cambell Scientific CS110 electric-field mill." } ], "responsiblepartyinfo_set": [ 102292, 102289, 102295, 102294, 102293, 102291, 102290, 102288 ], "onlineresource_set": [ 24409 ] }, { "ob_id": 20081, "uuid": "b70578ae62b745ec9dc2ba42d2ee1311", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global dataset of inherent optical properties (IOP) gridded on a sinusoidal projection, Version 2.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 2.0 inherent optical properties (IOP) product (in mg/m3) on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, the IOP data are also included in the 'All Products' dataset. \r\n\r\nThe inherent optical properties (IOP) dataset consists of the total absorption and particle backscattering coefficients, and, additionally, the fraction of detrital & dissolved organic matter absorption and phytoplankton absorption. The total absorption (units m-1), the total backscattering (m-1), the absorption by detrital and coloured dissolved organic matter, the backscattering by particulate matter, and the absorption by phytoplankton share the same spatial resolution of ~4 km. The values of IOP are reported for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm). \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2020-05-29T14:34:29", "updateFrequency": "", "dataLineage": "This data has been produced by the ESA Ocean Colour CCI project and provided to CEDA in the context of the ESA CCI Open Data Portal project", "removedDataReason": "", "keywords": "ESA, CCI, Ocean Colour, Sinusoidal", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "4km", "status": "superseded", "dataPublishedTime": "2016-12-12T17:01:30", "doiPublishedTime": null, "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": 20082, "dataPath": "/neodc/esacci/ocean_colour/data/v2-release/sinusoidal/netcdf/iop/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 6904794057143, "numberOfFiles": 8089, "fileFormat": "Data are in NetCDF" }, "timePeriod": { "ob_id": 5256, "startTime": "1997-09-03T23:00:00", "endTime": "2013-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2538, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 18, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_oc_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13365, "uuid": "de8aeb4f1bec4348a1e475691ea651d4", "short_code": "proj", "title": "ESA Ocean Colour Climate Change Initiative Project", "abstract": "The European Space Agency Ocean Colour Climate Change Initiative (Ocean Colour CCI) project aims to produce long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n \r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490 nm. Information on uncertainties is also provided." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 12066, 50512, 52664, 52665, 55884, 55885, 55886, 55887, 55888, 55889, 55891, 55892, 55893, 55894, 55895, 55896, 55898, 55899, 55900, 55901, 55902, 55903, 55904, 55905, 55906, 55907, 62502, 62503, 62504, 62505, 87700, 87701, 87702, 87703, 87704, 87705, 87706, 87707, 87708, 87709, 87710, 87711, 87712, 87713, 87714, 87715, 87716, 87717, 87718, 87719, 87720, 87721, 87722, 87723, 87724, 87725 ], "vocabularyKeywords": [ { "ob_id": 10177, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_aqua", "resolvedTerm": "Aqua" }, { "ob_id": 10242, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_modis", "resolvedTerm": "MODIS" }, { "ob_id": 10250, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_meris", "resolvedTerm": "MERIS" }, { "ob_id": 10181, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/procLev/proc_level3", "resolvedTerm": "Level 3" }, { "ob_id": 10215, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/freq/freq_day", "resolvedTerm": "day" }, { "ob_id": 10184, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_envisat", "resolvedTerm": "Envisat" }, { "ob_id": 10122, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org49", "resolvedTerm": "Plymouth Marine Laboratory" }, { "ob_id": 10343, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/freq/freq_mon", "resolvedTerm": "month" }, { "ob_id": 10469, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_envisat_prog", "resolvedTerm": "Environmental Satellite" }, { "ob_id": 10408, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_orbview2_prog", "resolvedTerm": "Orbview-2" }, { "ob_id": 10258, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_orbview2", "resolvedTerm": "Orbview-2" }, { "ob_id": 10293, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_seaWiFs", "resolvedTerm": "SeaWiFS" }, { "ob_id": 10198, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/product/prod_merged", "resolvedTerm": "MERGED" }, { "ob_id": 10264, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/dataType/dtype_iop", "resolvedTerm": "inherent optical properties" }, { "ob_id": 10234, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_oceanCol", "resolvedTerm": "ocean colour" }, { "ob_id": 10175, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/procLev/proc_level3S", "resolvedTerm": "Level 3S" }, { "ob_id": 10488, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_eos", "resolvedTerm": "EOS" }, { "ob_id": 10341, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/freq/freq_8day", "resolvedTerm": "8 days" }, { "ob_id": 10537, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/L22/current/TOOL0867/", "resolvedTerm": "Sea-viewing Wide Field-of-view Sensor - SeaWiFS" }, { "ob_id": 10582, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/L22/current/TOOL1035/", "resolvedTerm": "Moderate Resolution Imaging Spectroradiometer" }, { "ob_id": 10539, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/L22/current/TOOL1086/", "resolvedTerm": "Medium-Spectral Resolution, Imaging Spectrometer" }, { "ob_id": 10618, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/dataType/dtype_iop", "resolvedTerm": "inherent optical properties" }, { "ob_id": 10668, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_oceanCol", "resolvedTerm": "ocean colour" }, { "ob_id": 10678, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/freq/freq_8day", "resolvedTerm": "8 days" }, { "ob_id": 10680, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/freq/freq_day", "resolvedTerm": "day" }, { "ob_id": 10683, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/freq/freq_mon", "resolvedTerm": "month" }, { "ob_id": 10736, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/org/org49", "resolvedTerm": "Plymouth Marine Laboratory" }, { "ob_id": 10784, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_aqua", "resolvedTerm": "Aqua" }, { "ob_id": 10808, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_envisat", "resolvedTerm": "Envisat" }, { "ob_id": 10903, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_orbview2", "resolvedTerm": "Orbview-2" }, { "ob_id": 10938, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platformProg/plat_envisat_prog", "resolvedTerm": "Environmental Satellite" }, { "ob_id": 10939, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platformProg/plat_eos", "resolvedTerm": "EOS" }, { "ob_id": 10963, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platformProg/plat_orbview2_prog", "resolvedTerm": "Orbview-2" }, { "ob_id": 10984, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/procLev/proc_level3", "resolvedTerm": "Level 3" }, { "ob_id": 10986, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/procLev/proc_level3S", "resolvedTerm": "Level 3S" }, { "ob_id": 11020, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/product/prod_merged", "resolvedTerm": "MERGED" }, { "ob_id": 11120, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_seaWiFs", "resolvedTerm": "SeaWiFS" }, { "ob_id": 11105, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_modis", "resolvedTerm": "MODIS" }, { "ob_id": 11103, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_meris", "resolvedTerm": "MERIS" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 13548, "uuid": "93aecb2607294e25bc4638adc800f8e7", "short_code": "coll", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI) Dataset Collection", "abstract": "Datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI). The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490 nm. Information on uncertainties is also provided.\r\n\r\nThis dataset collection currently holds Version 1.0 data products, and later versions will be added in the future. Note, version 2.0 data products are now currently available directly from the Ocean Colour CCI team (see link in the documentation section)." }, { "ob_id": 20073, "uuid": "58268d53f02942fd9951bee50360b893", "short_code": "coll", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 2.0 Data", "abstract": "A collection of Version 2.0 datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI). The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490 nm. Information on uncertainties is also provided.\r\n\r\nThis dataset collection refers to the Version 2.0 data products held in the CEDA archive and available from ftp://anon-ftp.ceda.ac.uk/neodc/esacci/ocean_colour/data/v2-release . Links to the individual datasets that make up this collection are given in the record below. \r\n\r\nPlease note, this dataset has been superseded. Later version of the data are now available." }, { "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": [ 76373, 105374, 105200, 104977, 76556, 76372, 76371, 76370, 76368, 76582, 76608, 76634, 76660, 76686, 76712, 76738, 76764, 76790, 76816, 76842, 76868, 76894, 76920, 76946, 76972, 76998, 77024, 77050, 77076, 77102, 77128, 77154, 77180, 77206, 77232, 77258, 77284, 77310, 77336, 77362, 77388, 77414, 77440, 77466, 77492, 77518, 77544, 77570, 77596, 77622, 77648, 77674, 77700, 77726, 77752, 77778, 77804, 77830, 77856, 77882, 77908, 77934, 77960, 77986, 78012, 78038, 78064, 78090, 78116, 78142, 78168, 78194, 78220, 78246, 78272 ], "onlineresource_set": [ 16730, 16719, 16716, 16718, 16717 ] }, { "ob_id": 20086, "uuid": "0f1a958a130547febd40057f5ec1c837", "title": "EUSTACE/GlobTemperature: Global clear-sky land surface temperature from MODIS Aqua on the satellite swath with estimates of uncertainty components, v2.1, 2002-2016", "abstract": "This dataset consists of Land Surface Temperature (LST) data with uncertainty estimates, from the MODIS instrument on NASA's Aqua satellite. It forms part of the collection of datasets from the EUSTACE (EU Surface Temperature for All Corners of Earth) project, which is producing 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\nThe Level 2 Land Surface Temperature data in this dataset has been retrieved from MODIS Collection 6 L1B calibrated radiances, in the context of the GlobTemperature project, but new uncertainty estimates have been added as part of the EUSTACE project. This version of the LST dataset is v2.1 of the GT_MYG_2P product, with earlier versions produced under the GlobTemperature project. It consists of a complete set of LST and accompanying auxiliary (AUX) datafiles for the MODIS-Aqua mission for the period from 2002 until 2016. An equivalent dataset is also available for MODIS-Terra.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-08-08T15:16:10", "updateFrequency": "notPlanned", "dataLineage": "Datahave been provided and archived for the EU EUSTACE project, which has received funding by the European Union's Horizon 2020 research and innovation programme, under grant agreement no 640171. \r\nThis Land Surface Temperature data was originally derived in the context of the ESA DUE GlobTemperature project, but new uncertainty estimates have been added in the context of EUSTACE project. The MODIS data was acquired from the NASA Land Processes Distributed Active Archive Center (LP DAAC).", "removedDataReason": "", "keywords": "eustace, land surface temperature, LST", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1km at nadir", "status": "completed", "dataPublishedTime": "2019-03-18T12:06:28", "doiPublishedTime": "2019-03-18T12:15:05", "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": 26032, "dataPath": "/neodc/eustace/data/satellite_skin_temperature/UOL/land/MODIS_Aqua/L2/GT_MYG_2P/v2.1/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 27656165756283, "numberOfFiles": 2968297, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 6869, "startTime": "2002-07-03T23:00:00", "endTime": "2016-12-31T23:59:59" }, "resultQuality": { "ob_id": 3124, "explanation": "Data format checked ", "passesTest": true, "resultTitle": "Eustace Data Compliance Checker", "date": "2018-01-01" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 26033, "uuid": "c167e85367cb4caf9517ed81c5bf2b26", "short_code": "cmppr", "title": "Eustace: Land Surface Temperature retrieval from the MODIS-Aqua satellite instruments", "abstract": "Land Surface Temperature (LST) has been derived from calibrated radiance data from the MODIS instrument on the Aqua Satellite. It has been retrieved using the GlobTemperature Level-2 MODIS LST algorithm from the University of Leicester." }, "imageDetails": [ 214 ], "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": 19556, "uuid": "a52b2cc065a847b8a77a93896880349f", "short_code": "proj", "title": "EUSTACE (EU Surface Temperature for All Corners of Earth)", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is producing 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\nDay-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. Satellite data can be used to estimate temperatures at locations where no ground (or in situ) observations are available. To achieve this, we must develop an understanding of the relationships between traditional (land and marine) surface air temperature measurements and satellite measurements, i.e. land surface temperature, ice surface temperature, sea surface temperature and lake surface water temperature. These relationships can be derived either empirically, or with the help of physical understanding.\r\n\r\nTo achieve this the EUSTACE project is using new statistical techniques to provide information on higher spatial and temporal scales than are currently available, making optimum use of the information in data-rich eras. The final and intermediate products of EUSTACE (e.g. satellite skin temperature retrievals over all domains with consistent uncertainty estimates; station time series with discontinuities identified; information on the relationship between skin and air temperature over different domains and different seasons) will be interesting for many applications.\r\n\r\nThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640171." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 54670, 54671, 54674, 54675, 57596, 57599, 69213, 69214, 69215, 69216, 69217, 69218, 69219, 69220, 69221, 69222, 69223, 69224, 69225, 69226 ], "vocabularyKeywords": [], "identifier_set": [ 10501 ], "observationcollection_set": [ { "ob_id": 20098, "uuid": "7ebff7be4c0149d082ca9a32ec8df4da", "short_code": "coll", "title": "EUSTACE: Collection of products from the EUSTACE (EU Surface Temperature for All Corners of Earth) project", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is an EU Horizon 2020 project, producing 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\nThe data are publically available and consists of a number of different products: satellite skin temperature retrievals over all surface types; global surface air temperature derived from satellite skin temperature retrievals; homogonised surface meteorological station records for Europe and a European in filled analysis; global surface meteorological station records with discontinuities identified; and global analyses of daily surface air temperature going back to 1850, derived from both satellite and meteorological station data." }, { "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": [ 143593, 143592, 76394, 111388, 76392, 76393, 108982, 105461, 76395, 108948, 111387 ], "onlineresource_set": [ 16762, 26557 ] }, { "ob_id": 20087, "uuid": "b8285969426a4e00b7481434291ad603", "title": "EUSTACE / CCI: Global clear-sky sea surface temperature from the (A)ATSR series at 0.25 degrees with estimates of uncertainty components, v1.2, 1991-2012", "abstract": "This dataset consists of Sea Surface Temperature data with uncertainty estimates, from the Along Track Scanning Radiometer series of satellite instruments (ATSR-1, ATSR-2 and AATSR). It forms part of the collection of datasets from the EUSTACE (EU Surface Temperature for All Corners of Earth) project, which is producing publically 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\nThe Sea Surface Temperature data provided here were retrieved in the context of the European Space Agency's (ESA's) Climate Change Initiative (CCI) Sea Surface Temperature (SST) project, and comprise a Level 3c gridded product, on a 0.25 degree grid. This v1.2 product was provided for input into the EUSTACE project. It is provided here for traceability; more recent CCI data is available from the SST CCI catalogue pages.