Observation List
Get a list of Observation objects.
GET /api/v3/observations/?format=api&offset=7100
{ "count": 10256, "next": "https://api.catalogue.ceda.ac.uk/api/v3/observations/?format=api&limit=100&offset=7200", "previous": "https://api.catalogue.ceda.ac.uk/api/v3/observations/?format=api&limit=100&offset=7000", "results": [ { "ob_id": 32395, "uuid": "be30127db24d45c3826367af7d0fcc44", "title": "MOD06_L2 - MODIS/Terra Clouds 5-Min L2 Swath 1km and 5km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD06_L2\n\n\n\n\n\nThe MODIS Level-2 Cloud product consists of cloud optical and physical parameters. These parameters are derived using remotely sensed infrared, visible and near infrared solar reflected radiances. MODIS infrared channel radiances are used to derive cloud top temperature, cloud top height, effective emissivity, cloud phase (ice vs. water, opaque vs. non-opaque), and cloud fraction under both daytime and nighttime conditions. MODIS visible radiances are used to derive cloud optical thickness and effective particle radius and cloud shadow effects. Near-infrared solar reflected radiance provides additional information for the retrieval of cloud particle phase (ice vs. water, clouds vs. snow). The shortname for this Level-2 MODIS cloud product is MOD06_L2. MOD06_L2 consists of parameters at a spatial resolution of either 1km or 5km (at nadir). Each MOD06_L2 product file covers a 5-minute time interval. This means that for 5km resolution parameters, the output grid is 270 pixels wide by 406 pixels in length. Every tenth granule has an output grid size of 270 by 408 pixels. For 1-km resolution parameters, the output grid is 1354 pixels in width by 2030 pixels in length and every tenth granule has an output grid size of 1354 by 2040 pixels.\n\nMOD06_L2 product files are stored in Hierarchical Data Format (HDF-EOS). All gridded cloud parameters are stored as Scientific Data Sets (SDS) within the file, except two (band number and statistics). These are stored as Vdata (table arrays). Approximately 288 files are produced daily. Nighttime files are smaller than their daytime counterparts since only the cloud top properties are retrieved at night.\n\nThe MODIS Cloud Product will be used to investigate seasonal and inter-annual changes in cirrus (semi-transparent) global cloud cover and cloud phase with multispectral observations at 1km spatial resolution.\n\nFor additional details see the MODIS Atmospheres web site page onCollection 6.1 Updates.\n\nShortname: MOD06_L2 , Platform: Terra , Instrument: MODIS , Processing Level: Level-2 , Spatial Resolution: 1 km , Temporal Resolution: 5 minute , ArchiveSets: 61 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE06 , File Naming Convention: MOD06_L2.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf AYYYYDDD = Acqusition Year and Day of Year HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time AYYYYDDD = Year and Day of Year of acquisition , Citation: Platnick, S., Ackerman, S., King, M., et al., 2015. MODIS Atmosphere L2 Cloud Product (06_L2). NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MOD06_L2.061 , Keywords: Water Vapor, Precipitable Water ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-12-02T10:16:04", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "Water Vapor, Precipitable Water ", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:05:37.727802", "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": 32396, "dataPath": "/neodc/modis/data/MOD06_L2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 175835672066627, "numberOfFiles": 2774352, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8892, "startTime": "2000-02-23T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3622, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 25855, "uuid": "280deb3b3c7f46d0a29a80cb60c3c448", "short_code": "acq", "title": "MODIS data from the Terra Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nThe Terra Satellite is a NASA satellite flying 5 research instruments to study the Earth's atmosphere, ocean and land, including the MODIS instrument. It was launched in 2003 and is still currently returning data.\r\n\r\nA MODIS instrument is also flown on NASA's AQUA satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10895, "uuid": "524f1a46e6df4ed1c1d89459167e7cd0", "short_code": "proj", "title": "Terra Satellite Mission, part of the Earth Observing System Morning Constellation (EOS-AM)", "abstract": "Terra is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 62241, 62242, 64508, 64510, 64511, 64512, 64513, 64514, 64547, 64548, 64549, 64550, 64551, 64552, 64553, 64554, 64555, 64556, 64557, 64558, 64559, 64560, 64561, 64562, 64563, 64564, 64565, 64566, 64567, 64568, 64569, 64570, 64571, 64572, 64573, 64574, 64575, 64576, 64577, 64578, 64579, 64580, 64581, 64582, 64583, 64584, 64585, 64586, 64587, 64588, 64589, 64590, 64591, 64592, 64593, 64594, 64595, 64596, 64597, 64598, 64599, 64600, 64601, 64602, 64603, 64604, 64605, 64606, 64607, 64608, 64609, 64610, 64611, 64612, 64613, 64614, 64615, 64616, 64617, 64618, 64619, 64620, 64621, 64622, 64623, 64624, 64625, 64626, 64627, 64628, 64629, 64630, 64631 ], "vocabularyKeywords": [], "identifier_set": [ 10835 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144240, 144242, 144243, 144236, 144237, 144238, 144239, 144244 ], "onlineresource_set": [ 42488, 42489, 42490, 42491 ] }, { "ob_id": 32397, "uuid": "35bb28eafbaa461db578e1218808c038", "title": "MOD11A1 - MODIS/Terra Land Surface Temperature/Emissivity Daily L3 Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD11A1\n\n\n\n\n\nThe MODIS/Terra Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based to grid-based global products. The MODIS/Terra LST/E Daily L3 Global 1 km SIN Grid,(Short name: MOD11A1), is a gridded version of the L2 Daily LST/E data set, whose LSTs are retrieved by the split-window algorithm.\n\nThe Collection-4 (C4) LST/E L3 MOD11A1 product inputs include the MODIS L1B calibrated and geolocated radiances, geolocation, cloud mask, atmospheric profiles, land and snow cover. The band 31 and 32 emissivities are estimated by a classification-based emissivity method, which relies on the pixel's land cover type as determined by the land and snow cover inputs. Until June 2001, the AVHRR-based IGBP land cover product was used. Following that time, MODIS-derived land cover product was used. The estimated emissivities in arid and semi-arid areas are potentially uncertain, and users are advised to exercise caution in their applications. The day/night alogorithm extracts average temperatures (in Kelvin) and applies them to a pair of MODIS daytime and nighttime observations. This method yields 1 K accuracy for materials with known emissivities. The V4 MOD11A1 product has a temporal acquisition range of February 24, 2000 (2000-055) until January 3, 2007 (200-003). The C4 collection remains consistent with C41, and users may combine the two collections in a time-series analysis.\n\nThe MODIS/Terra Collection 41 (C41) products use a modified Collection-4 (C4) LST algorithm and Collection-5 (C5) data inputs. The C41 products primarily address underestimation problems in the C5 Climate Modeling Grid (CMG) products. Recent validation activities reveal that the C5 CMG products underestimate LSTs up to 6K especially in desert and semi-arid regions. The availability of this collection starts with MODIS/Terra data acquisition on January 1, 2007 (2007-001). This date is driven by the availability of the MODIS C5 data inputs (level-1B radiance data, geolocation data, cloud mask, atmospheric profiles, and land and snow cover data).\n\nThe MODIS/Terra C5 LST/E L3 Global 5 km Grid product incorporates 1-km pixels, which are produced daily using the generalized split-window LST algorithm. This algorithm is optimally used to separate ranges of atmospheric column water vapor and lower boundary air surface temperatures into tractable sub-ranges. The surface emissivities in bands 31 and 32 are estimated from land cover types. The C5 MOD11_L2 product's acquisition range started March 5, 2000 (2000-065) and will continue until some time after the C6 reprocessing is complete.\n\nThe C41 and C5 MODIS/Terra LST/E products, including the MOD11A1, are validated to Stage-2 with well-defined uncertainties over a range of representative conditions. Further details regarding MODIS land product validation for the LST/E products are available from the MODIS land team validation site referenced under 'Val Status' section.\n\nThe C41 LST products from 2007-001 will remain consistent with similar products from C4, and hence are amenable to combine them in a time-series analysis. Users should exercise caution, and not mix the C4.x (i.e., C4 and C41) and C5 LST products in their analyses.\n\nShortname: MOD11A1 , Platform: Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 1 km , Temporal Resolution: daily , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE16M , File Naming Convention: MOD11A1.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Zhengming Wan - University of California Santa Barbara, Simon Hook, Glynn Hulley - JPL and MODAPS SIPS - NASA. (2015). MOD11A1 MODIS/Terra Land Surface Temperature and the Emissivity Daily L3 Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MOD11A1.006 , Keywords: Climate Change, Land Surface Temperature, Emissivity, Fires ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2022-12-01T19:22:47", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "Climate Change, Land Surface Temperature, Emissivity, Fires ", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:05:49.312383", "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": 32398, "dataPath": "/neodc/modis/data/MOD11A1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2773452117017, "numberOfFiles": 1362985, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8893, "startTime": "2000-02-23T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3623, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 25855, "uuid": "280deb3b3c7f46d0a29a80cb60c3c448", "short_code": "acq", "title": "MODIS data from the Terra Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nThe Terra Satellite is a NASA satellite flying 5 research instruments to study the Earth's atmosphere, ocean and land, including the MODIS instrument. It was launched in 2003 and is still currently returning data.\r\n\r\nA MODIS instrument is also flown on NASA's AQUA satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10895, "uuid": "524f1a46e6df4ed1c1d89459167e7cd0", "short_code": "proj", "title": "Terra Satellite Mission, part of the Earth Observing System Morning Constellation (EOS-AM)", "abstract": "Terra is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64531, 64532, 64537, 64538, 64539, 64540, 64541, 64542, 64543, 64544, 64545, 64546 ], "vocabularyKeywords": [], "identifier_set": [ 10836 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144245, 144246, 144247, 144248, 144249, 144251, 144252, 144253 ], "onlineresource_set": [ 42492, 42493, 42494, 42495, 42496 ] }, { "ob_id": 32399, "uuid": "15f057994f074b08a60daa1f188014e6", "title": "MOD11A2 - MODIS/Terra Land Surface Temperature/3-Band Emissivity 8-Day L3 Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD11A2\n\n\n\n\n\nThe MOD11A2 Level-3 MODIS Land Surface Temperature and Emissivity (LST/E) 8-day products are composed of data from the daily 1-kilometer LST product (MOD11A1) stored on a 1-km Sinusoidal grid as the average values of clear-sky LSTs during an 8-day period.\n\nMOD11A2 is comprised of daytime and nighttime LSTs, quality assurance assessment, observation times, view angles, bits of clear sky days and nights, and emissivities estimated in Bands 31 and 32 from land cover types.\n\nCollection-5 MODIS/Terra Land Surface Temperature/Emissivity products are validated to Stage 2, which means that their accuracy has been assessed over a widely distributed set of locations and time periods via several ground-truth and validation efforts. Further details regarding MODIS land product validation for the LST/E products are available from the following URL: http://landval.gsfc.nasa.gov/ProductStatus.php?ProductID=MOD11.\n\nShortname: MOD11A2 , Platform: Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 1 km , Temporal Resolution: 8 day , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE31 , File Naming Convention: MOD11A2.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Zhengming Wan - University of California Santa Barbara, Simon Hook, Glynn Hulley - JPL and MODAPS SIPS - NASA. (2015). MOD11A2 MODIS/Terra Land Surface Temperature and the Emissivity 8-Day L3 Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MOD11A2.006 , Keywords: Climate Change, Land Surface Temperature, Emissivity, Fires ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2022-09-01T13:29:18", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "Climate Change, Land Surface Temperature, Emissivity, Fires ", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:05:57.400498", "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": 32400, "dataPath": "/neodc/modis/data/MOD11A2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 266773663355, "numberOfFiles": 70048, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8894, "startTime": "2000-02-23T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3624, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 25855, "uuid": "280deb3b3c7f46d0a29a80cb60c3c448", "short_code": "acq", "title": "MODIS data from the Terra Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nThe Terra Satellite is a NASA satellite flying 5 research instruments to study the Earth's atmosphere, ocean and land, including the MODIS instrument. It was launched in 2003 and is still currently returning data.\r\n\r\nA MODIS instrument is also flown on NASA's AQUA satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10895, "uuid": "524f1a46e6df4ed1c1d89459167e7cd0", "short_code": "proj", "title": "Terra Satellite Mission, part of the Earth Observing System Morning Constellation (EOS-AM)", "abstract": "Terra is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64527, 64528, 64529, 64530, 64531, 64532, 64533, 64534, 64535, 64536, 64537, 64538 ], "vocabularyKeywords": [], "identifier_set": [ 10837 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144254, 144255, 144256, 144257, 144258, 144260, 144261, 144262 ], "onlineresource_set": [ 42497, 42498, 42499, 42500, 42501, 42502 ] }, { "ob_id": 32401, "uuid": "d65aab04c69b4df391e6e7fc4b901aef", "title": "MOD13A2 - MODIS/Terra Vegetation Indices 16-Day L3 Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD13A2\n\n\n\n\n\nGlobal MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared reflectances, centered at 469-nanometers, 645-nanometers, and 858-nanometers, respectively, are used to determine the MODIS daily vegetation indices.\n\nThe MODIS Normalized Difference Vegetation Index (NDVI) complements NOAA's Advanced Very High Resolution Radiometer (AVHRR) NDVI products providing continuity for time series applications over this rich historical archive. MODIS also includes a new Enhanced Vegetation Index (EVI) product that minimizes canopy background variations and maintains sensitivity over dense vegetation conditions. The EVI also uses the blue band to remove residual atmosphere contamination caused by smoke and sub-pixel thin cloud clouds. The MODIS NDVI and EVI products are computed from atmospherically-corrected bi-directional surface reflectances that have been masked for water, clouds, heavy aerosols, and cloud shadows.\n\nGlobal MOD13A2 data are provided every 16 days at 1-kilometer spatial resolution as a gridded level-3 product in the Sinusoidal projection. Vegetation indices are used for global monitoring of vegetation conditions and are used in products displaying land cover and land cover changes. These data may be used as input for modeling global biogeochemical and hydrologic processes and global and regional climate. These data also may be used for characterizing land surface biophysical properties and processes, including primary production and land cover conversion.\n\nCollection-5 MODIS/Terra Vegetation Indices products are Validated at Stage 2, meaning that accuracy has been assessed over a widely distributed set of locations and time periods via several ground-truth and validation efforts. Although there may be later improved versions, these data are ready for use in scientific publications.\n\nShortname: MOD13A2 , Platform: Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 1 km , Temporal Resolution: 16 day , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE35 , File Naming Convention: MOD13A2.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Kamel Didan - University of Arizona, Alfredo Huete - University of Technology Sydney and MODAPS SIPS - NASA. (2015). MOD13A2 MODIS/Terra Vegetation Indices 16-Day L3 Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MOD13A2.006 , Keywords: Climate Change, Canopy Characteristics, Biomass, Vegetation Index, Plant Phenology, Length of Growing Season ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2023-02-19T14:27:12", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "Climate Change, Canopy Characteristics, Biomass, Vegetation Index, Plant Phenology, Length of Growing Season ", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:06:07.536427", "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": 32402, "dataPath": "/neodc/modis/data/MOD13A2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 527218355189, "numberOfFiles": 57650, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8895, "startTime": "2000-02-23T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3625, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 25855, "uuid": "280deb3b3c7f46d0a29a80cb60c3c448", "short_code": "acq", "title": "MODIS data from the Terra Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nThe Terra Satellite is a NASA satellite flying 5 research instruments to study the Earth's atmosphere, ocean and land, including the MODIS instrument. It was launched in 2003 and is still currently returning data.\r\n\r\nA MODIS instrument is also flown on NASA's AQUA satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10895, "uuid": "524f1a46e6df4ed1c1d89459167e7cd0", "short_code": "proj", "title": "Terra Satellite Mission, part of the Earth Observing System Morning Constellation (EOS-AM)", "abstract": "Terra is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64515, 64516, 64517, 64518, 64519, 64520, 64521, 64522, 64523, 64524, 64525, 64526 ], "vocabularyKeywords": [], "identifier_set": [ 10838 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144263, 144264, 144265, 144266, 144267, 144269, 144270, 144271 ], "onlineresource_set": [ 42503, 42504, 42505, 42506, 42507, 42508 ] }, { "ob_id": 32403, "uuid": "e3ee4b286e97482fb3c979ca9268f228", "title": "MOD14A1 - MODIS/Terra Thermal Anomalies/Fire Daily L3 Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD14A1\n\n\n\n\n\nMODIS Thermal Anomalies/Fire products are primarily derived from MODIS 4- and 11-micrometer radiances. The fire detection strategy is based on absolute detection of a fire (when the fire strength is sufficient to detect), and on detection relative to its background (to account for variability of the surface temperature and reflection by sunlight). Numerous tests are employed to reject typical false alarm sources like sun glint or an unmasked coastline.\n\nMOD14A1 is produced every 8 days at 1-kilometer resolution as a gridded level-3 product in the Sinusoidal projection. This product is unique in that it has three dimensions: fire-mask (1D) and a maximum fire-radiative-power (2D) are provided for each day (3D) in the 8-day period. For example, the fire-mask contains eight, band sequential (day) 1200 x 1200 images of fire data representing consecutive days of data collection.\n\nThe Terra MODIS instrument acquires data twice daily (10:30 AM and PM), as does the Aqua MODIS (1:30 PM and AM). These four daily MODIS fire observations serve to advance global monitoring of the fire process and its effects on ecosystems, the atmosphere, and climate.\n\nCollection-5 MODIS/Terra Thermal Anomalies/Fire products are Validated Stage 3, meaning that uncertainties in the product and its associated structure are well quantified from comparison with reference in situ or other suitable reference data. These data are ready for use in scientific publications.\n\nShortname: MOD14A1 , Platform: Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 1 km , Temporal Resolution: daily , ArchiveSets: 6 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE29 , File Naming Convention: MOD14A1.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Louis Giglio, Chris Justice - University of Maryland and MODAPS SIPS - NASA. (2015). MOD14A1 MODIS/Thermal Anomalies/Fire Daily L3 Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MOD14A1.006 , Keywords: Climate Change, Land Surface Temperature, Fires ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-05-10T17:46:37", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "Climate Change, Land Surface Temperature, Fires ", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:06:13.349801", "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": 32404, "dataPath": "/neodc/modis/data/MOD14A1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2866, "numberOfFiles": 7, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8896, "startTime": "2000-02-23T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3626, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 25855, "uuid": "280deb3b3c7f46d0a29a80cb60c3c448", "short_code": "acq", "title": "MODIS data from the Terra Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nThe Terra Satellite is a NASA satellite flying 5 research instruments to study the Earth's atmosphere, ocean and land, including the MODIS instrument. It was launched in 2003 and is still currently returning data.\r\n\r\nA MODIS instrument is also flown on NASA's AQUA satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10895, "uuid": "524f1a46e6df4ed1c1d89459167e7cd0", "short_code": "proj", "title": "Terra Satellite Mission, part of the Earth Observing System Morning Constellation (EOS-AM)", "abstract": "Terra is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64732, 64733, 64734, 64735 ], "vocabularyKeywords": [], "identifier_set": [ 10839 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144272, 144273, 144274, 144275, 144276, 144278, 144279, 144280 ], "onlineresource_set": [ 42509, 42510, 42511, 42512, 42513, 42514 ] }, { "ob_id": 32405, "uuid": "2a777ecbac9847639617c053072c4af2", "title": "MOD35_L2 - MODIS/Terra Cloud Mask and Spectral Test Results 5-Min L2 Swath 250m and 1km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD35_L2\n\n\n\n\n\n\"\nThe MODIS Cloud Mask product is a Level-2 product generated at 1-km and 250-m (at nadir) spatial resolutions. The algorithm employs a series of visible and infrared threshold and consistency tests to specify confidence that an unobstructed view of the Earth's surface has been observed. An indication of shadows affecting the scene is also provided. The 250-m cloud mask flags are based on visible channel data only. Radiometrically-accurate radiances are required, thus holes in the Cloud Mask will appear wherever the input radiances are incomplete or of poor quality assurance. There are two MODIS Cloud Mask data product files: MOD35_L2, containing data collected from the Terra platform; and MYD35_L2, containing data collected from the Aqua platform.\n\nThe MODIS cloud mask algorithm employs a battery of spectral tests, which use methodology applied in the AVHRR Processing scheme Over cLoudy Land and Ocean (APOLLO), International Satellite Cloud Climatology Project (ISCCP), CLoud Advanced Very high resolution Radiometer (CLAVR), and the Support of Environmental Requirements for Cloud Analysis and Archive (SERCAA) algorithms to identify cloudy FOVs. From these, a clear-sky confidence level (high confident clear, probably clear, undecided, cloudy) is assigned to each FOV. For inconclusive results, spatial- and temporal-variability tests are applied. The spectral tests rely on radiance (temperature) thresholds in the infrared and reflectance thresholds in the visible and near-infrared. Thresholds vary with surface type, atmospheric conditions (moisture, aerosol, etc.), and viewing geometry. In addition to the MOD02 calibrated radiances, a 1-km land/water mask, DEM, ecosystem analysis, snow/ice cover map, NCEP analysis of surface temperature and wind speed, and an estimate of precipitable water are required as inputs.\n\nA determination of the presence of global cloudiness is essential to the MODIS mission for two reasons. First, clouds play a critical role in the radiative balance of the Earth and must be accurately described to assess climate and potential climate change. Second, the presence of cloudiness must be accurately determined to properly retrieve many atmospheric and surface parameters. For many of these retrieval algorithms even thin cirrus represents contamination.\n\nCloud mask validation will be conducted using MODIS Airborne Simulator (MAS) data from several field campaigns, all-sky cameras, and comparison with NOAA operational instruments and possibly ASTER.\n\nFor additional details see the MODIS Atmospheres web site page onCollection 6.1 Updates. \"\n\nShortname: MOD35_L2 , Platform: Terra , Instrument: MODIS , Processing Level: Level-2 , Spatial Resolution: 250 m, 1 km , Temporal Resolution: 5 minute , ArchiveSets: 61 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE03 , File Naming Convention: MOD35_L2.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time AYYYYDDD = Year and Day of Year of acquisition , Citation: Ackerman, S., et al., 2015. MODIS Atmosphere L2 Cloud Mask Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MOD35_L2.061 , Keywords: Cloud Fraction, Climate Change, Atmospheric Correction ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-12-02T12:16:04", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "Cloud Fraction, Climate Change, Atmospheric Correction ", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "250 m, 1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:06:20.523948", "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": 32406, "dataPath": "/neodc/modis/data/MOD35_L2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 12183761451887, "numberOfFiles": 1567970, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8897, "startTime": "2000-02-23T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3627, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 25855, "uuid": "280deb3b3c7f46d0a29a80cb60c3c448", "short_code": "acq", "title": "MODIS data from the Terra Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nThe Terra Satellite is a NASA satellite flying 5 research instruments to study the Earth's atmosphere, ocean and land, including the MODIS instrument. It was launched in 2003 and is still currently returning data.\r\n\r\nA MODIS instrument is also flown on NASA's AQUA satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10895, "uuid": "524f1a46e6df4ed1c1d89459167e7cd0", "short_code": "proj", "title": "Terra Satellite Mission, part of the Earth Observing System Morning Constellation (EOS-AM)", "abstract": "Terra is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 62241, 62242, 64507, 64508, 64509, 64510, 64511, 64512, 64513, 64514 ], "vocabularyKeywords": [], "identifier_set": [ 10840 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144281, 144282, 144283, 144284, 144285, 144287, 144288, 144289 ], "onlineresource_set": [ 42515, 42516, 42517, 42518 ] }, { "ob_id": 32407, "uuid": "121756ef259340b0a0ac0f50e39a5220", "title": "MYD021KM - Level 1B Calibrated Radiances - 1km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD021KM\n\n\n\n\n\n\"The MODIS Level-1B data set contains calibrated and geolocated at-aperture radiances for 36 discrete bands located in the 0.4 µm to 14.4 µm region of the electromagentic spectrum. These data are generated from MODIS Level-1A scans of raw radiance, and in the process are converted to geophysical units of W/(m2µm sr). In addition, the Bidirectional Reflectance Distribution Function (BRDF) may be determined for the solar reflective bands (1-19, 26) through knowledge of the solar irradiance (e.g., determined from MODIS solar diffuser data, and from the target illumination geometry). Additional data are provided including quality flags, error estimates and calibration data.\n\nVisible, shortwave infrared, and near infrared measurements are only made during the daytime, while radiances for the thermal infrared region (bands 20-25, 27-36) are measured continuously.\n\nThe resolution of channels 1 and 2 is 250 m, channels 3 through 7 are 500m resolution, and the rest are 1 km resolution. However, for the MODIS L1B 1 km product, the 250 m and 500 m band radiance data and their associated uncertainties have been aggregated to 1 km resolution. Thus, the entire channel data set is referenced to the same spatial and geolocation scales. Separate L1B products are available for just the 250 m channels (MYD02QKM) and the 500 m channels (MYD02HKM) that preserve the original resolution of the data.\n\nSpatial resolution for pixels at nadir is 1 km, degrading to 4.8 km in the along-scan direction at the scan extremes. However, thanks to the overlapping of consecutive swaths and the respective pixels there, the resulting resolution at the scan extremes is about 2 km. A 55 degree scanning pattern at the EOS orbit of 705 km results in a 2330 km orbital swath width with global coverage every one to two days. A single MODIS Level-1B granule will nominally contain a scene built from 203 scans (or swaths) sampled 1354 times in the cross-track direction, corresponding to approximately 5 minutes worth of data. Since an individual MODIS scan (or swath) will contain 10 along-track spatial elements, the scene will be composed of 1354 by 2030 pixels, resulting in a spatial coverage of 2330 km by 2030 km. Due to the MODIS scan geometry, there will be increasing overlap occurring beyond about a 25 degree scan angle.\n\nUsers requiring the full-resolution geolocation and solar/satellite geometry can obtain the separate MODIS Level-1 Geolocation product (MYD03) from LAADS.\"\n\nShortname: MYD021KM , Platform: Aqua , Instrument: MODIS , Processing Level: Level-1B , Spatial Resolution: 1 km , Temporal Resolution: 5 minute , ArchiveSets: 61, 6 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE02 , File Naming Convention: MYD021KM.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf AYYYYDDD = Acqusition Year and Day of Year HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time YYYYDDD = Year and Day of Year of acquisition , Citation: MODIS Characterization Support Team (MCST), 2017. MODIS 1km Calibrated Radiances Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MYD021KM.061 , Keywords: Climate Change, Radiance ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-12-02T09:20:26", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "Climate Change, Radiance ", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:06:34.155993", "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": 32408, "dataPath": "/neodc/modis/data/MYD021KM", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 272449524400264, "numberOfFiles": 2478522, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8898, "startTime": "2002-07-03T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3628, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26034, "uuid": "85bb8321bc8b42f9a39cb6d83fabe79e", "short_code": "acq", "title": "MODIS data from the Aqua Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nIt is flown on NASA's Aqua Satellite which was launched on May 4, 2002, and has six Earth-observing instruments on board, collecting a variety of global data sets\r\n\r\nA MODIS instrument is also flown on NASA's Terra satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10904, "uuid": "ccc71008f3c0db6f9d2c70bbc4346f31", "short_code": "proj", "title": "Aqua Satellite Mission, part of the Earth Observing System Afternoon Constellation (EOS-PM)", "abstract": "Aqua is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64156, 64157, 64703, 64704, 64705, 64706, 64707, 64708, 64709, 64710, 64711, 64712, 64713, 64714, 64715, 64716, 64717, 64718, 64719, 64720, 64721, 64722, 64723, 64724, 64725, 64726, 64727, 64728, 64729, 64730, 64731 ], "vocabularyKeywords": [], "identifier_set": [ 10841 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144290, 144291, 144292, 144293, 144294, 144296, 144297, 144298 ], "onlineresource_set": [ 42519, 42520, 42521, 42522 ] }, { "ob_id": 32409, "uuid": "1f4e19c154e64d2489d6516d5fd19f91", "title": "MYD04_L2 - MODIS/Aqua Aerosol 5-Min L2 Swath 10km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD04_L2\n\n\n\n\n\n\"The MODIS Aerosol Product monitors the ambient aerosol optical thickness over the oceans globally and over a portion of the continents. Further, the aerosol size distribution is derived over the oceans, and the aerosol type is derived over the continents. Daily Level-2 data are produced at the spatial resolution of a 10x10 1-km pixel array (at nadir).\n\nPrior to MODIS, satellite measurements were limited to reflectance measurements in one (GOES, METEOSAT) or two (AVHRR) channels. There was no real attempt to retrieve aerosol content over land on a global scale. Algorithms had been developed for use only over dark vegetation. The blue channel on MODIS, not present on AVHRR, offers the possibility to extend the derivation of optical thickness over land to additional surfaces. The algorithms use MODIS bands 1 through 7 and 20 and require prior cloud screening using MODIS data. Over the land, the dynamic aerosol models are derived from ground-based sky measurements and used in the net retrieval process.\n\nOver the ocean, three parameters that describe the aerosol loading and size distribution are retrieved. Pre-assumptions on the general structure of the size distribution are required in the inversion of MODIS data, and the volume-size distribution is described with two log-normal modes: a single mode to describe the accumulation mode particles (radius < 0.5 µm) and a single coarse mode to describe dust and/or salt particles (radius > 1.0 µm).\n\nThe quality assurance control of these products will be based on comparison with ground stations and climatology.\n\nFor additional details see the MODIS Atmospheres web site page onCollection 6.1 Updates. \"\n\nShortname: MYD04_L2 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-2 , Spatial Resolution: 10 km , Temporal Resolution: 5 minute , ArchiveSets: 61 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE04 , File Naming Convention: MYD04_L2.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time AYYYYDDD = Year and Day of Year of acquisition , Citation: Levy, R., Hsu, C., et al., 2015. MODIS Atmosphere L2 Aerosol Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MYD04_L2.061 , Keywords: Climate Change, Atmospheric Correction, Aerosol Optical Depth/Thickness ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-12-01T01:17:44", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "Climate Change, Atmospheric Correction, Aerosol Optical Depth/Thickness ", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "10 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:06:47.819974", "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": 32410, "dataPath": "/neodc/modis/data/MYD04_L2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 3269775529851, "numberOfFiles": 1358202, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8899, "startTime": "2002-07-03T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3629, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26034, "uuid": "85bb8321bc8b42f9a39cb6d83fabe79e", "short_code": "acq", "title": "MODIS data from the Aqua Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nIt is flown on NASA's Aqua Satellite which was launched on May 4, 2002, and has six Earth-observing instruments on board, collecting a variety of global data sets\r\n\r\nA MODIS instrument is also flown on NASA's Terra satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10904, "uuid": "ccc71008f3c0db6f9d2c70bbc4346f31", "short_code": "proj", "title": "Aqua Satellite Mission, part of the Earth Observing System Afternoon Constellation (EOS-PM)", "abstract": "Aqua is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64632, 64633, 64634, 64635, 64636, 64637, 64638, 64639, 64640, 64641, 64642, 64643, 64644, 64645, 64646, 64647, 64648, 64649, 64650, 64651, 64652, 64653, 64654, 64655, 64656, 64657, 64658, 64659, 64660, 64661, 64662, 64663, 64664, 64665, 64666, 64667, 64668, 64669, 64670, 64671, 64672, 64673, 64674, 64675, 64676, 64677, 64678, 64679, 64680, 64681, 64682, 64683, 64684, 64685, 64686, 64687, 64688, 64689, 64690, 64691, 64692, 64693, 64694, 64695, 64696, 64697, 64698, 64699, 64700, 64701, 64702 ], "vocabularyKeywords": [], "identifier_set": [ 10842 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144299, 144300, 144301, 144302, 144303, 144305, 144306, 144307 ], "onlineresource_set": [ 42523, 42524, 42525, 42526 ] }, { "ob_id": 32411, "uuid": "b5e81b4a2be145b990ae3b8e198f9266", "title": "MYD06_L2 - MODIS/Aqua Clouds 5-Min L2 Swath 1km and 5km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD06_L2\n\n\n\n\n\nThe MODIS Level-2 Cloud product consists of cloud optical and physical parameters. These parameters are derived using remotely sensed infrared, visible and near infrared solar reflected radiances. MODIS infrared channel radiances are used to derive cloud top temperature, cloud top height, effective emissivity, cloud phase (ice vs. water, opaque vs. non-opaque), and cloud fraction under both daytime and nighttime conditions. MODIS visible radiances are used to derive cloud optical thickness and effective particle radius and cloud shadow effects. Near-infrared solar reflected radiance provides additional information for the retrieval of cloud particle phase (ice vs. water, clouds vs. snow). The shortname for this Level-2 MODIS cloud product is MYD06_L2. MYD06_L2 consists of parameters at a spatial resolution of either 1km or 5km (at nadir). Each MYD06_L2 product file covers a 5-minute time interval. This means that for 5km resolution parameters, the output grid is 270 pixels wide by 406 pixels in length. Every tenth granule has an output grid size of 270 by 408 pixels. For 1-km resolution parameters, the output grid is 1354 pixels in width by 2030 pixels in length and every tenth granule has an output grid size of 1354 by 2040 pixels.\n\nMYD06_L2 product files are stored in Hierarchical Data Format (HDF-EOS). All gridded cloud parameters are stored as Scientific Data Sets (SDS) within the file, except two (band number and statistics). These are stored as Vdata (table arrays). Approximately 288 files are produced daily. Nighttime files are smaller than their daytime counterparts since only the cloud top properties are retrieved at night.\n\nThe MODIS Cloud Product will be used to investigate seasonal and inter-annual changes in cirrus (semi-transparent) global cloud cover and cloud phase with multispectral observations at 1km spatial resolution.\n\nFor additional details see the MODIS Atmospheres web site page onCollection 6.1 Updates.\n\nShortname: MYD06_L2 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-2 , Spatial Resolution: 1 km , Temporal Resolution: 5 minute , ArchiveSets: 61 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE06 , File Naming Convention: MYD06_L2.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf AYYYYDDD = Acqusition Year and Day of Year HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time AYYYYDDD = Year and Day of Year of acquisition , Citation: Platnick, S., Ackerman, S., King, M., et al., 2015. MODIS Atmosphere L2 Cloud Product (06_L2). NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MYD06_L2.061 , Keywords: Water Vapor, Precipitable Water ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-11-29T01:16:59", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "Water Vapor, Precipitable Water ", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:07:26.880711", "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": 32412, "dataPath": "/neodc/modis/data/MYD06_L2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 146077385085823, "numberOfFiles": 2513681, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8900, "startTime": "2002-07-03T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3630, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26034, "uuid": "85bb8321bc8b42f9a39cb6d83fabe79e", "short_code": "acq", "title": "MODIS data from the Aqua Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nIt is flown on NASA's Aqua Satellite which was launched on May 4, 2002, and has six Earth-observing instruments on board, collecting a variety of global data sets\r\n\r\nA MODIS instrument is also flown on NASA's Terra satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10904, "uuid": "ccc71008f3c0db6f9d2c70bbc4346f31", "short_code": "proj", "title": "Aqua Satellite Mission, part of the Earth Observing System Afternoon Constellation (EOS-PM)", "abstract": "Aqua is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 62241, 62242, 64508, 64510, 64511, 64512, 64513, 64514, 64547, 64548, 64549, 64550, 64551, 64552, 64553, 64554, 64555, 64556, 64557, 64558, 64559, 64560, 64561, 64562, 64563, 64564, 64565, 64566, 64567, 64568, 64569, 64570, 64571, 64572, 64573, 64574, 64575, 64576, 64577, 64578, 64579, 64580, 64581, 64582, 64583, 64584, 64585, 64586, 64587, 64588, 64589, 64590, 64591, 64592, 64593, 64594, 64595, 64596, 64597, 64598, 64599, 64600, 64601, 64602, 64603, 64604, 64605, 64606, 64607, 64608, 64609, 64610, 64611, 64612, 64613, 64614, 64615, 64616, 64617, 64618, 64619, 64620, 64621, 64622, 64623, 64624, 64625, 64626, 64627, 64628, 64629, 64630, 64631, 91976, 91977, 91978, 91979, 91980, 91981, 91982, 91983, 91984, 91985, 91986, 91987, 91988, 91989, 91990, 91991, 91992, 91993, 91994, 91995, 91996, 91997, 91998, 91999, 92000, 92001, 92002, 92003, 92004, 92005, 92006, 92007, 92008, 92009 ], "vocabularyKeywords": [], "identifier_set": [ 10845 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144308, 144309, 144310, 144311, 144312, 144314, 144315, 144316 ], "onlineresource_set": [ 42527, 42528, 42529, 42530 ] }, { "ob_id": 32413, "uuid": "56b3282c25604434bc1417ab70ba9c79", "title": "MYD11A1 - MODIS/Aqua Land Surface Temperature/Emissivity Daily L3 Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD11A1\n\n\n\n\n\nThe MODIS/Aqua Land Surface Temperature and Emissivity (LST/E) products provide per-pixel temperature and emissivity values in a sequence of swath-based to grid-based global products. The MODIS/Aqua LST/E Daily L3 Global 1 km SIN Grid,(Short name: MYD11A1), is a gridded version of the L2 Daily LST/E data set, whose LSTs are retrieved by the split-window algorithm.\n\nThe Collection-4 (C4) LST/E L3 MYD11A1 product inputs include the MODIS L1B calibrated and geolocated radiances, geolocation, cloud mask, atmospheric profiles, land and snow cover. The band 31 and 32 emissivities are estimated by a classification-based emissivity method, which relies on the pixel's land cover type as determined by the land and snow cover inputs. Until June 2001, the AVHRR-based IGBP land cover product was used. Following that time, MODIS-derived land cover product was used. The estimated emissivities in arid and semi-arid areas are potentially uncertain, and users are advised to exercise caution in their applications. The day/night alogorithm extracts average temperatures (in Kelvin) and applies them to a pair of MODIS daytime and nighttime observations. This method yields 1 K accuracy for materials with known emissivities. The V4 MYD11A1 product has a temporal acquisition range of February 24, 2000 (2000-055) until January 3, 2007 (200-003). The C4 collection remains consistent with C41, and users may combine the two collections in a time-series analysis.\n\nThe MODIS/Aqua Collection 41 (C41) products use a modified Collection-4 (C4) LST algorithm and Collection-5 (C5) data inputs. The C41 products primarily address underestimation problems in the C5 Climate Modeling Grid (CMG) products. Recent validation activities reveal that the C5 CMG products underestimate LSTs up to 6K especially in desert and semi-arid regions. The availability of this collection starts with MODIS/Aqua data acquisition on January 1, 2007 (2007-001). This date is driven by the availability of the MODIS C5 data inputs (level-1B radiance data, geolocation data, cloud mask, atmospheric profiles, and land and snow cover data).\n\nThe MODIS/Aqua C5 LST/E L3 Global 5 km Grid product incorporates 1-km pixels, which are produced daily using the generalized split-window LST algorithm. This algorithm is optimally used to separate ranges of atmospheric column water vapor and lower boundary air surface temperatures into tractable sub-ranges. The surface emissivities in bands 31 and 32 are estimated from land cover types. The C5 MYD11_L2 product's acquisition range started March 5, 2000 (2000-065) and will continue until some time after the C6 reprocessing is complete.\n\nThe C41 and C5 MODIS/Aqua LST/E products, including the MYD11A1, are validated to Stage-2 with well-defined uncertainties over a range of representative conditions. Further details regarding MODIS land product validation for the LST/E products are available from the MODIS land team validation site referenced under 'Val Status' section.\n\nThe C41 LST products from 2007-001 will remain consistent with similar products from C4, and hence are amenable to combine them in a time-series analysis. Users should exercise caution, and not mix the C4.x (i.e., C4 and C41) and C5 LST products in their analyses.\n\nShortname: MYD11A1 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 1 km , Temporal Resolution: daily , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE16M , File Naming Convention: MYD11A1.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Zhengming Wan - University of California Santa Barbara, Simon Hook, Glynn Hulley - JPL and MODAPS SIPS - NASA. (2015). MYD11A1 MODIS/Aqua Land Surface Temperature and the Emissivity Daily L3 Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MYD11A1.006 , Keywords: Climate Change, Land Surface Temperature, Emissivity, Fires ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2023-05-18T09:19:29", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "Climate Change, Land Surface Temperature, Emissivity, Fires ", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:07:40.039088", "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": 32414, "dataPath": "/neodc/modis/data/MYD11A1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2663764927081, "numberOfFiles": 1305863, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8901, "startTime": "2002-07-03T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3631, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26034, "uuid": "85bb8321bc8b42f9a39cb6d83fabe79e", "short_code": "acq", "title": "MODIS data from the Aqua Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nIt is flown on NASA's Aqua Satellite which was launched on May 4, 2002, and has six Earth-observing instruments on board, collecting a variety of global data sets\r\n\r\nA MODIS instrument is also flown on NASA's Terra satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10904, "uuid": "ccc71008f3c0db6f9d2c70bbc4346f31", "short_code": "proj", "title": "Aqua Satellite Mission, part of the Earth Observing System Afternoon Constellation (EOS-PM)", "abstract": "Aqua is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64531, 64532, 64537, 64538, 64539, 64540, 64541, 64542, 64543, 64544, 64545, 64546 ], "vocabularyKeywords": [], "identifier_set": [ 10846 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144317, 144318, 144319, 144320, 144321, 144323, 144324, 144325 ], "onlineresource_set": [ 42531, 42532, 42533, 42534, 42535 ] }, { "ob_id": 32415, "uuid": "dfa34fb44ba649bf91397ff5a3eeae49", "title": "MYD11A2 - MODIS/Aqua Land Surface Temperature/3-Band Emissivity 8-Day L3 Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD11A2\n\n\n\n\n\nThe level-3 MODIS Land Surface Temperature and Emissivity (LST/E) 8-day data products are composed of data from the daily 1-kilometer LST product (MYD11A1) and stored on a 1-km Sinusoidal grid as the average values of clear-sky LSTs during an 8-day period.