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2019-03-24T18:25:48.371918", "updateFrequency": "notPlanned", "dataLineage": "The Sea Surface Temperature data were originally retrieved from the (A)ATSR series of satellite instruments in the context of the European Space Agency Climate Change Initiative product.\r\n\r\nData are provided and archived for the EU EUSTACE project, which has received funding by the European Union's Horizon 2020 research and inovation programme under grant agreement no 640171.", "removedDataReason": "", "keywords": "SST, EUSTACE, CCI", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "0.25 degree", "status": "completed", "dataPublishedTime": "2019-04-08T10:40:04", "doiPublishedTime": "2019-04-08T13:06:12", "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": 27446, "dataPath": "/neodc/eustace/data/satellite_skin_temperature/UOR/ocean/ATSR/L3C/v1.2/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 38475900280, "numberOfFiles": 7613, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 7366, "startTime": "1991-08-02T23:00:00", "endTime": "2012-04-08T22:59:59" }, "resultQuality": { "ob_id": 3274, "explanation": "Data are as provided by the project team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-03-21" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 27432, "uuid": "d75a78a832c74476a4739c6dff0991c1", "short_code": "cmppr", "title": "CCI SST retrieval process from the (A)ATSR series of instruments", "abstract": "The ESA Climate Change Initiative Sea Surface Temperature (SST) product has retrieved sea surface temperature from the (A)ATSR series of satellite instruments." }, "imageDetails": [ 214 ], "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": 19556, "uuid": "a52b2cc065a847b8a77a93896880349f", "short_code": "proj", "title": "EUSTACE (EU Surface Temperature for All Corners of Earth)", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is producing 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\nDay-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. Satellite data can be used to estimate temperatures at locations where no ground (or in situ) observations are available. To achieve this, we must develop an understanding of the relationships between traditional (land and marine) surface air temperature measurements and satellite measurements, i.e. land surface temperature, ice surface temperature, sea surface temperature and lake surface water temperature. These relationships can be derived either empirically, or with the help of physical understanding.\r\n\r\nTo achieve this the EUSTACE project is using new statistical techniques to provide information on higher spatial and temporal scales than are currently available, making optimum use of the information in data-rich eras. The final and intermediate products of EUSTACE (e.g. satellite skin temperature retrievals over all domains with consistent uncertainty estimates; station time series with discontinuities identified; information on the relationship between skin and air temperature over different domains and different seasons) will be interesting for many applications.\r\n\r\nThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640171." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 50415, 50417, 52536, 52539, 52542, 52543, 52545, 57986, 57987, 57989, 59095 ], "vocabularyKeywords": [], "identifier_set": [ 10510 ], "observationcollection_set": [ { "ob_id": 20098, "uuid": "7ebff7be4c0149d082ca9a32ec8df4da", "short_code": "coll", "title": "EUSTACE: Collection of products from the EUSTACE (EU Surface Temperature for All Corners of Earth) project", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is an EU Horizon 2020 project, producing 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\nThe data are publically available and consists of a number of different products: satellite skin temperature retrievals over all surface types; global surface air temperature derived from satellite skin temperature retrievals; homogonised surface meteorological station records for Europe and a European in filled analysis; global surface meteorological station records with discontinuities identified; and global analyses of daily surface air temperature going back to 1850, derived from both satellite and meteorological station data." }, { "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": [ 143590, 143589, 76398, 114679, 114676, 76396, 76399, 76397, 114677, 114680, 114678 ], "onlineresource_set": [ 16763, 26550, 26604 ] }, { "ob_id": 20088, "uuid": "e7419b5b877141dab0d283ba31e9d057", "title": "EUSTACE: Global Lake Surface Water Temperature data from satellite instruments with uncertainties", "abstract": "This dataset consists of Lake Surface Water Temperature data with uncertainty estimates. The Lake Surface Water Temperature data were originally retrieved in the context of ?, but new uncertainty estimates have been added in the context of the EUSTACE project? \r\n\r\nThe EUSTACE (EU Surface Temperature for All Corners of Earth) project is producing 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. In this context, satellite skin temperature for Land, Ocean, Lakes and Ice are being collated with consistent uncertainty information across all domains. This dataset provides the satellite Lake Surface Water Temperature data.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": null, "updateFrequency": "", "dataLineage": "Data are from the EUSTACE project", "removedDataReason": "", "keywords": "", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "planned", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": null, "timePeriod": null, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [], "permissions": [], "projects": [], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "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": [ 204977, 204976, 204975, 76389, 76390, 76388, 76391 ], "onlineresource_set": [ 16761 ] }, { "ob_id": 20089, "uuid": "60b820fa10804fca9c3f1ddfa5ef42a1", "title": "EUSTACE/AASTI: Global clear-sky ice surface temperature data from the AVHRR series on the satellite swath with estimates of uncertainty components, v1.1, 2000-2009", "abstract": "This dataset provides global clear-sky ice surface temperature data derived from infrared satellite measurements, with estimates of the uncertainty components included. It forms part of the collection of datasets from the EUSTACE (EU Surface Temperature for All Corners of Earth) project, which is producing 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\nThe data provided here is Level 2 ice surface temperature data from the AVHRR (Advanced Very High Resolution Radiometer) series of satellite instruments, provided on the original satellite swath. This original AASTI (Arctic and Antarctic Ice Surface Temperatures from thermal infrared satellite sensors ) was produced under the EU NACLIM and the NORMAP projects; This version of the dataset has been extended under the EUSTACE (EU Surface Temperature for All Corners of Earth) project to also include components of uncertainty.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2019-04-10T13:40:45", "updateFrequency": "", "dataLineage": "Data are provided and archived for the EU EUSTACE project, which has received funding by the European Union's Horizon 2020 research and innovation programme under grant agreement no 640171.\r\n\r\nThe Ice Surface Temperature data were originally produced as part of the EU FP7 NACLIM (The North Atlantic Climate) project and the NORMAP project, but new uncertainty component estimates have been added in the context of the EUSTACE project.", "removedDataReason": "", "keywords": "", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2019-04-10T14:22:16", "doiPublishedTime": "2019-04-10T14:41:36.173633", "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": 27464, "dataPath": "/neodc/eustace/data/satellite_skin_temperature/DMI/ice/AASTI/L2/v1.1/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 5343033209417, "numberOfFiles": 194140, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 7302, "startTime": "2000-01-01T00:00:00", "endTime": "2009-12-31T23:59:59" }, "resultQuality": { "ob_id": 3253, "explanation": "validated by the data providers", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-02-11" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 27173, "uuid": "f6591ed71196457eb0c9cdab2896a0b0", "short_code": "cmppr", "title": "Eustace / AASTI : Ice Surface Temperature retrieval from the AVHRR series of satellite instruments", "abstract": "Ice Surface Temperature has been derived from calibrated radiance data from the AVHRR (Advanced Very High Resolution Radiometer) series of satellite instruments." }, "imageDetails": [ 214 ], "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": 19556, "uuid": "a52b2cc065a847b8a77a93896880349f", "short_code": "proj", "title": "EUSTACE (EU Surface Temperature for All Corners of Earth)", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is producing 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\nDay-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. Satellite data can be used to estimate temperatures at locations where no ground (or in situ) observations are available. To achieve this, we must develop an understanding of the relationships between traditional (land and marine) surface air temperature measurements and satellite measurements, i.e. land surface temperature, ice surface temperature, sea surface temperature and lake surface water temperature. These relationships can be derived either empirically, or with the help of physical understanding.\r\n\r\nTo achieve this the EUSTACE project is using new statistical techniques to provide information on higher spatial and temporal scales than are currently available, making optimum use of the information in data-rich eras. The final and intermediate products of EUSTACE (e.g. satellite skin temperature retrievals over all domains with consistent uncertainty estimates; station time series with discontinuities identified; information on the relationship between skin and air temperature over different domains and different seasons) will be interesting for many applications.\r\n\r\nThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640171." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 52529, 52539, 53130, 53131, 57987, 66459, 69227, 69228, 69229, 69230, 69231, 69232, 69233, 69234, 69235, 69236, 69237, 69238, 69239, 69240 ], "vocabularyKeywords": [], "identifier_set": [ 10511 ], "observationcollection_set": [ { "ob_id": 20098, "uuid": "7ebff7be4c0149d082ca9a32ec8df4da", "short_code": "coll", "title": "EUSTACE: Collection of products from the EUSTACE (EU Surface Temperature for All Corners of Earth) project", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is an EU Horizon 2020 project, producing 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\nThe data are publically available and consists of a number of different products: satellite skin temperature retrievals over all surface types; global surface air temperature derived from satellite skin temperature retrievals; homogonised surface meteorological station records for Europe and a European in filled analysis; global surface meteorological station records with discontinuities identified; and global analyses of daily surface air temperature going back to 1850, derived from both satellite and meteorological station data." }, { "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": [ 143595, 143594, 76384, 113806, 113805, 76387, 76386, 76385, 114811, 114812, 114813 ], "onlineresource_set": [ 16753, 92575, 92576, 92577, 26596, 92568, 92569, 92570, 92571, 92572, 92573, 92574 ] }, { "ob_id": 20092, "uuid": "81784e3642bd465aa69c7fd40ffe1b1b", "title": "EUSTACE / ECA&D: European land station daily air temperature measurements, homogenised", "abstract": "This dataset consists of homogenised time series of daily temperature observations for meteorological stations throughout Europe and the Mediterranean. The version of the dataset described here is a homogenised version of the ECA&D (European Climate Assessment & Dataset) daily dataset, produced with funding from the EU Horizon2020 EUSTACE (EU Surface Temperature for All Corners of Earth) project. \r\n\r\nThe data is available directly from the ECA&D website and is referenced here to form part of the EUSTACE collection of data. The EUSTACE version of the product is that labelled 'Homogenized ECA Dataset'. This dataset will continue to be updated by the ECA&D project beyond the end of EUSTACE.\r\n\r\nData is available for non-commercial purposes under the ECA&D terms and conditions (see https://www.ecad.eu//documents/ECAD_datapolicy.pdf).\r\n\r\nTo cite this dataset please use Squintu, AA, van der Schrier, G, Brugnara, Y, Klein Tank, A. \r\nHomogenization of daily temperature series in the European Climate Assessment & Dataset. /Int J Climatol/. 2019; 39: 1243– 1261. https://doi.org/10.1002/joc.5874\r\n\r\nThe EU EUSTACE project has received funding by the European Union's Horizon 2020 research and innovation programme under grant agreement no 640171.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": null, "updateFrequency": "unknown", "dataLineage": "This data forms part of the European Climate Assessment & Dataset (ECA&D) (www.ecad.eu) It has been derived from the non-homogenised version of the ECA&D data. \r\n\r\nThis dataset has been produced under funding from the EU EUSTACE project, which has received funding by the European Union's Horizon 2020 research and innovation programme under grant agreement no 640171.", "removedDataReason": "", "keywords": "", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2019-04-09T16:26:03", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 929, "bboxName": "Europe", "eastBoundLongitude": 45.0, "westBoundLongitude": -30.0, "southBoundLatitude": 30.0, "northBoundLatitude": 75.0 }, "verticalExtent": null, "result_field": { "ob_id": 27401, "dataPath": "https://www.ecad.eu/dailydata/predefinedseries.php", "oldDataPath": [], "storageLocation": "external", "storageStatus": "online", "volume": 0, "numberOfFiles": 0, "fileFormat": "ASCII format" }, "timePeriod": { "ob_id": 7354, "startTime": "1951-01-01T00:00:00", "endTime": "2015-12-31T23:59:59" }, "resultQuality": { "ob_id": 3272, "explanation": "This is an external dataset. See the ECA&D webpages for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-03-12" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 27402, "uuid": "be1daa81f36b4befa090894daec5bbef", "short_code": "comp", "title": "Derivation of the EUSTACE European land station daily air temperature measurements, bias adjusted for 1951-2015", "abstract": "Details of the derivation of these datasets are given in the following papers: \r\n\r\n1) Homogenization of daily ECA&D temperature series Antonello Angelo Squintu, Gerard van der Schrier, Yuri Brugnara, Albert Klein Tank: 2018, Intern. J. Climatology (published on line), doi:10.1002/joc.5874 https://www.ecad.eu/publications/index.php. \r\n\r\n2) Building long homogeneous temperature series across Europe: a new approach for the blending of neighboring series Antonello A. Squintu, Gerard van der Schrier, Else J. M. van den Besselaar, Richard C. Cornes, Albert Klein Tank, submitted" }, "procedureCompositeProcess": null, "imageDetails": [ 214 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2632, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 81, "licenceURL": "https://www.ecad.eu/documents/ECAD_datapolicy.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 19556, "uuid": "a52b2cc065a847b8a77a93896880349f", "short_code": "proj", "title": "EUSTACE (EU Surface Temperature for All Corners of Earth)", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is producing 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\nDay-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. Satellite data can be used to estimate temperatures at locations where no ground (or in situ) observations are available. To achieve this, we must develop an understanding of the relationships between traditional (land and marine) surface air temperature measurements and satellite measurements, i.e. land surface temperature, ice surface temperature, sea surface temperature and lake surface water temperature. These relationships can be derived either empirically, or with the help of physical understanding.\r\n\r\nTo achieve this the EUSTACE project is using new statistical techniques to provide information on higher spatial and temporal scales than are currently available, making optimum use of the information in data-rich eras. The final and intermediate products of EUSTACE (e.g. satellite skin temperature retrievals over all domains with consistent uncertainty estimates; station time series with discontinuities identified; information on the relationship between skin and air temperature over different domains and different seasons) will be interesting for many applications.\r\n\r\nThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640171." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 20098, "uuid": "7ebff7be4c0149d082ca9a32ec8df4da", "short_code": "coll", "title": "EUSTACE: Collection of products from the EUSTACE (EU Surface Temperature for All Corners of Earth) project", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is an EU Horizon 2020 project, producing 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\nThe data are publically available and consists of a number of different products: satellite skin temperature retrievals over all surface types; global surface air temperature derived from satellite skin temperature retrievals; homogonised surface meteorological station records for Europe and a European in filled analysis; global surface meteorological station records with discontinuities identified; and global analyses of daily surface air temperature going back to 1850, derived from both satellite and meteorological station data." }, { "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": [ 204930, 204929, 114525, 114528, 114526, 114524, 76415, 76414, 114529, 114847, 114848 ], "onlineresource_set": [ 16754, 26513, 26514, 26595 ] }, { "ob_id": 20093, "uuid": "7925ded722d743fa8259a93acc7073f2", "title": "EUSTACE: Global land station daily air temperature measurements with non-climatic discontinuities identified, for 1850-2015", "abstract": "This dataset consists of a global collection of land surface air temperature data from meteorological stations covering the period from 1850-2015. It has been compiled as part of the European Union Horizon 2020 EUSTACE (EU Surface Temperature for All Corners of Earth) project.\r\n\r\nThe dataset provides daily maximum and minimum temperatures from stations globally, brought together from a number of public databases: Global Historical Climatology Network Daily Temperatures (GHCN-D); European Climate Assessment & Dataset (ECA&D) non-blended; International Surface Temperature Initiative (ISTI); DECADE (Data on Climate and Extreme weather for the Central Andes); and ERA-CLIM (European Reanalysis of Global Climate Observations). These data have then been quality controlled through the removal of duplicates and unreliable data sources, and come with a large amount of additional information on quality, homogeneity and resolution.\r\n\r\nThis data is available for non-commercial use.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2019-01-11T15:54:23", "updateFrequency": "notPlanned", "dataLineage": "Data have been produced and archived for the EU EUSTACE project, which has received funding by the European Union's Horizon 2020 research and innovation programme under grant agreement no 640171. \r\n\r\nThis dataset is built on data from the following data collections:\r\nGlobal Historical Climatology Network (GHCN)-Daily, European Climate Assessment & Dataset (ECA&D), International Surface Temperature Initiative (ISTI), the DECADE datasets for the Central Plateau in South America, and surface observations digitised during the ERA-CLIM project. (See the documentation section for references)\r\n\r\nThe following data providers also contributed to the full EUSTACE product, but data could not be redistributed due to licensing: Servicio Meteorológico Nacional (SMN); Royal Netherlands Meteorological Institute (KNMI); University of Bern", "removedDataReason": "", "keywords": "eustace, land surface temperature, station", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2019-02-22T09:31:30", "doiPublishedTime": "2019-02-22T09:48:17", "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": 26930, "dataPath": "/neodc/eustace/data/station/ubern/land/global/daily/v1.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 20093416149, "numberOfFiles": 171, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 7247, "startTime": "1850-01-01T00:00:00", "endTime": "2015-12-31T23:59:59" }, "resultQuality": { "ob_id": 3216, "explanation": "Data have been quality controlled as described in the product user guide", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-01-15" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26931, "uuid": "fd310daa42fd4f18a7f73aee86a248ff", "short_code": "comp", "title": "Derivation of the EUSTACE land station daily air temperature measurements with non-climatic discontinuities identified", "abstract": "The EUSTACE dataset, 'Global land station daily air temperature measurements with non-climatic discontinuities applied, for 1850-2015', has been produced by bringing together daily maximum and minimum temperatures from various public databases (GHCN-D, ECA&D, DECADE, ISTI and ERA-CLIM). These data have then been quality controlled through the removal of duplicates and unreliable data sources, and were assessed for homogenity by applying tests to look for breakpoints in the time series.\r\nThe data were also assessed to provide a rough estimation of the reporting resolution for each year in the series.\r\n\r\nFor further details see the EUSTACE product user guide.\r\n\r\nThe following datasets have been used as input:\r\nGlobal Historical Climatology Network (GHCN)-Daily v3.22 (Menne, M. J., Durre, I., Vose, R. S., Gleason, B. E., & Houston, T. G. (2012). An overview of the global historical climatology network-daily database. Journal of Atmospheric and Oceanic Technology, 29(7), 897-910.); European Climate Assessment & Dataset (ECA&D) – October 2016 update (Klein-Tank, A., Wijngaard, J. B., Können, G. P., Böhm, R., Demarée, G., Gocheva, A., et al. (2002). Daily dataset of 20th‐century surface air temperature and precipitation series for the European Climate Assessment. International Journal of Climatology, 22(12), 1441-1453.); International Surface Temperature Initiative (ISTI) v1.00 (Rennie, J. J., Lawrimore, J. H., Gleason, B. E., Thorne, P. W., Morice, C. P., Menne, M. J., et al. (2014). The international surface temperature initiative global land surface databank: Monthly temperature data release description and methods. Geoscience Data Journal, 1(2), 75-102.); Project DECADE (Hunziker, S., Gubler, S., Calle, J., Moreno, I., Andrade, M., Velarde, F., et al. (2017). Identifying, attributing, and overcoming common data quality issues of manned station observations. International Journal of Climatology, 37(11), 4131-4145.); Projects ERA-CLIM / ERA-CLIM2 (Stickler, A., Brönnimann, S., Valente, M. A., Bethke, J., Sterin, A., Jourdain, S., et al. (2014). ERA-CLIM: historical surface and upper-air data for future reanalyses. Bulletin of the American Meteorological Society, 95(9), 1419-1430.)" }, "procedureCompositeProcess": null, "imageDetails": [ 214 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "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": 19556, "uuid": "a52b2cc065a847b8a77a93896880349f", "short_code": "proj", "title": "EUSTACE (EU Surface Temperature for All Corners of Earth)", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is producing 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\nDay-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. Satellite data can be used to estimate temperatures at locations where no ground (or in situ) observations are available. To achieve this, we must develop an understanding of the relationships between traditional (land and marine) surface air temperature measurements and satellite measurements, i.e. land surface temperature, ice surface temperature, sea surface temperature and lake surface water temperature. These relationships can be derived either empirically, or with the help of physical understanding.\r\n\r\nTo achieve this the EUSTACE project is using new statistical techniques to provide information on higher spatial and temporal scales than are currently available, making optimum use of the information in data-rich eras. The final and intermediate products of EUSTACE (e.g. satellite skin temperature retrievals over all domains with consistent uncertainty estimates; station time series with discontinuities identified; information on the relationship between skin and air temperature over different domains and different seasons) will be interesting for many applications.\r\n\r\nThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640171." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 69338, 69339, 69340, 69341, 69342, 69343, 69344, 69345, 69346, 69347, 69348, 69349, 69350, 69351, 69352, 69353, 69354, 69355, 69356, 69357, 69358, 69359, 69360, 69361 ], "vocabularyKeywords": [], "identifier_set": [ 10484 ], "observationcollection_set": [ { "ob_id": 20098, "uuid": "7ebff7be4c0149d082ca9a32ec8df4da", "short_code": "coll", "title": "EUSTACE: Collection of products from the EUSTACE (EU Surface Temperature for All Corners of Earth) project", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is an EU Horizon 2020 project, producing 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\nThe data are publically available and consists of a number of different products: satellite skin temperature retrievals over all surface types; global surface air temperature derived from satellite skin temperature retrievals; homogonised surface meteorological station records for Europe and a European in filled analysis; global surface meteorological station records with discontinuities identified; and global analyses of daily surface air temperature going back to 1850, derived from both satellite and meteorological station data." }, { "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": [ 143612, 143611, 76401, 113036, 112949, 76400, 76402, 76403, 113037, 113229, 113230, 113231, 113232 ], "onlineresource_set": [ 16755, 26474, 38029, 26556, 87780, 95037 ] }, { "ob_id": 20094, "uuid": "b2670fb9d6e14733b303865c85c2065d", "title": "EUSTACE / E-OBS: Gridded European surface air temperature based on homogenised land station records since 1950", "abstract": "This dataset consists of an infilled analysis of European surface air temperature which has been based on homogenised meteorological land station records since 1950. The original homogenised station records are also available as a separate dataset. This dataset is a version of the ECA&D (European Climate Assessment & Dataset) E-OBS dataset, produced with funding from the EU Horizon2020 EUSTACE (EU Surface Temperature for All Corners of Earth) project and contract C3S_311a_Lot4 with the Copernicus Climate Change Service. \r\n\r\nThe data is available directly from the ECA&D website and is referenced here to form part of the EUSTACE collection of data. The EUSTACE version of the product is E-OBSv19.0eHOM and future versions of the gridded dataset using homogenised temperature data will be produced operationally from E-OBSv20.0e onward. \r\n\r\nData is available for non-commercial purposes under the ECA&D terms and conditions (see https://www.ecad.eu//documents/ECAD_datapolicy.pdf).\r\n\r\nThe EU EUSTACE project has received funding by the European Union's Horizon 2020 research and innovation programme under grant agreement no 640171 and contract C3S_311a_Lot4 with the Copernicus Climate Change Service.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": null, "updateFrequency": "", "dataLineage": "This dataset is a version of the ECA&D (European Climate Assessment & Dataset) E-OBS dataset, produced with funding from the EU Horizon2020 EUSTACE (EU Surface Temperature for All Corners of Earth) project and contract C3S_311a_Lot4 with the Copernicus Climate Change Service.", "removedDataReason": "", "keywords": "", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2019-04-09T16:21:11", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 929, "bboxName": "Europe", "eastBoundLongitude": 45.0, "westBoundLongitude": -30.0, "southBoundLatitude": 30.0, "northBoundLatitude": 75.0 }, "verticalExtent": null, "result_field": { "ob_id": 27403, "dataPath": "https://www.ecad.eu//download/ensembles/download.php", "oldDataPath": [], "storageLocation": "external", "storageStatus": "online", "volume": 0, "numberOfFiles": 0, "fileFormat": "Data are in NetCDF-4 format" }, "timePeriod": { "ob_id": 5265, "startTime": "1950-01-01T00:00:00", "endTime": "2015-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 27404, "uuid": "156440fab651474498f786a80e30d023", "short_code": "comp", "title": "Derivation of the EUSTACE in-filled analysis of European surface air temperature based on homogenised meteorological station records since 1950", "abstract": "This dataset has been derived by gridding European Homogenised Station data using the E-OBS methodology, as described in Cornes, R. C., van der Schrier, G., Besselaar, E. J. M., & Jones, P. D. \r\n( 2018). An ensemble version of the E‐OBS temperature and precipitation data sets. /Journal of Geophysical Research: Atmospheres/, 123, 9391– 9409. https://doi.org/10.1029/2017JD028200" }, "procedureCompositeProcess": null, "imageDetails": [ 214 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2632, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 81, "licenceURL": "https://www.ecad.eu/documents/ECAD_datapolicy.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 19556, "uuid": "a52b2cc065a847b8a77a93896880349f", "short_code": "proj", "title": "EUSTACE (EU Surface Temperature for All Corners of Earth)", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is producing 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\nDay-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. Satellite data can be used to estimate temperatures at locations where no ground (or in situ) observations are available. To achieve this, we must develop an understanding of the relationships between traditional (land and marine) surface air temperature measurements and satellite measurements, i.e. land surface temperature, ice surface temperature, sea surface temperature and lake surface water temperature. These relationships can be derived either empirically, or with the help of physical understanding.