\n\nMYD11A2 is comprised of daytime and nighttime LSTs, quality assurance assessment, observation times, view angles, bits of clear sky days and nights, and emissivities estimated in Bands 31 and 32 from land cover types.\n\nCollection-5 MODIS/Aqua Land Surface Temperature/Emissivity products are validated to Stage 2, which means that their accuracy has been assessed over a widely distributed set of locations and time periods via several ground-truth and validation efforts. Further details regarding MODIS land product validation for the LST/E products are available from the following URL: http://landval.gsfc.nasa.gov/ProductStatus.php?ProductID=MYD11.\n\nShortname: MYD11A2 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 1 km , Temporal Resolution: 8 day , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE31 , File Naming Convention: MYD11A2.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Zhengming Wan - University of California Santa Barbara, Simon Hook, Glynn Hulley - JPL and MODAPS SIPS - NASA. (2015). MYD11A2 MODIS/Aqua Land Surface Temperature and the Emissivity 8-Day L3 Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MYD11A2.006 , Keywords: Climate Change, Land Surface Temperature, Emissivity, Fires ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2023-02-28T03:17:04", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "Climate Change, Land Surface Temperature, Emissivity, Fires ", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:07:49.992594", "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": 32416, "dataPath": "/neodc/modis/data/MYD11A2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 380310356946, "numberOfFiles": 97627, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8902, "startTime": "2002-07-03T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3632, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26034, "uuid": "85bb8321bc8b42f9a39cb6d83fabe79e", "short_code": "acq", "title": "MODIS data from the Aqua Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nIt is flown on NASA's Aqua Satellite which was launched on May 4, 2002, and has six Earth-observing instruments on board, collecting a variety of global data sets\r\n\r\nA MODIS instrument is also flown on NASA's Terra satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10904, "uuid": "ccc71008f3c0db6f9d2c70bbc4346f31", "short_code": "proj", "title": "Aqua Satellite Mission, part of the Earth Observing System Afternoon Constellation (EOS-PM)", "abstract": "Aqua is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64527, 64528, 64529, 64530, 64531, 64532, 64533, 64534, 64535, 64536, 64537, 64538 ], "vocabularyKeywords": [], "identifier_set": [ 10848 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144326, 144327, 144328, 144329, 144330, 144332, 144333, 144334 ], "onlineresource_set": [ 42536, 42537, 42538, 42539, 42540 ] }, { "ob_id": 32417, "uuid": "f10420bececd447eb1b74db9d66ef12a", "title": "MYD13A2 - MODIS/Aqua Vegetation Indices 16-Day L3 Global 1km SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD13A2\n\n\n\n\n\nGlobal MODIS vegetation indices are designed to provide consistent spatial and temporal comparisons of vegetation conditions. Blue, red, and near-infrared reflectances, centered at 469-nanometers, 645-nanometers, and 858-nanometers, respectively, are used to determine the MODIS daily vegetation indices.\n\nThe MODIS Normalized Difference Vegetation Index (NDVI) complements NOAA's Advanced Very High Resolution Radiometer (AVHRR) NDVI products providing continuity for time series applications over this rich historical archive. MODIS also includes a new Enhanced Vegetation Index (EVI) product that minimizes canopy background variations and maintains sensitivity over dense vegetation conditions. The EVI also uses the blue band to remove residual atmosphere contamination caused by smoke and sub-pixel thin cloud clouds. The MODIS NDVI and EVI products are computed from atmospherically-corrected bi-directional surface reflectances that have been masked for water, clouds, heavy aerosols, and cloud shadows.\n\nGlobal MYD13A2 data are provided every 16 days at 1-kilometer spatial resolution as a gridded level-3 product in the Sinusoidal projection. Vegetation indices are used for global monitoring of vegetation conditions and are used in products displaying land cover and land cover changes. These data may be used as input for modeling global biogeochemical and hydrologic processes and global and regional climate. These data also may be used for characterizing land surface biophysical properties and processes, including primary production and land cover conversion.\n\nCollection-5 MODIS/Aqua Vegetation Indices products are Validated at Stage 2, meaning that accuracy has been assessed over a widely distributed set of locations and time periods via several ground-truth and validation efforts. Although there may be later improved versions, these data are ready for use in scientific publications.\n\nShortname: MYD13A2 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 1 km , Temporal Resolution: 16 day , ArchiveSets: 6, 61 , Collection: MODIS Collection 6 (ArchiveSet 6) , PGE Number: PGE35 , File Naming Convention: MYD13A2.AYYYYDDD.hHHvVV.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition hHH = Horizontal tile number (0-35) vVV = Vertical tile number (0-17) CCC = Collection number YYYYDDDHHMMSS = Production Date and Time , Citation: Kamel Didan - University of Arizona, Alfredo Huete - University of Technology Sydney and MODAPS SIPS - NASA. (2015). MYD13A2 MODIS/Aqua Vegetation Indices 16-Day L3 Global 1km SIN Grid. NASA LP DAAC. http://doi.org/10.5067/MODIS/MYD13A2.006 , Keywords: Climate Change, Canopy Characteristics, Biomass, Vegetation Index, Plant Phenology, Length of Growing Season ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2023-02-27T21:18:42", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "Climate Change, Canopy Characteristics, Biomass, Vegetation Index, Plant Phenology, Length of Growing Season ", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:08:00.082364", "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": 32418, "dataPath": "/neodc/modis/data/MYD13A2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 389452185266, "numberOfFiles": 42205, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8903, "startTime": "2002-07-03T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3633, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26034, "uuid": "85bb8321bc8b42f9a39cb6d83fabe79e", "short_code": "acq", "title": "MODIS data from the Aqua Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nIt is flown on NASA's Aqua Satellite which was launched on May 4, 2002, and has six Earth-observing instruments on board, collecting a variety of global data sets\r\n\r\nA MODIS instrument is also flown on NASA's Terra satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10904, "uuid": "ccc71008f3c0db6f9d2c70bbc4346f31", "short_code": "proj", "title": "Aqua Satellite Mission, part of the Earth Observing System Afternoon Constellation (EOS-PM)", "abstract": "Aqua is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64515, 64516, 64517, 64518, 64519, 64520, 64522, 64523, 64524, 64525, 64526, 83850 ], "vocabularyKeywords": [], "identifier_set": [ 10849 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144335, 144336, 144337, 144338, 144339, 144341, 144342, 144343 ], "onlineresource_set": [ 42541, 42542, 42543, 42544, 42545, 42546 ] }, { "ob_id": 32419, "uuid": "bac493ecc5f14b4d809f35f89eceb834", "title": "MYD35_L2 - MODIS/Aqua Cloud Mask and Spectral Test Results 5-Min L2 Swath 250m and 1km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD35_L2\n\n\n\n\n\n\"\nThe MODIS Cloud Mask product is a Level-2 product generated at 1-km and 250-m (at nadir) spatial resolutions. The algorithm employs a series of visible and infrared threshold and consistency tests to specify confidence that an unobstructed view of the Earth's surface has been observed. An indication of shadows affecting the scene is also provided. The 250-m cloud mask flags are based on visible channel data only. Radiometrically-accurate radiances are required, thus holes in the Cloud Mask will appear wherever the input radiances are incomplete or of poor quality assurance. There are two MODIS Cloud Mask data product files: MOD35_L2, containing data collected from the Terra platform; and MYD35_L2, containing data collected from the Aqua platform.\n\nThe MODIS cloud mask algorithm employs a battery of spectral tests, which use methodology applied in the AVHRR Processing scheme Over cLoudy Land and Ocean (APOLLO), International Satellite Cloud Climatology Project (ISCCP), CLoud Advanced Very high resolution Radiometer (CLAVR), and the Support of Environmental Requirements for Cloud Analysis and Archive (SERCAA) algorithms to identify cloudy FOVs. From these, a clear-sky confidence level (high confident clear, probably clear, undecided, cloudy) is assigned to each FOV. For inconclusive results, spatial- and temporal-variability tests are applied. The spectral tests rely on radiance (temperature) thresholds in the infrared and reflectance thresholds in the visible and near-infrared. Thresholds vary with surface type, atmospheric conditions (moisture, aerosol, etc.), and viewing geometry. In addition to the MYD02 calibrated radiances, a 1-km land/water mask, DEM, ecosystem analysis, snow/ice cover map, NCEP analysis of surface temperature and wind speed, and an estimate of precipitable water are required as inputs.\n\nA determination of the presence of global cloudiness is essential to the MODIS mission for two reasons. First, clouds play a critical role in the radiative balance of the Earth and must be accurately described to assess climate and potential climate change. Second, the presence of cloudiness must be accurately determined to properly retrieve many atmospheric and surface parameters. For many of these retrieval algorithms even thin cirrus represents contamination.\n\nCloud mask validation will be conducted using MODIS Airborne Simulator (MAS) data from several field campaigns, all-sky cameras, and comparison with NOAA operational instruments and possibly ASTER.\n\nFor additional details see the MODIS Atmospheres web site page onCollection 6.1 Updates. \"\n\nShortname: MYD35_L2 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-2 , Spatial Resolution: 250 m, 1 km , Temporal Resolution: 5 minute , ArchiveSets: 61 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE03 , File Naming Convention: MYD35_L2.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf YYYYDDD = Year and Day of Year of acquisition HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time AYYYYDDD = Year and Day of Year of acquisition , Citation: Ackerman, S., et al., 2017. MODIS Atmosphere L2 Cloud Mask Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MYD35_L2.061 , Keywords: Cloud Fraction, Climate Change, Atmospheric Correction ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-12-02T10:16:13", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "Cloud Fraction, Climate Change, Atmospheric Correction ", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "250 m, 1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:08:08.717207", "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": 32420, "dataPath": "/neodc/modis/data/MYD35_L2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 19455990088840, "numberOfFiles": 2484689, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8904, "startTime": "2002-07-03T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3634, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26034, "uuid": "85bb8321bc8b42f9a39cb6d83fabe79e", "short_code": "acq", "title": "MODIS data from the Aqua Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nIt is flown on NASA's Aqua Satellite which was launched on May 4, 2002, and has six Earth-observing instruments on board, collecting a variety of global data sets\r\n\r\nA MODIS instrument is also flown on NASA's Terra satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10904, "uuid": "ccc71008f3c0db6f9d2c70bbc4346f31", "short_code": "proj", "title": "Aqua Satellite Mission, part of the Earth Observing System Afternoon Constellation (EOS-PM)", "abstract": "Aqua is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 62241, 62242, 64507, 64508, 64509, 64510, 64511, 64512, 64513, 64514 ], "vocabularyKeywords": [], "identifier_set": [ 10850 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144344, 144345, 144346, 144347, 144348, 144350, 144351, 144352 ], "onlineresource_set": [ 42547, 42548, 42549, 42550 ] }, { "ob_id": 32422, "uuid": "05a18921d3a44c89a9158809fd813eb3", "title": "MOD09A1 - MODIS/Terra Surface Reflectance 8-Day L3 Global 500m SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD09A1\n\n\n\n\n\nShortname: MOD09A1 , Platform: Terra , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 500 m , Temporal Resolution: 8 day , ArchiveSets: 61, 6 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE21 ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2023-05-17T18:17:28", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "500 m ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:38:31.845471", "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": 32423, "dataPath": "/neodc/modis/data/MOD09A1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 6727043429785, "numberOfFiles": 105629, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8905, "startTime": "2000-02-23T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3635, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 25855, "uuid": "280deb3b3c7f46d0a29a80cb60c3c448", "short_code": "acq", "title": "MODIS data from the Terra Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nThe Terra Satellite is a NASA satellite flying 5 research instruments to study the Earth's atmosphere, ocean and land, including the MODIS instrument. It was launched in 2003 and is still currently returning data.\r\n\r\nA MODIS instrument is also flown on NASA's AQUA satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10895, "uuid": "524f1a46e6df4ed1c1d89459167e7cd0", "short_code": "proj", "title": "Terra Satellite Mission, part of the Earth Observing System Morning Constellation (EOS-AM)", "abstract": "Terra is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64494, 64495, 64496, 64497, 64498, 64499, 64500, 64501, 64502, 64503, 64504, 64505, 64506 ], "vocabularyKeywords": [], "identifier_set": [ 10852 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144355, 144356, 144357, 144358, 144359, 144361, 144362, 144363 ], "onlineresource_set": [ 42551, 42552 ] }, { "ob_id": 32424, "uuid": "4bc9628787174d9198f0d4dc153b15c4", "title": "MOD09GA - MODIS/Terra Surface Reflectance Daily L2G Global 1km and 500m SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MOD09GA\n\n\n\n\n\nShortname: MOD09GA , Platform: Terra , Instrument: MODIS , Processing Level: Level-2 Tiled , Spatial Resolution: 500 m, 1 km , Temporal Resolution: daily , ArchiveSets: 61, 6 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE13 ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2023-05-18T09:19:30", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "500 m, 1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:38:59.647150", "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": 32425, "dataPath": "/neodc/modis/data/MOD09GA", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 156024160299121, "numberOfFiles": 1511216, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8906, "startTime": "2000-02-23T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3636, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 25855, "uuid": "280deb3b3c7f46d0a29a80cb60c3c448", "short_code": "acq", "title": "MODIS data from the Terra Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nThe Terra Satellite is a NASA satellite flying 5 research instruments to study the Earth's atmosphere, ocean and land, including the MODIS instrument. It was launched in 2003 and is still currently returning data.\r\n\r\nA MODIS instrument is also flown on NASA's AQUA satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10895, "uuid": "524f1a46e6df4ed1c1d89459167e7cd0", "short_code": "proj", "title": "Terra Satellite Mission, part of the Earth Observing System Morning Constellation (EOS-AM)", "abstract": "Terra is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64452, 64453, 64454, 64455, 64456, 64457, 64458, 64459, 64460, 64461, 64462, 64463, 64464, 64465, 64466, 64467, 64468, 64469, 64470, 64471, 64472, 64473, 64474, 64475, 64476, 64477, 64478, 64479, 64480, 64481, 64482, 64483, 64484, 64485, 64486, 64487, 64488, 64489, 64490, 64491, 64492, 64493 ], "vocabularyKeywords": [], "identifier_set": [ 10853 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144364, 144365, 144366, 144367, 144368, 144370, 144371, 144372 ], "onlineresource_set": [ 42553, 42554 ] }, { "ob_id": 32426, "uuid": "9dc47e606d50479bbe81872308679ca4", "title": "MYD09A1 - MODIS/Aqua Surface Reflectance 8-Day L3 Global 500m SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD09A1\n\n\n\n\n\nShortname: MYD09A1 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-3 , Spatial Resolution: 500 m , Temporal Resolution: 8 day , ArchiveSets: 61, 6 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE21 ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2023-02-28T05:16:45", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "500 m ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:39:37.077351", "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": 32427, "dataPath": "/neodc/modis/data/MYD09A1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 7105777769771, "numberOfFiles": 117935, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8907, "startTime": "2002-07-03T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3637, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26034, "uuid": "85bb8321bc8b42f9a39cb6d83fabe79e", "short_code": "acq", "title": "MODIS data from the Aqua Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nIt is flown on NASA's Aqua Satellite which was launched on May 4, 2002, and has six Earth-observing instruments on board, collecting a variety of global data sets\r\n\r\nA MODIS instrument is also flown on NASA's Terra satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10904, "uuid": "ccc71008f3c0db6f9d2c70bbc4346f31", "short_code": "proj", "title": "Aqua Satellite Mission, part of the Earth Observing System Afternoon Constellation (EOS-PM)", "abstract": "Aqua is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64494, 64495, 64496, 64497, 64498, 64499, 64500, 64501, 64502, 64503, 64504, 64505, 64506 ], "vocabularyKeywords": [], "identifier_set": [ 10854 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144373, 144374, 144375, 144376, 144377, 144379, 144380, 144381 ], "onlineresource_set": [ 42555, 42556 ] }, { "ob_id": 32428, "uuid": "b8cb8a5d02b143fc8257d030f81bcf76", "title": "MYD09GA - MODIS/Aqua Surface Reflectance Daily L2G Global 1km and 500m SIN Grid", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD09GA\n\n\n\n\n\nShortname: MYD09GA , Platform: Aqua , Instrument: MODIS , Processing Level: Level-2 Tiled , Spatial Resolution: 500 m, 1 km , Temporal Resolution: daily , ArchiveSets: 61, 6 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE13 ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2023-05-18T09:19:26", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "500 m, 1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:40:11.018403", "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": 32429, "dataPath": "/neodc/modis/data/MYD09GA", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 149596701852414, "numberOfFiles": 1477621, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8908, "startTime": "2002-07-03T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3638, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26034, "uuid": "85bb8321bc8b42f9a39cb6d83fabe79e", "short_code": "acq", "title": "MODIS data from the Aqua Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nIt is flown on NASA's Aqua Satellite which was launched on May 4, 2002, and has six Earth-observing instruments on board, collecting a variety of global data sets\r\n\r\nA MODIS instrument is also flown on NASA's Terra satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10904, "uuid": "ccc71008f3c0db6f9d2c70bbc4346f31", "short_code": "proj", "title": "Aqua Satellite Mission, part of the Earth Observing System Afternoon Constellation (EOS-PM)", "abstract": "Aqua is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64452, 64453, 64454, 64455, 64456, 64457, 64458, 64459, 64460, 64461, 64462, 64463, 64464, 64465, 64466, 64467, 64468, 64469, 64470, 64471, 64472, 64473, 64474, 64475, 64476, 64477, 64478, 64479, 64480, 64481, 64482, 64483, 64484, 64485, 64486, 64487, 64488, 64489, 64490, 64491, 64492, 64493 ], "vocabularyKeywords": [], "identifier_set": [ 10855 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144382, 144383, 144384, 144385, 144386, 144388, 144389, 144390 ], "onlineresource_set": [ 42557, 42558 ] }, { "ob_id": 32430, "uuid": "692a3e1b71f24d8cbfc359eba26a7754", "title": "MYD03 - Geolocation - 1km", "abstract": "These data are a copy of MODIS data from the NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). The copy is potentially only a subset. Below is the description from https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/products/MYD03\n\n\n\n\n\nThe MYD03 product inculdes the geolocation fields that are calculated for each 1 km MODIS Instantaneous Field of Views (IFOV) for all orbits daily. The locations and ancillary information correspond to the intersection of the centers of each IFOV from 10 detectors in an ideal 1 km band on the Earth's surface. A digital terrain model is used to model the Earth's surface. The main inputs are the spacecraft attitude and orbit, the instrument telemetry and the digital elevation model. The geolocation fields include geodetic Latitude, Longitude, surface height above the geoid, solar zenith and azimuth angles, satellite zenith and azimuth angles, and a land/sea mask for each 1 km sample. Additional information is included in the header to enable the calculation of the approximate location of the center of the detectors for any of the 36 MODIS bands. This product is used as input by a large number of subsequent MODIS products, particularly those produced by the Land team.\n\nShortname: MYD03 , Platform: Aqua , Instrument: MODIS , Processing Level: Level-1A , Spatial Resolution: 1 km , Temporal Resolution: 5 minute , ArchiveSets: 61, 6 , Collection: MODIS Collection 6.1 - Level 1, Atmosphere, Land (ArchiveSet 61) , PGE Number: PGE01 , File Naming Convention: MYD03.AYYYYDDD.HHMM.CCC.YYYYDDDHHMMSS.hdf AYYYYDDD = Acqusition Year and Day of Year HHMM = Hour and Minute of acquisition CCC = Collection number YYYYDDDHHMMSS = Production Date and Time YYYYDDD = Year and Day of Year of acquisition , Citation: MODIS Characterization Support Team (MCST), 2017. MODIS Geolocation Fields Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA: http://dx.doi.org/10.5067/MODIS/MYD03.061 ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-12-02T10:16:04", "updateFrequency": "asNeeded", "dataLineage": "Data were downloaded from https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/ to support UK research groups, especially NCEO.", "removedDataReason": "", "keywords": "", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1 km ", "status": "ongoing", "dataPublishedTime": "2021-04-15T14:41:08.073990", "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": 32431, "dataPath": "/neodc/modis/data/MYD03", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 76712329151168, "numberOfFiles": 2478753, "fileFormat": "HDF" }, "timePeriod": { "ob_id": 8909, "startTime": "2002-07-03T23:55:00", "endTime": null }, "resultQuality": { "ob_id": 3639, "explanation": "Look on the data source site (https://ladsweb.modaps.eosdis.nasa.gov) for quality information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26034, "uuid": "85bb8321bc8b42f9a39cb6d83fabe79e", "short_code": "acq", "title": "MODIS data from the Aqua Satellite", "abstract": "The Moderate Resolution Imaging Spectroradiometer (MODIS) provides high radiometric sensitivity in 36 spectral bands ranging from 0.4 to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km.\r\n\r\nIt is flown on NASA's Aqua Satellite which was launched on May 4, 2002, and has six Earth-observing instruments on board, collecting a variety of global data sets\r\n\r\nA MODIS instrument is also flown on NASA's Terra satellite" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 128 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2557, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 29, "licenceURL": "https://modaps.modaps.eosdis.nasa.gov/services/faq/LAADS_Data-Use_Citation_Policies.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 10904, "uuid": "ccc71008f3c0db6f9d2c70bbc4346f31", "short_code": "proj", "title": "Aqua Satellite Mission, part of the Earth Observing System Afternoon Constellation (EOS-PM)", "abstract": "Aqua is under the NASA-led international Earth Observation System (EOS), a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans, to enhance our understanding on the Earth System. The objective of the mission is to collect data on atmospheric, oceanic, cryospheric (snow and ice) and land surface conditions as well as the energy budget, together with other satellites in the Morning Constellation (the M-Train). The satellite was launched on 18th December 1999, and the data collection for data products began in February 2000." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64156, 64157, 64724, 64726, 64727, 64728, 64729, 64730, 64731, 65398, 65399, 65400, 65401, 65402, 65403, 65404, 65405, 65406, 65407, 65408, 65409, 65410, 65411, 65412, 65413, 65414, 65415, 65416, 65417, 65418, 65419, 65420, 65421, 65422, 65423, 65424, 65425, 65426, 65427, 65428, 65429, 65430, 65431, 65432, 65433, 65434 ], "vocabularyKeywords": [], "identifier_set": [ 10856 ], "observationcollection_set": [ { "ob_id": 10892, "uuid": "34e75e7e8e838b0f3ee5916856d510b4", "short_code": "coll", "title": "Moderate Resolution Imaging Spectroradiometer (MODIS) Data", "abstract": "Data products from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra and Aqua satellites as part of NASA-led international Earth Observation System (EOS) programme. MODIS provides high radiometric sensitivity (12 bit) in 36 spectral bands ranging in wavelength from 0.4 micrometres to 14.4 micrometres. Two bands are imaged at a nominal resolution of 250 m at nadir, with five bands at 500 m, and the remaining 29 bands at 1 km. A +/- 55-degree scanning pattern at the EOS orbit of 705 km achieves a 2,330-km swath and provides global coverage every one to two days. The main objective of MODIS is to enhance our understandings on global dynamics and processes occurring on the land, in the oceans and in the lower atmosphere, and these data are also essential in the development of validated, global and interactive Earth system models." }, { "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": [ 144391, 144392, 144393, 144394, 144395, 144397, 144398, 144399 ], "onlineresource_set": [ 42559, 42560, 42561, 42562 ] }, { "ob_id": 32440, "uuid": "212f2ed8d9df42e38e5786683c486c48", "title": "NERC-ARF Flight 2018_135a - for GB18_56: Airborne remote sensing measurements", "abstract": "Airborne remote sensing measurements collected on 15 May 2018 by the Natural Environment Research Council Airborne Research Facility (NERC-ARF) onboard the British Antarctic Survey (BAS) Twin-Otter aircraft for the NERC-ARF GB18_56 Project: Methane emission sources, UK (GB18_56)(flight reference: 2018_135a). This dataset comprises: hyperspectral data collected using a Specim Aisa FENIX imager and hyperspectral data collected using a Specim Aisa OWL imager.\r\n\r\nData were collected over the Harwell, UK area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2019-01-22T11:36:30", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by the NERC-ARF facility and deposited at the Centre for Environmental Data Analysis (CEDA) for archiving.", "removedDataReason": "", "keywords": "GB18_56, GB18/56, aircraft, hyperspectral, remote sensing, NERC-ARF, ARSF", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-04-23T11:00:44", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2748, "bboxName": "", "eastBoundLongitude": 1.1473148644735627, "westBoundLongitude": 0.9958475795040317, "southBoundLatitude": 52.09342930501146, "northBoundLatitude": 52.132280748683016 }, "verticalExtent": null, "result_field": { "ob_id": 32441, "dataPath": "/neodc/arsf/2018/GB18_56/GB18_56-2018_135a_Methane_Sites", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 25296536893, "numberOfFiles": 141, "fileFormat": "Hyperspectral data are ENVI binary, LiDAR data are LAS and aerial photography are TIF formats" }, "timePeriod": { "ob_id": 8912, "startTime": "2018-05-15T11:43:21", "endTime": "2018-05-15T12:00:36" }, "resultQuality": { "ob_id": 3642, "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": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32442, "uuid": "ea79bc10eb944002abd4727383701aca", "short_code": "acq", "title": "Acquisition for: NERC-ARF 2018_135a - GB18_56 Flight: Airborne remote sensing measurements", "abstract": "" }, "procedureComputation": null, "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": 32421, "uuid": "69f391cc3607494a8cf77f630b0ddb2d", "short_code": "proj", "title": "NERC-ARF GB18_56 Project: Methane emission sources, UK", "abstract": "The aim of this project was to investigate well-defined local methane emission sources in the UK to apply and evaluate the hyperspectral processing method currently developed at the University of Leicester.\r\n\r\nThis project used NERC-ARF (NERC Airborne Research Facility) Remote Sensing instruments collected on board the British Antarctic Survey (BAS) Twin-Otter aircraft." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 144427, 144428, 144429, 144430, 144431, 144432, 144433, 144434 ], "onlineresource_set": [ 42567, 42568 ] }, { "ob_id": 32444, "uuid": "0f49c8eb20bb4a0fa20f1f1b2670ba4c", "title": "NERC-ARF Flight 2018_123 - for CA18_207: Airborne remote sensing measurements", "abstract": "Airborne remote sensing measurements collected on 03 May 2018 by the Natural Environment Research Council Airborne Research Facility (NERC-ARF) onboard the British Antarctic Survey (BAS) Twin-Otter aircraft for the NERC-ARF CA18_207 Project: Canadian Wildfire Observations with SLSTR and Aircraft. Ontario, Canada area (CA18_207) (flight reference: 2018_123). This dataset comprises: hyperspectral data collected using a Specim Aisa FENIX imager and digital photography data collected using a Leica RCD105 camera.\r\n\r\nData were collected over the Rothamsted, UK area prior to a detachment to Ontario, Canada.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-12-07T09:57:39", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by the NERC-ARF facility and deposited at the Centre for Environmental Data Analysis (CEDA) for archiving.", "removedDataReason": "", "keywords": "CA18_207, CA18/207, aircraft, hyperspectral, remote sensing, NERC-ARF, ARSF", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-04-23T11:00:06", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2749, "bboxName": "", "eastBoundLongitude": -0.3629166097637084, "westBoundLongitude": -0.39727101512377117, "southBoundLatitude": 51.80004192491934, "northBoundLatitude": 51.822618533045386 }, "verticalExtent": null, "result_field": { "ob_id": 32445, "dataPath": "/neodc/arsf/2018/CA18_207/CA18_207-2018_123_Rothamsted", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 104845641381, "numberOfFiles": 316, "fileFormat": "Hyperspectral data are ENVI binary, LiDAR data are LAS and aerial photography are TIF formats" }, "timePeriod": { "ob_id": 8913, "startTime": "2018-05-03T14:44:56", "endTime": "2018-05-03T14:56:29" }, "resultQuality": { "ob_id": 3643, "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": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32446, "uuid": "a2dc229ee8e14bb7afb812e053b8b421", "short_code": "acq", "title": "Acquisition for: NERC-ARF 2018_123 - CA18_207 Flight: Airborne remote sensing measurements", "abstract": "Acquisition for: NERC-ARF 2018_123 - CA18_207 Flight: Airborne remote sensing measurements" }, "procedureComputation": null, "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": 32374, "uuid": "a1b5bcaac129435889888fe95d6a75cd", "short_code": "proj", "title": "NERC-ARF CA18_207 Project: Canadian Wildfire Observations with SLSTR and Aircraft. Ontario, Canada area", "abstract": "Canadian Wildfire Observations with SLSTR and Aircraft: Directional Effects of Thermally Emitted Radiation and Exploration of Flaming/Smouldering Partitioning and Plume Trace Gas Emission Ratios. This project used NERC-ARF (NERC Airborne Research Facility) Remote Sensing instruments collected on board the British Antarctic Survey (BAS) Twin-Otter aircraft." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 144438, 144439, 144440, 144441, 144442, 144443, 144444, 144445 ], "onlineresource_set": [ 42569, 42570 ] }, { "ob_id": 32448, "uuid": "932bf0c7937345d7af5be9d018da2a07", "title": "NERC-ARF Flight 2018_135b - for GB18_56: Airborne remote sensing measurements", "abstract": "Airborne remote sensing measurements collected on 15 May 2018 by the Natural Environment Research Council Airborne Research Facility (NERC-ARF) onboard the British Antarctic Survey (BAS) Twin-Otter aircraft for the NERC-ARF GB18_56 Project: Methane emission sources, UK (GB18_56) (flight reference: 2018_135b). This dataset comprises: hyperspectral data collected using a Specim Aisa FENIX imager and hyperspectral data collected using a Specim Aisa OWL imager.\r\n\r\nData were collected over various locations in the UK.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2019-11-15T20:40:06", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by the NERC-ARF facility and deposited at the Centre for Environmental Data Analysis (CEDA) for archiving.", "removedDataReason": "", "keywords": "GB18_56, GB18/56, aircraft, hyperspectral, remote sensing, NERC-ARF, ARSF", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-04-23T10:59:22", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2750, "bboxName": "", "eastBoundLongitude": -0.747077943142916, "westBoundLongitude": -0.8394999872174435, "southBoundLatitude": 53.34176255807064, "northBoundLatitude": 53.43532662810588 }, "verticalExtent": null, "result_field": { "ob_id": 32449, "dataPath": "/neodc/arsf/2018/GB18_56/GB18_56-2018_135b_Methane_Sites", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 42146427847, "numberOfFiles": 219, "fileFormat": "Hyperspectral data are ENVI binary, LiDAR data are LAS and aerial photography are TIF formats" }, "timePeriod": { "ob_id": 8914, "startTime": "2018-05-15T13:02:30", "endTime": "2018-05-15T13:37:51" }, "resultQuality": { "ob_id": 3644, "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": "2021-04-15" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32450, "uuid": "e3a576bd97af4abf9f1d6d499afee38d", "short_code": "acq", "title": "Acquisition for: NERC-ARF 2018_135b - GB18_56 Flight: Airborne remote sensing measurements", "abstract": "" }, "procedureComputation": null, "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": 32421, "uuid": "69f391cc3607494a8cf77f630b0ddb2d", "short_code": "proj", "title": "NERC-ARF GB18_56 Project: Methane emission sources, UK", "abstract": "The aim of this project was to investigate well-defined local methane emission sources in the UK to apply and evaluate the hyperspectral processing method currently developed at the University of Leicester.\r\n\r\nThis project used NERC-ARF (NERC Airborne Research Facility) Remote Sensing instruments collected on board the British Antarctic Survey (BAS) Twin-Otter aircraft." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 144448, 144449, 144450, 144451, 144452, 144453, 144454, 144455 ], "onlineresource_set": [ 42571, 42572 ] }, { "ob_id": 32454, "uuid": "1c9d56f23b134c75963a1d85b059059c", "title": "QA4ECV spectral albedo", "abstract": "The QA4ECV Spectral Albedo product produced by UCL (MSSL and Geography) and Brockmann Consult has achieved an Advanced status for the Product details and Traceability chain; Intermediate status for Assessment against Standards; and Basic status for Quality Flags, uncertainty assessment, and validation.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-11-22T13:40:30", "updateFrequency": "notPlanned", "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "QA4ECV, Albedo", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 32453, "dataPath": "/neodc/qa4ecv/data/spectral_albedo", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 44329193570, "numberOfFiles": 2927, "fileFormat": "These data are provided in netCDF file format." }, "timePeriod": null, "resultQuality": { "ob_id": 3645, "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": "2021-04-22" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [], "permissions": [ { "ob_id": 2528, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 8, "licenceURL": "http://creativecommons.org/licenses/by/4.0/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [], "inspireTheme": [], "topicCategory": [], "phenomena": [ 50415, 50417, 50512, 57665, 57666, 57667, 57668, 57669, 57670, 57671, 57672, 57673, 57674, 57675, 57676, 57677, 57678, 57679, 57680, 57681, 57682, 57683, 57684, 57685, 57686, 57687, 57688, 57689, 57690, 57691, 57692, 57693 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 144459, 144460, 144461, 144462, 144463, 144464, 147573 ], "onlineresource_set": [] }, { "ob_id": 32458, "uuid": "ed1bc64e34a14ca28fedd2731735d18a", "title": "OpenIFS@home: ensemble of forecast simulations from Ex-tropical cyclone Karl case study", "abstract": "This dataset contains the 2000-member original validation test case for OpenIFS@home as presented in Sparrow et al 2021, GMD.\r\n\r\nThese are results from an ensemble of forecast simulations of the tropical cyclone Karl from September 2016, studied during the NAWDEX field campaign. This cyclone underwent extratropical transition and intensified in mid-latitudes to give rise to an intense jet-streak near Scotland and heavy rainfall over Norway.\r\n\r\nThe OpenIFS@Home data comprises output from the European Centre for Medium Range Weather Forecasts (ECMWF) OpenIFS model run under the BOINC framework and managed by http://climateprediction.net/ at the University of Oxford. OpenIFS is derived from ECMWF's IFS operational forecast model. The dataset consists of a 2000 member ensemble of the ECMWF OpenIFS cycle 40 release 1 model, run on the OpenIFS@home volunteer framework. The spatial resolution of the dataset is approximately 125km at the equator (corresponding to a spectral resolution of T159) with 60 vertical levels\r\n\r\nThe model output data format is WMO GRIB. Single level parameters and surface fields use GRIB-1 format whilst multi-level upper air fields use GRIB-2 format\r\n\r\nTo work with GRIB files requires the ECMWF ecCodes package. This software provides command line tools for linux/macOS for inspecting the contents of these files, such as listing parameters and meta-information\r\n\r\nThe model output files are on the native IFS grid, the so-called reduced Gaussian grid, rather than a regular latitude-longitude grid commonly used in plotting. The ECMWF metview application can be used to produce plots directly from the model output files without the need to interpolate first. Other applications exist, such as the Climate Data Operators (CDO) that can be used to first convert the GRIB model output files to netCDF for use in other plotting packages. \r\n\r\nThe data is arranged into subdirectories (one per ensemble member), each containing a zip file of the output GRIB data for that simulation. These follow the standard OpenIFS output format and represent 6 hourly snapshots throughout the forecast. The number in the filename denotes the hour of the forecast contained in each respective GRIB file", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-04-30T10:34:11", "updateFrequency": "notPlanned", "dataLineage": "Data were generated using ECMWF OpenIFS deployed under the CPDN distributed computing framework and then passed on to the Centre for Environmental Data (CEDA) for archiving.", "removedDataReason": "", "keywords": "OpenIFS@home, cyclone, Karl", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-05-24T09:30:32", "doiPublishedTime": "2021-05-24T11:26:49.891857", "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": 32459, "dataPath": "/badc/openifs_at_home/data/tc_karl/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 132390667932, "numberOfFiles": 1969, "fileFormat": "Data are WMO GRIB formatted." }, "timePeriod": { "ob_id": 8917, "startTime": "2016-09-25T00:00:00", "endTime": "2016-10-01T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32461, "uuid": "692a4500a73c4355868b72da0dd0c1a1", "short_code": "comp", "title": "ECMWF OpenIFS model deployed on unknown computer", "abstract": "ECMWF OpenIFS model deployed on unknown computer" }, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2526, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 32468, "uuid": "be3b9f0e861b4380b4b8ae8f78e796aa", "short_code": "proj", "title": "OpenIFS@home", "abstract": "OpenIFShome brings together two powerful tools: OpenIFS, an easy-to-use, supported version of ECMWF’s Integrated Forecasting System (IFS) widely used in research and education; and Climateprediction.net (CPDN) at the University of Oxford, a highly successful volunteer computing project that has been running since 2003.\r\n\r\nWeather forecasting requires powerful computer systems and state-of-the-art computer models. The European Centre for Medium-Range Weather Forecasts’ Integrated Forecast System (IFS) is one of the world’s leading weather forecasting models. A version of their model, OpenIFS, is available to universities and research institutes for teaching and research. As well as producing a 10-day weather forecast from the best estimate of the current weather, a large number of slightly different forecast scenarios, known as an ensemble, are created to allow a measure of certainty on the forecast to be provided.\r\n\r\nThrough OpenIFS@home it is now possible to run a slightly different weather forecast on many hundreds or thousands of volunteer computers, making it possible to ask questions such as how predictable certain events are, particularly damaging extreme events such as intense rain or wind. The OpenIFS@Home facility offers researchers a new tool to study weather forecasts and related questions" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [ 10891 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 144495, 144496, 144497, 144498, 144499, 144500, 144502, 144503, 144504, 144505, 144506, 144507, 144508, 144509, 144510 ], "onlineresource_set": [ 42578, 42579, 42580, 42581, 42582, 42583 ] }, { "ob_id": 32464, "uuid": "5565b28f7da0402ca12e20ae9a9e7c24", "title": "Indoor air population study: Volatile Organic Compounds (VOC) concentrations", "abstract": "This dataset contains Volatile Organic Compounds (VOC) concentrations taken from a large, population-scale study, which was conducted for a total of 19 weeks during the winter and summer of 2019. VOC concentration data were collected for 39 VOC species across 60 houses in Ashford, United Kingdom. Samples were collected in evacuated stainless-steel canisters over 72 hours using restricted flow inlets. A number of houses were randomly selected to also collect an outdoor sample. Each household, per campaign, was associated with at least three canister IDs and some with an additional outdoor sample. \r\n\r\nThis dataset contains information on all VOCs collected, listing in which season each sample was taken, the associated canister ID and the analytical instrument with which each VOC was measured. Household, demographic, and product use information is available, as is a logbook outlining further sample information.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-04-28T11:26:54", "updateFrequency": "", "dataLineage": "Data were collected by the University of York in collaboration with Givaudan UK, who provided a cohort of study participants and aided in survey design. Data were then sent for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "NERC, indoor, VOC, population", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2022-01-18T16:30:07", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2751, "bboxName": "", "eastBoundLongitude": 30.06, "westBoundLongitude": 0.52, "southBoundLatitude": 47.27, "northBoundLatitude": 51.8 }, "verticalExtent": null, "result_field": { "ob_id": 32462, "dataPath": "/badc/deposited2021/population_study_indoor_air_19/data/v1/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 918471, "numberOfFiles": 8, "fileFormat": "Data are BADC CSV formatted." }, "timePeriod": { "ob_id": 8918, "startTime": "2019-02-11T00:00:00", "endTime": "2019-09-25T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32463, "uuid": "0139762429424deab7851a48a4f34931", "short_code": "acq", "title": "Indoor air population study: Volatile Organic Compounds (VOC) concentrations", "abstract": "Indoor air population study: Volatile Organic Compounds (VOC) concentrations" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2526, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [], "inspireTheme": [], "topicCategory": [], "phenomena": [ 46622, 46623, 46624, 46625, 46626, 46627, 46628, 46629, 46630, 46631, 46632, 46633, 46634, 46635, 46636, 46637, 46638, 46639, 46640, 46641, 46642, 46643, 46644, 46645, 46646, 46647, 46648, 46649, 46650, 46651, 46652, 46653, 46654, 46655, 46656, 46657, 46658, 46659, 46660, 46661, 46662, 46663, 46664, 46665, 46666, 46667 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 144512, 144513, 144514, 144515, 144516, 144517, 144519, 144518, 144520, 144521, 144522, 144523, 144524, 144525 ], "onlineresource_set": [] }, { "ob_id": 32469, "uuid": "9314b7b6417049beb18570632b435e5b", "title": "SG-WEx: Unified Model output for January 2015 over South Georgia, without island orography (run: u-ag706)", "abstract": "This dataset contains modelling output from the u-ag706 run of a high-resolution (1.5 km horizontal grid, 118 vertical levels up to around 75 km altitude, 30 s timestep) local-area configuration of the Met Office Unified Model run in a box over the island of South Georgia (54S, 36W), as part of the South Georgia Wave Experiment (SG-WEx) project. This run was for the time period January 2015 with a flat orography file for the island. See related dataset for output from a complementary run with the island's orography included for the same time period. These were part of a group of 6 model runs for the SG-WEx project.