\r\n\r\nTo achieve this the EUSTACE project is using new statistical techniques to provide information on higher spatial and temporal scales than are currently available, making optimum use of the information in data-rich eras. The final and intermediate products of EUSTACE (e.g. satellite skin temperature retrievals over all domains with consistent uncertainty estimates; station time series with discontinuities identified; information on the relationship between skin and air temperature over different domains and different seasons) will be interesting for many applications.\r\n\r\nThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640171." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 20098, "uuid": "7ebff7be4c0149d082ca9a32ec8df4da", "short_code": "coll", "title": "EUSTACE: Collection of products from the EUSTACE (EU Surface Temperature for All Corners of Earth) project", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is an EU Horizon 2020 project, producing 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\nThe data are publically available and consists of a number of different products: satellite skin temperature retrievals over all surface types; global surface air temperature derived from satellite skin temperature retrievals; homogonised surface meteorological station records for Europe and a European in filled analysis; global surface meteorological station records with discontinuities identified; and global analyses of daily surface air temperature going back to 1850, derived from both satellite and meteorological station data." }, { "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": [ 204954, 204953, 76383, 114844, 114531, 114530, 76382, 76381, 114532, 114845, 114846 ], "onlineresource_set": [ 16756, 26522, 26523, 26593, 26594 ] }, { "ob_id": 20095, "uuid": "f883e197594f4fbaae6edebafb3fddb3", "title": "EUSTACE: Globally gridded clear-sky daily air temperature estimates from satellites with uncertainty estimates for land, ocean and ice, 1995-2016", "abstract": "This dataset consists of gloabl surface air temperature estimates derived from satellite surface skin temperature measurements, with uncertainties provided. It has been compiled as part of the European Union Horizon 2020 EUSTACE (EU Surface Temperature for All Corners of Earth) project.\r\n\r\n The global surface air temperatures are provided separately for areas over land, sea and ice. These surface air temperatures have been derived from satellite skin temperatures using relationships between air and skin temperatures for each surface derived as part of the EUSTACE project. The air temperatures and uncertainty information are presented in a consistent format.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-04-30T21:54:55", "updateFrequency": "notPlanned", "dataLineage": "Data have been produced and archived for the EU EUSTACE project, which has received funding by the European Union's Horizon 2020 research and innovation programme under grant agreement no 640171.", "removedDataReason": "", "keywords": "EUSTACE, surface air temperature, satellite", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2019-04-08T10:41:58", "doiPublishedTime": "2019-04-08T11:51:16", "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": 27452, "dataPath": "/neodc/eustace/data/satellitederived/mohc/eustace/v1.0/day/0/0/R001336/20190111/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 457406744912, "numberOfFiles": 28469, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 7368, "startTime": "1995-06-01T23:00:00", "endTime": "2016-12-31T23:59:59" }, "resultQuality": { "ob_id": 3277, "explanation": "Data are as provided by the EUSTACE project", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-04-04" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 27453, "uuid": "c6b7896243de4f4c91eed735e61d4b69", "short_code": "comp", "title": "Derivation of the EUSTACE globally gridded clear-sky daily air temperature estimates from satellites with uncertainty estimates for land, ocean and ice, 1995-2016", "abstract": "Surface air temperature estimates have been calculated from satellite-derived surface skin temperature measurements within the EUSTACE project. Research was done to investigate the relationship between these air and skin temperatures based on temporally and spatially collocated observations, and empirical relationships have been derived. These have then been applied to the satellite skin temperatures used in the EUSTACE project to estimate surface air temperatures. 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Satellite data can be used to estimate temperatures at locations where no ground (or in situ) observations are available. To achieve this, we must develop an understanding of the relationships between traditional (land and marine) surface air temperature measurements and satellite measurements, i.e. land surface temperature, ice surface temperature, sea surface temperature and lake surface water temperature. These relationships can be derived either empirically, or with the help of physical understanding.\r\n\r\nTo achieve this the EUSTACE project is using new statistical techniques to provide information on higher spatial and temporal scales than are currently available, making optimum use of the information in data-rich eras. The final and intermediate products of EUSTACE (e.g. satellite skin temperature retrievals over all domains with consistent uncertainty estimates; station time series with discontinuities identified; information on the relationship between skin and air temperature over different domains and different seasons) will be interesting for many applications.\r\n\r\nThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640171." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 21681, 21682, 25444, 25445, 25446, 25447, 25449, 31712, 31713, 31714, 31715, 31716, 31717, 31718, 31719, 31720, 31721, 31722, 31723, 31724, 31725, 31726, 31727, 31728, 31729, 31730, 31731, 31732, 31733, 31734, 31735, 31736, 31737, 31738, 31739, 31740, 31741, 31742, 31743, 31744, 31745, 31746, 31747, 31748, 31749, 31750, 31751, 31752, 31753, 31754, 31755, 31756, 31757, 31758, 31759, 31760, 31761, 31762, 31763, 31764, 31765, 31766, 31767, 31768 ], "vocabularyKeywords": [], "identifier_set": [ 10509 ], "observationcollection_set": [ { "ob_id": 20098, "uuid": "7ebff7be4c0149d082ca9a32ec8df4da", "short_code": "coll", "title": "EUSTACE: Collection of products from the EUSTACE (EU Surface Temperature for All Corners of Earth) project", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is an EU Horizon 2020 project, producing 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\nThe data are publically available and consists of a number of different products: satellite skin temperature retrievals over all surface types; global surface air temperature derived from satellite skin temperature retrievals; homogonised surface meteorological station records for Europe and a European in filled analysis; global surface meteorological station records with discontinuities identified; and global analyses of daily surface air temperature going back to 1850, derived from both satellite and meteorological station data." }, { "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": [ 76417, 142261, 142260, 114769, 114765, 76419, 76418, 76416, 114771, 114793, 114766, 114767, 114770, 114768, 114772, 114794, 114795 ], "onlineresource_set": [ 16757, 26603, 87682 ] }, { "ob_id": 20096, "uuid": "4f9f712ec0e743ea81a1fde9c1f57514", "title": "EUSTACE: Regionally-complete gridded daily air temperature combining surface and satellite data, with uncertainty estimates, for 1850-2016", "abstract": "This dataset consists of a globally-complete daily analysis of surface air temperature for the whole Earth since 1850, based on combined information from satellite and in situ data sources. Uncertainty estimates are provided with the data. \r\n\r\nThe EUSTACE (EU Surface Temperature for All Corners of Earth) project is producing 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. This particular dataset has been infilled to provide a globally-complete analysis with an 'Ambitious' statistical infilling method...", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": null, "updateFrequency": "", "dataLineage": "Data are from the EUSTACE project", "removedDataReason": "", "keywords": "", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "planned", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": null, "timePeriod": { "ob_id": 5264, "startTime": "1850-01-01T00:00:00", "endTime": "2015-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [], "permissions": [], "projects": [], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "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": [ 204907, 204906, 204905, 76409, 76408, 76410, 76411 ], "onlineresource_set": [ 16758 ] }, { "ob_id": 20097, "uuid": "468abcf18372425791a31d15a41348d9", "title": "EUSTACE: Global daily air temperature combining surface and satellite data, with uncertainty estimates, for 1850-2015, v1.0", "abstract": "This dataset consists of a global daily analysis of surface air temperature for the whole Earth since 1850, based on combined information from satellite and in situ data sources, including uncertainty estimates. This is v1.0 of the product, which has been compiled as part of the European Union Horizon 2020 EUSTACE (EU Surface Temperature for All Corners of Earth) project. \r\n\r\nThis product provides global mean air temperature data on a regular lat-lon grid with a grid spacing of 0.25 degrees, and provides daily data from 1850 to 2015. Uncertainty estimates are also provided, with both a 'total' uncertainty, and an ensemble of 10 samples. The mean temperature data and uncertainty estimates provided are consistent across a broad range of space and time scales from daily 0.25° to multidecadal global averages. The coverage is significantly better than is available from station data alone, and covers land, ocean and ice areas.\r\n\r\nThis data has been derived using a statistical method to estimate air temperatures at all places and times. It takes into account uncertainty in the input data sets covering errors in the in situ measurements, land station homogenisation and errors in the air temperatures estimated from satellite data . Although the statistical model estimates temperatures at all locations, the product is not globally complete, as areas with too few data to provide a reliable air temperature estimate have been masked out.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T03:10:01", "updateFrequency": "notPlanned", "dataLineage": "Data have been produced and archived for the EU EUSTACE project, which has received funding by the European Union's Horizon 2020 research and innovation programme under grant agreement no 640171.", "removedDataReason": "", "keywords": "EUSTACE, surface air temperature", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "0.25 degrees", "status": "completed", "dataPublishedTime": "2019-05-30T16:29:50", "doiPublishedTime": "2019-05-30T16:45:46", "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": 27503, "dataPath": "/neodc/eustace/data/combined/mohc/eustace/v1.0/day/0/0/R001400/20190326/global/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1640021735505, "numberOfFiles": 60631, "fileFormat": "Data are in NetCDF format." }, "timePeriod": { "ob_id": 7384, "startTime": "1850-01-01T00:00:00", "endTime": "2015-12-31T23:59:59" }, "resultQuality": { "ob_id": 3284, "explanation": "validated by the data providers", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-05-30" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 27504, "uuid": "a8a2432b702c482d86c6d4f299c0c110", "short_code": "comp", "title": "Derivation of the EUSTACE Global daily air temperature combining surface and satellite data, with uncertainty estimates, for 1850-2015, v1.0", "abstract": "Global mean surface air temperature measurements have been derived daily for the period between 1850-2015 based on combined information from satellite and in-situ data sources. This data has been derived using a statistical method to estimate air temperatures at all places and times. It takes into account uncertainty in the input data sets covering errors in the in situ measurements, land station homogenisation and errors in the air temperatures estimated from satellite data . Although the statistical model estimates temperatures at all locations, the product is not globally complete, as areas with too few data to provide a reliable air temperature estimate have been masked out. The derivation of this dataset and the statistical model used has been described further in the EUSTACE Scientific and Product User Guides." }, "procedureCompositeProcess": null, "imageDetails": [ 214 ], "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": 19556, "uuid": "a52b2cc065a847b8a77a93896880349f", "short_code": "proj", "title": "EUSTACE (EU Surface Temperature for All Corners of Earth)", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is producing 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\nDay-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. Satellite data can be used to estimate temperatures at locations where no ground (or in situ) observations are available. To achieve this, we must develop an understanding of the relationships between traditional (land and marine) surface air temperature measurements and satellite measurements, i.e. land surface temperature, ice surface temperature, sea surface temperature and lake surface water temperature. These relationships can be derived either empirically, or with the help of physical understanding.\r\n\r\nTo achieve this the EUSTACE project is using new statistical techniques to provide information on higher spatial and temporal scales than are currently available, making optimum use of the information in data-rich eras. The final and intermediate products of EUSTACE (e.g. satellite skin temperature retrievals over all domains with consistent uncertainty estimates; station time series with discontinuities identified; information on the relationship between skin and air temperature over different domains and different seasons) will be interesting for many applications.\r\n\r\nThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640171." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 25449, 69340, 69341, 70148, 70149, 70150, 70151, 70152, 70153 ], "vocabularyKeywords": [], "identifier_set": [ 10528 ], "observationcollection_set": [ { "ob_id": 20098, "uuid": "7ebff7be4c0149d082ca9a32ec8df4da", "short_code": "coll", "title": "EUSTACE: Collection of products from the EUSTACE (EU Surface Temperature for All Corners of Earth) project", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is an EU Horizon 2020 project, producing 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\nThe data are publically available and consists of a number of different products: satellite skin temperature retrievals over all surface types; global surface air temperature derived from satellite skin temperature retrievals; homogonised surface meteorological station records for Europe and a European in filled analysis; global surface meteorological station records with discontinuities identified; and global analyses of daily surface air temperature going back to 1850, derived from both satellite and meteorological station data." }, { "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": [ 143588, 143587, 76405, 114965, 114964, 76407, 76406, 76404, 114967, 114968, 114971, 114969, 114966, 114972, 114970 ], "onlineresource_set": [ 16759, 26663, 94813 ] }, { "ob_id": 20102, "uuid": "e7abb935751a465981c6155593ba6dd3", "title": "CARDOMOM 2001 - 2010 global carbon model data", "abstract": "The CARbon DAta MOdel fraMework (CARDAMOM; Bloom et al., 2015 in review) outputs are derived from a global 1-degree x 1-degree 2001-2010 model-data fusion (MDF) analysis. The data include allocation fractions (AF) residence times (RT), mean carbon pool stocks (CP) and fluxes (FL). The Data Assimilation Linked Ecosystem Carbon model version 2 (DALEC2) and the Markov Chain Monte Carlo MDF algorithm are described by Bloom & Williams (2015); the fire module is described by Bloom et al., (2015; in review). Data constraints used in the CARDAMOM analysis consist of MODIS leaf area index (LAI), Harmonised World Soil Database (HWSD; Hiederer & Kochy, 2012) and tropical biomass (Saatchi et al., 2011). For each 1-degree x 1-degree gridcell, the metrics (e.g. mean, median, etc.) are based on 4000 DALEC2 model parameter samples unique to that grid-cell. ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-11-29T16:29:55", "updateFrequency": "", "dataLineage": "The data was produce by Mat Williamas and Jean Francoise Exbrayat of the University of Edinburgh as part of the NCEO work programme", "removedDataReason": "", "keywords": "carbon cycle, biomass, soil carbon, allocation, residence time", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "underDevelopment", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": null, "verticalExtent": null, "result_field": null, "timePeriod": null, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 5002, "uuid": "60e718d3f2957f742c89b2b4fc159718", "short_code": "proj", "title": "National Centre for Earth Observation (NCEO)", "abstract": "The National Centre for Earth Observation is a partnership of scientists and institutions, from a range of disciplines, who are using data from Earth observation satellites to monitor global and regional changes in the environment and to improve understanding of the Earth system so that we can predict future environmental conditions.\r\n\r\nNCEO's Vision is to unlock the full potential of Earth observation to monitor, diagnose and predict climate and environmental changes, ensuring that these scientific advances are delivered to the wider community embedded in world class science." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 30127, "uuid": "82b29f96b8c94db28ecc51a479f8c9c6", "short_code": "coll", "title": "National Centre for Earth Observation (NCEO) Core datasets", "abstract": "This NCEO Core data set collection contains data generated by the National Centre for Earth Observation core scientific programmes. NCEO is a National Environment Research Council (NERC) research centre with more than 80 scientists distributed across leading UK universities and research organisations and led by Professor John Remedios at the University of Leicester.\r\n\r\nNCEO provides the UK with core expertise in Earth Observation science, data sets and merging techniques, and model evaluation to underpin Earth System research and the UK’s international contribution to environmental science. NCEO scientists work strategically with space agencies, play significant roles in mission planning, and generate internationally-recognised data products from 20 different satellite instruments." } ], "responsiblepartyinfo_set": [ 204983, 204982, 204981, 204980, 204979, 204978, 79059 ], "onlineresource_set": [ 16782 ] }, { "ob_id": 20108, "uuid": "e4f39152bc50466f8887bd2a343cac93", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity data for the Greenland Northern Drainage basin from ERS-1 for winter 1991-1992, v1.1 (June 2016 release)", "abstract": "This dataset contains ice velocities for the Greenland Northern Drainage Basin for winter 1991-1992, which have been produced as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. The data has been derived from intensity-tracking of ERS-1 Ice phase (3 days repeat) data aquired between 29th December 1991 and 22nd March 1992.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E). The horizontal velocity is provided in true meters per day, towards EASTING(x) and NORTHING(y) direction of the grid, and the vertical displacement (z), derived from a digital elevation\r\nmodel, is also provided. (Please note that in earlier versions of this product the horizontal velocities were provided as true East and North velocities).\r\n\r\n Both a single NetCDF file (including all measurements and annotation), and separate geotiff files with the velocity components are provided. The product was generated by DTU Space - Microwaves and Remote Sensing.\r\n\r\nPlease note - this product was released on the Greenland Ice Sheets download page in June 2016, but an earlier product (also accidentally labelled v1.1) was available through the CCI Open Data Portal and the CEDA archive until 29th November 2016. Please now use this later v1.1 product.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-11-29T18:15:00.549763", "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI Greenland Ice Sheet project team and supplied to CEDA in the context of the ESA CCI Open Data Portal Project.", "removedDataReason": "", "keywords": "Greenland, Ice sheet, CCI, ESA", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2016-11-29T19:14:40", "doiPublishedTime": null, "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": 20109, "dataPath": "/neodc/esacci/ice_sheets_greenland/data/greenland_ice_velocity/greenland_northern_drainage_basins_ERS1_winter_1991_1992/v1.1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 58641253, "numberOfFiles": 8, "fileFormat": "Data are in NetCDF and GeoTiff format" }, "timePeriod": { "ob_id": 5267, "startTime": "1991-12-29T00:00:00", "endTime": "1992-03-22T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "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": [ 6023, 11952, 11953, 12066, 13204, 13205, 13206, 13207, 13228, 18431, 18432, 18433 ], "vocabularyKeywords": [ { "ob_id": 10187, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" }, { "ob_id": 10666, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" }, { "ob_id": 11047, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_amisar", "resolvedTerm": "AMI-SAR" }, { "ob_id": 10809, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_ers1", "resolvedTerm": "ERS-1" } ], "identifier_set": [], "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": [ 76431, 105352, 105176, 104956, 76432, 76433, 76427, 76426 ], "onlineresource_set": [ 16783, 16786, 16784, 26088, 16785 ] }, { "ob_id": 20115, "uuid": "0c724d2a018c48cab18e1a14f0fee6df", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Gravimetric Mass Balance from GRACE data, derived by TU Dresden, v1.0", "abstract": "This dataset provides the Gravitational Mass Balance (GMB) product derived from the GRACE satellite instrument, by TU Dresden. The data consists of two products, a mass change time series for the Greenland Ice Sheet and individual basins, and mass trend grids for 5-year periods. \r\n\r\nThe mass change time series contains the mass change (with respect to a chosen reference month) for all of the Greenland Ice Sheet and each individual drainage basin. For each month (defined by a decimal year) a mass change in Gt and its associated error (also in Gt) is provided. The mass trend grid product is given in units of mm water equivalent per year.\r\n\r\nMass balance is an important variable to understand glacial thinning and ablation rates to enable mapping glacier area change. The time series allows the longer term comparison of trends whereas the mass trend grids provide a yearly snapshot which can be further analysed and compared across the data set.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-11-29T17:14:55.195550", "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI Greenland Ice Sheet project team and supplied to CEDA in the context of the ESA CCI Open Data Portal Project.", "removedDataReason": "", "keywords": "Greenland, Ice sheet, CCI, ESA", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2016-11-30T17:02:45", "doiPublishedTime": null, "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": 20116, "dataPath": "/neodc/esacci/ice_sheets_greenland/data/greenland_gravimetric_mass_balance/TU_Dresden/v1.0", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 7587456, "numberOfFiles": 30, "fileFormat": "Mass trend grids are in NetCDF format.\r\nTime series are in ASCII and png format." }, "timePeriod": { "ob_id": 5278, "startTime": "2002-07-31T23:00:00", "endTime": "2016-01-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "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": [ 12066, 50542, 50543, 55952, 55953, 55954, 55955 ], "vocabularyKeywords": [ { "ob_id": 10187, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" }, { "ob_id": 10666, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_iceSheet", "resolvedTerm": "ice sheets" } ], "identifier_set": [], "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": [ 76458, 105351, 105175, 104955, 76459, 76460, 76457, 76456 ], "onlineresource_set": [ 16798, 16799, 16797, 16800 ] }, { "ob_id": 20130, "uuid": "889fc3c877e8447bb7b2a100ef17a3f4", "title": "Using Optimisation Algorithms to tune Climate Models (OptClim): perturbed parameter configurations for HadAM3 and HadCM3 model runs", "abstract": "Results and software from HadAM3 and HadCM3 model runs for the Using Optimisation Algorithms to tune Climate Models (OptClim) project. These data are principally PP binary output files from a set of climate model runs along with their associated model configuration parameters as reported in Tett et al, (2017) - see online resources for full link.\r\n\r\nThe simulation output are mainly from HadAM3 model runs, though some HadCM3 output data are also present. Data were produced on the University of Edinburgh computing cluster.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2017-08-04T14:16:50.472260", "updateFrequency": "notPlanned", "dataLineage": "Data produced at the University of Edinburgh. Sent to the CEDA Archive in support of a NERC funded science publication.", "removedDataReason": "", "keywords": "Perturbed Physics, HadAM3, HadCM3, Optimisation, Model Calibration", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2017-06-13T09:53:34", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 20128, "dataPath": "/badc/optclim/data", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1879618632303, "numberOfFiles": 412635, "fileFormat": "pp" }, "timePeriod": null, "resultQuality": { "ob_id": 3087, "explanation": "See publications on project. ", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2017-06-13" }, "validTimePeriod": { "ob_id": 5280, "startTime": "1999-01-01T00:00:00", "endTime": "2010-12-31T23:59:59" }, "procedureAcquisition": null, "procedureComputation": { "ob_id": 20129, "uuid": "9e32937868fd46c383080bacb11b261a", "short_code": "comp", "title": "HadAM3 and HadCM3 deployed on University of Edinburgh computing cluster", "abstract": "deployed on University of Edinburgh computing cluster" }, "procedureCompositeProcess": null, "imageDetails": [ 2 ], "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": 20126, "uuid": "c6d5f0a1c9834f6a8cacedbb01bbb385", "short_code": "proj", "title": "OptClim: Using Optimisation Algorithms to tune Climate Models", "abstract": "OptCliM investigated climate modelling advances from mathematical optimization research. Our focus was upon parameterised processes that represent physics that are unresolved within climate models. These unresolved processes were represented through equations that include fixed parameters, with a typical climate model having around a hundred parameters. For example, thunderstorms not only generate heavy rain but are also one route for moisture into the atmosphere. One of the parameters expressed the rate at which moist air in the storm is mixed into the atmosphere. A range of values for each parameter was consistent with theory and measurement with changes in some parameters having a dramatic effect on future climate predictions. It was therefore necessary to have realistic parameter values in order to adequately model past or future climates. " } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6023, 8322, 9042, 9043, 18924, 19038, 19039, 19040, 19041, 19042, 19043, 19055, 19056, 50512, 50542, 50543, 50652, 50653, 50654, 50655, 50656, 50657, 50658, 50659, 50660, 50661, 50662, 50663, 50664, 50665, 50666, 50667, 50668, 50669, 50670, 50671, 50672, 50673, 50674, 50675, 50676, 50677, 50678, 50679, 50680, 50681, 50682, 50683, 50684, 50685, 50686, 50687, 50688, 50689, 50690, 50691, 50692, 50693, 50694, 50695, 50696, 50697, 50698, 50699, 50700, 50701, 50702, 50703, 50705, 50706, 50707, 50708, 50709, 50710, 50711, 50712, 50713, 50714, 50715, 50716, 50717, 50718, 50719, 50720, 50721, 50722, 50723, 50724, 50726, 50727, 50728, 50729, 50730, 50731, 50732, 50733, 50734, 50735, 50736, 50737, 50738, 50739, 50740, 50741, 50742, 50743, 50744, 50745, 50746, 50747, 50748, 50749, 50750, 50751, 50754, 50755, 50756, 50757, 50758, 50759, 50760, 50761, 50762, 50763, 50764, 50765, 50766, 50770, 50771, 50772, 50776, 50777, 50780, 50781, 50782, 50783, 50784, 50785, 50786, 50787, 50788, 50789, 50790, 50791, 50792, 50793, 50794, 50795, 50796, 50797, 50798, 50799, 50800, 50801, 50802, 50803, 50804, 51582, 51583, 52359, 52565, 52568, 52573, 52580, 52586, 52589, 52593, 52761, 53106, 54104, 54114, 54115, 54116, 54117, 54118, 54119, 54121, 54123, 54124, 54125, 54130, 54135, 54136, 54141, 54147, 54150, 55622, 55623, 55624, 55625, 55626, 55627, 55628, 55629, 55630, 55631, 55632, 55633, 55634, 55635, 55636, 55637, 55638, 55639, 55640, 55641, 55642, 55643, 55644, 55645, 55646, 55647, 55648, 55649, 55650, 55651, 55652, 55653, 55654, 55655, 55656, 55657, 55658, 55659, 55660, 55661, 55662, 55663, 55664, 55665, 55666, 55667, 55668, 55669, 55670, 55671, 55672, 55673, 55674, 55675, 55676 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 104800, 105353, 105177, 101535, 101534, 101533, 78296, 78291, 78292, 78293, 78294, 78295 ], "onlineresource_set": [] }, { "ob_id": 20138, "uuid": "72fcd8b56e6d4e468a80cfa01d645d20", "title": "SPECS - MPI-ESM-LR model output prepared for SPECS decadal (1901-2015)", "abstract": "This dataset includes the MPI-ESM-LR model output prepared for SPECS decadal (1901-2015). These data were prepared by the Max Planck Institute for Meteorology (MPI-M), as part of the SPECS project. \r\n \r\nModel id is MPI-ESM-LR (MPI-ESM-LR 2015; atmosphere: ECHAM6 v6.3.01p2 (REV: 3904), T63L47; land: JSBACH (REV: 3904); ocean: MPIOM v1.6.1p1 (REV: 3753) marine biogeochemistry HAMOCC included, GR15L40; sea ice (REV: 3753). Frequency is daily and monthly. \r\n\r\nDaily Atmospheric variables are:\r\nclt hfls hfss pr prc psl rlds rlut rsds tas tasmin tasmax uas vas zg \r\n\r\nDaily land variables are: \r\nmrso \r\n\r\nMonthly atmos variables:\r\nclt hfls hfss hus pr prsn psl rlds rlut rsds rsdt rsut ta tas tasmax tasmin tauu tauv ua uas vas va zg \r\n\r\nMonthly ocean variables:\r\nmlotst so thetao tos uo vo zos \r\n\r\nMonthly land variables:\r\nmrro mrso\r\n\r\nMonthly sea ice variables:\r\nsit", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2025-07-18T01:56:38", "updateFrequency": "notPlanned", "dataLineage": "Data were supplied by SPECS participants to CEDA for archiving in 2017. Data was checked for compliance with CF standards and SPECS requirements.", "removedDataReason": "", "keywords": "specs, MPI-ESM, climate, model, decadal", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2017-01-10T13:35:52", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 528, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 20139, "dataPath": "/badc/specs/data/SPECS/output/MPI-M/MPI-ESM-LR/decadal", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2465179424764, "numberOfFiles": 29334, "fileFormat": "The data are provided in CF-compliant NetCDF format" }, "timePeriod": { "ob_id": 5239, "startTime": "1901-01-01T00:00:00", "endTime": "2015-12-31T23:59:59" }, "resultQuality": { "ob_id": 3058, "explanation": " Data have been quality controlled by CEDA, including internal metadata consistency for SPECS data is complete and that data are CF-compliant.