\r\n\r\nThe aim of the modelling runs was to examine gravity wave generation and deep vertical propagation over this mountainous island. Three model time periods are archived within the SG-WEx dataset collection: January 2015, June 2015 and July 2015, each containing two runs, one including the island's orography and one without. Initial and boundary conditions are supplied by a global forecast to ensure that conditions over the island remain realistic. Meteorological fields such as wind, temperature, pressure etc were outputted and saved in hourly steps. These runs also coincided with radiosonde campaigns launched from the island.\r\n\r\nTechnical details regarding the configuration of these runs is described Vosper (2015, doi:10.1002/qj.2566). Further information and science results can be found in Jackson et al. (2018, doi:10.1175/BAMS-D-16-0151.1) and Hindley (2021, doi:10.5194/acp-21-7695-2021). See online resources linked to this record for further details.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-05-07T16:32:42", "updateFrequency": "notPlanned", "dataLineage": "Data were produced from runs of the Met Office Unified Model on the Met Office system and provided to the Centre for Environmental Data Analysis (CEDA) for long-term archiving.", "removedDataReason": "", "keywords": "Unified Model, NWP, South Atlantic", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "final", "dataPublishedTime": "2021-05-11T08:42:08", "doiPublishedTime": "2021-05-12T16:00:00", "removedDataTime": null, "geographicExtent": { "ob_id": 2752, "bboxName": "SG-WEx local-area model domain", "eastBoundLongitude": -26.879, "westBoundLongitude": -47.373, "southBoundLatitude": -58.162, "northBoundLatitude": -50.162 }, "verticalExtent": { "ob_id": 25, "highestLevelBound": 32767.0, "lowestLevelBound": 0.0, "units": "m" }, "result_field": { "ob_id": 32575, "dataPath": "/badc/sg-wex/data/um-data/sgwex_Jan2015_nSG_u-ag706", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1444719255896, "numberOfFiles": 1168, "fileFormat": "Data are netCDF formatted." }, "timePeriod": { "ob_id": 8941, "startTime": "2015-01-09T13:00:00", "endTime": "2015-01-31T12:00:00" }, "resultQuality": { "ob_id": 3287, "explanation": "No quality control information has been provided for these data by the data provider, nor has any been undertaken by the data centre.", "passesTest": true, "resultTitle": "CEDA: No provider or CEDA QC done statement", "date": "2019-06-03" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32587, "uuid": "da680a867c1e4ddba41bd06f8a4784b0", "short_code": "comp", "title": "Met Office Unified Model United Kingdom Variable resolution (UKV) version 8.5, run u-ag706", "abstract": "Run u-ag706 of a high-resolution (1.5 km horizontal grid, 118 vertical levels up to around 75 km altitude, 30 s timestep) local-area configuration of the United Kingdom Variable resolution (UKV) version 8.5 model run in a box over the island of South Georgia (54S, 36W), as part of the South Georgia Wave Experiment (SG-WEx) project. This run was for the time period January 2015 with a flat orography file for the island. See related dataset for output from a complementary run with the island's orography included for the same time period. These were part of a group of 6 model runs for the SG-WEx project.\r\n\r\nTechnical details regarding the configuration of these runs follow those described in Vosper (2015, doi:10.1002/qj.2566) - see online resources linked to this record." }, "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": 26590, "uuid": "202c185a201645ad86f06bfa834f1fca", "short_code": "proj", "title": "The South Georgia Wave Experiment (SG-WEX)", "abstract": "Gravity waves are an important type of atmospheric wave. They play a key role in many atmospheric processes, ranging from convection to the mixing of chemical species to influencing the global-scale circulation of the stratosphere and mesosphere. Because of this, it is essential to represent their effects in numerical weather prediction and climate models.\r\n\r\nGravity waves are generated by sources including winds blowing over mountains, jet-stream instabilities and strong convection. The waves can transport energy and momentum away from these sources and deposit them at greater heights, thus exerting a significant \"drag\" on the circulation and so coupling together different layers of the atmosphere. \r\n\r\nRecent studies have shown that isolated mountainous islands in regions of strong winds can be intense sources of gravity waves that can have climatologically-significant effects on atmospheric circulation. However, most climate and numerical weather prediction models cannot accurately model waves from such small, intense island sources because the islands are too small compared to the resolution of the models - this is the \"small island problem\". \r\n\r\nThe South Geogia -Wave EXperiment (SG-WEX), was a NERC funded project (grant awards NE/K015117/1, NE/K012614/1 and NE/K012584/1) proposed a major coordinated observational and modelling experiment to determine the nature and impacts of gravity waves generated by the most important of all these islands, South Georgia in the Southern Atlantic. \r\n\r\nThe SG-WEx project sought to answer the following questions:\r\n\r\n1. What is the nature of gravity waves generated by South Georgia and what is their variability?\r\n\r\n2. What is the contribution of these gravity waves to the total field of gravity waves over the South Atlantic?\r\n\r\n3. What is the influence of gravity waves from South Georgia on the mesosphere?\r\n\r\n4. How can these observations be used to improve gravity-wave parametrizations in models?\r\n\r\n5. How important is South Georgia in comparison to other gravity-wave sources and how does it impact local winds and the development of synoptic systems?\r\n\r\nTo answer these questions the project made measurements of gravity waves over and around South Georgia in two radiosondes campaigns in which meteorological balloons were launched from South Georgia. The observations were then placed in context with measurements made by satellite across the whole South Atlantic. Significantly, the project also deploy the first atmospheric radar on South Georgia - a meteor radar that making the first ever measurements of gravity waves (and winds, tides and large-scale planetary waves) in the mesosphere over South Georgia at heights of 80 - 100 km.\r\n\r\nThese experimental results were then complemented by a programme of modelling work that explored the propagation of gravity waves away from their sources. The observations will be used to help guide the development of new, improved, mathematical representations of gravity waves (so-called \"parametrizations\") allowing such islands to be better represented in the Met Office's Unified Model used for numerical weather prediction and climate studies. Finally, modelling studies integrated these studies and determine the relative importance of South Georgia compared to other waves sources and investigate the impact of Gravity waves from South Georgia on local winds and the development of synoptic (weather) systems.\r\n\r\nObjectives: \r\nThe primary academic beneficiaries will be the community of atmospheric scientists who have interests in the structure and dynamics of the middle atmosphere and in understanding how it is coupled to the underlying troposphere.\r\n\r\nNumerical Weather Prediction (NWP) and climate models all rely on parametrizations of gravity waves to produce realistic middle atmospheres. The project's results will help constrain such parametrizations and thus will thus also be of interest to these communities of scientists - including those meteorologists working with NWP models. This work will thus contribute to the broader activities of weather prediction and climate-change prediction which benefits society at large." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 1314, 6913, 6925, 6982, 7012, 7014, 7015, 11281, 11282, 13296, 13818, 20748, 20749, 20758, 21072, 21073, 21074, 21078, 21080, 21081, 21086, 21093, 21094, 21095, 21096, 30118, 30124, 30126, 30127, 33910, 33911, 33912, 33913, 33914, 33915, 33916, 33917, 33918, 33919, 33920, 33921, 33922, 33923, 33924, 33925, 33926, 33927, 33928 ], "vocabularyKeywords": [], "identifier_set": [ 10878 ], "observationcollection_set": [ { "ob_id": 29893, "uuid": "585b29ba4a054760ac4e53e7d95290b9", "short_code": "coll", "title": "SG-WEx: a collection of meteor radar observations, radiosondes and numerical modelling output over South Georgia", "abstract": "The NERC-funded South Georgia Wave EXperiment (SG-WEx) project (grant numbers NE/K015117/1, NE/K012614/1 and NE/K012584/1) was a major coordinated observational and modelling campaign to study the nature and deep vertical propagation of atmospheric gravity waves over the mountainous island of South Georgia in the Southern Atlantic.\r\n\r\nThis dataset collection contains meteor radar and radiosonde measurements from King Edward Point Magnetic Observatory on South Georgia and output from high-resolution (1.5km grid, 118 vertical levels) Met Office Unified Model simulations in a box 1200km x 900km centred on the island that coincide with the radiosonde campaigns.\r\n\r\nThe meteor radar observations included in this collection are continuous from February 2016 to November 2020, funding for which was continued as part of the follow-on NERC DRAGON-WEx project (NE/R001391/1,NE/R001235/1).\r\n\r\nThe project also made use of 3rd party satellite data from NASA, not included in this collection." } ], "responsiblepartyinfo_set": [ 144537, 144538, 144539, 144540, 144541, 144542, 144543, 144544, 145020, 144545, 144546, 144547, 144548 ], "onlineresource_set": [ 42666, 42664, 42665, 91229, 91230, 91231, 91232, 91233, 91234 ] }, { "ob_id": 32470, "uuid": "fe3cb5120fa74fa7974820c2e2a238a7", "title": "Global Ocean Lagrangian Trajectories based on AVISO velocities, v2.0, 1998-2018", "abstract": "The National Centre for Earth Observation (NCEO) Long Term Science Single Centre (LTSS) Global Ocean Lagrangian Trajectories (OLTraj) provides 30-day forward and backward Lagrangian trajectories based on AVISO (Satellite Altimetry Data project) surface velocities. Each trajectory represents the path that a water mass would move along starting at a given pixel and a given day. OLTraj can be thus used to implement analyses of oceanic data in a Lagrangian framework. The purpose of OLTraj is to allow non-specialists to conduct Lagrangian analyses of surface ocean data.\r\n\r\nThe dataset has global coverage and spans 1998-2018 with a daily temporal resolution. The trajectories were generated starting from zonal and meridional model velocity fields that were integrated using the LAMTA (6-hour time step - part of ) as described in Nencioli et al., 2018 and SPASSO (Software package for and adaptive satellite-based sampling for ocean graphic cruises containing LAMTA) software user guide. Please see the documentation section below for further information.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2024-03-09T03:17:45", "updateFrequency": "", "dataLineage": "Data were produced by the NCEO Plymouth Marine Laboratory project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "AVISO, Global, Ocean Lagrangian Trajectories, LAMTA, zonal, meridional model, OLTraj_SEALEVEL_GLO_PHY_L4_REP_OBSERVATIONS_008_047", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-05-06T09:35:10", "doiPublishedTime": "2021-05-10T15:47:54", "removedDataTime": null, "geographicExtent": { "ob_id": 2687, "bboxName": "OLTraj", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 32471, "dataPath": "/neodc/oltraj/data/v2.0", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1789609906795, "numberOfFiles": 8401, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 8690, "startTime": "1998-01-01T00:00:00", "endTime": "2018-11-25T00:00:00" }, "resultQuality": { "ob_id": 3652, "explanation": "Validated by Plymouth Marine Laboratory Science Team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-30" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32472, "uuid": "0bfc6301e7c1413da71093e853b03f83", "short_code": "comp", "title": "NCEO OLTraj V2.0", "abstract": "The trajectories were generated starting from zonal and meridional model velocity fields from the AVISO project; please see the Global ocean gridded L4 sea surface heights and derived variables reprocessed reference in the documentation section for more details on the dataset. The output of which was integrated using the LAMTA package (6-hour time step) as previously described in Nencioli et al., 2018 (also available in the documentation section)." }, "procedureCompositeProcess": null, "imageDetails": [ 130 ], "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": 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": [ 4385, 18405, 18408, 30129, 30130 ], "vocabularyKeywords": [], "identifier_set": [ 10866 ], "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": [ 144554, 144556, 144549, 144550, 144551, 144552, 144553, 144555, 144557 ], "onlineresource_set": [ 42596, 42598, 42602, 42603, 94676, 94677 ] }, { "ob_id": 32473, "uuid": "c58391ab280746b186d2aa6f3adcc0c7", "title": "BAS-MASIN flight 292 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 292 on 28 February 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project. This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-09-02T14:34:42", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by British Antarctic Survey (BAS) and a quality-controlled revision of the data was generated at UEA.", "removedDataReason": "", "keywords": "IGP, AFIS, aircraft, meteorology, BAS, MASIN, twin-otter", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-05-07T10:52:02", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2753, "bboxName": "", "eastBoundLongitude": -18.069944381713867, "westBoundLongitude": -21.882347106933594, "southBoundLatitude": 65.64600372314453, "northBoundLatitude": 69.43681335449219 }, "verticalExtent": null, "result_field": { "ob_id": 32474, "dataPath": "/badc/igp/data/twinotter/flight292_20180228", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 71216690, "numberOfFiles": 3, "fileFormat": "MASIN data are in NetCDF format" }, "timePeriod": { "ob_id": 8919, "startTime": "2018-02-28T07:34:09", "endTime": "2018-02-28T11:51:10" }, "resultQuality": { "ob_id": 3653, "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": "2021-04-30" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32486, "uuid": "b365026a1bc5474586156232f2d694f6", "short_code": "acq", "title": "Acquisition for: BAS-MASIN flight 292 core meteorological data from the Iceland Greenland Seas Project (IGP)", "abstract": "Acquisition for: BAS-MASIN flight 292 core meteorological data from the Iceland Greenland Seas Project (IGP)" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 24899, "uuid": "2780d047461c42f0a12534ccf42f487a", "short_code": "proj", "title": "Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)", "abstract": "The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel) were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes. \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function. In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 33929, 33930, 33931, 33932, 33933, 33934, 33935, 33936, 33937, 33938, 33939, 33940, 33941, 33942, 33943, 33944, 33945, 33946, 33947, 33948, 33949, 33950, 33951 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 27445, "uuid": "b3e807b8df824a8ca83468ce2e5b54e5", "short_code": "coll", "title": "In situ observations of air-sea interaction processes from the Iceland Greenland seas Project (IGP)", "abstract": "This collection contains a range of in situ observations of meteorological and air-sea interaction processes from a range of instruments on several platforms (buoy, ship , radiosonde) from the Iceland Greenland seas Project (IGP). \r\n\r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US and Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)" }, { "ob_id": 7571, "uuid": "8be3dd7cdf44090d89aeb8f105421506", "short_code": "coll", "title": "BAS Masin Twin-Otter aircraft data", "abstract": "Data is collected on board the British Antarctic Survey MASIN Twin Otter aircraft for a range of projects in the Antarctic and at other locations. These projects include atmospheric, boundary layer and cloud/aerosol studies.\r\n\r\n\r\nThe instrument suite includes standard temperature and water vapour sensors as well as a turbulence probe allowing full atmospheric profile measurements of temperature, dew point and winds. A DMT Cloud and aerosol spectrometer (CAPS) probe is used for cloud studies and a closed path Licor H2O/CO2 instrument, Grimm optical particle counter and cloud condensation nuclei counter are fed from simple Rosemount inlets." } ], "responsiblepartyinfo_set": [ 144559, 144560, 144561, 144562, 144563, 144564, 144565, 144566, 144567, 144568, 144766, 144767 ], "onlineresource_set": [ 42599 ] }, { "ob_id": 32478, "uuid": "4c506d968f40478382dcc2f5b9f073fc", "title": "BAS-MASIN flight 293 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 293 on 01 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project.\r\n\r\nThis dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA).\r\nData were collected over the Iceland and Greenland Sea area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T13:05:32", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by British Antarctic Survey (BAS) and a quality-controlled revision of the data was generated at UEA.", "removedDataReason": "", "keywords": "IGP, AFIS, aircraft, meteorology, BAS, MASIN, twin-otter", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-05-07T10:57:09", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2754, "bboxName": "", "eastBoundLongitude": -17.456592559814453, "westBoundLongitude": -22.173479080200195, "southBoundLatitude": 65.64640808105469, "northBoundLatitude": 70.47631072998047 }, "verticalExtent": null, "result_field": { "ob_id": 32479, "dataPath": "/badc/igp/data/twinotter/flight293_20180301", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 62041090, "numberOfFiles": 3, "fileFormat": "MASIN data are in NetCDF format" }, "timePeriod": { "ob_id": 8920, "startTime": "2018-03-01T08:02:05", "endTime": "2018-03-01T11:45:16" }, "resultQuality": { "ob_id": 3654, "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": "2021-04-30" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32480, "uuid": "55ed39ad593e49e3a21da8c32c6f6eaa", "short_code": "acq", "title": "Acquisition for: BAS-MASIN flight 293 core meteorological data from the Iceland Greenland Seas Project (IGP)", "abstract": "Acquisition for: BAS-MASIN flight 293 core meteorological data from the Iceland Greenland Seas Project (IGP)" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 24899, "uuid": "2780d047461c42f0a12534ccf42f487a", "short_code": "proj", "title": "Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)", "abstract": "The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel) were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes. \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function. In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 61212, 61213, 61214, 61215, 61216, 61217, 61218, 61219, 61220, 61222, 61223, 61224, 61225, 61226, 61227, 61228, 61229, 61230, 61231, 61232, 61233, 74368, 74369 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 27445, "uuid": "b3e807b8df824a8ca83468ce2e5b54e5", "short_code": "coll", "title": "In situ observations of air-sea interaction processes from the Iceland Greenland seas Project (IGP)", "abstract": "This collection contains a range of in situ observations of meteorological and air-sea interaction processes from a range of instruments on several platforms (buoy, ship , radiosonde) from the Iceland Greenland seas Project (IGP). \r\n\r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US and Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)" }, { "ob_id": 7571, "uuid": "8be3dd7cdf44090d89aeb8f105421506", "short_code": "coll", "title": "BAS Masin Twin-Otter aircraft data", "abstract": "Data is collected on board the British Antarctic Survey MASIN Twin Otter aircraft for a range of projects in the Antarctic and at other locations. These projects include atmospheric, boundary layer and cloud/aerosol studies.\r\n\r\n\r\nThe instrument suite includes standard temperature and water vapour sensors as well as a turbulence probe allowing full atmospheric profile measurements of temperature, dew point and winds. A DMT Cloud and aerosol spectrometer (CAPS) probe is used for cloud studies and a closed path Licor H2O/CO2 instrument, Grimm optical particle counter and cloud condensation nuclei counter are fed from simple Rosemount inlets." } ], "responsiblepartyinfo_set": [ 144572, 144573, 144574, 144575, 144576, 144577, 144578, 144579, 144580, 144581, 144771, 144772 ], "onlineresource_set": [ 42600 ] }, { "ob_id": 32482, "uuid": "59e9e7ae4f9040d38d9f203a4aae96e2", "title": "BAS-MASIN flight 294 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 294 on 01 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project.\r\nThis dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA).\r\nData were collected over the Iceland and Greenland Sea area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-09-02T15:35:18", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by British Antarctic Survey (BAS) and a quality-controlled revision of the data was generated at UEA.", "removedDataReason": "", "keywords": "IGP, AFIS, aircraft, meteorology, BAS, MASIN, twin-otter", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-05-07T11:00:56", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2755, "bboxName": "", "eastBoundLongitude": -15.936248779296875, "westBoundLongitude": -22.6532039642334, "southBoundLatitude": 66.00090026855469, "northBoundLatitude": 70.74533081054688 }, "verticalExtent": null, "result_field": { "ob_id": 32483, "dataPath": "/badc/igp/data/twinotter/flight294_20180301", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 83633130, "numberOfFiles": 3, "fileFormat": "MASIN data are in NetCDF format" }, "timePeriod": { "ob_id": 8921, "startTime": "2018-03-01T12:59:15", "endTime": "2018-03-01T18:02:03" }, "resultQuality": { "ob_id": 3655, "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": "2021-04-30" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32484, "uuid": "96ca2a8811f945e28afa6c24367aed7c", "short_code": "acq", "title": "Acquisition for: BAS-MASIN flight 294 core meteorological data from the Iceland Greenland Seas Project (IGP)", "abstract": "" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 24899, "uuid": "2780d047461c42f0a12534ccf42f487a", "short_code": "proj", "title": "Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)", "abstract": "The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel) were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes. \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function. In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 61212, 61213, 61214, 61215, 61216, 61217, 61218, 61219, 61220, 61222, 61223, 61224, 61225, 61226, 61227, 61228, 61229, 61230, 61231, 61232, 61233, 74368, 74369 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 27445, "uuid": "b3e807b8df824a8ca83468ce2e5b54e5", "short_code": "coll", "title": "In situ observations of air-sea interaction processes from the Iceland Greenland seas Project (IGP)", "abstract": "This collection contains a range of in situ observations of meteorological and air-sea interaction processes from a range of instruments on several platforms (buoy, ship , radiosonde) from the Iceland Greenland seas Project (IGP). \r\n\r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US and Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)" }, { "ob_id": 7571, "uuid": "8be3dd7cdf44090d89aeb8f105421506", "short_code": "coll", "title": "BAS Masin Twin-Otter aircraft data", "abstract": "Data is collected on board the British Antarctic Survey MASIN Twin Otter aircraft for a range of projects in the Antarctic and at other locations. These projects include atmospheric, boundary layer and cloud/aerosol studies.\r\n\r\n\r\nThe instrument suite includes standard temperature and water vapour sensors as well as a turbulence probe allowing full atmospheric profile measurements of temperature, dew point and winds. A DMT Cloud and aerosol spectrometer (CAPS) probe is used for cloud studies and a closed path Licor H2O/CO2 instrument, Grimm optical particle counter and cloud condensation nuclei counter are fed from simple Rosemount inlets." } ], "responsiblepartyinfo_set": [ 144585, 144586, 144587, 144588, 144589, 144590, 144591, 144592, 144593, 144594, 144797, 144798 ], "onlineresource_set": [ 42601 ] }, { "ob_id": 32487, "uuid": "5631c55a2caa4cd2bcdf1bf75365bcc8", "title": "APHH: High Resolution Time of Flight Mass Spectrometer measurements made at the Indira Gandhi Delhi Technical University for Women (IGDTUW) site during the DelhiFlux field campaigns", "abstract": "This dataset contains Organic aerosols, NO3-, SO4=, Cl- and NH4+ submicron concentrations in µg m-3 measured with High Resolution Time of Flight Aerosol Mass Spectrometer (HR-ToF-AMS) and Organic aerosol factors (Cooking Organic Aerosol (COA), Nitrogen-rich Hydrocarbon-like Organic Aerosol (NHOA), Solid-Fuel Organic Aerosol (SFOA), Hydrocarbon-like Organic Aerosol (HOA), Semi-Volatility Biomass Burning Organic Aerosol (SVBBOA), Low-Volatility Oxygenated Organic Aerosol (LVOOA), Semi-Volatility Oxygenated Organic Aerosol (SVOOA)) identified using positive matrix factorization. The instrument was located at the Indira Gandhi Delhi Technical University for Women (IGDTUW) from May to Nov 2018. The instrument sampled initially at 7 m above ground level, then was moved to 35 m above ground on the 5th of November 2018.\r\n\r\nThe data were collected as part of the DelhiFlux project under the Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme, and the UKCEH’s SUNRISE programme delivering National Capability to NERC.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T13:05:48", "updateFrequency": "notPlanned", "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "APHH, Delhi, HOA, LVOOA, BBOA, COA and SVOOA", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-06-29T15:27:43", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2310, "bboxName": "Delhi for APHH", "eastBoundLongitude": 77.4, "westBoundLongitude": 77.0, "southBoundLatitude": 28.4, "northBoundLatitude": 28.8 }, "verticalExtent": null, "result_field": { "ob_id": 32488, "dataPath": "/badc/aphh/data/delhi/delhiflux/ceh-hr-tof-ams/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2581629, "numberOfFiles": 3, "fileFormat": "Data are NASA Ames formatted." }, "timePeriod": { "ob_id": 8922, "startTime": "2018-05-26T00:00:00", "endTime": "2018-11-23T23:59:59" }, "resultQuality": { "ob_id": 3656, "explanation": "Data are as given by the data provider with quality control flags defined within each file. No quality control has been performed by the Centre for Environmental Data Analysis (CEDA)", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-05-05" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32490, "uuid": "5652fbfd1c7447fc8ca115a6cf422971", "short_code": "acq", "title": "APHH: High Resolution Time of Flight Mass Spectrometer measurements made at the Indira Gandhi Delhi Technical University for Women (IGDTUW) site during the DelhiFlux field campaigns", "abstract": "APHH: High Resolution Time of Flight Mass Spectrometer measurements made at the Indira Gandhi Delhi Technical University for Women (IGDTUW) site during the DelhiFlux field campaigns" }, "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": 24808, "uuid": "7ed9d8a288814b8b85433b0d3fec0300", "short_code": "proj", "title": "Atmospheric Pollution & Human Health in a Developing Megacity (APHH)", "abstract": "The Atmospheric Pollution & Human Health in a Developing Megacity (APHH) programme has two separate streams of activity looking at urban air pollution and its impact on Health in Chinese and Indian Megacities. The programme is a collaboration between NERC, the Medical Research Council (MRC) in the UK and the National Natural Science Foundation of China (NSFC) in China, and the Ministry of Earth Sciences (MoES) and Department of Biotechnology (DBT) in India." }, { "ob_id": 30221, "uuid": "ba27c1c6a03b450e9269f668566658ec", "short_code": "proj", "title": "(APHH India) Megacity Delhi atmospheric emission quantification, assessment and impacts (DelhiFlux)", "abstract": "The project, part of the Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme, has four specific objectives:\r\n\r\nTo improve the emission factor database for key source types and compounds in Delhi through a combination of lab and field based emission factor measurements, using harmonised instrumentation.\r\nPrerequisite\r\n\r\nTo compile a state-of-the-art emission inventory for the greater Delhi area at a spatial resolution of (1.6 km)2, together with temporal profiles of the diurnal and seasonal variability.\r\nTo inform and evaluate this emission inventory through direct and independent emission flux measurements at the urban scale (~10 km2).\r\nTo apply atmospheric transport modelling to assess the performance of the emission inventory against concentration measurements and quantify the implications of the emissions improvements for air quality indicators.\r\n\r\nGrant Ref: NE/P016472/1" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 67711 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 32625, "uuid": "04f9006457e54c49b628913912827ad7", "short_code": "coll", "title": "(APHH India) Megacity Delhi atmospheric emission quantification, assessment and impacts (DelhiFlux): Air quality measurements", "abstract": "This dataset collection contains air quality data from the Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme 'Megacity Delhi atmospheric emission quantification, assessment and impacts (DelhiFlux)'." } ], "responsiblepartyinfo_set": [ 144653, 144654, 144655, 144656, 144657, 144658, 144659, 144652, 144662, 144663, 144664 ], "onlineresource_set": [ 42604 ] }, { "ob_id": 32504, "uuid": "723f7b8c12b046de94436f74c6d260cc", "title": "Air quality and meteorological measurements taken from Guangzhou Institute of Geochemistry (GIG), China (31/07/2019 -31/12/2019)", "abstract": "This dataset contains ozone, NO, NO2, NOX, SO2 and PM2.5 air quality and meteorological measurements from two campaigns undertaken in Guangzhou, China in 2019. NO, NO2 and NOX were measured by Chemiluminescence with a Thermo scientific 42i-TL. Ozone were measured via UV with a Thermo scientific 49i. PM2.5 were measured by a continuous particulate monitor (BAM-1020, Met One instruments Inc). SO2 were measured via Pulsed fluorescence with a Thermo scientific 43i-TLE. \r\nThis data were collected as part of the NERC project Investigating the large source of particulate mass from nitrophenols observed in Beijing during winter haze events (NITRO-PM).", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T03:14:26", "updateFrequency": "notPlanned", "dataLineage": "Data were collected, quality controlled and prepared for archiving by the instrument scientists before upload to the Centre for Environmental Data Analysis (CEDA) for long term archiving.", "removedDataReason": "", "keywords": "NO, NO2, NOX, SO2, PM2.5, air quality, meteorology, China", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-06-09T15:47:46", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2762, "bboxName": "Guangzhou Institute of Geochemistry, Chi", "eastBoundLongitude": 113.447, "westBoundLongitude": 113.447, "southBoundLatitude": 23.162, "northBoundLatitude": 23.162 }, "verticalExtent": null, "result_field": { "ob_id": 32505, "dataPath": "/badc/deposited2021/nitro-pm/data/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 13933932, "numberOfFiles": 3, "fileFormat": "Data are NASA-Ames formatted" }, "timePeriod": { "ob_id": 8929, "startTime": "2019-07-31T00:00:00", "endTime": "2019-12-31T00:00:00" }, "resultQuality": { "ob_id": 3663, "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": "2021-05-05" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32507, "uuid": "ff7b13190810488db4cb15cee34b0038", "short_code": "acq", "title": "Acquisition for: Air quality and meteorological measurements taken from Guangzhou Institute of Geochemistry (GIG), China (31/07/2019 -31/12/2019)", "abstract": "Acquisition for: Air quality and meteorological measurements taken from Guangzhou Institute of Geochemistry (GIG), China (31/07/2019 -31/12/2019)" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2526, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 32506, "uuid": "0de645442b7d48d5b295941ba23f5705", "short_code": "proj", "title": "Investigating the large source of particulate mass from nitrophenols observed in Beijing during winter haze events (NITRO-PM)", "abstract": "Add info" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 46836, 46837, 46838, 46839, 46840, 46841, 46842, 46843, 46844, 46845 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 144710, 144711, 144712, 144713, 144714, 144715, 144720, 144721, 144722, 144723, 144724 ], "onlineresource_set": [] }, { "ob_id": 32521, "uuid": "4edcd686e1e74e2f8e4cf108eb054cc8", "title": "SG-WEx: Unified Model output for July 2015 over South Georgia, without island orography (run: u-ab978)", "abstract": "This dataset contains modelling output from the u-ab978 run of a high-resolution (1.5 km horizontal grid, 118 vertical levels up to around 75 km altitude, 30 s timestep) local-area configuration of the Met Office Unified Model run in a box over the island of South Georgia (54S, 36W), as part of the South Georgia Wave Experiment (SG-WEx) project. This run was for the time period July 2015 with a flat orography file for the island. See related dataset for output from a complementary run with the island's orography included for the same time period. These were part of a group of 6 model runs for the SG-WEx project.\r\n\r\nThe aim of the modelling runs was to examine gravity wave generation and deep vertical propagation over this mountainous island. Three model time periods are archived within the SG-WEx dataset collection: January 2015, June 2015 and July 2015, each containing two runs, one including the island's orography and one without. Initial and boundary conditions are supplied by a global forecast to ensure that conditions over the island remain realistic. Meteorological fields such as wind, temperature, pressure etc were outputted and saved in hourly steps. These runs also coincided with radiosonde campaigns launched from the island.\r\n\r\nTechnical details regarding the configuration of these runs is described Vosper (2015, doi:10.1002/qj.2566). Further information and science results can be found in Jackson et al. (2018, doi:10.1175/BAMS-D-16-0151.1) and Hindley (2021, doi:10.5194/acp-21-7695-2021). See online resources linked to this record for further details.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-05-07T17:39:22", "updateFrequency": "notPlanned", "dataLineage": "Data were produced from runs of the Met Office Unified Model on the Met Office system and provided to the Centre for Environmental Data Analysis (CEDA) for long-term archiving.", "removedDataReason": "", "keywords": "Unified Model, NWP, South Atlantic", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "final", "dataPublishedTime": "2021-05-11T08:19:42", "doiPublishedTime": "2021-05-12T14:26:38", "removedDataTime": null, "geographicExtent": { "ob_id": 2752, "bboxName": "SG-WEx local-area model domain", "eastBoundLongitude": -26.879, "westBoundLongitude": -47.373, "southBoundLatitude": -58.162, "northBoundLatitude": -50.162 }, "verticalExtent": { "ob_id": 25, "highestLevelBound": 32767.0, "lowestLevelBound": 0.0, "units": "m" }, "result_field": { "ob_id": 32526, "dataPath": "/badc/sg-wex/data/um-data/sgwex_July2015_nSG_u-ab978", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 191515774305, "numberOfFiles": 161, "fileFormat": "Data are netCDF formatted." }, "timePeriod": { "ob_id": 8943, "startTime": "2015-07-03T13:00:00", "endTime": "2015-07-06T12:00:00" }, "resultQuality": { "ob_id": 3287, "explanation": "No quality control information has been provided for these data by the data provider, nor has any been undertaken by the data centre.", "passesTest": true, "resultTitle": "CEDA: No provider or CEDA QC done statement", "date": "2019-06-03" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32585, "uuid": "91ff8a893f4647ab9224e67666d0a345", "short_code": "comp", "title": "Met Office Unified Model United Kingdom Variable resolution (UKV) version 8.5, run u-ab978", "abstract": "Run u-ab978 of a high-resolution (1.5 km horizontal grid, 118 vertical levels up to around 75 km altitude, 30 s timestep) local-area configuration of the United Kingdom Variable resolution (UKV) version 8.5 model run in a box over the island of South Georgia (54S, 36W), as part of the South Georgia Wave Experiment (SG-WEx) project. This run was for the time period July 2015 with a flat orography file for the island. See related dataset for output from a complementary run with the island's orography included for the same time period. These were part of a group of 6 model runs for the SG-WEx project.\r\n\r\nTechnical details regarding the configuration of these runs follow those described in Vosper (2015, doi:10.1002/qj.2566) - see online resources linked to this record." }, "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": 26590, "uuid": "202c185a201645ad86f06bfa834f1fca", "short_code": "proj", "title": "The South Georgia Wave Experiment (SG-WEX)", "abstract": "Gravity waves are an important type of atmospheric wave. They play a key role in many atmospheric processes, ranging from convection to the mixing of chemical species to influencing the global-scale circulation of the stratosphere and mesosphere. Because of this, it is essential to represent their effects in numerical weather prediction and climate models.\r\n\r\nGravity waves are generated by sources including winds blowing over mountains, jet-stream instabilities and strong convection. The waves can transport energy and momentum away from these sources and deposit them at greater heights, thus exerting a significant \"drag\" on the circulation and so coupling together different layers of the atmosphere. \r\n\r\nRecent studies have shown that isolated mountainous islands in regions of strong winds can be intense sources of gravity waves that can have climatologically-significant effects on atmospheric circulation. However, most climate and numerical weather prediction models cannot accurately model waves from such small, intense island sources because the islands are too small compared to the resolution of the models - this is the \"small island problem\". \r\n\r\nThe South Geogia -Wave EXperiment (SG-WEX), was a NERC funded project (grant awards NE/K015117/1, NE/K012614/1 and NE/K012584/1) proposed a major coordinated observational and modelling experiment to determine the nature and impacts of gravity waves generated by the most important of all these islands, South Georgia in the Southern Atlantic. \r\n\r\nThe SG-WEx project sought to answer the following questions:\r\n\r\n1. What is the nature of gravity waves generated by South Georgia and what is their variability?\r\n\r\n2. What is the contribution of these gravity waves to the total field of gravity waves over the South Atlantic?\r\n\r\n3. What is the influence of gravity waves from South Georgia on the mesosphere?\r\n\r\n4. How can these observations be used to improve gravity-wave parametrizations in models?\r\n\r\n5. How important is South Georgia in comparison to other gravity-wave sources and how does it impact local winds and the development of synoptic systems?\r\n\r\nTo answer these questions the project made measurements of gravity waves over and around South Georgia in two radiosondes campaigns in which meteorological balloons were launched from South Georgia. The observations were then placed in context with measurements made by satellite across the whole South Atlantic. Significantly, the project also deploy the first atmospheric radar on South Georgia - a meteor radar that making the first ever measurements of gravity waves (and winds, tides and large-scale planetary waves) in the mesosphere over South Georgia at heights of 80 - 100 km.\r\n\r\nThese experimental results were then complemented by a programme of modelling work that explored the propagation of gravity waves away from their sources. The observations will be used to help guide the development of new, improved, mathematical representations of gravity waves (so-called \"parametrizations\") allowing such islands to be better represented in the Met Office's Unified Model used for numerical weather prediction and climate studies. Finally, modelling studies integrated these studies and determine the relative importance of South Georgia compared to other waves sources and investigate the impact of Gravity waves from South Georgia on local winds and the development of synoptic (weather) systems.\r\n\r\nObjectives: \r\nThe primary academic beneficiaries will be the community of atmospheric scientists who have interests in the structure and dynamics of the middle atmosphere and in understanding how it is coupled to the underlying troposphere.\r\n\r\nNumerical Weather Prediction (NWP) and climate models all rely on parametrizations of gravity waves to produce realistic middle atmospheres. The project's results will help constrain such parametrizations and thus will thus also be of interest to these communities of scientists - including those meteorologists working with NWP models. This work will thus contribute to the broader activities of weather prediction and climate-change prediction which benefits society at large." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 13296, 51582, 51583, 51584, 53811, 53860, 56834, 56938, 56939, 56941, 56942, 56943, 56945, 56947, 56948, 56949, 56950, 56951, 56952, 56953, 56954, 56955, 56958, 56959, 56960, 56961, 56962, 56965, 56966, 56968, 56969, 56970, 56971, 56972, 56973, 56976, 61142, 61143, 80373, 80374, 80375, 80376, 80377, 80378 ], "vocabularyKeywords": [], "identifier_set": [ 10874 ], "observationcollection_set": [ { "ob_id": 29893, "uuid": "585b29ba4a054760ac4e53e7d95290b9", "short_code": "coll", "title": "SG-WEx: a collection of meteor radar observations, radiosondes and numerical modelling output over South Georgia", "abstract": "The NERC-funded South Georgia Wave EXperiment (SG-WEx) project (grant numbers NE/K015117/1, NE/K012614/1 and NE/K012584/1) was a major coordinated observational and modelling campaign to study the nature and deep vertical propagation of atmospheric gravity waves over the mountainous island of South Georgia in the Southern Atlantic.\r\n\r\nThis dataset collection contains meteor radar and radiosonde measurements from King Edward Point Magnetic Observatory on South Georgia and output from high-resolution (1.5km grid, 118 vertical levels) Met Office Unified Model simulations in a box 1200km x 900km centred on the island that coincide with the radiosonde campaigns.\r\n\r\nThe meteor radar observations included in this collection are continuous from February 2016 to November 2020, funding for which was continued as part of the follow-on NERC DRAGON-WEx project (NE/R001391/1,NE/R001235/1).\r\n\r\nThe project also made use of 3rd party satellite data from NASA, not included in this collection." } ], "responsiblepartyinfo_set": [ 144774, 144775, 144776, 144773, 144777, 144778, 144779, 144780, 145024, 144781, 144782, 144783, 144784 ], "onlineresource_set": [ 42663, 42661, 42662, 91235, 91236, 91237, 91238, 91239, 91240 ] }, { "ob_id": 32522, "uuid": "a945f294d03143d8b5197e65f8005915", "title": "SG-WEx: Unified Model output for June-July 2015 over South Georgia, without island orography (run: u-af015)", "abstract": "This dataset contains modelling output from the u-af015 run of a high-resolution (1.5 km horizontal grid, 118 vertical levels up to around 75 km altitude, 30 s timestep) local-area configuration of the Met Office Unified Model run in a box over the island of South Georgia (54S, 36W), as part of the South Georgia Wave Experiment (SG-WEx) project. This run was for the time period June-July 2015 with a flat orography file for the island. See related dataset for output from a complementary run with the island's orography included for the same time period. These were part of a group of 6 model runs for the SG-WEx project.\r\n\r\nThe aim of the modelling runs was to examine gravity wave generation and deep vertical propagation over this mountainous island. Three model time periods are archived within the SG-WEx dataset collection: January 2015, June 2015 and July 2015, each containing two runs, one including the island's orography and one without. Initial and boundary conditions are supplied by a global forecast to ensure that conditions over the island remain realistic. Meteorological fields such as wind, temperature, pressure etc were outputted and saved in hourly steps. These runs also coincided with radiosonde campaigns launched from the island.\r\n\r\nTechnical details regarding the configuration of these runs is described Vosper (2015, doi:10.1002/qj.2566). Further information and science results can be found in Jackson et al. (2018, doi:10.1175/BAMS-D-16-0151.1) and Hindley (2021, doi:10.5194/acp-21-7695-2021). See online resources linked to this record for further details.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T03:20:53", "updateFrequency": "notPlanned", "dataLineage": "Data were produced from runs of the Met Office Unified Model on the Met Office system and provided to the Centre for Environmental Data Analysis (CEDA) for long-term archiving.", "removedDataReason": "", "keywords": "Unified Model, NWP, South Atlantic", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "final", "dataPublishedTime": "2021-05-11T09:50:10", "doiPublishedTime": "2021-05-12T14:32:12", "removedDataTime": null, "geographicExtent": { "ob_id": 2752, "bboxName": "SG-WEx local-area model domain", "eastBoundLongitude": -26.879, "westBoundLongitude": -47.373, "southBoundLatitude": -58.162, "northBoundLatitude": -50.162 }, "verticalExtent": { "ob_id": 25, "highestLevelBound": 32767.0, "lowestLevelBound": 0.0, "units": "m" }, "result_field": { "ob_id": 32523, "dataPath": "/badc/sg-wex/data/um-data/sgwex_June2015_nSG_u-af015", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1532126175650, "numberOfFiles": 1274, "fileFormat": "Data are netCDF formatted." }, "timePeriod": { "ob_id": 8945, "startTime": "2015-06-12T13:00:00", "endTime": "2015-07-06T12:00:00" }, "resultQuality": { "ob_id": 3287, "explanation": "No quality control information has been provided for these data by the data provider, nor has any been undertaken by the data centre.", "passesTest": true, "resultTitle": "CEDA: No provider or CEDA QC done statement", "date": "2019-06-03" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32590, "uuid": "948d8cd87c0543818e178437b39ac2f8", "short_code": "comp", "title": "Met Office Unified Model United Kingdom Variable resolution (UKV) version 8.5, run u-af015", "abstract": "Run u-af015 of a high-resolution (1.5 km horizontal grid, 118 vertical levels up to around 75 km altitude, 30 s timestep) local-area configuration of the United Kingdom Variable resolution (UKV) version 8.5 model run in a box over the island of South Georgia (54S, 36W), as part of the South Georgia Wave Experiment (SG-WEx) project. This run was for the time period June-July 2015 with a flat orography file for the island. See related dataset for output from a complementary run with the island's orography included for the same time period. These were part of a group of 6 model runs for the SG-WEx project.\r\n\r\nTechnical details regarding the configuration of these runs follow those described in Vosper (2015, doi:10.1002/qj.2566) - see online resources linked to this record." }, "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": 26590, "uuid": "202c185a201645ad86f06bfa834f1fca", "short_code": "proj", "title": "The South Georgia Wave Experiment (SG-WEX)", "abstract": "Gravity waves are an important type of atmospheric wave. They play a key role in many atmospheric processes, ranging from convection to the mixing of chemical species to influencing the global-scale circulation of the stratosphere and mesosphere. Because of this, it is essential to represent their effects in numerical weather prediction and climate models.\r\n\r\nGravity waves are generated by sources including winds blowing over mountains, jet-stream instabilities and strong convection. The waves can transport energy and momentum away from these sources and deposit them at greater heights, thus exerting a significant \"drag\" on the circulation and so coupling together different layers of the atmosphere. \r\n\r\nRecent studies have shown that isolated mountainous islands in regions of strong winds can be intense sources of gravity waves that can have climatologically-significant effects on atmospheric circulation. However, most climate and numerical weather prediction models cannot accurately model waves from such small, intense island sources because the islands are too small compared to the resolution of the models - this is the \"small island problem\". \r\n\r\nThe South Geogia -Wave EXperiment (SG-WEX), was a NERC funded project (grant awards NE/K015117/1, NE/K012614/1 and NE/K012584/1) proposed a major coordinated observational and modelling experiment to determine the nature and impacts of gravity waves generated by the most important of all these islands, South Georgia in the Southern Atlantic. \r\n\r\nThe SG-WEx project sought to answer the following questions:\r\n\r\n1. What is the nature of gravity waves generated by South Georgia and what is their variability?\r\n\r\n2. What is the contribution of these gravity waves to the total field of gravity waves over the South Atlantic?\r\n\r\n3. What is the influence of gravity waves from South Georgia on the mesosphere?\r\n\r\n4. How can these observations be used to improve gravity-wave parametrizations in models?\r\n\r\n5. How important is South Georgia in comparison to other gravity-wave sources and how does it impact local winds and the development of synoptic systems?\r\n\r\nTo answer these questions the project made measurements of gravity waves over and around South Georgia in two radiosondes campaigns in which meteorological balloons were launched from South Georgia. The observations were then placed in context with measurements made by satellite across the whole South Atlantic. Significantly, the project also deploy the first atmospheric radar on South Georgia - a meteor radar that making the first ever measurements of gravity waves (and winds, tides and large-scale planetary waves) in the mesosphere over South Georgia at heights of 80 - 100 km.\r\n\r\nThese experimental results were then complemented by a programme of modelling work that explored the propagation of gravity waves away from their sources. The observations will be used to help guide the development of new, improved, mathematical representations of gravity waves (so-called \"parametrizations\") allowing such islands to be better represented in the Met Office's Unified Model used for numerical weather prediction and climate studies. Finally, modelling studies integrated these studies and determine the relative importance of South Georgia compared to other waves sources and investigate the impact of Gravity waves from South Georgia on local winds and the development of synoptic (weather) systems.\r\n\r\nObjectives: \r\nThe primary academic beneficiaries will be the community of atmospheric scientists who have interests in the structure and dynamics of the middle atmosphere and in understanding how it is coupled to the underlying troposphere.\r\n\r\nNumerical Weather Prediction (NWP) and climate models all rely on parametrizations of gravity waves to produce realistic middle atmospheres. The project's results will help constrain such parametrizations and thus will thus also be of interest to these communities of scientists - including those meteorologists working with NWP models. This work will thus contribute to the broader activities of weather prediction and climate-change prediction which benefits society at large." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 13296, 51582, 51583, 51584, 53811, 53860, 56834, 56938, 56939, 56941, 56942, 56943, 56945, 56947, 56948, 56949, 56950, 56951, 56952, 56953, 56954, 56955, 56958, 56959, 56960, 56961, 56962, 56965, 56966, 56968, 56969, 56970, 56971, 56972, 56973, 56976, 61142, 61143, 80373, 80374, 80375, 80376, 80377, 80378 ], "vocabularyKeywords": [], "identifier_set": [ 10877 ], "observationcollection_set": [ { "ob_id": 29893, "uuid": "585b29ba4a054760ac4e53e7d95290b9", "short_code": "coll", "title": "SG-WEx: a collection of meteor radar observations, radiosondes and numerical modelling output over South Georgia", "abstract": "The NERC-funded South Georgia Wave EXperiment (SG-WEx) project (grant numbers NE/K015117/1, NE/K012614/1 and NE/K012584/1) was a major coordinated observational and modelling campaign to study the nature and deep vertical propagation of atmospheric gravity waves over the mountainous island of South Georgia in the Southern Atlantic.\r\n\r\nThis dataset collection contains meteor radar and radiosonde measurements from King Edward Point Magnetic Observatory on South Georgia and output from high-resolution (1.5km grid, 118 vertical levels) Met Office Unified Model simulations in a box 1200km x 900km centred on the island that coincide with the radiosonde campaigns.\r\n\r\nThe meteor radar observations included in this collection are continuous from February 2016 to November 2020, funding for which was continued as part of the follow-on NERC DRAGON-WEx project (NE/R001391/1,NE/R001235/1).\r\n\r\nThe project also made use of 3rd party satellite data from NASA, not included in this collection." } ], "responsiblepartyinfo_set": [ 144785, 144786, 144787, 144788, 144789, 144790, 144791, 144792, 145019, 144793, 144794, 144795, 144796 ], "onlineresource_set": [ 42675, 42674, 42673, 91211, 91212, 91213, 91214, 91215, 91216 ] }, { "ob_id": 32527, "uuid": "6af300ef78e649e38719f1e1a53007f1", "title": "SG-WEx: Unified Model output for June-July 2015 over South Georgia, with island orography included (run: u-ae766)", "abstract": "This dataset contains modelling output from the u-ae766 run of a high-resolution (1.5 km horizontal grid, 118 vertical levels up to around 75 km altitude, 30 s timestep) local-area configuration of the Met Office Unified Model run in a box over the island of South Georgia (54S, 36W), as part of the South Georgia Wave Experiment (SG-WEx) project. This run was for the time period June-July 2015 with the island orography included. See related dataset for output from a complementary run with a flat orography file for the island for the same time period. These were part of a group of 6 model runs for the SG-WEx project.\r\n\r\nThe aim of the modelling runs was to examine gravity wave generation and deep vertical propagation over this mountainous island. Three model time periods are archived within the SG-WEx dataset collection: January 2015, June 2015 and July 2015, each containing two runs, one including the island's orography and one without. Initial and boundary conditions are supplied by a global forecast to ensure that conditions over the island remain realistic. Meteorological fields such as wind, temperature, pressure etc were outputted and saved in hourly steps. These runs also coincided with radiosonde campaigns launched from the island.\r\n\r\nTechnical details regarding the configuration of these runs is described Vosper (2015, doi:10.1002/qj.2566). Further information and science results can be found in Jackson et al. (2018, doi:10.1175/BAMS-D-16-0151.1) and Hindley (2021, doi:10.5194/acp-21-7695-2021). See online resources linked to this record for further details.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-05-07T19:57:46", "updateFrequency": "notPlanned", "dataLineage": "Data were produced from runs of the Met Office Unified Model on the Met Office system and provided to the Centre for Environmental Data Analysis (CEDA) for long-term archiving.", "removedDataReason": "", "keywords": "Unified Model, NWP, South Atlantic", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "final", "dataPublishedTime": "2021-05-11T09:41:48", "doiPublishedTime": "2021-05-12T14:31:22", "removedDataTime": null, "geographicExtent": { "ob_id": 2752, "bboxName": "SG-WEx local-area model domain", "eastBoundLongitude": -26.879, "westBoundLongitude": -47.373, "southBoundLatitude": -58.162, "northBoundLatitude": -50.162 }, "verticalExtent": { "ob_id": 25, "highestLevelBound": 32767.0, "lowestLevelBound": 0.0, "units": "m" }, "result_field": { "ob_id": 32530, "dataPath": "/badc/sg-wex/data/um-data/sgwex_June2015_SG_u-ae766", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1468287585116, "numberOfFiles": 1221, "fileFormat": "Data are netCDF formatted." }, "timePeriod": { "ob_id": 8946, "startTime": "2015-06-12T13:00:00", "endTime": "2015-07-05T12:00:00" }, "resultQuality": { "ob_id": 3287, "explanation": "No quality control information has been provided for these data by the data provider, nor has any been undertaken by the data centre.", "passesTest": true, "resultTitle": "CEDA: No provider or CEDA QC done statement", "date": "2019-06-03" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32589, "uuid": "def5b5d175a643abb8f9dbe624a752f5", "short_code": "comp", "title": "Met Office Unified Model United Kingdom Variable resolution (UKV) version 8.5, run u-ae766", "abstract": "Run u-ae766 of a high-resolution (1.5 km horizontal grid, 118 vertical levels up to around 75 km altitude, 30 s timestep) local-area configuration of the United Kingdom Variable resolution (UKV) version 8.5 model run in a box over the island of South Georgia (54S, 36W), as part of the South Georgia Wave Experiment (SG-WEx) project. This run was for the time period June-July 2015 with the island orography included. See related dataset for output from a complementary run with a flat orography file for the island for the same time period. These were part of a group of 6 model runs for the SG-WEx project.\r\n\r\nTechnical details regarding the configuration of these runs follow those described in Vosper (2015, doi:10.1002/qj.2566) - see online resources linked to this record." }, "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": 26590, "uuid": "202c185a201645ad86f06bfa834f1fca", "short_code": "proj", "title": "The South Georgia Wave Experiment (SG-WEX)", "abstract": "Gravity waves are an important type of atmospheric wave. They play a key role in many atmospheric processes, ranging from convection to the mixing of chemical species to influencing the global-scale circulation of the stratosphere and mesosphere. Because of this, it is essential to represent their effects in numerical weather prediction and climate models.\r\n\r\nGravity waves are generated by sources including winds blowing over mountains, jet-stream instabilities and strong convection. The waves can transport energy and momentum away from these sources and deposit them at greater heights, thus exerting a significant \"drag\" on the circulation and so coupling together different layers of the atmosphere. \r\n\r\nRecent studies have shown that isolated mountainous islands in regions of strong winds can be intense sources of gravity waves that can have climatologically-significant effects on atmospheric circulation. However, most climate and numerical weather prediction models cannot accurately model waves from such small, intense island sources because the islands are too small compared to the resolution of the models - this is the \"small island problem\". \r\n\r\nThe South Geogia -Wave EXperiment (SG-WEX), was a NERC funded project (grant awards NE/K015117/1, NE/K012614/1 and NE/K012584/1) proposed a major coordinated observational and modelling experiment to determine the nature and impacts of gravity waves generated by the most important of all these islands, South Georgia in the Southern Atlantic. \r\n\r\nThe SG-WEx project sought to answer the following questions:\r\n\r\n1. What is the nature of gravity waves generated by South Georgia and what is their variability?\r\n\r\n2. What is the contribution of these gravity waves to the total field of gravity waves over the South Atlantic?\r\n\r\n3. What is the influence of gravity waves from South Georgia on the mesosphere?\r\n\r\n4. How can these observations be used to improve gravity-wave parametrizations in models?\r\n\r\n5. How important is South Georgia in comparison to other gravity-wave sources and how does it impact local winds and the development of synoptic systems?\r\n\r\nTo answer these questions the project made measurements of gravity waves over and around South Georgia in two radiosondes campaigns in which meteorological balloons were launched from South Georgia. The observations were then placed in context with measurements made by satellite across the whole South Atlantic. Significantly, the project also deploy the first atmospheric radar on South Georgia - a meteor radar that making the first ever measurements of gravity waves (and winds, tides and large-scale planetary waves) in the mesosphere over South Georgia at heights of 80 - 100 km.\r\n\r\nThese experimental results were then complemented by a programme of modelling work that explored the propagation of gravity waves away from their sources. The observations will be used to help guide the development of new, improved, mathematical representations of gravity waves (so-called \"parametrizations\") allowing such islands to be better represented in the Met Office's Unified Model used for numerical weather prediction and climate studies. Finally, modelling studies integrated these studies and determine the relative importance of South Georgia compared to other waves sources and investigate the impact of Gravity waves from South Georgia on local winds and the development of synoptic (weather) systems.\r\n\r\nObjectives: \r\nThe primary academic beneficiaries will be the community of atmospheric scientists who have interests in the structure and dynamics of the middle atmosphere and in understanding how it is coupled to the underlying troposphere.\r\n\r\nNumerical Weather Prediction (NWP) and climate models all rely on parametrizations of gravity waves to produce realistic middle atmospheres. The project's results will help constrain such parametrizations and thus will thus also be of interest to these communities of scientists - including those meteorologists working with NWP models. This work will thus contribute to the broader activities of weather prediction and climate-change prediction which benefits society at large." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 13296, 51582, 51583, 51584, 53811, 53860, 56834, 56938, 56939, 56941, 56942, 56943, 56945, 56948, 56949, 56950, 56951, 56952, 56953, 56954, 56955, 56958, 56959, 56960, 56961, 56962, 56965, 56966, 56968, 56969, 56970, 56971, 56972, 56973, 56976, 61142, 61143, 61144, 80373, 80374, 80375, 80376, 80377, 80378 ], "vocabularyKeywords": [], "identifier_set": [ 10876 ], "observationcollection_set": [ { "ob_id": 29893, "uuid": "585b29ba4a054760ac4e53e7d95290b9", "short_code": "coll", "title": "SG-WEx: a collection of meteor radar observations, radiosondes and numerical modelling output over South Georgia", "abstract": "The NERC-funded South Georgia Wave EXperiment (SG-WEx) project (grant numbers NE/K015117/1, NE/K012614/1 and NE/K012584/1) was a major coordinated observational and modelling campaign to study the nature and deep vertical propagation of atmospheric gravity waves over the mountainous island of South Georgia in the Southern Atlantic.\r\n\r\nThis dataset collection contains meteor radar and radiosonde measurements from King Edward Point Magnetic Observatory on South Georgia and output from high-resolution (1.5km grid, 118 vertical levels) Met Office Unified Model simulations in a box 1200km x 900km centred on the island that coincide with the radiosonde campaigns.\r\n\r\nThe meteor radar observations included in this collection are continuous from February 2016 to November 2020, funding for which was continued as part of the follow-on NERC DRAGON-WEx project (NE/R001391/1,NE/R001235/1).\r\n\r\nThe project also made use of 3rd party satellite data from NASA, not included in this collection." } ], "responsiblepartyinfo_set": [ 144802, 144803, 144804, 144805, 144806, 144807, 144808, 144809, 145022, 144810, 144811, 144812, 144813 ], "onlineresource_set": [ 42670, 42672, 42671, 91217, 91218, 91219, 91220, 91221, 91222 ] }, { "ob_id": 32528, "uuid": "ca00a04014ad4426abc03e952f793dde", "title": "SG-WEx: Unified Model output for July 2015 over South Georgia, with island orography included (run: u-ab326)", "abstract": "This dataset contains modelling output from the u-ab326 run of a high-resolution (1.5 km horizontal grid, 118 vertical levels up to around 75 km altitude, 30 s timestep) local-area configuration of the Met Office Unified Model run in a box over the island of South Georgia (54S, 36W), as part of the South Georgia Wave Experiment (SG-WEx) project. This run was for the time period July 2015 with the island orography included. See related dataset for output from a complementary run with a flat orography file for the island for the same time period. These were part of a group of 6 model runs for the SG-WEx project.\r\n\r\nThe aim of the modelling runs was to examine gravity wave generation and deep vertical propagation over this mountainous island. Three model time periods are archived within the SG-WEx dataset collection: January 2015, June 2015 and July 2015, each containing two runs, one including the island's orography and one without. Initial and boundary conditions are supplied by a global forecast to ensure that conditions over the island remain realistic. Meteorological fields such as wind, temperature, pressure etc were outputted and saved in hourly steps. These runs also coincided with radiosonde campaigns launched from the island.\r\n\r\nTechnical details regarding the configuration of these runs is described Vosper (2015, doi:10.1002/qj.2566). Further information and science results can be found in Jackson et al. (2018, doi:10.1175/BAMS-D-16-0151.1) and Hindley (2021, doi:10.5194/acp-21-7695-2021). See online resources linked to this record for further details.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-05-07T17:20:55", "updateFrequency": "notPlanned", "dataLineage": "Data were produced from runs of the Met Office Unified Model on the Met Office system and provided to the Centre for Environmental Data Analysis (CEDA) for long-term archiving.", "removedDataReason": "", "keywords": "Unified Model, NWP, South Atlantic", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "final", "dataPublishedTime": "2021-05-11T08:16:30", "doiPublishedTime": "2021-05-12T14:25:40", "removedDataTime": null, "geographicExtent": { "ob_id": 2752, "bboxName": "SG-WEx local-area model domain", "eastBoundLongitude": -26.879, "westBoundLongitude": -47.373, "southBoundLatitude": -58.162, "northBoundLatitude": -50.162 }, "verticalExtent": { "ob_id": 25, "highestLevelBound": 32767.0, "lowestLevelBound": 0.0, "units": "m" }, "result_field": { "ob_id": 32529, "dataPath": "/badc/sg-wex/data/um-data/sgwex_July2015_SG_u-ab326", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 510708721731, "numberOfFiles": 426, "fileFormat": "Data are netCDF formatted." }, "timePeriod": { "ob_id": 8944, "startTime": "2015-07-02T13:00:00", "endTime": "2015-07-07T12:00:00" }, "resultQuality": { "ob_id": 3287, "explanation": "No quality control information has been provided for these data by the data provider, nor has any been undertaken by the data centre.", "passesTest": true, "resultTitle": "CEDA: No provider or CEDA QC done statement", "date": "2019-06-03" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32586, "uuid": "7e791b00ce5e46129f055851325a741c", "short_code": "comp", "title": "Met Office Unified Model United Kingdom Variable resolution (UKV) version 8.5, run u-ab326", "abstract": "Run u-ab326 of a high-resolution (1.5 km horizontal grid, 118 vertical levels up to around 75 km altitude, 30 s timestep) local-area configuration of the United Kingdom Variable resolution (UKV) version 8.5 model run in a box over the island of South Georgia (54S, 36W), as part of the South Georgia Wave Experiment (SG-WEx) project. This run was for the time period July 2015 with the island orography included. See related dataset for output from a complementary run with a flat orography file for the island for the same time period. These were part of a group of 6 model runs for the SG-WEx project.\r\n\r\nTechnical details regarding the configuration of these runs follow those described in Vosper (2015, doi:10.1002/qj.2566) - see online resources linked to this record." }, "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": 26590, "uuid": "202c185a201645ad86f06bfa834f1fca", "short_code": "proj", "title": "The South Georgia Wave Experiment (SG-WEX)", "abstract": "Gravity waves are an important type of atmospheric wave. They play a key role in many atmospheric processes, ranging from convection to the mixing of chemical species to influencing the global-scale circulation of the stratosphere and mesosphere. Because of this, it is essential to represent their effects in numerical weather prediction and climate models.\r\n\r\nGravity waves are generated by sources including winds blowing over mountains, jet-stream instabilities and strong convection. The waves can transport energy and momentum away from these sources and deposit them at greater heights, thus exerting a significant \"drag\" on the circulation and so coupling together different layers of the atmosphere. \r\n\r\nRecent studies have shown that isolated mountainous islands in regions of strong winds can be intense sources of gravity waves that can have climatologically-significant effects on atmospheric circulation. However, most climate and numerical weather prediction models cannot accurately model waves from such small, intense island sources because the islands are too small compared to the resolution of the models - this is the \"small island problem\". \r\n\r\nThe South Geogia -Wave EXperiment (SG-WEX), was a NERC funded project (grant awards NE/K015117/1, NE/K012614/1 and NE/K012584/1) proposed a major coordinated observational and modelling experiment to determine the nature and impacts of gravity waves generated by the most important of all these islands, South Georgia in the Southern Atlantic. \r\n\r\nThe SG-WEx project sought to answer the following questions:\r\n\r\n1. What is the nature of gravity waves generated by South Georgia and what is their variability?\r\n\r\n2. What is the contribution of these gravity waves to the total field of gravity waves over the South Atlantic?\r\n\r\n3. What is the influence of gravity waves from South Georgia on the mesosphere?\r\n\r\n4. How can these observations be used to improve gravity-wave parametrizations in models?\r\n\r\n5. How important is South Georgia in comparison to other gravity-wave sources and how does it impact local winds and the development of synoptic systems?\r\n\r\nTo answer these questions the project made measurements of gravity waves over and around South Georgia in two radiosondes campaigns in which meteorological balloons were launched from South Georgia. The observations were then placed in context with measurements made by satellite across the whole South Atlantic. Significantly, the project also deploy the first atmospheric radar on South Georgia - a meteor radar that making the first ever measurements of gravity waves (and winds, tides and large-scale planetary waves) in the mesosphere over South Georgia at heights of 80 - 100 km.\r\n\r\nThese experimental results were then complemented by a programme of modelling work that explored the propagation of gravity waves away from their sources. The observations will be used to help guide the development of new, improved, mathematical representations of gravity waves (so-called \"parametrizations\") allowing such islands to be better represented in the Met Office's Unified Model used for numerical weather prediction and climate studies. Finally, modelling studies integrated these studies and determine the relative importance of South Georgia compared to other waves sources and investigate the impact of Gravity waves from South Georgia on local winds and the development of synoptic (weather) systems.\r\n\r\nObjectives: \r\nThe primary academic beneficiaries will be the community of atmospheric scientists who have interests in the structure and dynamics of the middle atmosphere and in understanding how it is coupled to the underlying troposphere.\r\n\r\nNumerical Weather Prediction (NWP) and climate models all rely on parametrizations of gravity waves to produce realistic middle atmospheres. The project's results will help constrain such parametrizations and thus will thus also be of interest to these communities of scientists - including those meteorologists working with NWP models. This work will thus contribute to the broader activities of weather prediction and climate-change prediction which benefits society at large." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 13296, 51582, 51583, 51584, 53811, 53860, 56834, 56938, 56939, 56941, 56942, 56943, 56945, 56947, 56948, 56949, 56950, 56951, 56952, 56954, 56955, 56958, 56959, 56960, 56961, 56962, 56965, 56966, 56968, 56969, 56970, 56971, 56972, 56973, 56976, 61141, 61142, 61143, 61307, 80374, 80375, 80376, 80377, 80378 ], "vocabularyKeywords": [], "identifier_set": [ 10873 ], "observationcollection_set": [ { "ob_id": 29893, "uuid": "585b29ba4a054760ac4e53e7d95290b9", "short_code": "coll", "title": "SG-WEx: a collection of meteor radar observations, radiosondes and numerical modelling output over South Georgia", "abstract": "The NERC-funded South Georgia Wave EXperiment (SG-WEx) project (grant numbers NE/K015117/1, NE/K012614/1 and NE/K012584/1) was a major coordinated observational and modelling campaign to study the nature and deep vertical propagation of atmospheric gravity waves over the mountainous island of South Georgia in the Southern Atlantic.\r\n\r\nThis dataset collection contains meteor radar and radiosonde measurements from King Edward Point Magnetic Observatory on South Georgia and output from high-resolution (1.5km grid, 118 vertical levels) Met Office Unified Model simulations in a box 1200km x 900km centred on the island that coincide with the radiosonde campaigns.\r\n\r\nThe meteor radar observations included in this collection are continuous from February 2016 to November 2020, funding for which was continued as part of the follow-on NERC DRAGON-WEx project (NE/R001391/1,NE/R001235/1).\r\n\r\nThe project also made use of 3rd party satellite data from NASA, not included in this collection." } ], "responsiblepartyinfo_set": [ 144814, 144815, 144816, 144817, 144819, 144820, 144821, 145008, 145023, 144818, 144822, 144823, 144824 ], "onlineresource_set": [ 42660, 42658, 42659, 91241, 91242, 91243, 91244, 91245, 91246 ] }, { "ob_id": 32531, "uuid": "0ad5bcadb29e4b4998f5dcd26375f349", "title": "BAS-MASIN flight 295 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 295 on 04 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project. This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-09-02T15:36:10", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by British Antarctic Survey (BAS) and a quality-controlled revision of the data was generated at UEA.", "removedDataReason": "", "keywords": "IGP, AFIS, aircraft, meteorology, BAS, MASIN, twin-otter", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-05-07T11:21:12", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2763, "bboxName": "", "eastBoundLongitude": -16.833900451660156, "westBoundLongitude": -19.00248908996582, "southBoundLatitude": 65.64497375488281, "northBoundLatitude": 70.31584167480469 }, "verticalExtent": null, "result_field": { "ob_id": 32532, "dataPath": "/badc/igp/data/twinotter/flight295_20180304", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 82991290, "numberOfFiles": 3, "fileFormat": "MASIN data are in NetCDF format" }, "timePeriod": { "ob_id": 8930, "startTime": "2018-03-04T10:08:36", "endTime": "2018-03-04T15:09:02" }, "resultQuality": { "ob_id": 3664, "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": "2021-05-07" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32533, "uuid": "a23b9c7d361b45949cc5a5ae58d69605", "short_code": "acq", "title": "Acquisition for: BAS-MASIN flight 295 core meteorological data from the Iceland Greenland Seas Project (IGP)", "abstract": "" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 24899, "uuid": "2780d047461c42f0a12534ccf42f487a", "short_code": "proj", "title": "Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)", "abstract": "The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel) were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes. \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function. In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 33929, 33930, 33931, 33932, 33933, 33934, 33935, 33936, 33937, 33938, 33939, 33940, 33941, 33942, 33943, 33944, 33945, 33946, 33947, 33948, 33949, 33950, 33951 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 27445, "uuid": "b3e807b8df824a8ca83468ce2e5b54e5", "short_code": "coll", "title": "In situ observations of air-sea interaction processes from the Iceland Greenland seas Project (IGP)", "abstract": "This collection contains a range of in situ observations of meteorological and air-sea interaction processes from a range of instruments on several platforms (buoy, ship , radiosonde) from the Iceland Greenland seas Project (IGP). \r\n\r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US and Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)" }, { "ob_id": 7571, "uuid": "8be3dd7cdf44090d89aeb8f105421506", "short_code": "coll", "title": "BAS Masin Twin-Otter aircraft data", "abstract": "Data is collected on board the British Antarctic Survey MASIN Twin Otter aircraft for a range of projects in the Antarctic and at other locations. These projects include atmospheric, boundary layer and cloud/aerosol studies.\r\n\r\n\r\nThe instrument suite includes standard temperature and water vapour sensors as well as a turbulence probe allowing full atmospheric profile measurements of temperature, dew point and winds. A DMT Cloud and aerosol spectrometer (CAPS) probe is used for cloud studies and a closed path Licor H2O/CO2 instrument, Grimm optical particle counter and cloud condensation nuclei counter are fed from simple Rosemount inlets." } ], "responsiblepartyinfo_set": [ 144826, 144827, 144828, 144829, 144830, 144831, 144832, 144833, 144834, 144835, 144836, 144837 ], "onlineresource_set": [ 42645 ] }, { "ob_id": 32535, "uuid": "52f829aaebdb4989b748e006d02e2029", "title": "BAS-MASIN flight 296 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 296 on 05 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project. This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-09-02T15:36:21", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by British Antarctic Survey (BAS) and a quality-controlled revision of the data was generated at UEA.", "removedDataReason": "", "keywords": "IGP, AFIS, aircraft, meteorology, BAS, MASIN, twin-otter", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-05-07T11:21:24", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2764, "bboxName": "", "eastBoundLongitude": -18.7762508392334, "westBoundLongitude": -22.013267517089844, "southBoundLatitude": 64.122802734375, "northBoundLatitude": 65.17945098876953 }, "verticalExtent": null, "result_field": { "ob_id": 32536, "dataPath": "/badc/igp/data/twinotter/flight296_20180305", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 17039970, "numberOfFiles": 3, "fileFormat": "MASIN data are in NetCDF format" }, "timePeriod": { "ob_id": 8931, "startTime": "2018-03-05T12:19:48", "endTime": "2018-03-05T13:17:03" }, "resultQuality": { "ob_id": 3665, "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": "2021-05-07" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32537, "uuid": "629c2268e818465c8d3fd1a5bf4e838a", "short_code": "acq", "title": "Acquisition for: BAS-MASIN flight 296 core meteorological data from the Iceland Greenland Seas Project (IGP)", "abstract": "" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 24899, "uuid": "2780d047461c42f0a12534ccf42f487a", "short_code": "proj", "title": "Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)", "abstract": "The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel) were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes. \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function. In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 61212, 61213, 61214, 61215, 61216, 61217, 61218, 61219, 61220, 61222, 61223, 61224, 61225, 61226, 61227, 61228, 61229, 61230, 61231, 61232, 61233, 74368, 74369 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 27445, "uuid": "b3e807b8df824a8ca83468ce2e5b54e5", "short_code": "coll", "title": "In situ observations of air-sea interaction processes from the Iceland Greenland seas Project (IGP)", "abstract": "This collection contains a range of in situ observations of meteorological and air-sea interaction processes from a range of instruments on several platforms (buoy, ship , radiosonde) from the Iceland Greenland seas Project (IGP). \r\n\r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US and Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)" }, { "ob_id": 7571, "uuid": "8be3dd7cdf44090d89aeb8f105421506", "short_code": "coll", "title": "BAS Masin Twin-Otter aircraft data", "abstract": "Data is collected on board the British Antarctic Survey MASIN Twin Otter aircraft for a range of projects in the Antarctic and at other locations. These projects include atmospheric, boundary layer and cloud/aerosol studies.\r\n\r\n\r\nThe instrument suite includes standard temperature and water vapour sensors as well as a turbulence probe allowing full atmospheric profile measurements of temperature, dew point and winds. A DMT Cloud and aerosol spectrometer (CAPS) probe is used for cloud studies and a closed path Licor H2O/CO2 instrument, Grimm optical particle counter and cloud condensation nuclei counter are fed from simple Rosemount inlets." } ], "responsiblepartyinfo_set": [ 144841, 144842, 144843, 144844, 144845, 144846, 144847, 144848, 144849, 144850, 144851, 144852 ], "onlineresource_set": [ 42646 ] }, { "ob_id": 32539, "uuid": "e4bc229019c6442ea7060fcf6a97a600", "title": "BAS-MASIN flight 297 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 297 on 06 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project. This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-09-02T15:36:29", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by British Antarctic Survey (BAS) and a quality-controlled revision of the data was generated at UEA.", "removedDataReason": "", "keywords": "IGP, AFIS, aircraft, meteorology, BAS, MASIN, twin-otter", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-05-07T11:21:36", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2765, "bboxName": "", "eastBoundLongitude": -15.494669914245605, "westBoundLongitude": -18.21215057373047, "southBoundLatitude": 65.64469146728516, "northBoundLatitude": 69.57386779785156 }, "verticalExtent": null, "result_field": { "ob_id": 32540, "dataPath": "/badc/igp/data/twinotter/flight297_20180306", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 91773651, "numberOfFiles": 3, "fileFormat": "MASIN data are in NetCDF format" }, "timePeriod": { "ob_id": 8932, "startTime": "2018-03-06T08:41:27", "endTime": "2018-03-06T14:14:16" }, "resultQuality": { "ob_id": 3666, "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": "2021-05-07" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32541, "uuid": "da0a3677c3194d2889e0dbfccf049848", "short_code": "acq", "title": "Acquisition for: BAS-MASIN flight 297 core meteorological data from the Iceland Greenland Seas Project (IGP)", "abstract": "" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 24899, "uuid": "2780d047461c42f0a12534ccf42f487a", "short_code": "proj", "title": "Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)", "abstract": "The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel) were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes. \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function. In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 61212, 61213, 61214, 61215, 61216, 61217, 61218, 61219, 61220, 61222, 61223, 61224, 61225, 61226, 61227, 61228, 61229, 61230, 61231, 61232, 61233, 74368, 74369 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 27445, "uuid": "b3e807b8df824a8ca83468ce2e5b54e5", "short_code": "coll", "title": "In situ observations of air-sea interaction processes from the Iceland Greenland seas Project (IGP)", "abstract": "This collection contains a range of in situ observations of meteorological and air-sea interaction processes from a range of instruments on several platforms (buoy, ship , radiosonde) from the Iceland Greenland seas Project (IGP). \r\n\r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US and Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)" }, { "ob_id": 7571, "uuid": "8be3dd7cdf44090d89aeb8f105421506", "short_code": "coll", "title": "BAS Masin Twin-Otter aircraft data", "abstract": "Data is collected on board the British Antarctic Survey MASIN Twin Otter aircraft for a range of projects in the Antarctic and at other locations. These projects include atmospheric, boundary layer and cloud/aerosol studies.\r\n\r\n\r\nThe instrument suite includes standard temperature and water vapour sensors as well as a turbulence probe allowing full atmospheric profile measurements of temperature, dew point and winds. A DMT Cloud and aerosol spectrometer (CAPS) probe is used for cloud studies and a closed path Licor H2O/CO2 instrument, Grimm optical particle counter and cloud condensation nuclei counter are fed from simple Rosemount inlets." } ], "responsiblepartyinfo_set": [ 144856, 144857, 144858, 144859, 144860, 144861, 144862, 144863, 144864, 144865, 144866, 144867 ], "onlineresource_set": [ 42647 ] }, { "ob_id": 32543, "uuid": "3a91ec64a9f8440ebb565ea9411e2a89", "title": "BAS-MASIN flight 298 airborne meteorological observationsa from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 298 on 08 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project. This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-09-02T15:36:37", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by British Antarctic Survey (BAS) and a quality-controlled revision of the data was generated at UEA.", "removedDataReason": "", "keywords": "IGP, AFIS, aircraft, meteorology, BAS, MASIN, twin-otter", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-05-07T11:21:48", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2766, "bboxName": "", "eastBoundLongitude": -18.06971549987793, "westBoundLongitude": -22.893617630004883, "southBoundLatitude": 65.64469146728516, "northBoundLatitude": 70.4422378540039 }, "verticalExtent": null, "result_field": { "ob_id": 32544, "dataPath": "/badc/igp/data/twinotter/flight298_20180308", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 60793572, "numberOfFiles": 3, "fileFormat": "MASIN data are in NetCDF format" }, "timePeriod": { "ob_id": 8933, "startTime": "2018-03-08T08:18:19", "endTime": "2018-03-08T11:56:54" }, "resultQuality": { "ob_id": 3667, "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": "2021-05-07" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32545, "uuid": "33f06173d1f64d44880c99e314be6e25", "short_code": "acq", "title": "Acquisition for: BAS-MASIN flight 298 core meteorological data from the Iceland Greenland Seas Project (IGP)", "abstract": "" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 24899, "uuid": "2780d047461c42f0a12534ccf42f487a", "short_code": "proj", "title": "Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)", "abstract": "The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel) were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes. \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function. In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 33929, 33930, 33931, 33932, 33933, 33934, 33935, 33936, 33937, 33938, 33939, 33940, 33941, 33942, 33943, 33944, 33945, 33946, 33947, 33948, 33949, 33950, 33951 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 27445, "uuid": "b3e807b8df824a8ca83468ce2e5b54e5", "short_code": "coll", "title": "In situ observations of air-sea interaction processes from the Iceland Greenland seas Project (IGP)", "abstract": "This collection contains a range of in situ observations of meteorological and air-sea interaction processes from a range of instruments on several platforms (buoy, ship , radiosonde) from the Iceland Greenland seas Project (IGP). \r\n\r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US and Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)" }, { "ob_id": 7571, "uuid": "8be3dd7cdf44090d89aeb8f105421506", "short_code": "coll", "title": "BAS Masin Twin-Otter aircraft data", "abstract": "Data is collected on board the British Antarctic Survey MASIN Twin Otter aircraft for a range of projects in the Antarctic and at other locations. These projects include atmospheric, boundary layer and cloud/aerosol studies.\r\n\r\n\r\nThe instrument suite includes standard temperature and water vapour sensors as well as a turbulence probe allowing full atmospheric profile measurements of temperature, dew point and winds. A DMT Cloud and aerosol spectrometer (CAPS) probe is used for cloud studies and a closed path Licor H2O/CO2 instrument, Grimm optical particle counter and cloud condensation nuclei counter are fed from simple Rosemount inlets." } ], "responsiblepartyinfo_set": [ 144871, 144872, 144873, 144874, 144875, 144876, 144877, 144878, 144879, 144880, 144881, 144882 ], "onlineresource_set": [ 42648 ] }, { "ob_id": 32547, "uuid": "2b290f3138fe431a83f5203d690a4893", "title": "BAS-MASIN flight 299 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 299 on 08 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project. This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T12:40:32", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by British Antarctic Survey (BAS) and a quality-controlled revision of the data was generated at UEA.", "removedDataReason": "", "keywords": "IGP, AFIS, aircraft, meteorology, BAS, MASIN, twin-otter", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-05-07T11:21:59", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2767, "bboxName": "", "eastBoundLongitude": -18.334707260131836, "westBoundLongitude": -24.013635635375977, "southBoundLatitude": 65.41260528564453, "northBoundLatitude": 70.74539184570312 }, "verticalExtent": null, "result_field": { "ob_id": 32548, "dataPath": "/badc/igp/data/twinotter/flight299_20180308", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 93509331, "numberOfFiles": 3, "fileFormat": "MASIN data are in NetCDF format" }, "timePeriod": { "ob_id": 8934, "startTime": "2018-03-08T13:22:36", "endTime": "2018-03-08T19:01:49" }, "resultQuality": { "ob_id": 3668, "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": "2021-05-07" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32549, "uuid": "7534c28745dd4e9396ee1d09e18e5ac0", "short_code": "acq", "title": "Acquisition for: BAS-MASIN flight 299 core meteorological data from the Iceland Greenland Seas Project (IGP)", "abstract": "" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 24899, "uuid": "2780d047461c42f0a12534ccf42f487a", "short_code": "proj", "title": "Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)", "abstract": "The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel) were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes. \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function. In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 33929, 33930, 33931, 33932, 33933, 33934, 33935, 33936, 33937, 33938, 33939, 33940, 33941, 33942, 33943, 33944, 33945, 33946, 33947, 33948, 33949, 33950, 33951 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 27445, "uuid": "b3e807b8df824a8ca83468ce2e5b54e5", "short_code": "coll", "title": "In situ observations of air-sea interaction processes from the Iceland Greenland seas Project (IGP)", "abstract": "This collection contains a range of in situ observations of meteorological and air-sea interaction processes from a range of instruments on several platforms (buoy, ship , radiosonde) from the Iceland Greenland seas Project (IGP). \r\n\r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US and Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)" }, { "ob_id": 7571, "uuid": "8be3dd7cdf44090d89aeb8f105421506", "short_code": "coll", "title": "BAS Masin Twin-Otter aircraft data", "abstract": "Data is collected on board the British Antarctic Survey MASIN Twin Otter aircraft for a range of projects in the Antarctic and at other locations. These projects include atmospheric, boundary layer and cloud/aerosol studies.