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2016-09-23" }, "validTimePeriod": { "ob_id": 5281, "startTime": "1901-01-01T00:00:00", "endTime": "2015-12-31T23:59:59" }, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 153 ], "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": 12970, "uuid": "c9b4b1fcab734987bcbfb36437734ca7", "short_code": "proj", "title": "Seasonal-to-decadal climate Prediction for the improvement of European Climate Services (SPECS)", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nThe improved understanding and seamless predictions will offer better estimates of the future frequency of high-impact, extreme climatic events and of the prediction uncertainty. New services to convey climate information and its quality will be used.\r\n\r\nSPECS will be, among other things, the glue to coalesce the outcome of previous research efforts that hardly took climate prediction into account. It will ensure interoperability so as to easily incorporate their application in an operational context, provide the basis for improving the capacity of European policy making, industry and society to adapt to near-future climate variations and a coordinated response to some of the GFCS components.\r\n\r\nThis project is funded by the Seventh Framework Programme (FP7) of the European Commission (GA 308378)." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6021, 6022, 6255, 11044, 11045, 50426, 50429, 50431, 50475, 50496, 50498, 50554, 50555, 50559, 50561, 50566, 50568, 50569, 50579, 50586, 50587, 50588, 50589, 50591, 50592, 50596, 50598, 50603, 50608, 52741, 52747, 52748, 52755, 53094, 53107, 53108, 53109, 53110, 53113, 53128, 53129, 53130, 53131, 53133, 53143, 54228, 54796, 54797, 54798, 54799, 62501, 63972, 79918, 82362 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 6086, "uuid": "2d9c5f2cc621fb9bc0062356851b31b9", "short_code": "coll", "title": "SPECS: Seasonal-to-decadal climate prediction model outputs", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nA core set of common experiments has been defined, to which most forecast systems will contribute. Another set of coordinated experiments, tier 1, includes the experiments that one or more forecast systems are planning to run. \r\n\r\nA standard seasonal experimental set up will consist of ten-member ensembles, with two start dates per year (first of May and November) over the 1981-2012 period and seven-month forecast length. \r\n\r\nThe standard decadal experimental set up consists in five-member ensembles, starting on the first of November (or some time close to that date) of the years 1960, 1963, 1965, 1968, 1970, 1973, 1975, 1978, 1980, 1983, 1985, 1988, 1990, 1993, 1995, 1998, 2000, 2003, 2005, 2008, 2010, 2013, with a five-year forecast length. \r\n\r\nA description of the main experiments, with the minimum contribution in terms of start dates, forecast length and ensemble size follows: \r\n1 - Assessment of the impact of soil-moisture initial conditions (seasonal): contributing EC-Earth, IFS/NEMO (ECMWF), CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG);\r\n2 - Assessment of the impact of sea-ice initialization (interannual); contributing EC-Earth (IC3), IPSL-CM5, CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG)\r\n3 - Assessment of impact of increased horizontal resolution (seasonal and decadal); contributing CNRM-CM5 (CERFACS, decadal; MeteoF, seasonal), EC-Earth (IC3, seasonal; KNMI and SMHI, decadal), MPI-ESM (MPG, seasonal and decadal), IPSL-CM5 (decadal), UM (seasonal and decadal); \r\n4 - Assessment of impact of an improved stratosphere (seasonal and decadal) including interannually-varying ozone; contributing EC-Earth (KNMI seasonal with ozone; SMHI decadal), IFS/NEMO (ECMWF, seasonal), CNRM-CM5 (MeteoF, seasonal), UM (seasonal, decadal);\r\n5 - Assessment of impact of additional start dates (decadal); contributing EC-Earth (KNMI, SMHI), MPI-ESM (MPG), IPSL-CM5.\r\n\r\nSPECS research has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under SPECS project (grant agreement n° 308378)." } ], "responsiblepartyinfo_set": [ 78317, 78318, 78320, 78315, 78310, 78309, 78308, 78314, 78313, 78312, 78319, 78311, 78316 ], "onlineresource_set": [] }, { "ob_id": 20150, "uuid": "dc36731ace3046b284dafd809eecf7b9", "title": "UKCIP02: 5km gridded data for UK climate projection scenarios (2002)", "abstract": "5km gridded resolution data for four climate projection scenarios, produced in support of the UK Climate Impacts Programme 2002 (UKCIP02) by the Met Office Hadley Centre. \r\n\r\nThere are data for monthly and seasonal average anomalies with respect to simulated 1961~90 average for four alternative future climates for the UK. The four emissions scenarios are Low (LO), Medium-Low (ML), Medium-High (MH) and High (HI).\r\n\r\nMonthly data for cloud, precipitation (prec), temperature (temp), maximum temperature (tmax), minimum temperature (tmin) and wind are available using the following convention in the filename:\r\n2020s = predictions for 2011 to 2040,\r\n2050s = predictions for 2041 to 2070,\r\n2080s = predictions for 2071 to 2100.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2017-01-16T09:10:29.686045", "updateFrequency": "", "dataLineage": "Data were produced by the Met Office Hadley Centre, analysed by the Tyndall Centre and passed to the NCAS British Atmospheric Data Centre (NCAS BADC) for archival.", "removedDataReason": "", "keywords": "UKCIP, UKCIP02, Climate, Projections, UKCP", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "5 km", "status": "completed", "dataPublishedTime": "2017-02-20T12:46:09", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 509, "bboxName": "UKCIP02", "eastBoundLongitude": 3.0, "westBoundLongitude": -11.0, "southBoundLatitude": 49.0, "northBoundLatitude": 61.0 }, "verticalExtent": null, "result_field": { "ob_id": 20154, "dataPath": "/badc/ukcip02/data/5km_resolution/gridded", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 365426164, "numberOfFiles": 865, "fileFormat": "The data are provided as text files. " }, "timePeriod": { "ob_id": 3269, "startTime": "1961-01-01T00:00:00", "endTime": "2100-12-31T23:59:59" }, "resultQuality": { "ob_id": 3071, "explanation": "Data were quality controlled by UKCIP prior to release.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2017-01-12" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 11713, "uuid": "53e0417188a9587755a047eeee58f9ea", "short_code": "comp", "title": "UKCIP02 Scenario Computations", "abstract": "The UK Climate Impact Programme 2002 (UKCIP02) climate change scenarios are based exclusively on experiments completed using the HadCM3 global climate model, HadAM3H high-resolution atmosphere model and the HadRM3 regional climate mode by the Met Office Hadley Centrel. 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The climate change scenarios provide a common starting point for assessing climate change vulnerability, impacts and adaptation in the UK. \r\n\r\nThe UKCIP02 scenarios represent an advance in the description of future UK climates compared to the scenarios published for UKCIP in 1998. This is because they are based on new global emissions scenarios published in 2000 by the Intergovernmental Panel on Climate Change (IPCC) in their Special Report on Emissions Scenarios, and because they are based on a series of climate modelling experiments completed by the Hadley Centre using their most recently developed models. The scenarios describe four alternative future climates for the UK labelled, respectively, Low Emissions, Medium-Low Emissions, Medium-High Emissions and High Emissions. The scenarios are designed to be used in conjunction with other UKCIP reports and products. \r\n\r\nNo probabilities can be attached to these four climate futures – in line with the IPCC, UKCIP02 do not suggest that one is more likely than another. While they represent a wide range of possible future climates, the UKCIP02 scenarios do not capture the entire range of future possibilities." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 11710, "uuid": "eb1d7cd4265b240d14707d9df2d9e828", "short_code": "coll", "title": "UKCIP02: UK Climate Impact Programme (2002) projection scenarios datasets", "abstract": "The UK Climate Impacts Programme 2002 (UKCIP02) comprises a set of four scenarios of future climate change produced for assessing climate change vulnerability, impacts and adaptation in the UK based on the understanding of the science of climate change in 2002. \r\n\r\nData are provided at two resolutions 50km and 5km. The 5km resolution data are provided in both a gridded and time-series format. The four alternative future climates for the UK are labelled respectively, Low Emissions, Medium-Low Emissions, Medium-High Emissions and High Emissions. No probabilities can be attached to these four climate futures – in line with the IPCC, UKCIP02 do not suggest that one is more likely than another. While they represent a wide range of possible future climates, the UKCIP02 scenarios do not capture the entire range of future possibilities. The scenarios are designed to be used in conjunction with other UKCIP reports and products." } ], "responsiblepartyinfo_set": [ 78344, 78347, 78346, 78345, 78370, 78343, 78342, 78340, 78339, 78348, 78341, 78371, 148607 ], "onlineresource_set": [ 16856, 16857, 16858, 16869 ] }, { "ob_id": 20153, "uuid": "937eac83d9864174aed500b05c8fc012", "title": "UKCIP02: 5km temperature time-series data for UK climate projection scenarios (2002)", "abstract": "The 5km temperature time-series data for four climate projection scenarios produced in support of the UK Climate Impacts Programme 2002 (UKCIP02).\r\n\r\nMonthly temperature time-series data for four alternative future climates for the UK. The four emissions scenarios are Low (LO), Medium-Low (ML), Medium-High (MH) and High (HI).", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2017-01-16T08:56:46.962314", "updateFrequency": "", "dataLineage": "Data were produced by the Met Office Hadley Centre, analysed by the Tyndall Centre and passed to the NCAS British Atmospheric Data Centre (NCAS BADC) for archival.", "removedDataReason": "", "keywords": "UKCIP, UKCIP02, Climate, Projections, UKCP", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "5 km", "status": "completed", "dataPublishedTime": "2017-02-20T12:49:19", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 509, "bboxName": "UKCIP02", "eastBoundLongitude": 3.0, "westBoundLongitude": -11.0, "southBoundLatitude": 49.0, "northBoundLatitude": 61.0 }, "verticalExtent": null, "result_field": { "ob_id": 20155, "dataPath": "/badc/ukcip02/data/5km_resolution/timeseries", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1827334916, "numberOfFiles": 4321, "fileFormat": "The data are provided in text format." }, "timePeriod": { "ob_id": 3269, "startTime": "1961-01-01T00:00:00", "endTime": "2100-12-31T23:59:59" }, "resultQuality": { "ob_id": 3070, "explanation": "Data were quality controlled by UKCIP prior to release.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2017-01-12" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 11713, "uuid": "53e0417188a9587755a047eeee58f9ea", "short_code": "comp", "title": "UKCIP02 Scenario Computations", "abstract": "The UK Climate Impact Programme 2002 (UKCIP02) climate change scenarios are based exclusively on experiments completed using the HadCM3 global climate model, HadAM3H high-resolution atmosphere model and the HadRM3 regional climate mode by the Met Office Hadley Centrel. 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The climate change scenarios provide a common starting point for assessing climate change vulnerability, impacts and adaptation in the UK. \r\n\r\nThe UKCIP02 scenarios represent an advance in the description of future UK climates compared to the scenarios published for UKCIP in 1998. This is because they are based on new global emissions scenarios published in 2000 by the Intergovernmental Panel on Climate Change (IPCC) in their Special Report on Emissions Scenarios, and because they are based on a series of climate modelling experiments completed by the Hadley Centre using their most recently developed models. The scenarios describe four alternative future climates for the UK labelled, respectively, Low Emissions, Medium-Low Emissions, Medium-High Emissions and High Emissions. The scenarios are designed to be used in conjunction with other UKCIP reports and products. \r\n\r\nNo probabilities can be attached to these four climate futures – in line with the IPCC, UKCIP02 do not suggest that one is more likely than another. 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These data were prepared by the Max Planck Institute for Meteorology (MPI-M), as part of the SPECS project. \r\n \r\nModel id is MPI-ESM-LR (MPI-ESM-LR 2015; atmosphere: ECHAM6 v6.3.01p2 (REV: 3904), T63L47; land: JSBACH (REV: 3904); ocean: MPIOM v1.6.1p1 (REV: 3753) marine biogeochemistry HAMOCC included, GR15L40; sea ice (REV: 3753). Frequency is daily and monthly. \r\n\r\nDaily Atmospheric variables are:\r\nclt hfls hfss pr prc psl rlds rlut rsds tas uas vas\r\n\r\nMonthly atmos variables:\r\nhus pr psl ta tas ua va zg\r\n\r\nMonthly ocean variables:\r\nmlotst tos uo vo \r\n\r\nMonthly land variables:\r\nmrro mrso\r\n\r\nMonthly sea ice variable:\r\nsit", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2017-01-10T08:42:13.591593", "updateFrequency": "notPlanned", "dataLineage": "Data were supplied by SPECS participants to CEDA for archiving in 2015. 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New services to convey climate information and its quality will be used.\r\n\r\nSPECS will be, among other things, the glue to coalesce the outcome of previous research efforts that hardly took climate prediction into account. It will ensure interoperability so as to easily incorporate their application in an operational context, provide the basis for improving the capacity of European policy making, industry and society to adapt to near-future climate variations and a coordinated response to some of the GFCS components.\r\n\r\nThis project is funded by the Seventh Framework Programme (FP7) of the European Commission (GA 308378)." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6021, 6022, 6023, 6255, 11044, 11045, 50416, 50426, 50429, 50431, 50475, 50496, 50498, 50554, 50555, 50559, 50561, 50566, 50568, 50569, 50579, 50586, 50587, 50588, 50589, 50591, 50592, 50596, 50598, 50603, 50608, 52741, 52747, 52748, 52755, 53094, 53095, 53107, 53108, 53109, 53110, 53113, 53128, 53129, 53130, 53131, 53133, 53143, 54228, 54796, 54797, 54798, 54799 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 6086, "uuid": "2d9c5f2cc621fb9bc0062356851b31b9", "short_code": "coll", "title": "SPECS: Seasonal-to-decadal climate prediction model outputs", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nA core set of common experiments has been defined, to which most forecast systems will contribute. 