\r\n\r\n\r\nThe instrument suite includes standard temperature and water vapour sensors as well as a turbulence probe allowing full atmospheric profile measurements of temperature, dew point and winds. A DMT Cloud and aerosol spectrometer (CAPS) probe is used for cloud studies and a closed path Licor H2O/CO2 instrument, Grimm optical particle counter and cloud condensation nuclei counter are fed from simple Rosemount inlets." } ], "responsiblepartyinfo_set": [ 144886, 144887, 144888, 144889, 144890, 144891, 144892, 144893, 144894, 144895, 144896, 144897 ], "onlineresource_set": [ 42649 ] }, { "ob_id": 32551, "uuid": "257233ecd1c64544862d93ce09ac5aee", "title": "BAS-MASIN flight 300 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 300 on 09 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project. This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-09-02T14:36:54", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by British Antarctic Survey (BAS) and a quality-controlled revision of the data was generated at UEA.", "removedDataReason": "", "keywords": "IGP, AFIS, aircraft, meteorology, BAS, MASIN, twin-otter", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-05-07T11:22:09", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2768, "bboxName": "", "eastBoundLongitude": -18.084840774536133, "westBoundLongitude": -23.36092185974121, "southBoundLatitude": 65.72164154052734, "northBoundLatitude": 69.23255157470703 }, "verticalExtent": null, "result_field": { "ob_id": 32552, "dataPath": "/badc/igp/data/twinotter/flight300_20180309", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 79822771, "numberOfFiles": 3, "fileFormat": "MASIN data are in NetCDF format" }, "timePeriod": { "ob_id": 8935, "startTime": "2018-03-09T09:58:22", "endTime": "2018-03-09T14:47:07" }, "resultQuality": { "ob_id": 3669, "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": "2021-05-07" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32553, "uuid": "8f5183c710ee4e8ca809b339c66f24db", "short_code": "acq", "title": "Acquisition for: BAS-MASIN flight 300 core meteorological data from the Iceland Greenland Seas Project (IGP)", "abstract": "" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 24899, "uuid": "2780d047461c42f0a12534ccf42f487a", "short_code": "proj", "title": "Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)", "abstract": "The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel) were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes. \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function. In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 61212, 61213, 61214, 61215, 61216, 61217, 61218, 61219, 61220, 61222, 61223, 61224, 61225, 61226, 61227, 61228, 61229, 61230, 61231, 61232, 61233, 74368, 74369 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 27445, "uuid": "b3e807b8df824a8ca83468ce2e5b54e5", "short_code": "coll", "title": "In situ observations of air-sea interaction processes from the Iceland Greenland seas Project (IGP)", "abstract": "This collection contains a range of in situ observations of meteorological and air-sea interaction processes from a range of instruments on several platforms (buoy, ship , radiosonde) from the Iceland Greenland seas Project (IGP). \r\n\r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US and Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)" }, { "ob_id": 7571, "uuid": "8be3dd7cdf44090d89aeb8f105421506", "short_code": "coll", "title": "BAS Masin Twin-Otter aircraft data", "abstract": "Data is collected on board the British Antarctic Survey MASIN Twin Otter aircraft for a range of projects in the Antarctic and at other locations. These projects include atmospheric, boundary layer and cloud/aerosol studies.\r\n\r\n\r\nThe instrument suite includes standard temperature and water vapour sensors as well as a turbulence probe allowing full atmospheric profile measurements of temperature, dew point and winds. A DMT Cloud and aerosol spectrometer (CAPS) probe is used for cloud studies and a closed path Licor H2O/CO2 instrument, Grimm optical particle counter and cloud condensation nuclei counter are fed from simple Rosemount inlets." } ], "responsiblepartyinfo_set": [ 144901, 144902, 144903, 144904, 144905, 144906, 144907, 144908, 144909, 144910, 144911, 144912 ], "onlineresource_set": [ 42650 ] }, { "ob_id": 32555, "uuid": "161295e94805427b9a295057f66f60e4", "title": "BAS-MASIN flight 301 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 301 on 12 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project. This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-09-02T15:37:03", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by British Antarctic Survey (BAS) and a quality-controlled revision of the data was generated at UEA.", "removedDataReason": "", "keywords": "IGP, AFIS, aircraft, meteorology, BAS, MASIN, twin-otter", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-05-07T11:22:21", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2769, "bboxName": "", "eastBoundLongitude": -18.06656265258789, "westBoundLongitude": -24.609283447265625, "southBoundLatitude": 64.1262435913086, "northBoundLatitude": 65.6668701171875 }, "verticalExtent": null, "result_field": { "ob_id": 32556, "dataPath": "/badc/igp/data/twinotter/flight301_20180312", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 101591267, "numberOfFiles": 3, "fileFormat": "MASIN data are in NetCDF format" }, "timePeriod": { "ob_id": 8936, "startTime": "2018-03-12T12:04:34", "endTime": "2018-03-12T18:13:35" }, "resultQuality": { "ob_id": 3670, "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": "2021-05-07" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32557, "uuid": "14005342c5b740f4ad3fe0d8ffb22841", "short_code": "acq", "title": "Acquisition for: BAS-MASIN flight 301 core meteorological data from the Iceland Greenland Seas Project (IGP)", "abstract": "" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 24899, "uuid": "2780d047461c42f0a12534ccf42f487a", "short_code": "proj", "title": "Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)", "abstract": "The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel) were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes. \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function. In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 33929, 33930, 33931, 33932, 33933, 33934, 33935, 33936, 33937, 33938, 33939, 33940, 33941, 33942, 33943, 33944, 33945, 33946, 33947, 33948, 33949, 33950, 33951 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 27445, "uuid": "b3e807b8df824a8ca83468ce2e5b54e5", "short_code": "coll", "title": "In situ observations of air-sea interaction processes from the Iceland Greenland seas Project (IGP)", "abstract": "This collection contains a range of in situ observations of meteorological and air-sea interaction processes from a range of instruments on several platforms (buoy, ship , radiosonde) from the Iceland Greenland seas Project (IGP). \r\n\r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US and Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)" }, { "ob_id": 7571, "uuid": "8be3dd7cdf44090d89aeb8f105421506", "short_code": "coll", "title": "BAS Masin Twin-Otter aircraft data", "abstract": "Data is collected on board the British Antarctic Survey MASIN Twin Otter aircraft for a range of projects in the Antarctic and at other locations. These projects include atmospheric, boundary layer and cloud/aerosol studies.\r\n\r\n\r\nThe instrument suite includes standard temperature and water vapour sensors as well as a turbulence probe allowing full atmospheric profile measurements of temperature, dew point and winds. A DMT Cloud and aerosol spectrometer (CAPS) probe is used for cloud studies and a closed path Licor H2O/CO2 instrument, Grimm optical particle counter and cloud condensation nuclei counter are fed from simple Rosemount inlets." } ], "responsiblepartyinfo_set": [ 144916, 144917, 144918, 144919, 144920, 144921, 144922, 144923, 144924, 144925, 144926, 144927 ], "onlineresource_set": [ 42651 ] }, { "ob_id": 32559, "uuid": "ab10878dace441b6b6bdd2baa8528b92", "title": "BAS-MASIN flight 306 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 306 on 19 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project. This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-09-02T15:37:54", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by British Antarctic Survey (BAS) and a quality-controlled revision of the data was generated at UEA.", "removedDataReason": "", "keywords": "IGP, AFIS, aircraft, meteorology, BAS, MASIN, twin-otter", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-05-07T11:22:31", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2770, "bboxName": "", "eastBoundLongitude": -18.050004959106445, "westBoundLongitude": -22.62369728088379, "southBoundLatitude": 65.63907623291016, "northBoundLatitude": 66.79524993896484 }, "verticalExtent": null, "result_field": { "ob_id": 32560, "dataPath": "/badc/igp/data/twinotter/flight306_20180319", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 75072251, "numberOfFiles": 3, "fileFormat": "MASIN data are in NetCDF format" }, "timePeriod": { "ob_id": 8937, "startTime": "2018-03-19T12:58:18", "endTime": "2018-03-19T17:29:32" }, "resultQuality": { "ob_id": 3671, "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": "2021-05-07" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32561, "uuid": "111c2d411eaf453a9ac9c9fcd0f9a059", "short_code": "acq", "title": "Acquisition for: BAS-MASIN flight 306 core meteorological data from the Iceland Greenland Seas Project (IGP)", "abstract": "" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 24899, "uuid": "2780d047461c42f0a12534ccf42f487a", "short_code": "proj", "title": "Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)", "abstract": "The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel) were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes. \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function. In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 61212, 61213, 61214, 61215, 61216, 61217, 61218, 61219, 61220, 61222, 61223, 61224, 61225, 61226, 61227, 61228, 61229, 61230, 61231, 61232, 61233, 74368, 74369 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 27445, "uuid": "b3e807b8df824a8ca83468ce2e5b54e5", "short_code": "coll", "title": "In situ observations of air-sea interaction processes from the Iceland Greenland seas Project (IGP)", "abstract": "This collection contains a range of in situ observations of meteorological and air-sea interaction processes from a range of instruments on several platforms (buoy, ship , radiosonde) from the Iceland Greenland seas Project (IGP). \r\n\r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US and Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)" }, { "ob_id": 7571, "uuid": "8be3dd7cdf44090d89aeb8f105421506", "short_code": "coll", "title": "BAS Masin Twin-Otter aircraft data", "abstract": "Data is collected on board the British Antarctic Survey MASIN Twin Otter aircraft for a range of projects in the Antarctic and at other locations. These projects include atmospheric, boundary layer and cloud/aerosol studies.\r\n\r\n\r\nThe instrument suite includes standard temperature and water vapour sensors as well as a turbulence probe allowing full atmospheric profile measurements of temperature, dew point and winds. A DMT Cloud and aerosol spectrometer (CAPS) probe is used for cloud studies and a closed path Licor H2O/CO2 instrument, Grimm optical particle counter and cloud condensation nuclei counter are fed from simple Rosemount inlets." } ], "responsiblepartyinfo_set": [ 144931, 144932, 144933, 144934, 144935, 144936, 144937, 144938, 144939, 144940, 144941, 144942 ], "onlineresource_set": [ 42652 ] }, { "ob_id": 32563, "uuid": "51976f12732a491b95433d008afc291f", "title": "BAS-MASIN flight 303 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 303 on 14 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project. This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-09-02T15:37:30", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by British Antarctic Survey (BAS) and a quality-controlled revision of the data was generated at UEA.", "removedDataReason": "", "keywords": "IGP, AFIS, aircraft, meteorology, BAS, MASIN, twin-otter", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-05-07T11:22:40", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2771, "bboxName": "", "eastBoundLongitude": -18.249908447265625, "westBoundLongitude": -22.6533203125, "southBoundLatitude": 66.03550720214844, "northBoundLatitude": 71.8899917602539 }, "verticalExtent": null, "result_field": { "ob_id": 32564, "dataPath": "/badc/igp/data/twinotter/flight303_20180314", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 92126211, "numberOfFiles": 3, "fileFormat": "MASIN data are in NetCDF format" }, "timePeriod": { "ob_id": 8938, "startTime": "2018-03-14T12:54:06", "endTime": "2018-03-14T18:28:13" }, "resultQuality": { "ob_id": 3672, "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": "2021-05-07" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32565, "uuid": "d565820add31474eac38171fe98105c9", "short_code": "acq", "title": "Acquisition for: BAS-MASIN flight 303 core meteorological data from the Iceland Greenland Seas Project (IGP)", "abstract": "" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 24899, "uuid": "2780d047461c42f0a12534ccf42f487a", "short_code": "proj", "title": "Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)", "abstract": "The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel) were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes. \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function. In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 61212, 61213, 61214, 61215, 61216, 61217, 61218, 61219, 61220, 61222, 61223, 61224, 61225, 61226, 61227, 61228, 61229, 61230, 61231, 61232, 61233, 74368, 74369 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 27445, "uuid": "b3e807b8df824a8ca83468ce2e5b54e5", "short_code": "coll", "title": "In situ observations of air-sea interaction processes from the Iceland Greenland seas Project (IGP)", "abstract": "This collection contains a range of in situ observations of meteorological and air-sea interaction processes from a range of instruments on several platforms (buoy, ship , radiosonde) from the Iceland Greenland seas Project (IGP). \r\n\r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US and Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)" }, { "ob_id": 7571, "uuid": "8be3dd7cdf44090d89aeb8f105421506", "short_code": "coll", "title": "BAS Masin Twin-Otter aircraft data", "abstract": "Data is collected on board the British Antarctic Survey MASIN Twin Otter aircraft for a range of projects in the Antarctic and at other locations. These projects include atmospheric, boundary layer and cloud/aerosol studies.\r\n\r\n\r\nThe instrument suite includes standard temperature and water vapour sensors as well as a turbulence probe allowing full atmospheric profile measurements of temperature, dew point and winds. A DMT Cloud and aerosol spectrometer (CAPS) probe is used for cloud studies and a closed path Licor H2O/CO2 instrument, Grimm optical particle counter and cloud condensation nuclei counter are fed from simple Rosemount inlets." } ], "responsiblepartyinfo_set": [ 144946, 144947, 144948, 144949, 144950, 144951, 144952, 144953, 144954, 144955, 144956, 144957 ], "onlineresource_set": [ 42653 ] }, { "ob_id": 32567, "uuid": "4f8c49b537c54b85af1538a74685c6a5", "title": "BAS-MASIN flight 304 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 304 on 16 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project. This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T13:08:11", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by British Antarctic Survey (BAS) and a quality-controlled revision of the data was generated at UEA.", "removedDataReason": "", "keywords": "IGP, AFIS, aircraft, meteorology, BAS, MASIN, twin-otter", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-05-07T11:22:49", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2772, "bboxName": "", "eastBoundLongitude": -16.815567016601562, "westBoundLongitude": -18.355791091918945, "southBoundLatitude": 65.64727020263672, "northBoundLatitude": 66.24910736083984 }, "verticalExtent": null, "result_field": { "ob_id": 32568, "dataPath": "/badc/igp/data/twinotter/flight304_20180316", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 35192291, "numberOfFiles": 3, "fileFormat": "MASIN data are in NetCDF format" }, "timePeriod": { "ob_id": 8939, "startTime": "2018-03-16T09:41:15", "endTime": "2018-03-16T11:45:26" }, "resultQuality": { "ob_id": 3673, "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": "2021-05-07" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32569, "uuid": "c121bc7c617c41728306df006ea3050f", "short_code": "acq", "title": "Acquisition for: BAS-MASIN flight 304 core meteorological data from the Iceland Greenland Seas Project (IGP)", "abstract": "" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 24899, "uuid": "2780d047461c42f0a12534ccf42f487a", "short_code": "proj", "title": "Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)", "abstract": "The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel) were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes. \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function. In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 61217, 61218, 61225, 61229, 61230, 61231, 63818, 63819, 63820, 63821, 63822, 63823, 63824, 63825, 63826, 63827, 63828, 63829, 63830, 63831, 63832, 63833, 63834 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 27445, "uuid": "b3e807b8df824a8ca83468ce2e5b54e5", "short_code": "coll", "title": "In situ observations of air-sea interaction processes from the Iceland Greenland seas Project (IGP)", "abstract": "This collection contains a range of in situ observations of meteorological and air-sea interaction processes from a range of instruments on several platforms (buoy, ship , radiosonde) from the Iceland Greenland seas Project (IGP). \r\n\r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US and Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)" }, { "ob_id": 7571, "uuid": "8be3dd7cdf44090d89aeb8f105421506", "short_code": "coll", "title": "BAS Masin Twin-Otter aircraft data", "abstract": "Data is collected on board the British Antarctic Survey MASIN Twin Otter aircraft for a range of projects in the Antarctic and at other locations. These projects include atmospheric, boundary layer and cloud/aerosol studies.\r\n\r\n\r\nThe instrument suite includes standard temperature and water vapour sensors as well as a turbulence probe allowing full atmospheric profile measurements of temperature, dew point and winds. A DMT Cloud and aerosol spectrometer (CAPS) probe is used for cloud studies and a closed path Licor H2O/CO2 instrument, Grimm optical particle counter and cloud condensation nuclei counter are fed from simple Rosemount inlets." } ], "responsiblepartyinfo_set": [ 144961, 144962, 144963, 144964, 144965, 144966, 144967, 144968, 144969, 144970, 144971, 144972 ], "onlineresource_set": [ 42654 ] }, { "ob_id": 32571, "uuid": "378139c15c784477bfdd7bd8c204c0f6", "title": "BAS-MASIN flight 305 airborne meteorological observations from the Iceland Greenland Seas Project (IGP)", "abstract": "In-situ airborne observations collected during flight 305 on 18 March 2018 by the Meteorological Airborne Science Instrumentation (MASIN) on board the British Antarctic Survey (BAS) Twin-otter aircraft for the Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS) project. This dataset is a quality-controlled revision of the core meteorological data, generated at the University of East Anglia (UEA). \r\nData were collected over the Iceland and Greenland Sea area.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T13:08:13", "updateFrequency": "notPlanned", "dataLineage": "Data were collected and processed by British Antarctic Survey (BAS) and a quality-controlled revision of the data was generated at UEA.", "removedDataReason": "", "keywords": "IGP, AFIS, aircraft, meteorology, BAS, MASIN, twin-otter", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-05-07T11:23:16", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2773, "bboxName": "", "eastBoundLongitude": -7.92543888092041, "westBoundLongitude": -18.19221305847168, "southBoundLatitude": 65.64600372314453, "northBoundLatitude": 70.66168212890625 }, "verticalExtent": null, "result_field": { "ob_id": 32572, "dataPath": "/badc/igp/data/twinotter/flight305_20180318", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 98974187, "numberOfFiles": 3, "fileFormat": "MASIN data are in NetCDF format" }, "timePeriod": { "ob_id": 8940, "startTime": "2018-03-18T09:00:10", "endTime": "2018-03-18T14:59:32" }, "resultQuality": { "ob_id": 3674, "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": "2021-05-07" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32573, "uuid": "d8049354950842cb93de0f0ff6195ac2", "short_code": "acq", "title": "Acquisition for: BAS-MASIN flight 305 core meteorological data from the Iceland Greenland Seas Project (IGP)", "abstract": "" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 24899, "uuid": "2780d047461c42f0a12534ccf42f487a", "short_code": "proj", "title": "Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)", "abstract": "The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel) were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes. \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function. In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 61212, 61213, 61214, 61215, 61216, 61217, 61218, 61219, 61220, 61221, 61222, 61223, 61224, 61225, 61226, 61227, 61228, 61229, 61230, 61231, 61232, 61233, 61234 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 27445, "uuid": "b3e807b8df824a8ca83468ce2e5b54e5", "short_code": "coll", "title": "In situ observations of air-sea interaction processes from the Iceland Greenland seas Project (IGP)", "abstract": "This collection contains a range of in situ observations of meteorological and air-sea interaction processes from a range of instruments on several platforms (buoy, ship , radiosonde) from the Iceland Greenland seas Project (IGP). \r\n\r\n\r\nThe Iceland Greenland seas Project (IGP) was an international project involving the UK, US and Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)" }, { "ob_id": 7571, "uuid": "8be3dd7cdf44090d89aeb8f105421506", "short_code": "coll", "title": "BAS Masin Twin-Otter aircraft data", "abstract": "Data is collected on board the British Antarctic Survey MASIN Twin Otter aircraft for a range of projects in the Antarctic and at other locations. These projects include atmospheric, boundary layer and cloud/aerosol studies.\r\n\r\n\r\nThe instrument suite includes standard temperature and water vapour sensors as well as a turbulence probe allowing full atmospheric profile measurements of temperature, dew point and winds. A DMT Cloud and aerosol spectrometer (CAPS) probe is used for cloud studies and a closed path Licor H2O/CO2 instrument, Grimm optical particle counter and cloud condensation nuclei counter are fed from simple Rosemount inlets." } ], "responsiblepartyinfo_set": [ 144976, 144977, 144978, 144979, 144980, 144981, 144982, 144983, 144984, 144985, 144986, 144987 ], "onlineresource_set": [ 42655 ] }, { "ob_id": 32576, "uuid": "0613b74ecc574fa7b6ac8a22838c5f81", "title": "Exploring the sensitivity of atmospheric nitrate concentrations to nitric acid uptake rate using the Met Office’s Unified Model: nitrate and nitric acid simulation data", "abstract": "This dataset contains nitrate and nitric acid simulation data to explore the sensitivity of atmospheric nitrate concentrations to nitric acid uptake rate using the Met Office’s Unified Model.\r\n\r\nThe files are seperated into directories by simulation name - 1. A control simulation with no nitrate aerosol (CNTL); 2. A simulation with NH4·NO3 reaching equilibrium instantaneously (INSTANT); 3. A simulation with the HNO3 uptake rate set to 0.193 (FAST); and 4. A simulation with the HNO3 uptake rate 0.001 (SLOW). All simulations are performed with the Met Office Unified Model (UM or MetUM) in an N96L85 resolution.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-05-10T11:19:06", "updateFrequency": "notPlanned", "dataLineage": "The data is model output from MetUM simulations performed on the Met Office Cray XC40 supercomputer. The output was then processed and made CF-compliant using Python with the Iris module. The data were sent to the Centre for Environmental Data Analysis (CEDA) for archiving.", "removedDataReason": "", "keywords": "Nitrate, nitric acid, Met Office, UM", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-05-12T09:33:37", "doiPublishedTime": "2021-05-14T10:25:27.211604", "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": 32577, "dataPath": "/badc/deposited2021/nitrates_metoffice-um/data/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 114355323714, "numberOfFiles": 192, "fileFormat": "Data are netCDF formatted" }, "timePeriod": { "ob_id": 8948, "startTime": "1993-12-01T00:00:00", "endTime": "2013-11-30T23:59:59" }, "resultQuality": { "ob_id": 3675, "explanation": "Data are as given by the data provider with quality control flags defined within each file. No quality control has been performed by the Centre for Environmental Data Analysis (CEDA)", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-05-10" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 475, "uuid": "084943f2cb4a4bf1a233cc518944b3aa", "short_code": "comp", "title": "Met Office operational unified model (UM) deployed on Met Office Computer network", "abstract": "This computation involved: Met Office operational unified model (UM) deployed on Met Office Computer network. The Unified Model is the name given to the suite of atmospheric and oceanic numerical modelling software developed and used at the Met Office. The formulation of the model supports global and regional domains and is applicable to a wide range of temporal and spatial scales that allow it to be used for both numerical weather prediction and climate modelling as well as a variety of related research activities. The Unified Model was introduced into operational service in 1992. Since then, both its formulation and capabilities have been substantially enhanced." }, "procedureCompositeProcess": null, "imageDetails": [], "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": 32578, "uuid": "2b4558f9e4954e1cad27dc6984055bd3", "short_code": "proj", "title": "SPF Clean Air framework", "abstract": "The Clean Air programme aims to bring together leading researchers from across atmospheric, medical and social science to better predict exposure to air pollution and its effects on vulnerable groups such as children and the elderly. It will identify practical and usable solutions to air pollution to help policy makers and business protect health and work towards a cleaner economy." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6023, 9042, 9043, 19043, 21990, 22005, 34066, 50510, 50512, 51186, 51187, 54872, 54873, 54874, 54875, 70600, 70601, 70602, 70603, 70604, 70605, 70606, 70607, 70608, 70609, 70610, 70611, 70612 ], "vocabularyKeywords": [], "identifier_set": [ 10886 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 144991, 144992, 144993, 144994, 144995, 144996, 144997, 144998, 168959, 144999, 145000, 145001, 145002, 145003, 145004, 145005, 145006, 145007 ], "onlineresource_set": [ 87796 ] }, { "ob_id": 32582, "uuid": "f75c4b7739f34e02ae1a52b793c3b839", "title": "University of Liverpool Botanical Gardens (Ness) Long-Term Monitoring: Automatic Weather Station 5 minute surface observations (2010 onwards)", "abstract": "This dataset contains 5 minute surface meteorological observations from an automatic weather station (AWS) deployed at the University of Liverpool's Ness Botanical Gardens in Cheshire, UK from 2010 onwards.\r\n\r\nThese data complement data from this site originally collected by the Met Office until 0900 UTC on 1st June 2011. Those earlier data are available within the MIDAS Open dataset collection provided under the Open Government Licence by the Met Office. Those data are also available via the Centre for Environmental Data (CEDA) Archive. This results in an overlap between the Met Office data for this site and the 5 minute AWS data within this dataset. \r\n\r\nBoth BADC-CSV and NetCDF formatted versions of the data have been provided to aid greatest usability possible of these data.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-05-10T15:54:00", "updateFrequency": "monthly", "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "surface meteorology, automatic weather station, 5 minunte", "publicationState": "preview", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "pending", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2774, "bboxName": "Ness Gardens (Ness Botanical station)", "eastBoundLongitude": -3.04654, "westBoundLongitude": -3.04654, "southBoundLatitude": 53.2716, "northBoundLatitude": 53.2716 }, "verticalExtent": null, "result_field": { "ob_id": 32583, "dataPath": "/badc/ness-aws/data/ness-aws", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 0, "numberOfFiles": 0, "fileFormat": "Data are netCDF and BADC-CSV formatted." }, "timePeriod": { "ob_id": 8949, "startTime": "2020-01-01T00:00:00", "endTime": null }, "resultQuality": { "ob_id": 3287, "explanation": "No quality control information has been provided for these data by the data provider, nor has any been undertaken by the data centre.", "passesTest": true, "resultTitle": "CEDA: No provider or CEDA QC done statement", "date": "2019-06-03" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32581, "uuid": "97384eb8c1d347248ae75744d1ef43ba", "short_code": "acq", "title": "Ness AWS long term monitoring", "abstract": "Ness AWS long term monitoring" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [], "projects": [ { "ob_id": 32584, "uuid": "318f78f2669a46e4ae1977740e59881d", "short_code": "proj", "title": "University of Liverpool Botanical Gardens (Ness) Long-Term Monitoring", "abstract": "University of Liverpool Botanical Gardens (Ness) Long-Term Monitoring continues surface meteorological observations at the Ness Botanical Gardens site following on from earlier observations undertaken by the Met Office." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 145047, 145048, 145049, 145050, 145051, 145052, 145053, 145054, 145076, 145077 ], "onlineresource_set": [] }, { "ob_id": 32592, "uuid": "653fdd814dba4103a301221955781e35", "title": "NCEO Kenya forest aboveground biomass map 2015 v21.0", "abstract": "The NCEO Kenya forest aboveground biomass map shows aboveground woody biomass (AGB) in Kenyan forests. Forest areas include vegetated wetlands and wooded grassland for the year 2015. The map was generated by combining field inventory plots (KFS) with Advanced Land Observing Satellite (ALOS-2), Phased Array type L-band Synthetic Aperture Radar (PALSAR-2) and multispectral optical data (NASA Landsat 8), by means of a Random Forests algorithm within a k-Fold calibration/validation framework. \r\n\r\nThe characterization of carbon stocks and dynamics at the national level is critical for countries engaging in climate change mitigation and adaptation strategies. However, several tropical countries, including Kenya, lack the essential information typically provided by a complete national forest inventory. These data were produced by the National Centre for Earth Observation (NCEO), University of Leicester, in collaboration with the Kenya Forest Service (KFS) with funding from the NCEO ODA Programme. \r\n\r\nKnown Issues: Residual scan line corrector (SLC) effects due to the use of the SLEEK land cover product as a retrieval mask (derived from Landsat imagery) are visible in some areas", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-05-09T18:18:56", "updateFrequency": "", "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "NCEO, AGB, Biomass, Kenya, forest, vegetated wetlands, wooded grassland", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-05-14T13:03:44", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2775, "bboxName": "Kenya", "eastBoundLongitude": 41.899, "westBoundLongitude": 33.909, "southBoundLatitude": -4.8995, "northBoundLatitude": 4.62 }, "verticalExtent": null, "result_field": { "ob_id": 32591, "dataPath": "/neodc/nceo_biomass_maps/data/kenya/v21.0/2015/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 575877009, "numberOfFiles": 11, "fileFormat": "GeoTiff \r\nPixel type: unsigned integer \r\nPixel Depth: 16 Bit NoData Value: 65535" }, "timePeriod": { "ob_id": 8950, "startTime": "2015-01-01T00:00:00", "endTime": "2015-01-31T00:00:00" }, "resultQuality": { "ob_id": 3676, "explanation": "Validated by the NCEO University of Leicester project team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-05-13" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 32596, "uuid": "dfee2403b85d4aad8bc655aec772be07", "short_code": "cmppr", "title": "NCEO Aboveground Biomass Map v21 2015", "abstract": "The map was generated by combining field inventory plots (KFS) with L-band SAR (JAXA ALOS-2 PALSAR-2) and multispectral optical data (NASA Landsat 8), by means of a Random Forests algorithm within a k-Fold calibration / validation framework." }, "imageDetails": [ 130 ], "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": 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": [ 145125, 145126, 145127, 145132, 145133, 145122, 145123, 145124, 145134, 145135 ], "onlineresource_set": [ 42682, 42683, 42684, 42685, 42686, 42687 ] }, { "ob_id": 32597, "uuid": "c7aa24fb8d5c458daefdf0f4410ba830", "title": "NCEO Manaus plots AGB map 2014 v1.0", "abstract": "The NCEO Manaus plots Above Ground Biomass (AGB) map 2014 v1.0 shows above ground woody biomass in plot sites around the city of Manaus in the state of Amazonas, Brazil. The data supports characterization of carbon stocks and dynamics at the national level, which is critical for countries engaging in climate change mitigation and adaptation strategies. \r\n\r\nThe data consists of AGB for 22 plot sites in the dbf data file. The file is accompanied by shape and metadata files (sbx, shp, shx and prj files) containing plot location information enabling display in GIS applications such as QGIS.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": null, "updateFrequency": "", "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA). At present only data files and minimal metadata have been provided. We have no information to date on how the data were collected.", "removedDataReason": "", "keywords": "NCEO, AGB, Biomass, Manaus, forest, vegetated wetlands, wooded grassland", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2025-09-23T14:20:50", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 4883, "bboxName": "Manaus Forest AGB plots", "eastBoundLongitude": -60.0217, "westBoundLongitude": -60.0217, "southBoundLatitude": -3.119, "northBoundLatitude": -3.119 }, "verticalExtent": null, "result_field": { "ob_id": 44806, "dataPath": "/neodc/nceo_biomass_maps/data/manaus/v1.0/2014", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 13925, "numberOfFiles": 7, "fileFormat": "dbf, sbx, shp, shx, prj" }, "timePeriod": { "ob_id": 12634, "startTime": "2014-01-01T00:00:00", "endTime": "2014-12-31T00:00:00" }, "resultQuality": { "ob_id": 3676, "explanation": "Validated by the NCEO University of Leicester project team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-05-13" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 130 ], "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": 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": [ 145137, 145138, 145139, 145141, 145142, 145143, 214917, 214918 ], "onlineresource_set": [] }, { "ob_id": 32598, "uuid": "32274aca008b4f7799e8cea69ad3508e", "title": "Yucatan Peninsula and Central Mexico above ground biomass maps 2010 v5.0", "abstract": "This dataset contains the biomass maps for epoch 2: 2010 (GlobBiomass project reference year) for Yucatan peninsula and Central Mexico with a 30m spatial resolution. \r\n\r\nThe dataset contains 4 raster files corresponding to 2 areas in Mexico; the Yucatan Peninsula AGB-MEX_Yucatan2010_v5.tif, AGB_MEX_Yucatan2010_QA_v5.tif, Central Mexico, AGBMEX_Central2010_v5.tif and AGB_MEX_Central2010_QA_v5.tif. \r\n\r\nThe maps show aboveground woody biomass in Mexican forests and were generated by combining the probabilistic outputs. from a Maximum Entropy (MaxEnt) algorithm. Field inventory plots (CONAFOR, INFyS) were used in combination with SAR (JAXA ALOS PALSAR) and optical data (NASA Landsat 7), as well as a digital elevation model (NASA SRTM).,An empirical linear regression model with AGB as dependant variable (Ln-transformed) and SAR backscatter intensity (DN values) of the HV polarization as the independent variable was fitted to estimate AGB over mangrove and other wetland vegetation\r\n\r\nFurther information can be found in the documnetation section and in a read me file archived with the data", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-05-07T16:55:59", "updateFrequency": "", "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "NCEO, AGB, Mexico, Yucatan", "publicationState": "preview", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2776, "bboxName": "Mexico", "eastBoundLongitude": -86.1, "westBoundLongitude": -117.17, "southBoundLatitude": 13.42, "northBoundLatitude": 32.38 }, "verticalExtent": null, "result_field": { "ob_id": 32599, "dataPath": "/neodc/nceo_biomass_maps/data/mexico/v5.0/2010/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 540158114, "numberOfFiles": 6, "fileFormat": "GeoTIFF" }, "timePeriod": { "ob_id": 8951, "startTime": "2010-01-01T00:00:00", "endTime": "2010-01-31T00:00:00" }, "resultQuality": { "ob_id": 3676, "explanation": "Validated by the NCEO University of Leicester project team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-05-13" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 32596, "uuid": "dfee2403b85d4aad8bc655aec772be07", "short_code": "cmppr", "title": "NCEO Aboveground Biomass Map v21 2015", "abstract": "The map was generated by combining field inventory plots (KFS) with L-band SAR (JAXA ALOS-2 PALSAR-2) and multispectral optical data (NASA Landsat 8), by means of a Random Forests algorithm within a k-Fold calibration / validation framework." }, "imageDetails": [ 147 ], "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": 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": [ 145147, 145148, 145149, 145150, 145151, 145152, 145153, 145154, 145155 ], "onlineresource_set": [ 94320 ] }, { "ob_id": 32600, "uuid": "7b3bddd5af4945c2ac508a6d25537f0a", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Grounding line location for key glaciers, Antarctica, 1994-2020, v2.0", "abstract": "This dataset contains grounding line locations (GLL) for key glaciers in Antarctica, produced as part of the ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci) project. The data have been derived from satellite observations from the ERS-1/2, TerraSAR-X and Copernicus Sentinel-1 satellites, acquired between 1994 and 2020.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-06-08T10:21:21", "updateFrequency": "", "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "Ground line location, Antarctica, ESA, CCI", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-06-17T13:38:20", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2777, "bboxName": "", "eastBoundLongitude": 162.943832958, "westBoundLongitude": -155.546940082, "southBoundLatitude": -80.550372083, "northBoundLatitude": -64.898453194 }, "verticalExtent": null, "result_field": { "ob_id": 32708, "dataPath": "/neodc/esacci/ice_sheets_antarctica/data/grounding_line_locations/key_glaciers/v2.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 7999482, "numberOfFiles": 6, "fileFormat": "Shapefiles" }, "timePeriod": { "ob_id": 8952, "startTime": "1994-01-28T00:00:00", "endTime": "2021-01-19T23:59:59" }, "resultQuality": { "ob_id": 3677, "explanation": "See the Antarctic Ice Sheet CCI project documentation", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-05-17" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 32678, "uuid": "be7021278e334bd4865ae4ebcb79b53c", "short_code": "cmppr", "title": "Composite process for the ESA Antarctic Ice Sheets CCI: Grounding line location for key glaciers, v2.0", "abstract": "-" }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "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": [], "vocabularyKeywords": [], "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": [ 145157, 145158, 145159, 145160, 145162, 145163, 145167, 146440, 145168, 145164, 145165, 145166 ], "onlineresource_set": [ 42858, 42701, 42702, 42700 ] }, { "ob_id": 32601, "uuid": "00fe090efc58446e8980992a617f632f", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Antarctic Ice Sheet monthly velocity from 2017 to 2020, derived from Sentinel-1, v1", "abstract": "This dataset contains monthly gridded ice velocity maps of the Antarctic Ice Sheet derived from Sentin\r\nel-1 data acquired between 2017-01-01 and 2020-08-31. It was generated by ENVEO, as part of the ESA Antarctic Ice Sheet Climate Change Initiative project (Antarctic_Ice_Sheet_cci).\r\n\r\nThe surface velocity is derived by applying feature tracking techniques using Sentinel-1 synthetic aperture radar (SAR) data acquired in the Interferometric Wide (IW) swath mode. Ice velocity is provided at 200m grid spacing in Polar Stereographic projection (EPSG: 3031). The horizontal velocity components are provided in true meters per day, towards easting and northing direction of the grid. The vertical displacement is derived from a digital elevation model. Provided is a NetCDF file with the velocity components: vx, vy, vz, along with maps showing the magnitude of the horizontal components, the valid pixel count and uncertainty. The product combines all ice velocity maps, based on 6- and 12-day repeats, acquired within a single month in a monthly averaged product.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-06-16T10:06:32", "updateFrequency": "", "dataLineage": "Data were processed by ENVEO as part of the ESA Antarctic Ice sheet CCI project and are archived on the ENVEO Cryoportal (http://cryoportal.enveo.at) They have been supplied to CEDA in the context of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "Antarctic, Ice Sheet Velocity, ESA, CCI", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-06-17T14:01:35", "doiPublishedTime": "2021-06-28T16:02:08.246398", "removedDataTime": null, "geographicExtent": { "ob_id": 2778, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": -56.0 }, "verticalExtent": null, "result_field": { "ob_id": 32743, "dataPath": "/neodc/esacci/ice_sheets_antarctica/data/ice_velocity/antarctic_ice_sheet/sentinel_1/monthly/v1.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 101295328588, "numberOfFiles": 45, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 8953, "startTime": "2017-01-01T00:00:00", "endTime": "2020-08-31T23:59:59" }, "resultQuality": { "ob_id": 3678, "explanation": "Data are as given by the data provider. For more information see the Antarctic Ice Sheets CCI project documentation", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-05-17" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 32701, "uuid": "426d8d365d97418087cde06c426c4afd", "short_code": "cmppr", "title": "Composite process for the ESA Antarctic Ice Sheet Ice velocity from Sentinel-1, v1 dataset", "abstract": "-" }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "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, 13204, 13205, 13206, 13207, 50347, 50348, 50349, 50547, 50548, 62645 ], "vocabularyKeywords": [], "identifier_set": [ 10898 ], "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": [ 145169, 145170, 145171, 145172, 145173, 145174, 145175, 146442, 145176, 145177, 145178, 145179 ], "onlineresource_set": [ 42857, 42703, 42704, 42956, 87634 ] }, { "ob_id": 32602, "uuid": "e1dfd0ee655944b8a82ce0479c518747", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Antarctic Ice Sheet monthly Gravimetric Mass Balance basin product, v3.0, 2002-2020", "abstract": "This dataset contains the Gravimetric Mass Balance (GMB) basin product for the Antarctic Ice Sheet (AIS), generated by TU Dresden as part of the ESA Antarctic Ice Sheet Climate Change Initiatve (Antarctic_Ice_Sheet_cci). \r\n\r\nThe Gravimetric Mass Balance (GMB) product for the Antarctic Ice Sheet (AIS) is based on monthly snapshots of the Earth’s gravity field provided by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on satellite mission (GRACE-FO). The product relies on monthly gravity field solutions (L2) of release 06 generated at the Center for Space Research (University of Texas at Austin) and spans the period from April 2002 through July 2020. The GMB product covers the full GRACE mission period (April 2002 - June 2017) and is extended by means of GRACE-FO data starting from June 2018, thus including 187 monthly solutions. The mass change estimation is based on the tailored sensitivity kernel approach developed at TU Dresden. (Groh & Horwath, 2021)\r\n\r\nThe GMB basin product provides time series of integrated mass changes for 26 drainage basins and the aggregations of the Antarctic Peninsula, East Antarctica, West Antarctica and the entire AIS. Based on the GMB basin product, ice mass balance estimates, i.e. linear trend in the change in ice mass, were derived for all drainage basins and aggregations. A gridded GMB product is also available as a separate dataset.\r\n\r\nGroh, A. & Horwath, M. (2021). Antarctic Ice Mass Change Products from GRACE/GRACE-FO Using Tailored Sensitivity Kernels. Remote Sens., 13(9), 1736. doi:10.3390/rs13091736", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-06-15T14:41:11", "updateFrequency": "notPlanned", "dataLineage": "The data were generated by TU Dresden within the ESA Antarctic Ice Sheet CCI project and deposited at the Centre for Environmental Data Analysis (CEDA) for archiving and distribution via the CCI Open Data Portal.", "removedDataReason": "", "keywords": "ESA CCI, Antarctica, Ice Sheet Mass Balance, GRACE, GRACE-FO", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-06-17T14:15:03", "doiPublishedTime": "2021-06-28T16:02:54.673524", "removedDataTime": null, "geographicExtent": { "ob_id": 2779, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": -60.0 }, "verticalExtent": null, "result_field": { "ob_id": 32742, "dataPath": "/neodc/esacci/ice_sheets_antarctica/data/gravimetric_mass_balance/basin/v3.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 147610, "numberOfFiles": 2, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 8954, "startTime": "2002-04-18T00:00:00", "endTime": "2020-07-16T23:59:59" }, "resultQuality": { "ob_id": 3701, "explanation": "see the Antarctic Ice Sheet CCI project webpage", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-05-27" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 32698, "uuid": "6a84d7e2a1c0408aae6e75dd67bcd89c", "short_code": "cmppr", "title": "Composite process for the Antarctic Ice Sheet CCI Gravimetric Mass Balance products (v3.0)", "abstract": "Composite process for the Antarctic Ice Sheet CCI Gravimetric Mass Balance products (v3.0)" }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "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": [ 67712, 67713, 67714, 67715, 67716, 67717, 67718, 67719, 67720, 67721, 67722 ], "vocabularyKeywords": [ { "ob_id": 10840, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_grace", "resolvedTerm": "GRACE" } ], "identifier_set": [ 10900 ], "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": [ 145180, 145181, 145182, 145183, 145184, 145185, 145186, 146441, 145188, 145187 ], "onlineresource_set": [ 42705, 42706, 42707, 42853, 42855, 42958 ] }, { "ob_id": 32605, "uuid": "5b22789f362c43f3b3d1c65bc30c30ee", "title": "Deanhill C-band rain radar dual polar products", "abstract": "Dual-polar products from the Met Office's Deanhill C-band rain radar, Whiteparish, Wiltshire, England. Data include augmented ldr (linear depolarization ratio) and zdr (differential reflectivity) scan data (both long and short pulse). The radar is a C-band (5.3 cm wavelength) radar and data are received by the Nimrod system at 5 minute intervals.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2025-07-18T01:57:38", "updateFrequency": "continual", "dataLineage": "Data are acquired from rain radar network in the UK and Europe by the Met Office's NIMROD system. Single site data are then sent to the BADC by the Met Office's DART operational dissemination system. Raw polar data from single sites are sent through from the RADARNET team at the Met Office. On arrival at the Centre for Environmental Data Analysis (CEDA) the data are ingested after a one day quarantine, having been compressed and then compiled into daily tar balls for each data type.", "removedDataReason": "", "keywords": "Met Office, NIMROD, rain radar", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-06-02T08:35:56", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 117, "bboxName": "Deanhill rain radar ranage", "eastBoundLongitude": 0.39, "westBoundLongitude": -3.39, "southBoundLatitude": 49.18, "northBoundLatitude": 53.18 }, "verticalExtent": null, "result_field": { "ob_id": 32606, "dataPath": "/badc/ukmo-nimrod/data/single-site/deanhill/raw-dual-polar/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 710833347529, "numberOfFiles": 652, "fileFormat": "Data are in NIMROD data format. See linked documentation for further details." }, "timePeriod": { "ob_id": 8955, "startTime": "2017-05-24T10:03:00", "endTime": null }, "resultQuality": { "ob_id": 1497, "explanation": "Data are from the Met Office's operational NIMROD system", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2013-12-16" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 5741, "uuid": "aa57dddaa9f343b791d33d2c5eaec6a1", "short_code": "acq", "title": "Acquisition Process for: Deanhill Rainfall Data from the Met Office Nimrod System", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: NIMROD system, Met Office C-band radar; PLATFORMS: Dean Hill Radar Station, UK; " }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 69 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2532, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "ukmo_wx", "label": "restricted: ukmo_wx group", "licence": { "ob_id": 12, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement.pdf", "licenceClassifications": [ { "ob_id": 4, "classification": "academic" } ] } }, { "ob_id": 2533, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "ukmo_wx_gov", "label": "restricted: ukmo_wx_gov group", "licence": { "ob_id": 13, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement_gov.pdf", "licenceClassifications": [ { "ob_id": 5, "classification": "policy" } ] } } ], "projects": [ { "ob_id": 5736, "uuid": "ced06d1e5a8eacb69bf0029bf5f0e17a", "short_code": "proj", "title": "Met Office NIMROD Database", "abstract": "The Met Office run the NIMROD system as a short-term forcasting tool, primarily used for collating observational data such as rain radar data from across Europe" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 32603, "uuid": "ea21f06880c345e0bba8862c03fdf54a", "short_code": "coll", "title": "GRACES: Collection of remote sensing and surface observations", "abstract": "Collection of datasets produced by the NERC funded GRACES (G-band RAdar for Cloud and prEcipitation Studies) project and third-party datasets utilised by the project.\r\n\r\nIn addition to 3 GHz and 94 GHz radar data collected specifically for the GRACES project at the Chilbolton Atmospheric Observatory (CAO) the project made use of standard data products from a range of surface instrumentation from the CAO site. These were augmented with the use of data from the Met Office NIMROD rain radar network for specific case studies." }, { "ob_id": 5709, "uuid": "82adec1f896af6169112d09cc1174499", "short_code": "coll", "title": "Met Office Rain Radar Data from the NIMROD System", "abstract": "A collection of products from rain radars operated by the Met Office and other European agencies for the UK and Europe. This collection includes rain composite plots and data for the UK and Europe, plus single site radar data including rain rate data, single and dual-polar data products. \r\n\r\nThese were produced by the Met Office's Nimrod system. Nimrod is a fully automated system for weather analysis and nowcasting based around a network of C-band rainfall radars. This dataset has the fine-resolution analyses of rain rate for the UK and Europe.\r\n\r\nThe UK has a network of C-band rainfall radars and data form these are processed by the Met Office NIMROD system. Four or five radar scans at different elevations at each site are processed to give the best possible estimate of rainfall at the ground. The main quality checking method is routine evaluation using rain gauges as ground truth.\r\n\r\nThe BADC holds the analyses of rainfall rate at a time resolution of 5 or 15 minutes. Data are available from late 2002. Images are available for the UK as well as a further image including neighbouring European countries from 1999. Data files are available on a 1 km and 5 km Cartesian grid. Single radar site data are available for 2 and 5 km Cartesian grids for various UK radar sites.\r\n\r\nThe value of radar-based data from the Nimrod system has been highlighted repeatedly. For example, in two severe flooding events during 1998 (at Easter over the Midlands and in late October over Wales), estimates of surface rainfall derived from radar data provided evidence of the extent and severity of the rainfall events. The 2 km data files reach to 100 km from the radar, the 5km files to 250 km.\r\n\r\nDetailed radar site location are given in the Met Office Weather Radar Factsheet.\r\n\r\nTime resolution is 5 or 15 minutes depending on the product.\r\n\r\nVarious scripts have been made available under the software directory to aid use of these data, including within GIS applications." } ], "responsiblepartyinfo_set": [ 145229, 145230, 145219, 145222, 145225, 145226, 145227, 145228 ], "onlineresource_set": [ 42708, 42709, 42711, 42710 ] }, { "ob_id": 32607, "uuid": "9252ff9ddeb249a2bd8433e9ae9dfe13", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged carbon dioxide from TANSAT, generated with the OCFP algorithm, for global land areas, version 1.0", "abstract": "This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (CO2), derived from the TANSAT satellite, using the University of Leicester Full-Physics Retrieval Algorithm (UoL-FP, also known as OCFP). This dataset is also referred to as CO2_TAN_OCFP. This version of the dataset provides data globally over land. For further information on the dataset, please see the linked documentation.\r\n\r\nInitially this dataset contains two months of data (June and August 2017), delivered as part of the GHG_cci Climate Research Data Package 6. Additional time periods will be added in the future.\r\n\r\n\r\nThis data has been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme, with support from the UK's National Centre for Earth Observation (NCEO).", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-08-04T17:31:20", "updateFrequency": "notPlanned", "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. This data has been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme, with support from the UK's National Centre for Earth Observation (NCEO).", "removedDataReason": "", "keywords": "ESA, CCI, satellite, TANSAT, atmosphere, carbon dioxide, CO2", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-08-06T10:42:35", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 33016, "dataPath": "/neodc/esacci/ghg/data/cci_plus/CO2_TAN_OCFP/v1.0_global_land/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 518692308, "numberOfFiles": 60, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 8956, "startTime": "2017-06-01T00:00:00", "endTime": "2017-08-31T23:59:59" }, "resultQuality": { "ob_id": 3550, "explanation": "For further information see the End to End ECV Uncertainty budget report", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2020-09-28" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 31873, "uuid": "1ff83a3b15e44b66a72005043d4cff27", "short_code": "cmppr", "title": "Composite Process for the ESA CCI Greenhouse Gases product: Column-averaged carbon dioxide from TANSAT, generated with the OCFP algorithm, version 1.0", "abstract": "Composite Process for the ESA CCI Greenhouse Gases product: Column-averaged carbon dioxide from TANSAT, generated with the OCFP algorithm, version 1.0" }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "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": [ 50542, 50543, 55535, 63576, 66452, 66456, 66719, 68622, 68624, 68625, 68626, 68630, 68635, 68636, 68637, 68638, 68639, 68640, 68641, 68646, 69372, 69373, 69374, 69375, 69629, 69802, 69803, 69804, 70614 ], "vocabularyKeywords": [ { "ob_id": 10664, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_ghg", "resolvedTerm": "greenhouse gases" } ], "identifier_set": [], "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." }, { "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": [ 145315, 145319, 145313, 145314, 145320, 145318, 145317, 145316, 145321, 147415 ], "onlineresource_set": [ 42717, 42712, 42713, 42714, 42715, 43345 ] }, { "ob_id": 32609, "uuid": "b0de069568a141b0b074ca0f7cee004b", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column averaged carbon dioxide from OCO-2 generated with the FOCAL algorithm, version 09", "abstract": "This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (XCO2), using the fast atmospheric trace gas retrieval for OCO2 (FOCAL-OCO2). The FOCAL-OCO2 algorithm which has been setup to retrieve XCO2 by analysing hyper spectral solar backscattered radiance measurements from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite. FOCAL includes a radiative transfer model which has been developed to approximate light scattering effects by multiple scattering at an optically thin scattering layer. This reduces the computational costs by several orders of magnitude. FOCAL's radiative transfer model is utilised to simulate the radiance in all three OCO-2 spectral bands allowing the simultaneous retrieval of CO2, H2O, and solar induced chlorophyll fluorescence. The product is limited to cloud-free scenes on the Earth's day side. This dataset is also referred to as CO2_OC2_FOCA.\r\n\r\nThis version of the data (v09) was produced as part of the European Space Agency's (ESA) \r\nClimate Change Initiative (CCI) Greenhouse Gases (GHG) project (GHG-CCI+, http://cci.esa.int/ghg)\r\nand got co-funding from the Univ. Bremen and EU H2020 projects CHE (grant agreement no. 776186) and VERIFY (grant agreement no. 776810).\r\n\r\nWhen citing this data, please also cite the following peer-reviewed publications:\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, V.Rozanov, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 1: Radiative Transfer and a Potential OCO-2 XCO2 Retrieval Setup, Remote Sensing, 9(11), 1159; doi:10.3390/rs9111159, 2017\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 2: Application to XCO2 Retrievals from OCO-2, Remote Sensing, 9(11), 1102; doi:10.3390/rs9111102, 2017", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-05-28T15:25:18", "updateFrequency": "notPlanned", "dataLineage": "This version of the data was produced as part of the European Space Agency's (ESA) \r\nClimate Change Initiative (CCI) Greenhouse Gases (GHG) project (GHG-CCI+, http://cci.esa.int/ghg)\r\nand got co-funding from the Univ. Bremen and EU H2020 projects CHE (grant agreement no. 776186) and VERIFY (grant agreement no. 776810).\r\nData were supplied to CEDA for archiving as part of the ESA CCI Open Data Portal.", "removedDataReason": "", "keywords": "ESA, CCI, satellite, CO2", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2021-09-02T15:55:52", "doiPublishedTime": "2021-09-08T10:43:16", "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": 32610, "dataPath": "/neodc/esacci/ghg/data/cci_plus/CO2_OC2_FOCA/v9.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 8044862560, "numberOfFiles": 1790, "fileFormat": "Data are netCDF formatted." }, "timePeriod": { "ob_id": 8957, "startTime": "2015-01-01T00:00:00", "endTime": "2020-05-30T23:59:59" }, "resultQuality": { "ob_id": 3389, "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA)", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2020-02-28" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 33058, "uuid": "4d90fa654eda41b982c9b59de3b0fc4e", "short_code": "cmppr", "title": "Composite process for the ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column averaged carbon dioxide from OCO-2 generated with the FOCAL algorithm", "abstract": "The data has been generated from the OCO-2 satellite using the FOCAL-OCO2 algorithm" }, "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": [ 1050, 1635, 1636, 11820, 11831, 11841, 11842, 11846, 11848, 23212, 28592, 28593, 28594, 28595, 28596, 28597 ], "vocabularyKeywords": [], "identifier_set": [ 10944 ], "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": [ 145326, 145328, 145322, 145325, 145324, 145323, 145329, 145327, 145330, 145331, 145332, 145333 ], "onlineresource_set": [ 42718, 42719, 42720, 42721, 42722, 42723, 42725, 42724, 42726, 94779 ] }, { "ob_id": 32612, "uuid": "67a3f8c8dc914ef99f7f08eb0d997e23", "title": "ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost active layer thickness for the Northern Hemisphere, v3.0", "abstract": "This dataset contains permafrost active layer thickness data produced as part of the European Space Agency's (ESA) Climate Change Initiative (CCI) Permafrost project. It forms part of the second version of their Climate Research Data Package (CRDP v2). It is derived from a thermal model driven and constrained by satellite data. Grid products of CDRP v2 are released in annual files, covering the start to the end of the Julian year. The maximum depth of seasonal thaw is provided, which corresponds to the active layer thickness.\r\n\r\nCase A: This covers the Northern Hemisphere (north of 30°) for the period 2003-2019 based on MODIS Land Surface temperature merged with downscaled ERA5 reanalysis near-surface air temperature data.\r\nCase B: This covers the Northern Hemisphere (north of 30°) for the period 1997-2002 based on downscaled ERA5 reanalysis near-surface air temperature data which are bias-corrected with the Case A product for the overlap period 2003-2019 using a pixel-specific statistics for each day of the year.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-05-21T14:16:10", "updateFrequency": "notPlanned", "dataLineage": "Data have been produced by the ESA CCI Permafrost project as part of ESA's Climate Change Initiative programme", "removedDataReason": "", "keywords": "Permafrost, CCI, Active layer thickness", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-06-25T16:58:28", "doiPublishedTime": "2021-06-28T12:35:46", "removedDataTime": null, "geographicExtent": { "ob_id": 2565, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": 30.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 32613, "dataPath": "/neodc/esacci/permafrost/data/active_layer_thickness/L4/area4/pp/v03.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 7139645166, "numberOfFiles": 24, "fileFormat": "Data are netCDF formatted." }, "timePeriod": { "ob_id": 8959, "startTime": "1997-01-01T00:00:00", "endTime": "2019-12-31T23:59:59" }, "resultQuality": { "ob_id": 3561, "explanation": "Data is as provided by the Permafrost CCI project. For further quality information see the permafrost CCI website and linked documentation.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2020-10-21" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32737, "uuid": "fbfa5bb9c569492bb7ec68678dff7d52", "short_code": "comp", "title": "Computation of Permafrost v3 datsets by the ESA Permafrost CCI", "abstract": "The Permafrost CCI project has created Earth Observation (EO) based products for the permafrost Essential Climate Variable (ECV) spanning the last two decades. Since ground temperature and thaw depth cannot be directly observed from space-borne sensors, a variety of satellite and reanalysis data are combined in a ground thermal model. The algorithm uses remotely sensed data sets of Land Surface Temperature (MODIS LST/ ESA LST CCI) and landcover (ESA LandcoverCCI) to drive the transient permafrost model CryoGrid 2, which yields thaw depth and ground temperature at various depths, while ground temperature forms the basis for permafrost fraction.\r\n\r\nInput data: MODIS Land surface temperature is used as the main input for the L4 production for 2003-2019 data. Sensors of auxiliary data are listed in the meta data.\r\nDownscaled and bias corrected ERA reanalyses data based on statistics of the overlap period between ERA reanalysis and MODIS LST are used for data before 2003. Sensors of auxiliary data are listed in the meta data." }, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "permissions": [ { "ob_id": 2596, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 58, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_permafrost_terms_and_conditions.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 29966, "uuid": "7133bbd64540498bbffd1c28bbbea9cd", "short_code": "proj", "title": "ESA Permafrost Climate Change Initiative Project", "abstract": "The Permafrost Climate Change Initiatve Project (Permafrost_cci) is part of the European Space Agency's Climate Change Initiative Programme. The ultimate objective of Permafrost_cci is to develop and deliver permafrost maps of Essential Climate Variable products, primarily derived from satellite measurements." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 27732, 50416, 50547, 50548, 70620 ], "vocabularyKeywords": [ { "ob_id": 11084, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_asar", "resolvedTerm": "ASAR" }, { "ob_id": 11091, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_avhrr3", "resolvedTerm": "AVHRR-3" }, { "ob_id": 11103, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_meris", "resolvedTerm": "MERIS" }, { "ob_id": 11105, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_modis", "resolvedTerm": "MODIS" }, { "ob_id": 11118, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_sarX", "resolvedTerm": "SAR-X" }, { "ob_id": 11133, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_vegetation", "resolvedTerm": "VEGETATION" }, { "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": 10888, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_noaa_15", "resolvedTerm": "NOAA-15" }, { "ob_id": 10889, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_noaa_16", "resolvedTerm": "NOAA-16" }, { "ob_id": 10890, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_noaa_17", "resolvedTerm": "NOAA-17" }, { "ob_id": 11135, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_probaV", "resolvedTerm": "PROBA-V" }, { "ob_id": 10923, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_terra", "resolvedTerm": "Terra" } ], "identifier_set": [ 10896 ], "observationcollection_set": [ { "ob_id": 32783, "uuid": "8239d5f6263f4551bf2bd100d3ecbead", "short_code": "coll", "title": "ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost version 3 data products", "abstract": "This collection of data forms the Permafrost Climate Research Data Package (CRDP v2), which comprises the Version 3.0 Permafrost data products from the European Space Agency's (ESA) Climate Change Initiative (CCI) Permafrost project. Data products include Ground Temperature, Active Layer Thickness and Permafrost Extent for the Northern Hemisphere (north of 30°) for the period 1997-2019. They are derived from a thermal model driven and constrained by satellite data. Gridded products are released in annual files, covering the start to the end of the Julian year. This corresponds to average annual ground temperatures, as well as the maximum depth of seasonal thaw, which corresponds to the active layer thickness." } ], "responsiblepartyinfo_set": [ 145356, 145349, 145350, 145351, 145352, 145355, 145353, 145354, 145357, 145358, 145359, 145360, 145361, 145362, 145363, 145364, 145365, 145366, 145367, 145368, 145369, 145370, 145371, 145372, 145373, 145374 ], "onlineresource_set": [ 42732, 42733, 42735, 42734, 89051, 89052, 89053, 89054, 89055, 89056, 89057, 89058, 87781 ] }, { "ob_id": 32614, "uuid": "6e2091cb0c8b4106921b63cd5357c97c", "title": "ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost extent for the Northern Hemisphere, v3.0", "abstract": "This dataset contains permafrost extent data produced as part of the European Space Agency's (ESA) Climate Change Initiative (CCI) Permafrost project. It forms part of the second version of their Climate Research Data Package (CRDP v2). It is derived from a thermal model driven and constrained by satellite data. Grid products of CDRP v2 are released in annual files, covering the start to the end of the Julian year. This corresponds to average annual ground temperatures (at 2 m depth) which forms the basis for the retrieval of yearly fraction of permafrost-underlain and permafrost-free area within a pixel. A classification according to the IPA (International Permafrost Association) zonation delivers the well-known permafrost zones, distinguishing isolated (0-10%) sporadic (10-50%), discontinuous (50-90%) and continuous permafrost (90-100%).\r\n\r\nCase A: This covers the Northern Hemisphere (north of 30°) for the period 2003-2019 based on MODIS Land Surface temperature merged with downscaled ERA5 reanalysis near-surface air temperature data. \r\nCase B: This covers the Northern Hemisphere (north of 30°) for the period 1997-2002 based on downscaled ERA5 reanalysis near-surface air temperature data which are bias-corrected with the Case A product for the overlap period 2003-2019 using a pixel-specific statistics for each day of the year.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-05-21T14:06:19", "updateFrequency": "notPlanned", "dataLineage": "Data have been produced by the ESA CCI Permafrost project as part of ESA's Climate Change Initiative programme", "removedDataReason": "", "keywords": "Permafrost, CCI, Permafrost Extent", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-06-25T16:57:59", "doiPublishedTime": "2021-06-28T12:35:13", "removedDataTime": null, "geographicExtent": { "ob_id": 2568, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": 30.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 32615, "dataPath": "/neodc/esacci/permafrost/data/permafrost_extent/L4/area4/pp/v03.0", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 3617214388, "numberOfFiles": 24, "fileFormat": "Data are netCDF formatted." }, "timePeriod": { "ob_id": 8958, "startTime": "1997-01-01T00:00:00", "endTime": "2019-12-31T23:59:59" }, "resultQuality": { "ob_id": 3563, "explanation": "Data are as provided by the Permafrost CCI project. For further quality information see the permafrost CCI website and linked documentation.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2020-10-21" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32737, "uuid": "fbfa5bb9c569492bb7ec68678dff7d52", "short_code": "comp", "title": "Computation of Permafrost v3 datsets by the ESA Permafrost CCI", "abstract": "The Permafrost CCI project has created Earth Observation (EO) based products for the permafrost Essential Climate Variable (ECV) spanning the last two decades. Since ground temperature and thaw depth cannot be directly observed from space-borne sensors, a variety of satellite and reanalysis data are combined in a ground thermal model. The algorithm uses remotely sensed data sets of Land Surface Temperature (MODIS LST/ ESA LST CCI) and landcover (ESA LandcoverCCI) to drive the transient permafrost model CryoGrid 2, which yields thaw depth and ground temperature at various depths, while ground temperature forms the basis for permafrost fraction.\r\n\r\nInput data: MODIS Land surface temperature is used as the main input for the L4 production for 2003-2019 data. Sensors of auxiliary data are listed in the meta data.\r\nDownscaled and bias corrected ERA reanalyses data based on statistics of the overlap period between ERA reanalysis and MODIS LST are used for data before 2003. Sensors of auxiliary data are listed in the meta data." }, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "permissions": [ { "ob_id": 2596, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 58, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_permafrost_terms_and_conditions.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 29966, "uuid": "7133bbd64540498bbffd1c28bbbea9cd", "short_code": "proj", "title": "ESA Permafrost Climate Change Initiative Project", "abstract": "The Permafrost Climate Change Initiatve Project (Permafrost_cci) is part of the European Space Agency's Climate Change Initiative Programme. The ultimate objective of Permafrost_cci is to develop and deliver permafrost maps of Essential Climate Variable products, primarily derived from satellite measurements." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 27732, 50416, 50547, 50548, 64149 ], "vocabularyKeywords": [ { "ob_id": 11084, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_asar", "resolvedTerm": "ASAR" }, { "ob_id": 11091, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_avhrr3", "resolvedTerm": "AVHRR-3" }, { "ob_id": 11103, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_meris", "resolvedTerm": "MERIS" }, { "ob_id": 11105, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_modis", "resolvedTerm": "MODIS" }, { "ob_id": 11118, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_sarX", "resolvedTerm": "SAR-X" }, { "ob_id": 11133, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_vegetation", "resolvedTerm": "VEGETATION" }, { "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": 10888, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_noaa_15", "resolvedTerm": "NOAA-15" }, { "ob_id": 10889, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_noaa_16", "resolvedTerm": "NOAA-16" }, { "ob_id": 10890, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_noaa_17", "resolvedTerm": "NOAA-17" }, { "ob_id": 11135, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_probaV", "resolvedTerm": "PROBA-V" }, { "ob_id": 10923, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_terra", "resolvedTerm": "Terra" } ], "identifier_set": [ 10895 ], "observationcollection_set": [ { "ob_id": 32783, "uuid": "8239d5f6263f4551bf2bd100d3ecbead", "short_code": "coll", "title": "ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost version 3 data products", "abstract": "This collection of data forms the Permafrost Climate Research Data Package (CRDP v2), which comprises the Version 3.0 Permafrost data products from the European Space Agency's (ESA) Climate Change Initiative (CCI) Permafrost project. Data products include Ground Temperature, Active Layer Thickness and Permafrost Extent for the Northern Hemisphere (north of 30°) for the period 1997-2019. They are derived from a thermal model driven and constrained by satellite data. Gridded products are released in annual files, covering the start to the end of the Julian year. This corresponds to average annual ground temperatures, as well as the maximum depth of seasonal thaw, which corresponds to the active layer thickness." } ], "responsiblepartyinfo_set": [ 145377, 145378, 145382, 145375, 145376, 145379, 145380, 145381, 145383, 145384, 145385, 145386, 145387, 145388, 145389, 145390, 145391, 145392, 145393, 145394, 145395, 145396, 145397, 145398, 145399, 145400 ], "onlineresource_set": [ 42738, 42736, 42737, 42739, 89059, 89060, 89061, 89062, 89063, 89064, 89065, 89066, 89067, 89068, 87772 ] }, { "ob_id": 32616, "uuid": "fdb8960260a64c5faf652f8f47c4df81", "title": "APHH: Non-methane volatile organic compound emission inventories from burning studies performed as part of the APHH-INDIA project (DelhiFlux).", "abstract": "This contains gridded non-methane volatile organic compound (NMVOC) emission inventories for India derived as part of burning studies performed during the APHH-INDIA campaign. For data files with more than 1 million rows, NASA AMES metadata headers have been provided as a separate document, which has the identical name of the data it applies to but also includes _metadata.\r\n\r\nFor years 1993, 1994, 1999, 2002, 2005, 2006, 2007, 2010, 2011 and 2016 inventories have been produced in terms of total NMVOC emission from each source sector (kg/km2). There are also two upper limit scenarios of emissions from cow dung cake combustion based on data from PPAC and PPAC supplemented with additional cow dung cake consumption for states now covered by this survey. The speciation factors of NMVOCs released from particular sources are also provided so that these years can be speciated by source simply by multiplying the total emission from each source by the ratio of species released from the source. This allows future users to produce speciated emission inventories for years other than 2011 if they need.\r\n\r\nGridded inventories are also provided for emissions of 21 polycyclic aromatic hydrocarbons for the year 2011 from fuelwood, cow dung cake, charcoal, liquefied petroleum gas and municipal solid waste. These are provided as total PAH emissions from a source with speciation factors also provided to allow speciation should it be required by multiplying the total NMVOC emission from a source by the speciation factors from that source. \r\n\r\nGridded inventories are provided for crop residue burning at 1km2 and 10km2. These were calculated with total agricultural area identified in a state from either NASA MODIS (1 km2) or Ramankutty et al. (2008) (10 km2). A second inventory was produced at 10km2 as it was felt that the NASA data offered little variation within respective states. These have been split into total emissions from each of the 5 emission factors applied, RiceEFyearlyVOCKG (for rice), WheatEFyearlyVOCKG (for wheat, coarse cereal and maize), JowarEFyearlyVOCKG (for Jowar and Bajra), MeanEFyearlyVOCKG (for 9 oilseeds, groundnut, rapeseed, mustard, sunflower, cotton, jute and mesta) and SugarcaneEFyearlyVOCKG (for sugarcane). \r\n\r\nThe inventories were produced using emission factors developed as part of the APHH-INDIA project as well as from a different publication focussed on the burning of crops. The inventories have been developed in the following manner. The emission factors used in this study come from a variety of recently published sources. All emission factors applied in this study included measurement by PTR-ToF-MS, a technique well suited to species released in significant quantities from solid fuel combustion such as small oxygenated species, phenolics and furanics. These species are often missed by GC measurement alone. Preference has been given to emission factors from studies which: (1) have many measurements (n), (2) use samples collected from India or (3) use samples collected from similar countries. Fully speciated emission factors are available from the references given. For residential fuel combustion, the emission factors measured by Stewart et al. (2021a) were used and were developed from 76 combustion experiments of fuel wood, cow dung cake, LPG and MSW samples collected from around Delhi. This study was extremely detailed and measured online, gas-phase, speciated NMVOC emission factors for up to 192 chemical species using dual-channel gas chromatography with flame ionisation detection (DC-GC-FID, n = 51), two-dimensional gas chromatography (GC×GC-FID, n = 74), proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS, n = 75) and solid-phase extraction two-dimensional gas chromatography with time-of-flight mass spectrometry (SPE-GC×GC-ToF-MS, n = 28). Comparison of these emission factors to those obtained in similar studies is provided in Stewart et al. (2021a). The emission factors used as part of this study are larger than those measured by Stockwell et al. (2016), Fleming et al. (2018) and several other studies which were based on gas chromatography techniques alone. The emission factors here measure many more NMVOC species, use techniques which target a range of species which more traditional GC analyses do not detect and make online measurements which minimise loss of intermediate-volatility and semi-volatile organic species, which may be lost through the collection of whole air samples, but have been shown to represent a large proportion of total emissions from biomass burning (Stockwell et al., 2015).\r\n\r\nEmission factors for combustion of crop residues on fields were taken from measurements by Stockwell et al. (2015) made using PTR-ToF-MS of 115 NMVOCs (Stockwell et al., 2015) for wheat straw (n = 6), sugarcane (n=2), rice straw (n=7) and millet (n=2). This study also included the mean crop residue emission factor for 19 food crops, for use when no current emission factor had been comprehensively measured using PTR-ToF-MS. The emission factor applied (38.8 g kg-1) was evaluated against that for crop residues used for domestic combustion in Delhi (37.9 g kg-1). Whilst the values measured by Stockwell et al. (2015) and Stewart et al. (2021a) were comparable, the value from Stockwell et al. (2015) was used as the crop types were more reflective of the crop residues burnt on fields after harvest, compared to those burnt to meet residential energy requirements. The mean emission factor for crop residue combustion on fields was used for specific crop types with smaller levels of cultivation.\r\nEmissions from coal burning were estimated using a mean emission factor from the combustion of bituminous coal from China (n = 14), a neighbouring Asian country, made using PTR-ToF-MS. Whilst the chemical composition of the coal may be more important than the development status of the country, there was overall a low level of reported residential coal use and this estimate was included for completeness. A total of 89 NMVOCs were identified, which represented 90-96% of the total mass spectra (Cai et al., 2019). \r\n\r\nIndian specific PAH emission factors were recently measured in gas- and particle-phases using PTR-ToF-MS and GC×GC-ToF-MS (Stewart et al., 2021). This dataset provided PAH emission factors collected from combustion of fuel wood (n = 16), cow dung cake (n = 3), crop residue from domestic combustion (n = 3), MSW (n = 3), LPG (n = 1) and charcoal (n = 1) samples. \r\n\r\nHigh resolution, gridded population data for India (WorldPop, 2017) was used at a resolution of 1 km2. Officially, urban populations in India are defined as having a population density > 400 people km-2, 75% of men employed in non-agricultural industries and a population of town > 5000 people. Rural populations in India cannot be identified simply by having a population density of < 400 people km-2, as some states such as Uttar Pradesh have an average population density of around 800 people km-2. Rural grid squares were therefore identified by calculating the population density threshold in each state in which the sum of the 1km2 grid squares below this threshold correctly reproduced the rural populations in these states from the 2001 and 2011 censuses (Government of India, 2014). A small uncertainty existed over the exact population of India and we used population statics indicated by the 2011 census. NMVOC and PAH emissions from domestic solid fuel combustion were plotted against this high-resolution population data in the R statistical programming language at 1 km2 for 2001 and 2011, with the population datasets scaled to the percentage changes in Indian population indicated by the World Bank for additional years of interest. \r\n\r\nPreference was given to large fuel usage surveys which included tens to hundreds of thousands of respondents. The Household Consumption of Goods and Services in India survey by the National Sample Survey Office (NSSO, 2007a, 2012a, 2014) gave state-wise kg capita-1 fuel wood, LPG, charcoal and coal burning statistics for rural and urban environments and was used for the years 2004-2005, 2009-2010 and 2011-2012. NMVOC emissions for these years were calculated by multiplying the NMVOC emission factor for the fuel, by the yearly fuel consumption per capita by the population of the grid cell. \r\n\r\n\r\nData were collected from additional large surveys previously conducted. These surveys collected data in terms of the number of households using specific fuels per 1000 households in different Indian states in rural and urban environments. The Fifth Quinquennial Survey on Consumer Expenditure provided data for 1993-1994 (NSSO, 1997), the Energy Sources of Indian Households for Cooking and Lighting provided data for years 2004-2005, 2009-2010 and 2010-2011 (NSSO, 2007b, 2012b, 2015) and the Household Consumer Expenditure and Employment-Unemployment Situation in India for 2002 and 2006-2007 (NSSO, 2003, 2008). The National Family Health Survey presented India-wide fuel use as a percentage of the population. To reflect spatial variation in fuel use, the raw data from these surveys were accessed (from the DHS Programme, U.S. Agency for International Development), extracted through the SPSS statistics software package and processed in the R programming language. This increased fuel usage data availability as the number of households per 1000 households using specific fuels in Indian states and covered the years 1992-1993, 1998-1999, 2005-2006 and 2015-2016 (International Institute for Population Sciences, 1995, 2000, 2007, 2017). These were extensive datasets with 1992-1993, 1998-1999 and 2005-2006 surveying just under 100,000 households and 2015-2016 around 600,000 households.\r\n\r\nTo allow the incorporation of data from years which were based on the number of households using a particular fuel per 1000 households (1993, 1994, 1999, 2002, 2006, 2007 and 2016), a scaling factor was developed. The scaling factor was based on the ratio of fuel use in the state from years where per capita data was available. It was possible to link the Household Consumption of Goods and Services in India and the Energy Sources of Indian Households for Cooking and Lighting surveys for the years 2005, 2010 and 2011. This was done using years where the number of households per 1000 households and kg capita-1 fuel usage statistics were available, as it was possible to calculate the amount of fuel a primary user would use. The fuel use of a primary user here was defined as the amount of fuel a person would burn who was recorded to use a specific fuel type. For example, if the per capita consumption in the Household Consumption of Goods and Services survey in India for fuel wood was 10 kg per capita per 30 days, and the Energy Sources of Indian Households for Cooking and Lighting survey showed 250 households per 1000 households used fuel wood, then the fuel use was estimated to be 40 kg per primary user per 30 days. This was achieved by multiplying the per capita usage for a particular fuel type by the inverse of the ratio of fuel usage in that state in rural or urban environments. The amount of fuel a primary user would use was then used to estimate the amount of fuel consumed per capita in years where only usage per 1000 household statistics were available.\r\n\r\nCow dung cake consumption was only reported as number of households per 1000 in these surveys and the amount of cow dung cake burnt per primary user was determined based on the energy density compared to fuel wood. This was done using calorimetry data which showed that cow dung cake was 1.3-1.9 times less efficient than fuel wood (EPA, 2000; Gadi et al., 2012). For this reason, the amount of fuel per primary user for fuel wood in a state has been multiplied by 1.6 to give the equivalent amount of cow dung cake a user would need to burn for their cooking needs. Upper and lower estimates for cow dung cake consumption were based on the range 1.3-1.9. This was then converted to fuel use per capita in kg per user per 30 days by rearranging E2. This has been evaluated to validate this approach, which estimated Indian cow dung cake consumption to be in the range 25.7-79.7 Tg yr-1 from 1993-2016. This was generally towards the lower end of consumption values previously reported of 35-128 Tg yr-1 (Habib et al., 2004). For this reason, emission inventory estimates were also compared to those produced using cow dung cake consumption based on the TERI Energy Data Directory and Yearbook (TEDDY) 2012/2013 data and a study from the Petroleum Planning & Analysis Cell (PPAC) from 2016 with population indicated at the 2011 level (TEDDY, 2012; PPAC, 2016).\r\n\r\n\r\nThe amount of MSW burnt was estimated using an established approach (IPCC, 2006; Wiedinmyer et al., 2014) with revised inputs for India based on per capita MSW generation from over 300 Indian cities (Annepu et al., 2012), state wise MSW collection figures (CPCB, 2013) as well as estimates of the amount of urban (NEERI, 2010) and rural MSW burnt (World Bank, 2012). This estimate does not include incineration for electrical power generation. \r\n\r\nWiedinmyer et al. (2014) assessed worldwide emissions from MSW burning based on IPCC guidelines (IPCC, 2006). The approach used here was similar, with modifications to the input data which made them more specific to India. The approach split the amount of MSW burnt into the MSW burnt by rural and urban populations in the country. For rural populations this was given by per capita rural MSW generation multiplied by the population of rural grid cell multiplied by the fraction of MSW burnt residentially. Per capita rural MSW generation was set at the lower limit indicated by the World Bank for South Asia of 0.12 kg capita-1 day-1 and evaluated in the range 0.08 kg capita-1 day-1 (Parmar and Pamnani, 2018) to 0.12 kg capita-1 day-1 (World Bank, 2012). The fraction of MSW burnt rurally was set to 0.6 which was the IPCC estimate (IPCC, 2006) and was further supported by a recent study which showed that only around 40% of rural MSW was collected in South Asia (Kaza et al., 2018).\r\n\r\nThe fraction of MSW burnt for an urban population was estimated by the sum of two calculations. The first was for street MSW burning which was calculated by per capita urban MSW generation multiplied by the population of urban grid cell multiplied by the fraction of MSW which was not collected multiplied by the fraction burnt.\r\n\r\nThe weighted per capita urban MSW generation was calculated by averaging per capita MSW generation statistics from 366 Indian cities by state (Annepu et al., 2012). The fraction of MSW which was uncollected was calculated from the Central Pollution Control Board (CPCB), as the difference in the amount of MSW generated and collected (CPCB, 2013). Urban per capita MSW generation was scaled to its estimated change for different years of interest.\r\n\r\nThe second calculation was for the MSW burnt on landfill sites, which was calculated by the MSW per capita produced in urban environments, multiplied by the urban population, multiplied by the fraction collected in an urban environment multiplied by the fraction burnt at the landfill site. The fraction of MSW collected came from CPCB statistics, but was reduced by 17-50% due to the informal recycling sector, based on very limited data from studies focussed on MSW recovery by the informal sector which showed 17% recovery in Delhi (Talyan et al., 2008), 20% recovery at a landfill site in Pune (Annepu et al., 2012), 4% in Pondicherry (Rajamanikam et al., 2014) and up to 40-50% in Mohali (Nandy et al., 2015). This was due to the large contribution of the informal recycling sector to recycling in India, where waste was collected by waste merchants, garbage collectors and waste pickers from highways, waste depots and landfill sites. This was an important consideration in India as studies have shown recovery of between 8.5-80 kg of material per picker per day and large cities such as Delhi having 80,000-100,000 pickers (Nandy et al., 2015). The fraction of waste burnt in a dump (Bfrac,dump) was given by NEERI who estimated that 10% of landfill MSW in Mumbai was burnt (NEERI, 2010). This was reinforced by a further study which examined the amount of waste burnt based on satellite studies of a landfill site in India which showed that approximately 10% of the waste that entered the site each day ended up being burnt (Sharma et al., 2019). Bfrac,dump was notably lower here (0.1) than in Wiedinmyer et al. (2014) (0.6) which was based on the 2006 IPCC Guidelines for National GHG Inventories. The estimate used in this study represented a conservative estimate of NMVOC emissions from landfill fires. Due to lack of reliable data in establishing Bfrac,dump, and the associated uncertainty, the sensitivity of urban landfill burning emissions over the range 0.1-0.6 was evaluated as part of the uncertainty range given in this study. This provided the upper limit to the uncertainty range of the potential amount of landfill waste burnt. This depicts scenarios before the new MSW management rules in 2016. \r\n\r\nNMVOC emissions from crop residue burning on fields in India were estimated to evaluate the relative importance of different burning sources using the most up-to-date input data currently available. A calculation was carried out for 2011, as NMVOC emissions from crop-residue burning on fields showed little year-on-year variation from 1995-2009 (Jain et al., 2014). The residue generated from the cultivation of four main categories of crops was estimated. The amount of crop types produced in each state (Ministry of Agriculture, 2012) was collated for cereals (rice, wheat, coarse cereals, maize, jowar, bajra), oilseeds (groundnut, rapeseed, mustard, sunflower and 9 oilseeds), fibres (cotton, jute and mesta) and sugarcane. The amount burnt was calculated using India specific estimates of the residue to crop ratio, dry matter fraction and fraction burnt (Jain et al., 2014). Emissions were estimated using factors from recent studies of crop residues routinely burnt on fields using PTR-ToF-MS (Stockwell et al., 2015). When the exact residue was measured (e.g., rice straw, wheat straw, sugarcane and millet) the correct emission factor was used. For cases where the exact residue was not measured, the mean reported crop residue emission factor was used. The spatial distribution of croplands was then either indicated using agricultural land identified by the high-resolution 500 m NASA MODIS land use product reduced to 1 km2 resolution or through croplands identified at 10 km2 through evaluation of the distribution of agricultural lands (Ramankutty et al., 2008). The total amount of crop residue burnt in a state was calculated using the approach given in Jain et al. (2014) but with the up-to-date inputs discussed. \r\n\r\nThe inventories were produced by Gareth Stewart at the University of York. Full details of the methodology are provided in the publication associated with these inventories. \r\n\r\nThe inventories provided here cover most of the land mass of India, but may vary slightly compared to those presented in the publication. This is associated with the North of India, particularly around the Pakistan and Chinese borders. This is due to how the boundaries of India were defined in the base data used for this study (WorldPop and GADM) and changes to states in the North of India after the period of interest (i.e. formation of Ladakh in 2019).