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In addition to developments for in-situ measurements, Professor Jim Haywood has pioneered airborne remote sensing techniques for measuring the spectral radiative effects of biomass burning, mineral dust, volcanic ash, and industrial pollution aerosols across the solar and terrestrial wavelengths and has considerable aerosol modelling experience at a range of spatial scales. The EXSCALABAR project will exploit the synergy of these research interests and will encompass both technological and numerical modelling activities. The cavity ringdown extinction and photoacoustic absorption technologies will be developed for use on-board the joint NERC-Met Office FAAM BAe-146 research aircraft, thus providing an aerosol measurement capability that is unique outside of the USA. The instrument will be deployed in conjunction with existing airborne remote sensing instrumentation from the FAAM aircraft over the UK and on major deployments in summer 2016. The combined in-situ and remotely sensed aerosol and radiative measurements will be used to perform a comprehensive radiative closure analysis focussed on spectral aerosol absorption and single scattering albedo. Results of this analysis will be used to update to the spectral aerosol properties represented in the HadGEM climate model and assess their climatic impacts. The studentship will span a broad range of activities including development of state-of-the-art spectroscopic instrumentation, participation in aircraft-based field missions and scientific analysis of results using radiative transfer models. The instrumentation will be available to the UK research community beyond the lifetime of the EXSCALABAR project, providing significant legacy for the FAAM aircraft and the UK atmospheric research community." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 50835, 50836, 50837, 50839, 50840, 50841, 50842, 50843, 50844, 50845, 50846, 50847, 50848, 50849, 50852, 50854, 50855, 50856, 50857, 50928, 50929, 50930, 50931, 50932, 50933, 50934, 50936, 50937, 50938, 50939, 50940, 50941, 50951, 50953, 50954, 50955, 50956, 50958, 50959, 50960, 50961, 50962, 50963, 50964, 50965, 50966, 50967, 50969, 50970, 50971, 50973, 50978, 50979, 50982, 50983, 50984, 50985, 50986, 50987, 50988, 50989, 50990, 50991, 50992, 50993, 50994, 50995, 50996, 50997, 50998, 50999, 51000, 51001, 51002, 51003, 51004, 51005, 51006, 51007, 51008, 51009, 51010, 51011, 51012, 51013, 51014, 51015, 51016, 51017, 51018, 51019, 51020, 51021, 51022, 51023, 51024, 51025, 51026, 51027, 51028, 51029, 51030, 51031, 51032, 51033, 51034, 51035, 51036, 51037, 51038, 51039, 51040, 51041, 51042, 51043, 51044, 51045, 51046, 51047, 51048, 51052, 51053, 51054, 51055, 51056, 51057, 51058, 51059, 51060, 51061, 51062, 51063, 51064, 51065, 51066, 51067, 51068, 51069, 51070, 51071, 51072, 51073, 51074, 51075, 51076, 51077, 51078, 51079, 51080, 51081, 51082, 51083, 51084, 51085, 51086, 51087, 51125, 51133, 51134, 51302, 51486, 51487, 51490, 51492, 51493, 51494, 51495, 51496, 51497, 51498, 51499, 51500, 51501, 51502, 51503, 51504, 51505, 51506, 51507, 51508, 51511, 51512, 51513, 51515, 51516, 51517, 51518, 51519, 51520, 51521, 51524, 51525, 51526, 51527, 51528, 51529, 51530, 51531, 51533, 51535, 51536, 51537, 51538, 51540, 51541, 51542, 51543, 51544, 51545, 51546, 51547, 51548, 51549, 51550, 51551, 51552, 51553, 51554, 51555, 51556, 51557, 51558, 51560, 51561, 51562, 51563, 51564, 51565, 51566, 51567, 51568, 51569, 51570, 51571, 51572, 51573, 51574, 51575, 51576, 51577, 51578, 51579, 53404, 53405, 53406, 53407, 53408, 53409, 53410, 53411, 53412, 53413, 53414, 53415, 53416, 53417, 53418, 53419, 53420, 53421, 53422, 53423, 53424, 53425, 53426, 53427, 53428, 53429, 53430, 53431, 53432, 53673, 53674, 53677, 53678, 53682, 54967, 54971, 54975, 54976, 60856, 62679, 65836, 65842, 65843, 74152, 74154, 74156, 74158, 75674, 75678, 75679, 75680, 75682, 75683, 75685, 75686, 79221, 79224, 79225, 79385, 82820, 87187, 87188 ], "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). 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Raw data are retained for longterm preservation but are not intended for general use." }, { "ob_id": 20198, "uuid": "024837cf6b194ba5bb9224846decab73", "short_code": "coll", "title": "EXSCALABAR: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for EXtinction, SCattering and Absorption of Light for AirBorne Aerosol Research (EXSCALABAR)." } ], "responsiblepartyinfo_set": [ 78558, 78557, 78556, 78555, 78554, 78551, 78550, 78549, 78552, 78553 ], "onlineresource_set": [ 16900, 16899 ] }, { "ob_id": 20206, "uuid": "46ca2a2cc8ce497fbf06beaf31f67098", "title": "FAAM B984 ISMAR and T-NAWDEX 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 ISMAR Test flight: International Sub-Millimetre Airborne Radiometer and T-NAWDEX (Pilot) - THORPEX - North Atlantic Waveguide and Downstream projects.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2019-12-06T23:06:06", "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": "ISMAR, T-NAWDEX, FAAM, airborne, atmospheric measurments", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2016-12-20T12:15:09.001364", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1673, "bboxName": "", "eastBoundLongitude": -1.2300665378570557, "westBoundLongitude": -9.282551765441895, "southBoundLatitude": 52.824649810791016, "northBoundLatitude": 61.110862731933594 }, "verticalExtent": null, "result_field": { "ob_id": 20205, "dataPath": "/badc/faam/data/2016/b984-oct-14", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 867759877, "numberOfFiles": 34, "fileFormat": "Data are netCDF and NASA-Ames formatted. 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AVAPS, SAW, BBRs, Mini Lidar, Core chemistry. WAS. Cloud Physics: 2D-C, 2D-P, PCASP, Fast FSSP, SID2, SID3, CIP25, CIP100, CDP, FWVS, CCN Counter, TSI -3025- CPG, FWVS. Nephelometer, PSAP, Filters, Bag Sampling." }, { "ob_id": 14837, "uuid": "4908f9c47f14418b990bd46dae55e304", "short_code": "proj", "title": "ISMAR Test flight: International Sub-Millimetre Airborne Radiometer", "abstract": "Project details needed. 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We are a group of nine UK institutes working with multiple international partners (including research centres, forecasting agencies, regulatory authorities and airlines)." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 50835, 50836, 50837, 50839, 50840, 50841, 50842, 50843, 50844, 50845, 50846, 50847, 50848, 50849, 50852, 50854, 50855, 50856, 50857, 50928, 50929, 50930, 50931, 50932, 50933, 50934, 50936, 50937, 50938, 50939, 50940, 50941, 50951, 50953, 50954, 50955, 50956, 50958, 50959, 50960, 50961, 50962, 50963, 50964, 50965, 50966, 50967, 50969, 50970, 50971, 50973, 50978, 50979, 50982, 50983, 50984, 50985, 50986, 50987, 50988, 50989, 50990, 50991, 50992, 50993, 50994, 50995, 50996, 50997, 50998, 50999, 51000, 51001, 51002, 51003, 51004, 51005, 51006, 51007, 51008, 51009, 51010, 51011, 51012, 51013, 51014, 51015, 51016, 51017, 51018, 51019, 51020, 51021, 51022, 51023, 51024, 51025, 51026, 51027, 51028, 51029, 51030, 51031, 51032, 51033, 51034, 51035, 51036, 51037, 51038, 51039, 51040, 51041, 51042, 51043, 51044, 51045, 51046, 51047, 51048, 51052, 51053, 51054, 51055, 51056, 51057, 51058, 51059, 51060, 51061, 51062, 51063, 51064, 51065, 51066, 51067, 51068, 51069, 51070, 51071, 51072, 51073, 51074, 51075, 51076, 51077, 51078, 51079, 51080, 51081, 51082, 51083, 51084, 51085, 51086, 51087, 51133, 51134, 51302, 51486, 51487, 51490, 51492, 51493, 51494, 51495, 51496, 51497, 51498, 51499, 51500, 51501, 51502, 51503, 51504, 51505, 51506, 51507, 51508, 51511, 51512, 51513, 51515, 51516, 51517, 51518, 51519, 51520, 51521, 51522, 51523, 51524, 51525, 51526, 51527, 51528, 51529, 51530, 51531, 51533, 51535, 51536, 51537, 51538, 51540, 51541, 51542, 51543, 51544, 51545, 51546, 51547, 51548, 51549, 51550, 51551, 51552, 51553, 51554, 51555, 51556, 51557, 51558, 51560, 51561, 51562, 51563, 51564, 51565, 51566, 51567, 51568, 51569, 51570, 51571, 51572, 51573, 51574, 51575, 51576, 51577, 51578, 51579, 53404, 53405, 53406, 53407, 53408, 53409, 53410, 53411, 53412, 53413, 53414, 53415, 53416, 53417, 53418, 53419, 53420, 53421, 53422, 53423, 53424, 53425, 53426, 53427, 53428, 53429, 53430, 53431, 53432, 53433, 53673, 53674, 53677, 53678, 53682, 54967, 54971, 54975, 54976, 55558, 62679, 65836, 65842, 65843, 74073, 74074, 74076, 74089, 74098, 74154, 74156, 74158, 75672, 75674, 75677, 79219, 79221, 79222, 79224, 79225, 79385, 79746, 79747, 79748, 79749, 79750, 79751, 79752, 80962, 82820 ], "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). 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Active and break periods in the monsoon have a major influence on the success of farming, while year-to-year variations in the rainfall have economic consequences on an international scale. The growing population and developing economy mean that understanding and predicting the monsoon is therefore vital. Despite this, our capability to model the monsoon, and to make forecasts on scales from days to the season ahead is limited by large errors that develop quickly. The relatively poor performance of weather prediction models over India is due to a very strong and complex relationship between the land, ocean and atmosphere, which are linked by the process of convection, in the form of the rain-bringing cumulonimbus clouds. Forecast errors occur primarily because the convective clouds are not accurately linked to the large-scale circulation or to the surface conditions, and these errors persist to long time scales. Worldwide, weather and climate forecast models are gaining resolution, and yet the errors in monsoon rainfall are not diminishing. A lack of detailed observations of the land, ocean and atmospheric parts of the monsoon system, on a range of temporal and spatial scales, is preventing a more thorough understanding of processes in monsoon convective clouds and at the land surface, and their interaction with the large-scale circulation. \r\n\r\nThe project used a programme of new measurements over India and the adjacent oceans to advance monsoon forecasting capability in the Indo-UK community. The first detachment of the FAAM research aircraft to India, in combination with an intensive ground-based observation campaign, will gather new observations of the land surface, the boundary layer structure over land and ocean, and atmospheric profiles. We will institute a new long-term series of measurements of energy and water exchanges at the land surface. Research measurements from one monsoon season will be combined with long-term observations on the Indian operational networks. Observations will be focused on two transects: in the northern plains of India, covering a range of surface types from irrigated to rain-fed agriculture, and wet to dry climatic zones; and across the Western Ghats, with transitions from land to ocean and across orography. The observational analysis will represent a unique and unprecedented characterization of monsoon processes linking the land, ocean and atmospheric patterns which control the rainfall. Long-term measurements will allow the computation of statistical relationships between the various factors. \r\n\r\nThe observational analysis fed directly into improved forecasting at the Met Office and NCMRWF. The Met Office Unified Model, which is used for weather forecasting at both institutions, was set up in a range of different ways for the observational period. In particular, the project pioneered the test development of a new 100m-resolution atmospheric model, which greatly improved the representation of land-ocean-atmosphere interactions. Another priority was to improve land surface modelling in monsoon forecasts. By comparing the results of the very high resolution models on small domains with lower-resolution models representing the global weather patterns, it was possible to describe the key processes controlling monsoon rainfall, and to indicate how these need to be represented in different applications, such as weather predictions or climate predictions. 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Active and break periods in the monsoon have a major influence on the success of farming, while year-to-year variations in the rainfall have economic consequences on an international scale. The growing population and developing economy mean that understanding and predicting the monsoon is therefore vital. Despite this, our capability to model the monsoon, and to make forecasts on scales from days to the season ahead is limited by large errors that develop quickly. The relatively poor performance of weather prediction models over India is due to a very strong and complex relationship between the land, ocean and atmosphere, which are linked by the process of convection, in the form of the rain-bringing cumulonimbus clouds. Forecast errors occur primarily because the convective clouds are not accurately linked to the large-scale circulation or to the surface conditions, and these errors persist to long time scales. Worldwide, weather and climate forecast models are gaining resolution, and yet the errors in monsoon rainfall are not diminishing. A lack of detailed observations of the land, ocean and atmospheric parts of the monsoon system, on a range of temporal and spatial scales, is preventing a more thorough understanding of processes in monsoon convective clouds and at the land surface, and their interaction with the large-scale circulation. \r\n\r\nThe project used a programme of new measurements over India and the adjacent oceans to advance monsoon forecasting capability in the Indo-UK community. The first detachment of the FAAM research aircraft to India, in combination with an intensive ground-based observation campaign, will gather new observations of the land surface, the boundary layer structure over land and ocean, and atmospheric profiles. We will institute a new long-term series of measurements of energy and water exchanges at the land surface. Research measurements from one monsoon season will be combined with long-term observations on the Indian operational networks. Observations will be focused on two transects: in the northern plains of India, covering a range of surface types from irrigated to rain-fed agriculture, and wet to dry climatic zones; and across the Western Ghats, with transitions from land to ocean and across orography. The observational analysis will represent a unique and unprecedented characterization of monsoon processes linking the land, ocean and atmospheric patterns which control the rainfall. Long-term measurements will allow the computation of statistical relationships between the various factors. \r\n\r\nThe observational analysis fed directly into improved forecasting at the Met Office and NCMRWF. The Met Office Unified Model, which is used for weather forecasting at both institutions, was set up in a range of different ways for the observational period. In particular, the project pioneered the test development of a new 100m-resolution atmospheric model, which greatly improved the representation of land-ocean-atmosphere interactions. Another priority was to improve land surface modelling in monsoon forecasts. By comparing the results of the very high resolution models on small domains with lower-resolution models representing the global weather patterns, it was possible to describe the key processes controlling monsoon rainfall, and to indicate how these need to be represented in different applications, such as weather predictions or climate predictions. Through model evaluation at a range of scales, the development of simple theoretical understanding of the rainfall processes, and working with groups responsible for operational model improvement, the project led directly to improvements in monsoon forecasts. \r\n\r\nObjectives: The grand objective of this project was to improve the skill of rainfall prediction in operational weather and climate models by way of better understanding and representation of interactions between the land surface, boundary layer, convection, the large-scale environment and monsoon variability on a range of scales.\r\n\r\nSpecific objectives:\r\n\r\n1a) To document and evaluate the characteristics of monsoon rainfall on sub-daily to intraseasonal time scales, as influenced by surface, thermodynamic and dynamic forcing, as monsoon air moves from the ocean inland and across the subcontinent.\r\n1b) To evaluate the representation of these rainfall processes in the Met Office Unified Model at a range of resolutions, and thereby to indicate the priorities for model development.