\r\nAn inventory for coal has not been included due to low total emissions. \r\n\r\nAcronyms\r\n\r\nPAH = Polycyclic aromatic hydrocarbon\r\n\r\nNMVOCs = non-methane volatile organic compounds\r\n\r\nMSW = Municipal solid waste\r\n\r\nCrop = agricultural crop residue \r\n\r\nWood = Fuel wood\r\n\r\nDung = Cow dung cakes\r\n\r\nCharcoal = Charcoal fuel\r\n\r\nCoal = Coal fuel\r\nAPHH-INDIA = Atmospheric Pollution and Human Health in an Indian Megacity project\r\n\r\n\r\nRiceEFyearlyVOCKG = Total NMVOC emission in 2011 from agricultural on field burning of agricultural rice residues\r\n\r\nWheatEFyearlyVOCKG = Total NMVOC emission in 2011 from agricultural on field burning of agricultural wheat, coarse cereal and maize residues\r\n\r\nJowarEFyearlyVOCKG = Total NMVOC emission in 2011 from agricultural on field burning of agricultural jowar and bajra residues\r\n\r\nMeanEFyearlyVOCKG = Total NMVOC emission in 2011 from agricultural on field burning of agricultural 9 oilseeds, groundnut, rapeseed, mustard, sunflower, cotton, jute and mesta residues\r\n\r\nSugarcaneEFyearlyVOCKG (for sugarcane) = Total NMVOC emission in 2011 from agricultural on field burning of agricultural sugarcane residues\r\n\r\nBfracdump = fraction of waste burnt in the dump", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-05-24T11:11:24", "updateFrequency": "notPlanned", "dataLineage": "The data were delivered to the Centre for Environmental Data Analysis (CEDA) for archiving by the data provider.", "removedDataReason": "", "keywords": "APHH, VOC, Delhi, inventories", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-05-26T10:22:43", "doiPublishedTime": "2021-05-26T10:35:53.775129", "removedDataTime": null, "geographicExtent": { "ob_id": 2780, "bboxName": "", "eastBoundLongitude": 98.0, "westBoundLongitude": 68.0, "southBoundLatitude": 6.5, "northBoundLatitude": 38.0 }, "verticalExtent": null, "result_field": { "ob_id": 32617, "dataPath": "/badc/aphh/data/delhi/delhiflux/york-gcxgc-fid_voc-inventory/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 72624481321, "numberOfFiles": 46, "fileFormat": "Data are NASA Ames formatted" }, "timePeriod": { "ob_id": 8960, "startTime": "1993-01-01T00:00:00", "endTime": "2016-12-31T00:00:00" }, "resultQuality": { "ob_id": 3680, "explanation": "Data are as given by the data provider with quality control flags defined within each file. No quality control has been performed by the Centre for Environmental Data Analysis (CEDA)", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-05-24" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 32618, "uuid": "5deec334bf504130bc2fcfad99cdf42b", "short_code": "acq", "title": "Acquisition for: Non-methane volatile organic compound emission inventories from burning studies performed as part of the APHH-INDIA project (DelhiFlux).", "abstract": "Acquisition for: Non-methane volatile organic compound emission inventories from burning studies performed as part of the APHH-INDIA project (DelhiFlux)." }, "procedureComputation": null, "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": 30221, "uuid": "ba27c1c6a03b450e9269f668566658ec", "short_code": "proj", "title": "(APHH India) Megacity Delhi atmospheric emission quantification, assessment and impacts (DelhiFlux)", "abstract": "The project, part of the Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme, has four specific objectives:\r\n\r\nTo improve the emission factor database for key source types and compounds in Delhi through a combination of lab and field based emission factor measurements, using harmonised instrumentation.\r\nPrerequisite\r\n\r\nTo compile a state-of-the-art emission inventory for the greater Delhi area at a spatial resolution of (1.6 km)2, together with temporal profiles of the diurnal and seasonal variability.\r\nTo inform and evaluate this emission inventory through direct and independent emission flux measurements at the urban scale (~10 km2).\r\nTo apply atmospheric transport modelling to assess the performance of the emission inventory against concentration measurements and quantify the implications of the emissions improvements for air quality indicators.\r\n\r\nGrant Ref: NE/P016472/1" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 41999 ], "vocabularyKeywords": [], "identifier_set": [ 10892 ], "observationcollection_set": [ { "ob_id": 32625, "uuid": "04f9006457e54c49b628913912827ad7", "short_code": "coll", "title": "(APHH India) Megacity Delhi atmospheric emission quantification, assessment and impacts (DelhiFlux): Air quality measurements", "abstract": "This dataset collection contains air quality data from the Air Pollution & Human Health in a Developing Indian Megacity (APHH-India) programme 'Megacity Delhi atmospheric emission quantification, assessment and impacts (DelhiFlux)'." } ], "responsiblepartyinfo_set": [ 145401, 145402, 145403, 145404, 145405, 145406, 145407, 145408, 168360, 145409 ], "onlineresource_set": [] }, { "ob_id": 32619, "uuid": "b25d4a6174de4ac78000d034f500a268", "title": "ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost Ground Temperature for the Northern Hemisphere, v3.0", "abstract": "This dataset contains permafrost ground temperature data produced as part of the European Space Agency's (ESA) Climate Change Initiative (CCI) Permafrost project. It forms part of the second version of their Climate Research Data Package (CRDP v2). It is derived from a thermal model driven and constrained by satellite data. Grid products of CDRP v2 are released in annual files, covering the start to the end of the Julian year. This corresponds to average annual ground temperatures and is provided for specific depths (surface, 1m, 2m, 5m , 10m).\r\n\r\nCase A: This covers the Northern Hemisphere (north of 30°) for the period 2003-2019 based on MODIS Land Surface temperature merged with downscaled ERA5 reanalysis near-surface air temperature data.\r\nCase B: This covers the Northern Hemisphere (north of 30°) for the period 1997-2002 based on downscaled ERA5 reanalysis near-surface air temperature data which are bias-corrected with the Case A product for the overlap period 2003-2019 using a pixel-specific statistics for each day of the year.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-05-25T17:57:05", "updateFrequency": "notPlanned", "dataLineage": "Data have been produced by the ESA CCI Permafrost project as part of ESA's Climate Change Initiative programme", "removedDataReason": "", "keywords": "Permafrost, CCI, Ground Temperature", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-06-25T16:59:05", "doiPublishedTime": "2021-06-28T12:36:20.964753", "removedDataTime": null, "geographicExtent": { "ob_id": 2567, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": 30.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 32620, "dataPath": "/neodc/esacci/permafrost/data/ground_temperature/L4/area4/pp/v03.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 35291367976, "numberOfFiles": 24, "fileFormat": "Data are netCDF formatted." }, "timePeriod": { "ob_id": 8999, "startTime": "1997-01-01T00:00:00", "endTime": "2019-12-31T23:59:59" }, "resultQuality": { "ob_id": 3359, "explanation": "Data are as provided by the CCI Permafrost project. For further quality information see the permafrost CCI website and linked documentation.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-12-04" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32737, "uuid": "fbfa5bb9c569492bb7ec68678dff7d52", "short_code": "comp", "title": "Computation of Permafrost v3 datsets by the ESA Permafrost CCI", "abstract": "The Permafrost CCI project has created Earth Observation (EO) based products for the permafrost Essential Climate Variable (ECV) spanning the last two decades. Since ground temperature and thaw depth cannot be directly observed from space-borne sensors, a variety of satellite and reanalysis data are combined in a ground thermal model. The algorithm uses remotely sensed data sets of Land Surface Temperature (MODIS LST/ ESA LST CCI) and landcover (ESA LandcoverCCI) to drive the transient permafrost model CryoGrid 2, which yields thaw depth and ground temperature at various depths, while ground temperature forms the basis for permafrost fraction.\r\n\r\nInput data: MODIS Land surface temperature is used as the main input for the L4 production for 2003-2019 data. Sensors of auxiliary data are listed in the meta data.\r\nDownscaled and bias corrected ERA reanalyses data based on statistics of the overlap period between ERA reanalysis and MODIS LST are used for data before 2003. Sensors of auxiliary data are listed in the meta data." }, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "permissions": [ { "ob_id": 2596, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 58, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_permafrost_terms_and_conditions.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 29966, "uuid": "7133bbd64540498bbffd1c28bbbea9cd", "short_code": "proj", "title": "ESA Permafrost Climate Change Initiative Project", "abstract": "The Permafrost Climate Change Initiatve Project (Permafrost_cci) is part of the European Space Agency's Climate Change Initiative Programme. The ultimate objective of Permafrost_cci is to develop and deliver permafrost maps of Essential Climate Variable products, primarily derived from satellite measurements." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 27732, 50416, 50547, 50548, 70621, 70622 ], "vocabularyKeywords": [ { "ob_id": 11084, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_asar", "resolvedTerm": "ASAR" }, { "ob_id": 11091, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_avhrr3", "resolvedTerm": "AVHRR-3" }, { "ob_id": 11103, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_meris", "resolvedTerm": "MERIS" }, { "ob_id": 11105, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_modis", "resolvedTerm": "MODIS" }, { "ob_id": 11118, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_sarX", "resolvedTerm": "SAR-X" }, { "ob_id": 11133, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_vegetation", "resolvedTerm": "VEGETATION" }, { "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": 10888, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_noaa_15", "resolvedTerm": "NOAA-15" }, { "ob_id": 10889, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_noaa_16", "resolvedTerm": "NOAA-16" }, { "ob_id": 10890, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_noaa_17", "resolvedTerm": "NOAA-17" }, { "ob_id": 11135, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_probaV", "resolvedTerm": "PROBA-V" }, { "ob_id": 10923, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_terra", "resolvedTerm": "Terra" } ], "identifier_set": [ 10897 ], "observationcollection_set": [ { "ob_id": 32783, "uuid": "8239d5f6263f4551bf2bd100d3ecbead", "short_code": "coll", "title": "ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost version 3 data products", "abstract": "This collection of data forms the Permafrost Climate Research Data Package (CRDP v2), which comprises the Version 3.0 Permafrost data products from the European Space Agency's (ESA) Climate Change Initiative (CCI) Permafrost project. Data products include Ground Temperature, Active Layer Thickness and Permafrost Extent for the Northern Hemisphere (north of 30°) for the period 1997-2019. They are derived from a thermal model driven and constrained by satellite data. Gridded products are released in annual files, covering the start to the end of the Julian year. This corresponds to average annual ground temperatures, as well as the maximum depth of seasonal thaw, which corresponds to the active layer thickness." } ], "responsiblepartyinfo_set": [ 145417, 145418, 145422, 145415, 145416, 145419, 145420, 145421, 145423, 145424, 145425, 145426, 145427, 145428, 145429, 145430, 145431, 145432, 145433, 145434, 145435, 145436, 145437, 145438, 145439, 145440 ], "onlineresource_set": [ 42741, 42740, 42742, 42945, 87518, 87519, 89223, 89224, 89225, 89226, 89227, 89228, 89229, 94595, 94596 ] }, { "ob_id": 32623, "uuid": "f6c384ae730744d2ba929e0fad77160a", "title": "Spectroscopic data for transitions in water (1H 16O2) extending into the near-ultraviolet", "abstract": "This dataset contains spectroscopic data for transitions in water (1H 16O2 (H2O with oxygen 16 and hydrogen 1)) extending into the near-ultraviolet. These data were calculated using a mixture of first principle quantum mechanics and input from the experiment. \r\n\r\nThe data is provided in HITRAN format as described in the associated readme file. The data were collected as part of the NERC grant Short wavelength absorption by water vapour (NE/T000767/1).", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-06-15T13:27:41", "updateFrequency": "notPlanned", "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "NERC, NE/T000767/1, Spectroscopic, UV", "publicationState": "published", "nonGeographicFlag": true, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-06-15T13:27:58", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": null, "verticalExtent": null, "result_field": { "ob_id": 32621, "dataPath": "/badc/deposited2021/WAT-UV296_water_line/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 121029527, "numberOfFiles": 3, "fileFormat": "Data are Hirtan formatted." }, "timePeriod": null, "resultQuality": { "ob_id": 3681, "explanation": "Data are as given by the data provider with quality control flags defined within each file. No quality control has been performed by the Centre for Environmental Data Analysis (CEDA)", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-05-26" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32673, "uuid": "7fe79daa538147ff84380b779ee1f72f", "short_code": "comp", "title": "First principle quantum mechanics", "abstract": "A mixture of first principle quantum mechanics and input from the experiment" }, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2526, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 32622, "uuid": "0bfd551eb6b942d0a77740652099c0d2", "short_code": "proj", "title": "Short wavelength absorption by water vapour", "abstract": "The aim of this proposal was to provide comprehensive and accurate data on water absorption at short wavelengths. These data were generated using techniques of first principle quantum mechanics that have been successfully applied to both absorption by water vapour at longer wavelengths and other key atmospheric species. Where possible the positions of absorption features were adjusted using laboratory measurements. The resulting line lists are made available to key groups involved monitoring the Earth's atmosphere in the near UV, placed in data depositories and made available to databases such as HITRAN." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 145445, 145446, 145447, 145448, 145449, 145450, 145451, 145452, 145453, 168961, 145454 ], "onlineresource_set": [ 42743 ] }, { "ob_id": 32669, "uuid": "7beeed0bc7fa41feb10be22ee9d10f00", "title": "Adverse Weather Scenarios for Future Electricity Systems", "abstract": "This dataset contains gridded meteorological data associated with challenging periods of weather for highly-renewable UK and European electricity systems of the future collected during the Adverse Weather Scenarios for Future Electricity Systems project. This project is a collaboration between the Met Office, the National Infrastructure Commission and the Climate Change Committee. More details about the project can be found in the associated documentation.\r\n\r\nTwo categories of challenging weather conditions; long duration adverse events and short duration wind ramping events, are provided.\r\n\r\nLong duration events\r\n\r\nThe long duration event component of the dataset provides daily time series at 60 x 60 km spatial resolution, covering a European domain, for surface temperature, 100 m wind speed and net surface solar radiation data, representative of a selection of adverse weather scenarios. Each adverse weather scenario is contained within a time slice of data. For summer-time events, one calendar year (January - December) of data is provided, with the summer-time event occurring in the summer of that year. For winter-time events, two calendar years of data are provided, with the winter-time event occurring in the winter (October-March) intersecting the two calendar years. In all cases, the start date, duration and severity of the adverse weather event, contained within the time slice of data, are given in the NetCDF global ttributes.\r\n\r\nThree types of long-duration adverse weather scenarios are represented: winter-time wind-drought-peak-demand events, summer-time wind-drought-peak-demand events, and summer-time surplus generation events. These are provided at various extreme levels (1 in 2, 5, 10, 20 ,50 and 100-year events); and for a range of current and nominal future climate change warming levels (1.2 [current day, early 2020s], 1.5, 2, 3, and 4 degrees Celsius above pre-industrial level), representative of events impacting either just the UK, or Europe as a whole.\r\n\r\nThe data provided are derived from the Met Office decadal prediction system hindcast (https://www.metoffice.gov.uk/research/approach/modelling-systems/unified-model/climate-models/depresys) according to the climate change impacts identified from UKCP18 (https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/index).\r\n\r\nShort duration events\r\nThe short duration event component of the dataset provides hourly time series at 4 x 4 km spatial resolution, covering a UK and surrounding offshore area domain, for 100 m wind speed, representative of a selection of wind generation ramping events. Each adverse weather scenario is contained within a time slice of data with up to one week before and one week after the day on which the event occurs (up to 15 days in total) provided. For the majority of events provided, the full 15 days are available, however for a small number of events which occur less than one week from the beginning or end of the underlying data used to derive this dataset, this is not possibly to supply, and these events are listed below. The start date and time along with the direction and magnitude of the ramp (change in wind capacity factor) contained\r\nwithin the time slice of data, are given in the NetCDF global attributes.\r\n\r\nThe short duration wind generation ramping events are representative of events impacting five separate regions of Great Britain and surrounding offshore areas, as defined in the accompanying documentation. These regions are Scotland, the East England, West England and Wales offshore North and offshore South. The events are defined by changes in wind capacity factors occurring over different length time windows (1-hour, 3-hour, 6-hour, 12-hour and 24-hour windows). These are provided at various extreme levels (1 in 2, 5, 10, 20 ,50 and 100-year events) for the 1.2 degrees Celsius above pre-industrial level (I.e. representative of early 2020s climate) and through the analysis outlined in the accompanying documentation are though to also be representative of the 2, 3, and 4 degrees Celsius above pre-industrial level nominal future climate change warming levels.\r\n\r\nThe data provided are derived from the UKCP18 local projections (https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/index).\r\n\r\nThe methods developed for characterising and representing these adverse weather scenarios, and the approach used to compile the final dataset are presented in the accompanying documentation.\r\n\r\nUse of this data is subject to the terms of the Open Government Licence (http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/) The following acknowledgment must be given when using the data: © Crown Copyright 2021, Met Office, funded by the National Infrastructure Commission.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2022-03-09T13:33:43", "updateFrequency": "notPlanned", "dataLineage": "This dataset has been developed by the Met Office as part of the 'Adverse Weather Scenarios for Future Electricity Systems' project, commissioned by the National Infrastructure Commission, and co-lead by the Climate Change Committee.\r\n\r\nThe data provided are derived from the Met Office decadal prediction system hindcast and UKCP18, according to the climate change impacts identified from UKCP18. Further information about the development of this dataset are presented in the accompanying reports. The data has been sent by the data providers to be archived at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "Adverse weather scenarios, future electricity systems, adverse weather scenarios for future electricity systems, UK, Europe, weather risk, climate risk, energy system, extreme weather scenarios, electricity system resilience, climate change", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-06-03T14:48:03", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2794, "bboxName": "", "eastBoundLongitude": 40.0, "westBoundLongitude": -30.0, "southBoundLatitude": 30.0, "northBoundLatitude": 75.0 }, "verticalExtent": null, "result_field": { "ob_id": 32670, "dataPath": "/badc/deposited2021/adverse_met_scenarios_electricity/data", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 689690747173, "numberOfFiles": 2624, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 8976, "startTime": "1960-01-01T00:00:00", "endTime": "2097-12-31T00:00:00" }, "resultQuality": { "ob_id": 3695, "explanation": "The scientific methods developed and applied within this project have undergone rigorous internal Met Office scientific and code quality assurance.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-05-26" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32672, "uuid": "81f04df0424245d4b54f4b8e64de73d2", "short_code": "comp", "title": "Computation for Adverse Weather Scenarios for Future Electricity Systems", "abstract": "The data provided are derived from the Met Office decadal prediction system hindcast (https://www.metoffice.gov.uk/research/approach/modelling-systems/unified-model/climate-models/depresys) and UKCP18 (https://www.metoffice.gov.uk/research/approach/collaboration/ukcp/index) according to the climate change impacts identified from UKCP18.\r\n\r\nThe methods developed for characterising and representing these adverse weather scenarios, and the approach used to compile the final dataset are presented in the accompanying documentation.\r\n\r\nUse of this data is subject to the terms of the Open Government Licence (http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/) The following acknowledgment must be given when using the data: © Crown Copyright 2021, Met Office, funded by the National Infrastructure Commission." }, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2526, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 32671, "uuid": "701276b1c63d48e784ba1f3673607628", "short_code": "proj", "title": "Adverse Weather Scenarios for Future Electricity Systems", "abstract": "There is wide agreement that greenhouse gas emissions from the energy sector must be reduced if climate change is to be limited to safe levels. As such, the UK and Europe are targeting net-zero emissions and plan for highly-renewable electricity systems. Whilst desirable this hugely increases the sensitivity of generation and demand to changes in the weather and climate. \r\n\r\nIt is therefore imperative to understand just how resilient future highly-renewable electricity systems are, and whether there are physically plausible periods of adverse weather (e.g. long periods of low wind speed and cold temperatures) that could jeopardise security of supply. \r\n\r\nThe Adverse Weather Scenarios for Future Electricity Systems project provides a dataset of adverse weather scenarios, based on physically plausible weather conditions, representing a range of possible extreme events, and the affect of future climate change. This dataset can be used to more rigorously stress test proposed future highly renewable electricity systems to ensure resilience to challenging weather and climate conditions.\r\n\r\nThe dataset has been developed by the Met Office, in collaboration with the National Infrastructure Commission, and the Climate Change Committee, and with guidance from an advisory group of energy experts, including representatives from the Department for Business, Energy & Industrial Strategy (BEIS), Ofgem, National grid ESO, Energy Systems Catapult, and University College London, and with guidance from experts at the University of Reading." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 2007, 2008, 6811, 11573, 21675, 21676, 21677, 21678, 46793, 46794, 46795, 46796 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 145687, 145688, 145689, 145690, 145691, 145692, 145697, 145698, 145699, 145700, 145701, 145702 ], "onlineresource_set": [ 42785, 42786, 42787, 42818, 42819, 43014, 43015, 43037 ] }, { "ob_id": 32688, "uuid": "feb1e0b5426d4f5c80f791909a3a2d37", "title": "High resolution Standardized Precipitation Evapotranspiration Index (SPEI) dataset for Central Asia", "abstract": "This dataset contains high-resolution (5 km) Standardized Precipitation Evaporation Index (SPEI-HR) drought data for Central Asia. There are forty-eight different SPEI time scales and the available period is from 1981 - 2018, the data was produced using Climate Hazards group InfraRed Precipitation with Station’s (CHIRPS) precipitation dataset and Global Land Evaporation Amsterdam Model’s (GLEAM) potential evaporation dataset. The SPEI-HR dataset, over time and space, correlates fairly well with SPEI values estimated from coarse-resolution Climate Research Unit (CRU) dataset. Furthermore, the SPEI-HR dataset, for 6-month timescale, displayed a good correlation of 0.66 with GLEAM root zone soil moisture and a positive correlation of 0.26 with normalized difference vegetation index (NDVI) from Global Inventory Monitoring and Modelling System (GIMMS).", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-05-27T15:23:42", "updateFrequency": "notPlanned", "dataLineage": "Data was prepared for a Masters Thesis at the Chair of Hydrology and River Basin Management and deposited at the Centre for Environmental Data Analysis (CEDA) for archiving.", "removedDataReason": "", "keywords": "SPEI, Central Asia, drought", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-06-03T08:29:27", "doiPublishedTime": "2022-02-28T13:13:25", "removedDataTime": null, "geographicExtent": { "ob_id": 2797, "bboxName": "", "eastBoundLongitude": 100.0, "westBoundLongitude": 45.0, "southBoundLatitude": 32.0, "northBoundLatitude": 58.0 }, "verticalExtent": null, "result_field": { "ob_id": 32689, "dataPath": "/badc/deposited2021/spei-central-asia/data", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 54700431523, "numberOfFiles": 51, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 8980, "startTime": "1981-01-01T00:00:00", "endTime": "2018-12-01T00:00:00" }, "resultQuality": { "ob_id": 3699, "explanation": "Data is as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA)..\n\n", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-05-27" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32691, "uuid": "c201b5be02374fb99c777c3602638453", "short_code": "comp", "title": "Standardized Precipitation Evapotranspiration Index (SPEI)", "abstract": "The SPEI dataset was developed by first aligning and formatting the precipitation and potential evaporation dataset using Climate Data Operators (CDO). Then a water deficit dataset was produced by subtracting these two datasets. Later, using R programming languages SPEI package, created by Santiago Beguería and Sergio M. Vicente-Serrano, the SPEI values were estimated for forty-eight different timescales. Finally, the dataset was validated using Climate Research Unit’s dataset, soil moisture dataset and Normalized Difference Vegetation Index dataset." }, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2526, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [], "inspireTheme": [], "topicCategory": [], "phenomena": [ 51981, 60423, 60424, 60425, 60426 ], "vocabularyKeywords": [], "identifier_set": [ 11032 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 145750, 145751, 145752, 145753, 145754, 145755, 145760, 145761, 145762, 168962, 145763, 145764 ], "onlineresource_set": [ 52076, 87696 ] }, { "ob_id": 32692, "uuid": "36dae49c76f845a18062fa96599be719", "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Antarctic Ice Sheet monthly Gravimetric Mass Balance gridded product, v3.0, 2002 - 2020", "abstract": "This dataset contains the Gravimetric Mass Balance (GMB) gridded product for the Antarctic Ice Sheet (AIS), generated by TU Dresden as part of the ESA Antarctic Ice Sheet Climate Change Initiatve (Antarctic_Ice_Sheet_cci). \r\n\r\nThe Gravimetric Mass Balance (GMB) product for the Antarctic Ice Sheet (AIS) is based on monthly snapshots of the Earth’s gravity field provided by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on satellite mission (GRACE-FO). The product relies on monthly gravity field solutions (L2) of release 06 generated at the Center for Space Research (University of Texas at Austin) and spans the period from April 2002 through July 2020. The GMB product covers the full GRACE mission period (April 2002 - June 2017) and is extended by means of GRACE-FO data starting from June 2018, thus including 187 monthly solutions. The mass change estimation is based on the tailored sensitivity kernel approach developed at TU Dresden. (Groh & Horwath, 2021)\r\n\r\nThe GMB gridded product comprises time series of ice mass changes for cells of polar-stereographic grid with a sampling of 50x50 km² covering the entire AIS. A GMB basin product is also available as a separate dataset.\r\n\r\nGroh, A. & Horwath, M. (2021). Antarctic Ice Mass Change Products from GRACE/GRACE-FO Using Tailored Sensitivity Kernels. Remote Sens., 13(9), 1736. doi:10.3390/rs13091736", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-06-15T13:41:57", "updateFrequency": "notPlanned", "dataLineage": "The data were generated by TU Dresden within the ESA Antarctic Ice Sheet CCI project and deposited at the Centre for Environmental Data Analysis (CEDA) for archiving and distribution via the CCI Open Data Portal.", "removedDataReason": "", "keywords": "ESA CCI, Antarctica, Ice Sheet Mass Balance, GRACE, GRACE-FO", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-06-17T14:09:06", "doiPublishedTime": "2021-06-28T16:02:33.560851", "removedDataTime": null, "geographicExtent": { "ob_id": 2779, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": -60.0 }, "verticalExtent": null, "result_field": { "ob_id": 32741, "dataPath": "/neodc/esacci/ice_sheets_antarctica/data/gravimetric_mass_balance/gridded/v3.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 17719816, "numberOfFiles": 2, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 8954, "startTime": "2002-04-18T00:00:00", "endTime": "2020-07-16T23:59:59" }, "resultQuality": { "ob_id": 3700, "explanation": "See the Antarctic Ice Sheets CCI webpage", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-05-27" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 32698, "uuid": "6a84d7e2a1c0408aae6e75dd67bcd89c", "short_code": "cmppr", "title": "Composite process for the Antarctic Ice Sheet CCI Gravimetric Mass Balance products (v3.0)", "abstract": "Composite process for the Antarctic Ice Sheet CCI Gravimetric Mass Balance products (v3.0)" }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "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": [ 52192, 52193, 67713, 67722, 67723, 67724, 67725, 67726, 67727 ], "vocabularyKeywords": [ { "ob_id": 10840, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_grace", "resolvedTerm": "GRACE" } ], "identifier_set": [ 10899 ], "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": [ 145767, 145768, 145769, 145770, 145771, 145772, 145773, 146443, 145774, 145775 ], "onlineresource_set": [ 42788, 42789, 42790, 42852, 42856, 42957 ] }, { "ob_id": 32702, "uuid": "12eae5e708e541f390898af4187a1c20", "title": "Global Ocean Lagrangian Trajectories based on AVISO velocities, v2.1", "abstract": "The National Centre for Earth Observation (NCEO) Long Term Science Single Centre (LTSS) Global Ocean Lagrangian Trajectories (OLTraj) provides 30-day forward and backward Lagrangian trajectories based on AVISO (Satellite Altimetry Data project) surface velocities. Each trajectory represents the path that a water mass would move along starting at a given pixel and a given day. OLTraj can be thus used to implement analyses of oceanic data in a Lagrangian framework. The purpose of OLTraj is to allow non-specialists to conduct Lagrangian analyses of surface ocean data.\r\n\r\nThe dataset has global coverage and spans the year 2018 with a daily temporal resolution. The trajectories were generated starting from zonal and meridional model velocity fields that were integrated using the LAMTA (6-hour time step - part of ) as described in Nencioli et al., 2018 and SPASSO (Software package for and adaptive satellite-based sampling for ocean graphic cruises containing LAMTA) software user guide. Please see the documentation section below for further information.\r\n\r\nVersion 2.1 has the same resolution as version V2.0 but has double value for time variables to permit access via THREDDS", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T01:40:38", "updateFrequency": "", "dataLineage": "Data were produced by the NCEO Plymouth Marine Laboratory project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "AVISO, Global, Ocean Lagrangian Trajectories, LAMTA, zonal, meridional model, OLTraj_SEALEVEL_GLO_PHY_L4_REP_OBSERVATIONS_008_047", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-08-19T14:44:17", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2687, "bboxName": "OLTraj", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 32703, "dataPath": "/neodc/oltraj/data/v2.1/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 6497487670, "numberOfFiles": 31, "fileFormat": "NetCDF file \r\nA reformatted version of the v2.0 dataset. In this version V2.1 the int64 time value was changed to double to allow Jupyter Notebook access via THREDDS/OpenDAP." }, "timePeriod": { "ob_id": 8981, "startTime": "1998-01-01T00:00:00", "endTime": "2019-12-31T00:00:00" }, "resultQuality": { "ob_id": 3652, "explanation": "Validated by Plymouth Marine Laboratory Science Team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-30" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 33040, "uuid": "29d77174c7b945fb86ca098e7af410a3", "short_code": "comp", "title": "NCEO OLTraj V2.1", "abstract": "The trajectories were generated starting from zonal and meridional model velocity fields from the AVISO project; please see the Global ocean gridded L4 sea surface heights and derived variables reprocessed reference in the documentation section for more details on the dataset. The output of which was integrated using the LAMTA package (6-hour time step) as previously described in Nencioli et al., 2018 (also available in the documentation section).\r\n\r\nThe computing is similar to that of OLTraj v2.0 supports double value for time variables instead of int64" }, "procedureCompositeProcess": null, "imageDetails": [ 130 ], "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": 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": [ 4385, 18405, 18408, 30129, 30130 ], "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": [ 145787, 145788, 145789, 145790, 145791, 145792, 145793, 145794, 145795 ], "onlineresource_set": [ 42797, 42798, 42799, 42800 ] }, { "ob_id": 32706, "uuid": "2c8f38fac04945b89cf12d6e9c928c6f", "title": "ECMWF ERA5: surface level invariant parameter data", "abstract": "This dataset contains ERA5 surface level invariant parameter data. ERA5 is the 5th generation reanalysis project from the European Centre for Medium-Range Weather Forecasts (ECWMF) - see linked documentation for further details. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record.\r\n\r\nModel level analysis and surface analysis and forecast data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset.\r\n\r\nThe ERA5 global atmospheric reanalysis of the covers 1979 to 2 months behind the present month. This follows on from the ERA-15, ERA-40 rand ERA-interim re-analysis projects.\r\n\r\nAn initial release of ERA5 data (ERA5t) is made roughly 5 days behind the present date. These will be subsequently reviewed ahead of being released by ECMWF as quality assured data within 3 months. CEDA holds a 6 month rolling copy of the latest ERA5t data. See related datasets linked to from this record. However, for the period 2000-2006 the initial ERA5 release was found to suffer from stratospheric temperature biases and so new runs to address this issue were performed resulting in the ERA5.1 release (see linked datasets). Note, though, that Simmons et al. 2020 (technical memo 859) report that \"ERA5.1 is very close to ERA5 in the lower and middle troposphere.\" but users of data from this period should read the technical memo 859 for further details.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T13:10:38", "updateFrequency": "notPlanned", "dataLineage": "Data are generated by the ERA5 project at European Centre for Medium-Range Weather Forecasts (ECMWF) before being prepared by CEDA staff using the ECMWF system and uploaded to Centre for Environmental Data Analysis (CEDA) for ingestion into the archive. Data are translated over to a regular latitude-longitude grid and converted to netCDF format ahead of transfer to the CEDA system.", "removedDataReason": "", "keywords": "ECMWF, ERA, ERA5, reanalysis, invariant, surface level", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2022-04-13T08:22:38", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": { "ob_id": 29, "highestLevelBound": 0.0, "lowestLevelBound": 0.0, "units": "Kilometers" }, "result_field": { "ob_id": 32707, "dataPath": "/badc/ecmwf-era5/data/invariants", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 7338834, "numberOfFiles": 15, "fileFormat": "Data are NetCDF formatted." }, "timePeriod": { "ob_id": 8225, "startTime": "1979-01-01T00:00:00", "endTime": null }, "resultQuality": { "ob_id": 1678, "explanation": "ECMWF quality controlled data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-08-26" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 30236, "uuid": "5656b9ce8a7949339c9511a7c3d6cd58", "short_code": "comp", "title": "ECMWF ERA5 Re-analysis Model deployed on ECMWF Computer", "abstract": "This computation involved: ECMWF ERA5 Re-analysis Model deployed on ECMWF Computer. The data assimilation system used to produce ERA5 is based on the Integrated Forecasting System (IFS)Cycle 41r2 release, with several added features specifically developed for reanalysis. The many changes and improvements incorporated into the IFS represent a decade of research and development in modelling and data assimilation. The ERA5 reanalysis benefits from research conducted in the EU-funded ERA-CLIM and ERA-CLIM2 projects carried out by ECMWF and partners. These led to improved input data for the assimilating model that better reflects observed changes in climate forcings, as well as many new or reprocessed observations for data assimilation.\r\n\r\n\r\nThe system includes :\r\n\r\n - Model input: Appropriate for climate (e.g. CMIP5 greenhouse gases, volcanic eruptions,\r\nSST and sea-ice cover)\r\n - Spatial resolution: 31 km globally, 137 levels to 0.01 hPa\r\n - Uncertainty estimates - From a 10-member Ensemble of Data Assimilations (EDA) at 63 km resolution\r\n - Output frequency: Hourly analysis and forecast fields, 3-hourly for the EDA\r\n - Input observations: As in ERA-40 and from Global Telecommunication System. In addition, various newly reprocessed datasets and recent instruments that could not be ingested in ERA-Interim\r\n - Variational bias scheme: Satellite radiances and also ozone, aircraft and surface pressure data\r\n - Satellite data: RTTOV-11, all-sky for various components\r\n - Additional innovations: Long-term evolution of CO2 in RTTOV, cell-pressure correction SSU, improved bias correction for radiosondes, EDA perturbations for sea-ice cover" }, "procedureCompositeProcess": null, "imageDetails": [ 55 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2536, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 16, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ecmwf-era-products.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 30234, "uuid": "7b64cf24f47f4b1aa499339c5a576be1", "short_code": "proj", "title": "ECMWF ERA5 Re-analysis project", "abstract": "The objectives of the European Centre for Medium-Range Weather Forecasts ERA5 project are to produce and promote use of a comprehensive set of global analyses describing the state of the atmosphere, land and ocean-wave conditions from 1979 to present. The ERA5 project builds on the previous work undertaken by the ERA-15, ERA-40 and ERA-Interim projects. ERA5 is continuously updated at ECMWF, with initial products upto 5 days behind the present day issued as ERA5t ahead of review and final release as the ERA5 data, typically 2 months behind the present month." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 51981, 59154, 59155, 61529 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 30248, "uuid": "5971cb20fae94540b862ae3ed3204c3f", "short_code": "coll", "title": "European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis 5 (ERA5) model data", "abstract": "ERA5 is the latest European Centre for Medium-Range Weather Forecasts (ECMWF) global atmospheric reanalysis of the period 1979 to present. This follows on from the ERA-15, ERA-40 and ERA-Interim re-analysis projects. This dataset collection includes data on surface and model levels on a regular latitude-longitude grid in netCDF from :\r\n - a high resolution 'HRES' (31 km horizontal, 137 model level, hourly output) reanalysis model \r\n - a reduced resolution ten member member ensemble runs, including data from all 10 members as well as means and spreads - produced to provide an uncertainty estimate for the 'HRES' output.\r\n - initial release 'ERA5t' data\r\n - re-run model output for 2000-2006 to address issues for this period - ERA5.1\r\n\r\nNote, the parameter selection for the data held in the CEDA archive is not the full range of available parameters. Users requiring other parameters or data on alternative level types should seek these products via the Copernicus Data Store (CDS) - see linked data tool resource.\r\n\r\nFor further details of the datasets and CEDA's holdings please see the individual datasets linked to on this dataset collection record." } ], "responsiblepartyinfo_set": [ 145818, 145819, 145822, 145823, 145824, 145825, 145826, 145827, 145821 ], "onlineresource_set": [ 42824, 42825, 42820, 42821, 42822, 42823 ] }, { "ob_id": 32738, "uuid": "5c2b70d069cb467ab73e80b84c3e395a", "title": "Global ocean lagrangian trajectories based on AVISO velocities, v2.2", "abstract": "The National Centre for Earth Observation (NCEO) Long Term Science Single Centre (LTSS) Global Ocean Lagrangian Trajectories (OLTraj) provide 30-day forward and backward Lagrangian trajectories based on AVISO (Satellite Altimetry Data project) surface velocities. Each trajectory represents the path that a water mass would move along starting at a given pixel and a given day. OLTraj can be thus used to implement analyses of oceanic data in a Lagrangian framework. The purpose of OLTraj is to allow non-specialists to conduct Lagrangian analyses of surface ocean data.\r\n\r\nThe dataset has global coverage and spans 1998-2019 with a daily temporal resolution. The trajectories were generated starting from zonal and meridional model velocity fields that were integrated using the LAMTA (6-hour time step - part of ) as described in Nencioli et al., 2018 and SPASSO (Software package for and adaptive satellite-based sampling for ocean graphic cruises containing LAMTA) software user guide. Please see the documentation section below for further information.\r\n\r\nVersion 2.2 is a higher resolution version of V2.0 and also has double value for time variables to permit access via THREDDS", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-07-07T18:16:45", "updateFrequency": "", "dataLineage": "Data were produced by the NCEO Plymouth Marine Laboratory project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "AVISO, Global, Ocean Lagrangian Trajectories, LAMTA, zonal, meridional model, OLTraj_SEALEVEL_GLO_PHY_L4_REP_OBSERVATIONS_008_047", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-08-19T14:44:50", "doiPublishedTime": "2021-09-08T10:40:06", "removedDataTime": null, "geographicExtent": { "ob_id": 2687, "bboxName": "OLTraj", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 32739, "dataPath": "/neodc/oltraj/data/v2.2/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 6858992869823, "numberOfFiles": 8044, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 8981, "startTime": "1998-01-01T00:00:00", "endTime": "2019-12-31T00:00:00" }, "resultQuality": { "ob_id": 3652, "explanation": "Validated by Plymouth Marine Laboratory Science Team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-04-30" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32740, "uuid": "e14a7e11c35f423a8887647f59d5027f", "short_code": "comp", "title": "NCEO OLTraj V2.2", "abstract": "The trajectories were generated starting from zonal and meridional model velocity fields from the AVISO project; please see the Global ocean gridded L4 sea surface heights and derived variables reprocessed reference in the documentation section for more details on the dataset. The output of which was integrated using the LAMTA package (6-hour time step) as previously described in Nencioli et al., 2018 (also available in the documentation section).\r\n\r\nThe computing is similar to that of OLTraj v2.0 but is of higher resolution and supports double value for time variables instead of int64" }, "procedureCompositeProcess": null, "imageDetails": [ 130 ], "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": 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": [ 3894, 18405, 18408, 30129, 30130 ], "vocabularyKeywords": [], "identifier_set": [ 10938 ], "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": [ 146106, 146108, 146101, 146102, 146103, 146104, 146105, 146107, 146109 ], "onlineresource_set": [ 42851, 42849, 42848, 42850, 94693, 94694 ] }, { "ob_id": 32744, "uuid": "1c9c816d0b8a4fbf878e7e0bfef5d79f", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from Sentinel-5P, generated with the WFM-DOAS algorithm, version 1.2, November 2017 - July 2020", "abstract": "This product is the column-average dry-air mole fraction of atmospheric methane, denoted XCH4. It has been retrieved from radiance measurements from the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite in the 2.3 µm spectral range of the solar spectral range, using the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS or WFMD) retrieval algorithm. This dataset is also referred to as CH4_S5P_WFMD. This version of the product is version 1.2, and covers the period from November 2017 - July 2020. \r\n\r\nThe WFMD algorithm is based on iteratively fitting a simulated radiance spectrum to the measured spectrum using a least-squares method. The algorithm is very fast as it is based on a radiative transfer model based look-up table scheme. The product is limited to cloud-free scenes on the Earth's day side.