\r\n\r\n2) Quantify land surface properties and fluxes, using in-situ and remote sensing measurements, as they interact with the monsoon on hourly to monthly time scales and from kilometre to continental spatial scales. \r\n\r\n3a) Quantify the role of the Indian land surface in the progression of the monsoon during the onset, and in monsoon variability, and relate it to the role of the ocean.\r\n3b) Evaluate the impact of improved land-surface representation on monsoon prediction and make recommendations for future land-atmosphere modelling strategy.\r\n\r\n4a) Evaluate the influence of local and short-term structures in convection and the boundary layer, on rainfall variability on intraseasonal and seasonal timescales, using observations, idealized models and a range of operational models. \r\n4b) Make recommendations for priorities in the parametrization of convective rainfall in the monsoon system." }, { "ob_id": 19202, "uuid": "3f348e446ee040c6a7f293d8e2e75f80", "short_code": "proj", "title": "South West Asian Aerosol Monsoon Interactions (SWAAMI)", "abstract": "SWAAMI contributed to the joint NERC-MoES programme: Drivers of Variability in the Asian Monsoon, through a detailed determination of aerosol physical and chemical properties across India in the advance of, and during, the Indian monsoon using UK and Indian research aircraft. The measurements delivered a chemical and physical characterisation of the aerosol that is considerably more detailed than any previous and enabled an assessment of aerosol composition and mixing state, provided source characterisation and deliver quantification of aerosol optical properties such as extinction, absorption and single scattering albedo. Such detailed characterisation allowed representations of aerosol properties in regional and global climate models. Aircraft measurements were combined with syntheses of long term data from across the continent and previous field studies to provide a data set that can challenge how well models represent aerosol across the region. Improving model representations of aerosol properties and testing the extent to which this improves model performance against data provided a framework for ensuring model aerosol schemes improve and in doing so allowed more reliable predictions of aerosols effects on the heat budget of the region and hence improve our knowledge of how aerosols may influence the Indian monsoon.\r\n\r\nSWAAMI combined measurements of the properties of aerosols across northern India and the Bay of Bengal during the pre-monsoon in unprecedented detail with long term measurements from ground based networks and data from previous intensive campaigns in order to challenge model representations of aerosols over India and their effects on the monsoon.\r\nKey objectives of SWAAMI were to:\r\n*Assess the impact of mineral dust, black carbon aerosol and co-emitted organic and inorganic species on the radiation budget via the direct, semi-direct and indirect effects\r\n*Assess the impact of the aerosol radiative forcing on the local energy budget, atmospheric dynamics and hydrological cycle over India\r\n*Assess the impact of the forcings and feedbacks arising from aerosols over Indian region on regional and global climate.\r\n\r\nGrant ref: NE/L013886/1" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1381, 1382, 1383, 1384, 1633, 3220, 3221, 3222, 3223, 3224, 3225, 3226, 3227, 3228, 3229, 3230, 3231, 3232, 3233, 3234, 3235, 3236, 3237, 3238, 3239, 3240, 3241, 3242, 3243, 3244, 3245, 3246, 3247, 3248, 3249, 3250, 3251, 3252, 3253, 3254, 3255, 3256, 3257, 3258, 3259, 3260, 3261, 3262, 3263, 3264, 3265, 3266, 3267, 3268, 3269, 3270, 3271, 3272, 3273, 3274, 3275, 3276, 3277, 3278, 3279, 3280, 3281, 3282, 3283, 3284, 3285, 3286, 3287, 3288, 3289, 3290, 3291, 3292, 3293, 3294, 3295, 3307, 3315, 3316, 3317, 3318, 3319, 3320, 3321, 3322, 3323, 3324, 3325, 3326, 3327, 3328, 3329, 3330, 3331, 3332, 3333, 3334, 3335, 3336, 3337, 3338, 3339, 3340, 3341, 3342, 3343, 3344, 3345, 7762, 7763, 14836, 14837, 14838, 14839, 14840, 14841, 14842, 14843, 14845, 14846, 14847, 14848, 14849, 14850, 14851, 14853, 14855, 14857, 14916, 14917, 14919, 14921, 14924, 14926, 14927, 14928, 14931, 14942, 14946, 14947, 15040, 15041, 15161, 15163, 15166, 15167, 15168, 15169, 15170, 15171, 15172, 15173, 15174, 15175, 15176, 15177, 15178, 15179, 15180, 15182, 15183, 15185, 15186, 15188, 15189, 15192, 15193, 15194, 15195, 15196, 15197, 15198, 15200, 15203, 15204, 15208, 15210, 15211, 15212, 15213, 15220, 15223, 15241, 15242, 15243, 15244, 15245, 15246, 15247, 15248, 15249, 15250, 15251, 15252, 15253, 15254, 15255, 15256, 15257, 15258, 15259, 15260, 15261, 15262, 15263, 15264, 15265, 15266, 15267, 15268, 15269, 15271, 15274, 15277, 15279, 15282, 15283, 15288, 15289, 15291, 15324, 15325, 15327, 15329, 15331, 15332, 15333, 15334, 15338, 15339, 15340, 15341, 15342, 15343, 15344, 15346, 15347, 15348, 15349, 15350, 15355, 15356, 15795, 15796, 15800, 15801, 15802, 15803, 15804, 15805, 15806, 15807, 15808, 15809, 15810, 15811, 15812, 15813, 15814, 15815, 15816, 15817, 15818, 15819, 15820, 15821, 15822, 15823, 15824, 15825, 15831, 15833, 15834, 15835, 15836, 15838, 15839, 15840, 15841, 15842, 15843, 15844, 15845, 15846, 15847, 15848, 15855, 15857, 15859, 15864, 16664, 16665, 16666, 16667, 16669, 18977, 18978 ], "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": 20235, "uuid": "c115c8f8693346bbbcad373348a32367", "short_code": "coll", "title": "SWAAMI: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for South West Asian Aerosol Monsoon Interactions (SWAAMI)." }, { "ob_id": 20240, "uuid": "1873b605e2a74cac8b4f5d12593e54fc", "short_code": "coll", "title": "INCOMPASS: radiosonde and in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "Radiosonde and in-situ airborne observations by the FAAM BAE-146 aircraft for Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS)." } ], "responsiblepartyinfo_set": [ 78718, 78717, 78716, 78715, 78714, 78711, 78710, 78709, 78712, 78713 ], "onlineresource_set": [ 16930, 16929 ] }, { "ob_id": 20248, "uuid": "a7c21f94ecb446a7a4ad8d91306809ee", "title": "FAAM B959 INCOMPASS flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) project.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-12-11T12:45:34", "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": "INCOMPASS, FAAM, airborne, atmospheric measurments", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2016-12-13T10:27:42.041549", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1683, "bboxName": "", "eastBoundLongitude": 77.82511138916016, "westBoundLongitude": 72.23981475830078, "southBoundLatitude": 12.24534797668457, "northBoundLatitude": 13.0669527053833 }, "verticalExtent": null, "result_field": { "ob_id": 20247, "dataPath": "/badc/faam/data/2016/b959-jun-21", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1542767134, "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": 5303, "startTime": "2016-06-21T00:38:45", "endTime": "2016-06-21T09:14:33" }, "resultQuality": { "ob_id": 3074, "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).", "passesTest": true, "resultTitle": "FAAM to CEDA Data Quality Statement", "date": "2015-09-03" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 20249, "uuid": "0baf50a52062451881848b60704058ec", "short_code": "acq", "title": "FAAM Flight B959 Acquisition", "abstract": "FAAM Flight B959 Acquisition" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 8 ], "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": 19201, "uuid": "2fb5f31126a3425f9af15e3ea85c552f", "short_code": "proj", "title": "Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS)", "abstract": "The monsoon supplies the majority of water for agriculture and industry in South Asia, and is therefore critical to the well-being of a billion people. Active and break periods in the monsoon have a major influence on the success of farming, while year-to-year variations in the rainfall have economic consequences on an international scale. The growing population and developing economy mean that understanding and predicting the monsoon is therefore vital. Despite this, our capability to model the monsoon, and to make forecasts on scales from days to the season ahead is limited by large errors that develop quickly. The relatively poor performance of weather prediction models over India is due to a very strong and complex relationship between the land, ocean and atmosphere, which are linked by the process of convection, in the form of the rain-bringing cumulonimbus clouds. Forecast errors occur primarily because the convective clouds are not accurately linked to the large-scale circulation or to the surface conditions, and these errors persist to long time scales. Worldwide, weather and climate forecast models are gaining resolution, and yet the errors in monsoon rainfall are not diminishing. A lack of detailed observations of the land, ocean and atmospheric parts of the monsoon system, on a range of temporal and spatial scales, is preventing a more thorough understanding of processes in monsoon convective clouds and at the land surface, and their interaction with the large-scale circulation. \r\n\r\nThe project used a programme of new measurements over India and the adjacent oceans to advance monsoon forecasting capability in the Indo-UK community. The first detachment of the FAAM research aircraft to India, in combination with an intensive ground-based observation campaign, will gather new observations of the land surface, the boundary layer structure over land and ocean, and atmospheric profiles. We will institute a new long-term series of measurements of energy and water exchanges at the land surface. Research measurements from one monsoon season will be combined with long-term observations on the Indian operational networks. Observations will be focused on two transects: in the northern plains of India, covering a range of surface types from irrigated to rain-fed agriculture, and wet to dry climatic zones; and across the Western Ghats, with transitions from land to ocean and across orography. The observational analysis will represent a unique and unprecedented characterization of monsoon processes linking the land, ocean and atmospheric patterns which control the rainfall. Long-term measurements will allow the computation of statistical relationships between the various factors. \r\n\r\nThe observational analysis fed directly into improved forecasting at the Met Office and NCMRWF. The Met Office Unified Model, which is used for weather forecasting at both institutions, was set up in a range of different ways for the observational period. In particular, the project pioneered the test development of a new 100m-resolution atmospheric model, which greatly improved the representation of land-ocean-atmosphere interactions. Another priority was to improve land surface modelling in monsoon forecasts. By comparing the results of the very high resolution models on small domains with lower-resolution models representing the global weather patterns, it was possible to describe the key processes controlling monsoon rainfall, and to indicate how these need to be represented in different applications, such as weather predictions or climate predictions. Through model evaluation at a range of scales, the development of simple theoretical understanding of the rainfall processes, and working with groups responsible for operational model improvement, the project led directly to improvements in monsoon forecasts. \r\n\r\nObjectives: The grand objective of this project was to improve the skill of rainfall prediction in operational weather and climate models by way of better understanding and representation of interactions between the land surface, boundary layer, convection, the large-scale environment and monsoon variability on a range of scales.\r\n\r\nSpecific objectives:\r\n\r\n1a) To document and evaluate the characteristics of monsoon rainfall on sub-daily to intraseasonal time scales, as influenced by surface, thermodynamic and dynamic forcing, as monsoon air moves from the ocean inland and across the subcontinent.\r\n1b) To evaluate the representation of these rainfall processes in the Met Office Unified Model at a range of resolutions, and thereby to indicate the priorities for model development.\r\n\r\n2) Quantify land surface properties and fluxes, using in-situ and remote sensing measurements, as they interact with the monsoon on hourly to monthly time scales and from kilometre to continental spatial scales. \r\n\r\n3a) Quantify the role of the Indian land surface in the progression of the monsoon during the onset, and in monsoon variability, and relate it to the role of the ocean.\r\n3b) Evaluate the impact of improved land-surface representation on monsoon prediction and make recommendations for future land-atmosphere modelling strategy.\r\n\r\n4a) Evaluate the influence of local and short-term structures in convection and the boundary layer, on rainfall variability on intraseasonal and seasonal timescales, using observations, idealized models and a range of operational models. \r\n4b) Make recommendations for priorities in the parametrization of convective rainfall in the monsoon system." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1381, 1382, 1383, 1384, 7565, 12182, 16664, 16665, 16666, 16667, 16669, 26714, 50835, 50836, 50837, 50839, 50840, 50841, 50843, 50844, 50845, 50846, 50847, 50848, 50849, 50850, 50852, 50854, 50855, 50856, 50857, 50929, 50930, 50931, 50934, 50936, 50937, 50938, 50939, 50940, 50941, 50951, 50953, 50954, 50955, 50956, 50958, 50959, 50960, 50961, 50962, 50963, 50964, 50965, 50966, 50967, 50969, 50970, 50971, 50973, 50978, 50979, 50982, 50983, 50984, 50985, 50986, 50987, 50988, 50989, 50990, 50991, 50992, 50993, 50994, 50995, 50996, 50997, 50998, 50999, 51000, 51001, 51002, 51003, 51004, 51005, 51006, 51007, 51008, 51009, 51010, 51011, 51012, 51013, 51014, 51015, 51016, 51017, 51018, 51019, 51020, 51021, 51022, 51023, 51024, 51025, 51026, 51027, 51028, 51029, 51030, 51031, 51032, 51033, 51034, 51035, 51036, 51037, 51038, 51039, 51040, 51041, 51042, 51043, 51044, 51045, 51046, 51047, 51048, 51052, 51054, 51055, 51056, 51057, 51058, 51059, 51060, 51061, 51062, 51063, 51064, 51065, 51066, 51067, 51068, 51069, 51070, 51071, 51072, 51073, 51074, 51075, 51076, 51077, 51078, 51079, 51080, 51081, 51082, 51083, 51084, 51087, 51156, 51157, 51159, 51302, 51486, 51487, 51490, 51492, 51493, 51494, 51495, 51496, 51497, 51498, 51499, 51500, 51501, 51502, 51503, 51504, 51505, 51506, 51507, 51508, 51511, 51512, 51513, 51515, 51516, 51517, 51518, 51519, 51520, 51521, 51522, 51524, 51525, 51526, 51527, 51528, 51529, 51530, 51531, 51533, 51535, 51536, 51537, 51538, 51540, 51541, 51542, 51543, 51544, 51546, 51547, 51548, 51549, 51550, 51551, 51552, 51553, 51554, 51555, 51556, 51557, 51558, 51560, 51561, 51562, 51564, 51565, 51566, 51567, 51568, 51569, 51570, 51571, 51572, 51573, 51574, 51575, 51576, 51577, 51578, 51579, 53404, 53405, 53406, 53407, 53408, 53409, 53410, 53411, 53412, 53413, 53414, 53415, 53416, 53417, 53418, 53419, 53420, 53421, 53422, 53423, 53424, 53425, 53426, 53427, 53428, 53429, 53430, 53431, 53432, 53433, 53673, 53674, 53677, 53678, 53682, 54967, 54971, 54975, 54976, 55558, 65836, 79219, 79221, 79224, 79225, 79385, 79386, 79387, 79388, 79955, 79956, 79957, 79958, 79959, 79960, 79961, 79962, 79963, 79964, 79965, 79966 ], "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": 20240, "uuid": "1873b605e2a74cac8b4f5d12593e54fc", "short_code": "coll", "title": "INCOMPASS: radiosonde and in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "Radiosonde and in-situ airborne observations by the FAAM BAE-146 aircraft for Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS)." } ], "responsiblepartyinfo_set": [ 78732, 78731, 78730, 78729, 78728, 78725, 78724, 78723, 78726, 78727 ], "onlineresource_set": [ 16933, 16932 ] } ] }