\r\n\r\nThese data were produced as part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project.\r\n\r\nWhen citing this dataset, please also cite the following peer-reviewed publication: \r\nSchneising, O., Buchwitz, M., Reuter, M., Bovensmann, H., Burrows, J. P., Borsdorff, T., Deutscher, N. M., Feist, D. G., Griffith, D. W. T., Hase, F., Hermans, C., Iraci, L. T., Kivi, R., Landgraf, J., Morino, I., Notholt, J., Petri, C., Pollard, D. F., Roche, S., Shiomi, K., Strong, K., Sussmann, R., Velazco, V. A., Warneke, T., and Wunch, D.: A scientific algorithm to simultaneously retrieve carbon monoxide and methane from TROPOMI onboard Sentinel-5 Precursor, Atmos. Meas. Tech., 12, 6771–6802, https://doi.org/10.5194/amt-12-6771-2019, 2019.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-07-15T17:30:28", "updateFrequency": "notPlanned", "dataLineage": "Data were processed by the ESA Climate Change Initiative (CCI) Greenhouse Gas project team and supplied to CEDA as part of the ESA CCI Open Data Portal.", "removedDataReason": "", "keywords": "ESA, CCI, satellite, Sentinel-5 Precursor, TROPOMI, atmosphere, methane, carbon monoxide", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2021-09-02T16:51:29", "doiPublishedTime": "2021-09-08T10:42:52", "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": 32745, "dataPath": "/neodc/esacci/ghg/data/cci_plus/CH4_S5P_WFMD/v1.2_extended_to_july2020/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 48435508668, "numberOfFiles": 953, "fileFormat": "Data are netCDF formatted." }, "timePeriod": { "ob_id": 9024, "startTime": "2017-11-10T00:00:00", "endTime": "2020-07-31T23:59:59" }, "resultQuality": { "ob_id": 3389, "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA)", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2020-02-28" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 32867, "uuid": "78c4897e8b5c4818b81a0213ddc198dd", "short_code": "cmppr", "title": "Composite process for the ESA Greenhouse Gases Climate Change Initiative CH4_S5P_WFMD product", "abstract": "The ESA Greenhouse Gases Climate Change Initiative CH4_S5P_WFMD product has been derived from the Tropomi instrument on the Sentinel-5P satellite, using the WFM-DOAS retrieval algorithm." }, "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": [ 54763, 54764, 55532, 55533, 55535, 63576, 66973, 66974, 68636, 68637, 69622, 69623, 69628, 69629, 69634, 69635, 74642, 74644, 74645, 74648, 74649, 74650, 74651, 74653, 74654, 74655, 74658, 74659, 74660, 79736 ], "vocabularyKeywords": [], "identifier_set": [ 10942 ], "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": [ 146112, 146118, 146111, 146115, 146114, 146113, 146117, 146116, 146119, 147520, 146120, 146121, 146122 ], "onlineresource_set": [ 42859, 42861, 42860, 42862, 42863, 43044, 43045, 94780 ] }, { "ob_id": 32748, "uuid": "fdd90615b0df45489d9ca47708d98325", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from GOSAT-2, generated with the SRFP (RemoTeC) full physics retrieval algorithm, version 1.0.0", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the RemoTeC SRFP Full Physics Retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-06-17T14:19:38", "updateFrequency": "notPlanned", "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. These data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI+) programme.", "removedDataReason": "", "keywords": "ESA, CCI, satellite, atmosphere, carbon dioxide, CO2", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2021-09-02T17:12:21", "doiPublishedTime": "2021-09-08T10:42:24", "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": 32749, "dataPath": "/neodc/esacci/ghg/data/cci_plus/CH4_GO2_SRFP/v1.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 266017657, "numberOfFiles": 249, "fileFormat": "Data are netCDF formatted." }, "timePeriod": { "ob_id": 8984, "startTime": "2019-02-05T00:00:00", "endTime": "2019-10-30T23:59:59" }, "resultQuality": { "ob_id": 3550, "explanation": "For further information see the End to End ECV Uncertainty budget report", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2020-09-28" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 32861, "uuid": "25daadec315b4127a5c80d4e1354c690", "short_code": "cmppr", "title": "Composite process for the ESA Greenhouse Gases Climate Change Initiative CH4_GO2_SRFP and CO2_GOS_SRFP products", "abstract": "The CH4_GO2_SRFP and CO2_GO2_SRFP products were derived from data from the TANSO-FTS/2 instrument on the GOSAT satellite, using the SRFP (Remotec) retrieval algorithm." }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "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": [ 1050, 1635, 1636, 11790, 11791, 11792, 11793, 11794, 11795, 11796, 11797, 11798, 11800, 11801, 11802, 11803, 11804, 11807, 11808, 11809, 11810, 11811, 11812, 11814, 11815, 11816, 11817, 11818, 11819, 11820, 11822, 11823, 11846, 13268, 13270, 13272, 13273, 36821, 36822, 36823, 36825, 36826, 36827 ], "vocabularyKeywords": [], "identifier_set": [ 10941 ], "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": [ 146132, 146126, 146133, 146131, 146130, 146129, 146127, 146994, 146995, 146996, 146997, 146998 ], "onlineresource_set": [ 42864, 42865, 42867, 42866, 42869, 42868, 90974, 90975, 90976, 90977, 90978, 90979 ] }, { "ob_id": 32750, "uuid": "722fe4748da2487ead0a755f6d09e6ab", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from GOSAT-2, generated with the SRPR (RemoTeC) proxy retrieval algorithm, version 1.0.0", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2(TANSO-FTS-2) Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the RemoTeC SRPR Proxy Retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2024-03-09T03:22:27", "updateFrequency": "notPlanned", "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. These data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI+) programme.", "removedDataReason": "", "keywords": "ESA, CCI, satellite, atmosphere, carbon dioxide, CO2", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2021-09-02T17:06:19", "doiPublishedTime": "2021-09-08T10:41:55", "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": 32853, "dataPath": "/neodc/esacci/ghg/data/cci_plus/CH4_GO2_SRPR/v1.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 405913974, "numberOfFiles": 249, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 8984, "startTime": "2019-02-05T00:00:00", "endTime": "2019-10-30T23:59:59" }, "resultQuality": { "ob_id": 3550, "explanation": "For further information see the End to End ECV Uncertainty budget report", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2020-09-28" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 32859, "uuid": "2fbdd374d2e245c38808ec69d41cad11", "short_code": "cmppr", "title": "Composite process for the ESA Greenhouse Gases Climate Change Initiative CH4_GO2_SRPR product", "abstract": "The CH4_GO2_SRPR product was derived from data from the TANSO-FTS/2 instrument on the GOSAT satellite, using the SRPR (Remotec) retrieval algorithm." }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "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": [ 1050, 1635, 1636, 11790, 11791, 11792, 11793, 11794, 11795, 11797, 11798, 11799, 11803, 11804, 11807, 11808, 11809, 11810, 11811, 11812, 11814, 11815, 11816, 11817, 11818, 11820, 11822, 11823, 11825, 11826, 11827, 11832, 11846, 13266, 13267, 13268, 13270, 13272, 13273, 13422, 13423, 36821, 36822, 36823, 36825, 36826, 36827 ], "vocabularyKeywords": [], "identifier_set": [ 10940 ], "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": [ 146135, 146136, 146137, 146138, 146139, 146140, 146141, 146999, 147000, 147001, 147002, 147003 ], "onlineresource_set": [ 42870, 42874, 42875, 42872, 42873, 42871, 90980, 90981, 90982, 90983, 90984, 90985 ] }, { "ob_id": 32751, "uuid": "f1b19872c12d477abfeb229f060a0969", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged carbon dioxide from GOSAT-2, derived using the SRFP (RemoTeC) full physics algorithm, version 1.0.0", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of carbon dioxide (XCO2). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) Near Infrared(NIR) and Shortwave Infrared (SWIR) spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the RemoTeC SRFP Full Physics Retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-06-17T14:48:51", "updateFrequency": "notPlanned", "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. These data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI+) programme.", "removedDataReason": "", "keywords": "ESA, CCI, satellite, atmosphere, carbon dioxide, CO2", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2021-09-02T17:08:43", "doiPublishedTime": "2021-09-08T10:41:31", "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": 32862, "dataPath": "/neodc/esacci/ghg/data/cci_plus/CO2_GO2_SRFP/v1.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 264108937, "numberOfFiles": 249, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 8984, "startTime": "2019-02-05T00:00:00", "endTime": "2019-10-30T23:59:59" }, "resultQuality": { "ob_id": 3550, "explanation": "For further information see the End to End ECV Uncertainty budget report", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2020-09-28" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 32861, "uuid": "25daadec315b4127a5c80d4e1354c690", "short_code": "cmppr", "title": "Composite process for the ESA Greenhouse Gases Climate Change Initiative CH4_GO2_SRFP and CO2_GOS_SRFP products", "abstract": "The CH4_GO2_SRFP and CO2_GO2_SRFP products were derived from data from the TANSO-FTS/2 instrument on the GOSAT satellite, using the SRFP (Remotec) retrieval algorithm." }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "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": [ 36825, 36826, 36827, 50542, 50543, 55529, 55531, 55532, 55533, 63576, 66434, 66435, 66436, 66439, 66440, 66441, 66442, 66443, 66444, 66445, 66446, 66449, 66450, 66451, 66452, 66458, 66460, 66473, 66474, 69612, 69613, 69614, 69615, 69616, 69617, 69618, 69619, 69620, 70615, 70616, 70617, 74867, 86917 ], "vocabularyKeywords": [], "identifier_set": [ 10939 ], "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": [ 146142, 146143, 146144, 146145, 146146, 146147, 146148, 147004, 147005, 147006, 147007, 147008 ], "onlineresource_set": [ 42880, 42881, 42879, 42877, 42876, 42878, 90986, 90987, 90988, 90989, 90990, 90991 ] }, { "ob_id": 32752, "uuid": "ad7de4e3b3b34cc0adca86c68e94d3a1", "title": "NCEO Analysis Ready Data", "abstract": "This project will create Analysis Ready Data for the whole of UK with data source from Sentinel 2 and Landsat 8 over 2017-2019. The output dataset will be surface reflectance with uncertainty quantifications and higher-level biophysical parameter retrieval will also be conducted", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-06-17T16:44:00", "updateFrequency": "", "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "NCEO, ARD, Landsat, Sentinel", "publicationState": "preview", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "planned", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2805, "bboxName": "NCEO ARD", "eastBoundLongitude": 1.75842677206059, "westBoundLongitude": -8.65065103713002, "southBoundLatitude": 49.88497210734906, "northBoundLatitude": 60.846505848366185 }, "verticalExtent": null, "result_field": null, "timePeriod": null, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 130 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "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": [ 146152, 146153, 146154, 146155, 146156, 146157 ], "onlineresource_set": [] }, { "ob_id": 32753, "uuid": "e972cb1afd34494c94d9b22c1b66daca", "title": "Sentinel 1A C-band Synthetic Aperture Radar (SAR): Interferometric Wide (IW) mode Ocean (OCN) Level 2 data, Instrument Processing Facility (IPF) v2", "abstract": "This dataset contains level-2 Interferometric Wide swath (IW) Ocean (OCN) C-band Synthetic Aperture Radar (SAR) data from the European Space Agency (ESA) Sentinel 1A satellite. Level-2 data consists of geolocated geophysical products derived from Level-1. Sentinel 1A was launched on 3rd April 2014 and provides continuous all-weather, day and night imaging radar data. The IW mode is the main operational mode. These level 2 OCN products provide Ocean Wind field (OWI) and Surface Radial Velocity (RVL).\r\n\r\nThe OWI component is a ground range gridded estimate of the surface wind speed and direction at 10 m above the surface, derived from IW mode. The OWI component contains a set of wind vectors for each processed Level-1 input product. The norm is the wind speed in m/s and the argument is wind direction in degrees (meteorological convention = clockwise direction from where the wind blows with respect to the North). The spatial resolution of the SAR wind speed is 1 km for IW mode.\r\n\r\nThe RVL surface radial velocity component is a ground range gridded difference between the measured Level-2 Doppler grid and the Level-1 calculated geometrical Doppler. The RVL component provides continuity of the ASAR Doppler grid. The RVL estimates are produced on a ground-range grid.\r\n\r\nThese data are available via CEDA to any registered CEDA user.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-06-05T19:14:06", "updateFrequency": "notPlanned", "dataLineage": "Data collected and prepared by European Space Agency (ESA). Downloaded from the Collaborative Hub for use by CEDA users.", "removedDataReason": "", "keywords": "Sentinel, radar, Synthetic Aperture Radar, SAR, Interferometric Wide, IW, OCN", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-06-23T15:43:56", "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": 32754, "dataPath": "/neodc/sentinel1a/data/IW/L2_OCN/IPF_v2/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1055164946685, "numberOfFiles": 620049, "fileFormat": "These data are provided in the ESA safe format as downloaded from the Sentinel data hubs." }, "timePeriod": { "ob_id": 3589, "startTime": "2015-04-01T00:00:00", "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": 32755, "uuid": "123da90e83e04211ad73c6cf7f91f531", "short_code": "cmppr", "title": "Composite Process for: Level 2 data from the Sentinel 1A C-band Synthetic Aperture Radar (SAR), Instrument Processing Facility (IPF) v2", "abstract": "Composite process for Level 2 data from the C-band Synthetic Aperture Radar (SAR) deployed on Sentinel 1. This consists of the Acquisition process for raw radar data from the Sentinel 1 SAR and the computation component to produce processed Level 2 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": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12314, "uuid": "06d1c86f906e42f58172de32c2640be2", "short_code": "coll", "title": "Sentinel 1A: 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 1A satellite. Sentinel 1A was launched on 3rd April 2014 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 optimised for emergency response and operational applications with Europe’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 user." }, { "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": [ 146158, 146159, 146160, 146161, 146162, 146163, 146164, 146165, 146168, 146167, 146166 ], "onlineresource_set": [ 42883, 42888, 42884, 42885, 42886, 42890, 42891, 42889 ] }, { "ob_id": 32759, "uuid": "465d86a5750447128f24f79c4f2ecdd4", "title": "BBUBL: 1 km gridded output from WRF v3.6.1 model runs for the Birmingham conurbation for 2015", "abstract": "This dataset contains a range of parameters from a 1 km gridded output from runs of version 3.6.1 of the Weather Research and Forecasting (WRF) model deployed on the ARCHER UK National Supercomputing Service. These runs were part of the NERC funded BBUBL project (Biotelemetry/Bio-aerial-platforms for the Urban Boundary Layer - also known as City Flocks, NERC grant award NE/N003195/1). The domain of the model runs was over the set over Birmingham conurbation for all of 2015. This geo-temporal domain encompasses measurements of the urban boundary layer obtained from instrumentation attached to birds flown around the area. See related dataset.\r\n\r\nThe WRF model set up followed that used by Heaviside et al. (2015) - see linked documentation for details - and was run on the ARCHER UK National Supercomputing Service. Meteorology data from the European Centre for Medium-range Weather Forecasts (ECMWF) ERA-interim reanalysis data for initial and lateral boundary conditions.\r\n\r\nThe WRF v3.6.1 model set up implemented in this study included four nested domains. The domains had grid resolutions of 36 km x 36 km, 12 km x 12 km, 3 km x 3 km and 1 km x 1 km. The finest domain covered the West Midlands, centering over Birmingham. The multi-layer building energy parametrization (BEP) scheme with three land-use types (low-intensity residential, high-intensity residential and industrial/commercial) was also used.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-06-22T10:18:22", "updateFrequency": "notPlanned", "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "urban meteorology, boundary layer", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1 km", "status": "completed", "dataPublishedTime": "2021-09-29T10:12:01", "doiPublishedTime": "2023-06-05T10:22:24.675814", "removedDataTime": null, "geographicExtent": { "ob_id": 2806, "bboxName": "BBUBL WRF run domain", "eastBoundLongitude": -1.26129, "westBoundLongitude": -2.53084, "southBoundLatitude": 52.1007, "northBoundLatitude": 52.8473 }, "verticalExtent": null, "result_field": { "ob_id": 32758, "dataPath": "/badc/deposited2021/bbubl/data/wrf_WestMidlands_2015_1km", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 105379533569, "numberOfFiles": 13, "fileFormat": "Data are CF-compliant NetCDF formatted" }, "timePeriod": { "ob_id": 8986, "startTime": "2015-01-01T00:00:00", "endTime": "2015-12-31T23:00:00" }, "resultQuality": { "ob_id": 3703, "explanation": "Model output has only been checked for CF convention compliance, otherwise supplied as-is.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-06-23" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32760, "uuid": "c445ebc429d84b86b9e62e01bac93ba2", "short_code": "comp", "title": "WRF model version 3.6.1 deployed on the ARCHER UK National Supercomputing Service.", "abstract": "WRF model version 3.6.1 deployed on the ARCHER UK National Supercomputing Service.\r\n\r\nMeteorology data from the European Centre for Medium-range Weather Forecasts (ECMWF) ERA-interim reanalysis data for initial and lateral boundary conditions.\r\n\r\nThe WRF v3.6.1 model set up implemented in this study included four nested domains. The domains had grid resolutions of 36 km × 36 km, 12 km × 12 km, 3 km × 3 km and 1 km × 1 km. The finest domain covered the West Midlands, centering over Birmingham. The multi-layer building energy parametrization (BEP) scheme with three land-use types (low-intensity residential, high-intensity residential and industrial/commercial) was also used.\r\n\r\nFull model set-up details match those in: Heaviside et al. (2015) - see linked documentation." }, "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": 32757, "uuid": "9883bef6085849fea4db955a3f74ec5f", "short_code": "proj", "title": "BBUBL: Biotelemetry/Bio-aerial-platforms for the Urban Boundary Layer (also known as City Flocks) - NE/N003195/1", "abstract": "Attempts to improve the urban component in meteorology and numerical weather prediction models in recent years have been hampered by a paucity of meteorological data in the urban boundary layer (UBL), especially in the region above, but close to, building height. This region is precisely where local energy balances and drag combine with prevailing synoptic patterns to transmit fluid dynamical information up and down spatial scales, with implications for (i) urban weather prediction, (ii) event forecasting (e.g. heatwaves, climatic conditions during sporting events, releases of hazardous substances), and (iii) sustainable urban planning for high density liveable cities. However, capturing meteorological data in urban areas above the mean roof height is problematic using conventional techniques.\r\n\r\nThe BBUBL project proposed Biotelemetry/bio-aerial-platforms as a novel and practicable solution to the data paucity above urban rooftops in the UBL, and to circumvent the regulatory issues related to use of unmanned aerial systems. The project developed a suite of low-cost Avian-Meteorology-Instrument Packages (AvMIPs) for ensemble deployment in Birmingham as a suitably large and heterogeneous test case.\r\n\r\nThe AvMIPs were tested rigorously to determine: (i) data biases and reliability; (ii) sensor response to temperature variations; (iii) effect of radiation; and (iv) effect of bird's body temperature and other 'platform effects'. After quality assurance and control of the packages had been determined to be adequate, the primary targets of the AvMIP deployment were the thermal and moisture structures of the UBL at the city and neighbourhood scales. Favourable weather conditions for deployment will be identified via pre-deployment modelling using a mesoscale meteorological model (WRF, Weather Research and Forecasting). \r\n\r\nSubsequent analysis and interpretation of the AvMIP data and synthesis of the data together with Birmingham's canyon (3m) meteorological data were assisted by post-deployment modelling for the measurement periods.\r\n\r\nOverall, this project aimed to deliver a novel, and rigorously tested, technology for probing the UBL. A unique dataset for the UBL of a major European conurbation was obtained, elucidating climate mitigation issues such as the cooling (or heating) capability/capacity of a large park (or a city centre) to a city's UBL, and scientific issues such as the magnitude of the 'blending height' at which the effect of urban surface heterogeneity is no longer detectable.\r\n\r\nSuccess of the project was seen as a necessary step towards deployment of chemical sensors, and lead to generation of unprecedented datasets of the urban atmosphere for both research and city-planning purposes. Novel field deployments of the kind proposed by the project require strong partnerships with a wide variety of stakeholders. The Royal Pigeon Racing Association (RPRA) provide critical support in terms of birds that will behave in well determined ways. The RPRA have experience of mounting payloads on pigeons and so can ensure that payloads are appropriately in size, weight, etc., and that pigeon deployments delivered the data sought. Birmingham City Council supported the project in three ways: 1. As one of the principal end-users of the results (feeding into improved diagnosis and forecasting of urban climatology across the city through the joint city-university BUCCANEER project); 2. In order to facilitate use of birds in open urban spaces such as parks; and 3. In order to facilitate access to city buildings on which gulls are nesting. Dr Stefan Bodnar, an ecological consultant, supported the project by acting as principal bird handler and as a consultant for public dissemination of our work.\r\n \r\nObjectives\r\n\r\nTo directly address the data sparsity of meteorological measurements in the urban boundary layer (UBL), especially in the region above, but close to, building height, and to circumvent the regulatory issues related to use of Unmanned Aerial Systems, the project proposed developing and deploying instrument payloads on birds.\r\n\r\nThe project set out the following research questions, to be addressed by a series of objectives. RESEARCH QUESTIONS: \r\n(1) Can biotelemetry/bio-aerial-platforms be used to deliver observations of temperature, humidity and wind speed in the UBL with accuracy and precision sufficient for research?\r\n(2) Can the data derived from biotelemetry/bioaerial-platforms be used to inform the structure of the UBL at the city scale and the local IBLs at neighbourhood scales?\r\n(3) If so, what is the cooling (or heating) capability/capacity of a large park (or a city centre) to a city's UBL and what is the magnitude of the blending height? \r\n(4) How do such measurements compare to results derived from a numerical weather prediction (NWP) model?\r\n(5) What lessons can be learnt to assess the feasibility of other payloads (e.g. chemical sensors)? \r\n\r\nOBJECTIVES were: \r\na) To develop a suite of low-cost Avian-Meteorology-Instrument Packages (AvMIPs) (i) capable of sensing temperature (changes of at least 0.2 degree with a 1 sec response time) and humidity (changes of 5% with a 15 sec response time) and (ii) suitable for a range of bird taxa (raptors, pigeons, and gulls [Larus spp.]), with increasing deployment duration from mins to hours to days, respectively. \r\nb) To test AvMIPs rigorously in the following aspects: (i) data biases and reliability; (ii) responses to temperature variations; (iii) effect of radiation; and (iv) effect of bird's body temperature. \r\nc) To conduct pre-deployment modelling using a NWP model. This will be used to design a deployment plan. The robustness of this approach will ensure scales of interest (city and neighbourhood scales only), time of day (mainly daytime and early morning), and seasonality (both summer and winter) are all taken into account. \r\nd) To execute the deployment plan derived from c) in Birmingham for the favourable synoptic weather conditions for the ensemble AvMIP deployment. Post-deployment modelling will also be completed. \r\ne) To synthesise and analyse the AvMIP and BUCL data along with post-deployment modelling output, to identify the feasibility, reliability, applicability and benefits of the AvMIPs as an observational platform. Results from this analysis will be used to make recommendations and to scope the design of future biotelemetry/bio-aerial-platform payloads and deployment strategies." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 50415, 50417, 53937, 53938, 53942, 53944, 58293, 58303, 58305, 58307, 58311, 58313, 58318, 58320, 58322, 58324, 58332, 58337, 58338, 58347, 58348, 58349, 58353, 58354, 58357, 58358, 58360, 58361, 58369, 58371, 61651, 61652, 61653, 61654, 61655, 61656, 61657, 61658, 61659, 61660, 61661, 61662, 61663, 61664, 61665, 61666, 61667, 61668, 61669, 61670, 61671, 61672, 61673, 61674, 61675, 61676, 61677, 61678, 75246, 83076 ], "vocabularyKeywords": [], "identifier_set": [ 12525 ], "observationcollection_set": [ { "ob_id": 33079, "uuid": "1c3a4c29b0ea42f5b0e254b7571aa3fa", "short_code": "coll", "title": "BBUBL: avian-borne met sensor package data and WRF model run data", "abstract": "This dataset collection contains data from avian-borne meteorological sensors from a series of flights over Birmingham as part of the Biotelemetry/Bio-aerial-platforms for the Urban Boundary Layer (BBUBL)(NERC grant: NE/N003195/1) project (also known as City Flocks) along with Weather Research and Forecasting (WRF) model run output for the same period." } ], "responsiblepartyinfo_set": [ 146183, 146184, 146185, 146186, 146187, 146188, 146189, 146190, 146276 ], "onlineresource_set": [ 42926, 42927, 42928 ] }, { "ob_id": 32762, "uuid": "18851d1f4454455dad76141c02ad740e", "title": "Sentinel 1B C-band Synthetic Aperture Radar (SAR): Interferometric Wide (IW) mode Ocean (OCN) Level 2 data, Instrument Processing Facility (IPF) v3", "abstract": "This dataset contains level-2 Interferometric Wide swath (IW) Ocean (OCN) C-band Synthetic Aperture Radar (SAR) data from the European Space Agency (ESA) Sentinel 1B satellite. Level-2 data consists of geolocated geophysical products derived from Level-1. 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. These level 2 OCN products provide Ocean Wind field (OWI) and Surface Radial Velocity (RVL). \r\n\r\nThe OWI component is a ground range gridded estimate of the surface wind speed and direction at 10 m above the surface, derived from IW mode. The OWI component contains a set of wind vectors for each processed Level-1 input product. The norm is the wind speed in m/s and the argument is wind direction in degrees (meteorological convention = clockwise direction from where the wind blows with respect to the North). The spatial resolution of the SAR wind speed is 1km for IW mode.\r\n\r\nThe RVL surface radial velocity component is a ground range gridded difference between the measured Level-2 Doppler grid and the Level-1 calculated geometrical Doppler. The RVL component provides continuity of the ASAR Doppler grid. The RVL estimates are produced on a ground-range grid.\r\n\r\nThese data are available via CEDA to any registered CEDA user.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-12-24T01:00:12", "updateFrequency": "asNeeded", "dataLineage": "Data collected and prepared by European Space Agency (ESA). Downloaded from the Collaborative Hub for use by CEDA users.", "removedDataReason": "", "keywords": "Sentinel, radar, Synthetic Aperture Radar, SAR, Interferometric Wide, IW, OCN", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-06-24T12:59:41", "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": 32763, "dataPath": "/neodc/sentinel1b/data/IW/L2_OCN/IPF_v3/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 935560923847, "numberOfFiles": 552782, "fileFormat": "These data are provided in the ESA safe format as downloaded from the Sentinel data hubs." }, "timePeriod": { "ob_id": 8988, "startTime": "2019-04-10T00:00:00", "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": 32764, "uuid": "0cea6c149f7842bca07e2b290a1b8e87", "short_code": "cmppr", "title": "Composite Process for: Level 2 data from the Sentinel 1B C-band Synthetic Aperture Radar (SAR), Instrument Processing Facility (IPF) v3", "abstract": "Composite process for Level 2 data from the C-band Synthetic Aperture Radar (SAR) deployed on Sentinel 1. This consists of the Acquisition process for raw radar data from the Sentinel 1 SAR and the computation component to produce processed Level 2 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": [], "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": [ 146198, 146199, 146200, 146201, 146202, 146203, 146204, 146205, 146208, 146206, 146207 ], "onlineresource_set": [ 42902, 42899, 42896, 42898, 42897, 42900, 42904, 42903 ] }, { "ob_id": 32766, "uuid": "4d10319960f442528a8f365ad5dfbcb4", "title": "ATSR-1 Ungridded Brightness Temperature (UBT) Data", "abstract": "Data from the Along Track Scanning Radiometer (ATSR-1) instrument on the ERS-1 platform operational between 1991 and 1996. The ATSR is an imaging radiometer providing images of the Earth from space. The ERS (Earth Resources Satellite) program was funded by and operated by ESA and was the first main ESA EO data campaign. ATSR-1 was placed on the ERS1 platform and ATSR-2 was on the ERS-2 platform. The ATSR-1 and 2 instruments were followed by the Advanced Along Track Scanning Radiometer (AATSR) on the ENVISAT platform in 2002.\r\n\r\nThe ATSR-1 instrument has been designed for exceptional sensitivity and stability of calibration, which are achieved through the incorporation of several innovative features in the instrument design. This design has, among other things, enabled the accurate measurement of sea surface temperature to an accuracy of +/- 0.3K. The design of the ATSR instrument incorporates a dual view made possible by the rotating scan mirror. There is a nadir view and then a subsequent along track view. These provide 2 images per scan and allow improved estimate of atmospheric attenuation. This coupled with the inclusion of consistent calibration using on-board black bodies allows for the collection of extremely radiometrically accurate data. \r\n\r\nThe data are Level1 Ungridded Brightness Temperatures (UBT). The data are in SADIST-2 format and CEDA is the primary archive for this data. The UBT product provides scenes for both nadir and forward views with a swath width of 512km and a ground pixel distance of 1km. \r\n\r\nThis dataset is superseded by the AATSR Multimission ATSR-1 data set that involved reprocessing this data with improved calibration and cloud masking and is available in a number of reprocessings so consistent with ENVISAT format data.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2020-06-05T19:51:54", "updateFrequency": "notPlanned", "dataLineage": "Data was producted by the ESA ERS Ground Segment and UBT and GBT (Gridded Brightness Temperature) products delivered to STFC RAL by tape. Data was initially made available to the NEODC (NERC Earth Observation Data Centre) to users authorised by the ESA/NERC Data Quality working group. CEDA maintains this data as the primary archive of ATSR UBT data.", "removedDataReason": "", "keywords": "Brightness Temperature, Radiometric Calibration, Dual View, Nadir view, Forward view, Reprocessed", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1km", "status": "completed", "dataPublishedTime": "2003-10-03T12:00:00", "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": 39200, "dataPath": "/neodc/atsrubt/atsr1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 8144579022490, "numberOfFiles": 2272699, "fileFormat": "SADIST-2" }, "timePeriod": { "ob_id": 10874, "startTime": "1991-07-17T00:00:00", "endTime": "1996-08-01T23:59:59" }, "resultQuality": { "ob_id": 4103, "explanation": "UBT Data from the ATSR series instruments are L1 radiometrically calibrated using integrated sterling cycle black bodies incorporated within each swath scan. Data are themselves 512km x 512km alongtrack scanned data incorporating 2 views: Nadir and Forward. These two views are made available as separate files but share filename attributes but delineated by \"NAD\" or \"FRWD\" within the filename.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2022-10-26" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 39199, "uuid": "77d1d5c7f73d4683a451a9380ea31ffb", "short_code": "acq", "title": "Acquisition process for ERS1 ATSR1 UBT", "abstract": "ATSR1 Ungridded Brightness Temperature collected 1991 to 1996" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 99 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2616, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "atsrubt", "label": "restricted: atsrubt group", "licence": { "ob_id": 73, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/atsrubt.pdf", "licenceClassifications": [] } } ], "projects": [ { "ob_id": 19905, "uuid": "fe42fbfd372d4d7e905cfb84f2728f77", "short_code": "proj", "title": "ATSR-1 Mission", "abstract": "Along-Track Scanning Radiometer (ATSR-1) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR)." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 10983, "uuid": "939c6aa57f9bcd5340157cb013b036d8", "short_code": "coll", "title": "ATSR-1/2 Ungridded Brightness Temperature (UBT) data", "abstract": "This dataset collection comprises Ungridded Brightness Temperature (UBT) products from both ATSR-1 and ATSR-2 on the respective ERS-1 & 2 platforms. The ATSR (Along Track Scanning Radiometer) is an imaging radiometer providing images of the Earth from space. The ERS (Earth Resources Satellite) was the first ESA satellite observation programme comprising 2 polar orbiters. The ERS-1 and 2 programmes commenced in 1991 and 1995 respectively with ERS1 ceasing operations in 2000 and ERS-2 in 2011. \r\n\r\nThe UBT data is an ungridded brightness temperature/reflectance product in the SADIST-2 data format. The product contains ungridded, calibrated brightness temperatures or reflectances from all or some of the ATSR-1/ATSR-2 detectors. Although the product remains ungridded, it may optionally contain pixel latitude/longitude positions, and/or pixel X/Y (across-track/along-track) co-ordinates. Ungridded products contain pixels in the ATSR scan geometry. There is a correspondence between the contents of a record and the contents of an ATSR instrument scan. ATSR data is notable in that it incorporated 2 look directions (nadir and forward) to aid in atmospheric correction and also incorporated consistent calibration for each scan/scene.\r\n\r\nATSR-1 and 2 data are available at CEDA to any registered UK user with correct authorisation from the ATSR-1/2 Science Team, and NERC Award reference. Non NERC users should have ESA Category 1 clearance. However, users are encouraged to use the ATSR-1/2 in the latest AATSR multimission format in preference to this UBT data. CEDA remains the primary archive for this data." } ], "responsiblepartyinfo_set": [ 146244, 146238, 146239, 146240, 146241, 146243, 190928, 146242 ], "onlineresource_set": [ 72898 ] }, { "ob_id": 32767, "uuid": "76202b367af44b82a1c7ba1d1a39e7b9", "title": "Sentinel 1A C-band Synthetic Aperture Radar (SAR): Interferometric Wide (IW) mode Single Look Complex (SLC) Level 0 data", "abstract": "This dataset contains level 0, raw Interferometric Wide swath (IW) Single Look Complex (SLC) C-band Synthetic Aperture Radar (SAR) data from the European Space Agency (ESA) Sentinel 1A satellite. Sentinel 1A was launched on 3rd April 2014 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 were archived as a test - CEDA does not regularly archive these products.\r\n\r\nThese data are available via CEDA to any registered CEDA user.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-04-29T15:26:43", "updateFrequency": "notPlanned", "dataLineage": "Data collected and prepared by European Space Agency (ESA). Downloaded from the Collaborative Hub for use by CEDA users.", "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": "completed", "dataPublishedTime": "2021-06-25T15:44:32", "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": 32768, "dataPath": "/neodc/sentinel1a/data/IW/L0_RAW/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 837020898568, "numberOfFiles": 1626, "fileFormat": "These data are provided in the ESA safe format as downloaded from the Sentinel data hubs." }, "timePeriod": { "ob_id": 8989, "startTime": "2018-11-01T00:00:00", "endTime": "2019-01-01T00:00:00" }, "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": { "ob_id": 12318, "uuid": "f95b77f14a554727a1975802b25ad8a7", "short_code": "acq", "title": "Acquisition Process for: Sentinel 1A C-band Synthetic Aperture Radar (SAR), Interferometric Wide (IW) mode.", "abstract": "The acquisition process for the collection of raw radar data from the European Space Agency (ESA) Sentinel 1A C-band Synthetic Aperture Radar (SAR) in Interferometric Wide (IW) mode." }, "procedureComputation": null, "procedureCompositeProcess": null, "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": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12314, "uuid": "06d1c86f906e42f58172de32c2640be2", "short_code": "coll", "title": "Sentinel 1A: 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 1A satellite. Sentinel 1A was launched on 3rd April 2014 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 optimised for emergency response and operational applications with Europe’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 user." }, { "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": [ 146246, 146249, 146245, 146247, 146252, 146251, 146250, 146248, 146253, 146254 ], "onlineresource_set": [ 42908, 42910, 42911, 42912 ] }, { "ob_id": 32769, "uuid": "0cea2aebf58b406784162a768bdfe0fb", "title": "CRU TS3.23 Maximum Temperature: Climatic Research Unit (CRU) Time-Series (TS) version 3.23 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2013)", "abstract": "TBC", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": null, "updateFrequency": "notPlanned", "dataLineage": "", "removedDataReason": "", "keywords": "CRU", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "0.5x0.5 degree grid", "status": "completed", "dataPublishedTime": null, "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": null, "timePeriod": null, "resultQuality": { "ob_id": 3416, "explanation": "The data are quality controlled by the Climatic Research Unit (CRU) at the University of East Anglia. Details are given in the paper Harris et al. 2020 and the release notes, links to both can be found in the documentation.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2020-05-21" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 20388, "uuid": "81842aa686174647ae132a4c841d73b6", "short_code": "comp", "title": "UEA Climatic Research Unit (CRU) high resolution gridding software deployed on UEA CRU computer system for v4.00", "abstract": "This computation involved: UEA Climate Research Unit (CRU) High Resolution gridding software deployed on UEA Climate Research Unit (CRU) computer system. For details about the production of CRU TS and CRU CY datasets, please refer to Harris et al. (2020) - see Details/Docs tab, moderated by the Release Notes for v4.00 (which outline the new gridding process)" }, "procedureCompositeProcess": null, "imageDetails": [ 103 ], "discoveryKeywords": [], "permissions": [], "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": [], "responsiblepartyinfo_set": [ 146261, 146263, 146264, 146265, 146266, 146267, 146268, 146262, 146269, 146270, 148571, 146271, 168463, 146272 ], "onlineresource_set": [ 42919, 42914, 42915, 42916, 42917, 42918, 42922, 42923, 42924, 42925 ] }, { "ob_id": 32771, "uuid": "8130ee8d2e33439aa85669b620e7b532", "title": "QA4ECV Bi-directional reflectance factor", "abstract": "QA4ECV Bi-directional reflectance factor data. This data provides masks for the AVHRR data.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-10-14T15:07:51", "updateFrequency": "notPlanned", "dataLineage": "Data are provided by the QA4ECV project for archival with CEDA. Data are in NetCDF format.", "removedDataReason": "", "keywords": "", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 32772, "dataPath": "/neodc/qa4ecv/data/bi-directional_reflectance_factor/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 191746904474, "numberOfFiles": 13162, "fileFormat": "These data are provided in NetCDF file format." }, "timePeriod": { "ob_id": 8995, "startTime": "1981-06-24T00:00:00", "endTime": "2017-08-01T23:59:59" }, "resultQuality": { "ob_id": 3217, "explanation": "Data as provided by the QA4ECV project, archived at CEDA", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-01-18" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 210 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2528, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 8, "licenceURL": "http://creativecommons.org/licenses/by/4.0/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 25937, "uuid": "130756538390418ea80ebe143542b01d", "short_code": "proj", "title": "Quality Assurance for Essential Climate Variables (QA4ECV)", "abstract": "The FP7 QA4ECV project was initiated in 2014 to demonstrate how reliable and traceable quality information can be provided for satellite and ground-based measurements of climate and air quality parameters. The project developed and applied a Quality Assurance framework on new and improved multi-decadal data records of the Land ECVs Albedo, Leaf Area Index (LAI), and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and on the Atmosphere ECVs nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO).\r\n\r\nQA4ECV provides multi-decadal satellite data records for 3 Land Essential Climate Variables (ECVs) and 3 Atmosphere ECV precursors." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 67728, 67729 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 146280, 146281, 146282, 146283, 146284, 146285, 146286, 146287, 146288, 146289 ], "onlineresource_set": [ 42930, 42931, 42932 ] }, { "ob_id": 32775, "uuid": "6ae95449b899409790e64e23120b48e8", "title": "Sentinel 1A C-band Synthetic Aperture Radar (SAR): SM mode SLC Level 1 data, Instrument Processing Facility (IPF) v2", "abstract": "This dataset contains Stripmap Mode (SM) C-band Synthetic Aperture Radar (SAR) Single Look Complex (SLC) data from the European Space Agency (ESA) Sentinel 1A satellite. Sentinel 1A was launched on 3rd April 2014 and provides continuous all-weather, day and night imaging radar data. The SM mode is used only on special request for extraordinary events such as emergency management. The SM mode supports single (HH or VV) and dual (HH+HV or VV+VH) polarisation. \r\n\r\nStripmap SLCs contain one image per polarisation band from one of six overlapping beams. Each beam covers 80.1 km, covering a combined range of 375 km. Pixel spacing is determined, in azimuth by the pulse repetition frequency (PRF), and in range by the radar range sampling frequency, providing natural pixel spacing.\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": "2020-03-31T10:18:21", "updateFrequency": "", "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, Stripmap, Single Look Complex", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-06-25T15:50:48", "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": 32776, "dataPath": "/neodc/sentinel1a/data/SM/L1_SLC/IPF_v2/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 6563765716239, "numberOfFiles": 12131, "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": 8997, "startTime": "2015-01-10T00:00:00", "endTime": "2019-06-25T23:59:59" }, "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": 32777, "uuid": "2a273bb40a9c44a7bfc46ac89f623d28", "short_code": "cmppr", "title": "Composite Process for: Level 1 data from the Sentinel 1A C-band Synthetic Aperture Radar (SAR), Stripmap (SM) mode, Instrument Processing Facility (IPF) v2", "abstract": "Composite process for Level 1 data from the C-band Synthetic Aperture Radar (SAR) deployed on Sentinel 1. 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": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12314, "uuid": "06d1c86f906e42f58172de32c2640be2", "short_code": "coll", "title": "Sentinel 1A: 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 1A satellite. Sentinel 1A was launched on 3rd April 2014 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 optimised for emergency response and operational applications with Europe’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 user." }, { "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": [ 146298, 146299, 146300, 146301, 146302, 146303, 146304, 146305, 146306, 146307 ], "onlineresource_set": [ 42934, 42935, 42933 ] }, { "ob_id": 32780, "uuid": "9cafde3874d54e2794fcfb372311883e", "title": "Sentinel 1A C-band Synthetic Aperture Radar (SAR): Interferometric Wide (IW) mode Single Look Complex (SLC) Level 1 data, Instrument Processing Facility (IPF) v3", "abstract": "This dataset contains level 1 Interferometric Wide swath (IW) Single Look Complex (SLC) C-band Synthetic Aperture Radar (SAR) data from the European Space Agency (ESA) Sentinel 1A satellite. Sentinel 1A was launched on 3rd April 2014 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\nThese data are available via CEDA to any registered CEDA user.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2025-07-18T00:01:21", "updateFrequency": "asNeeded", "dataLineage": "Data collected and prepared by European Space Agency (ESA). Downloaded from the Collaborative Hub for use by CEDA users.", "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": "2021-06-25T15:00:46", "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": 32781, "dataPath": "/neodc/sentinel1a/data/IW/L1_SLC/IPF_v3", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 5766391293430236, "numberOfFiles": 5714231, "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": 8998, "startTime": "2019-04-10T00:00:00", "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": 32782, "uuid": "972c15a7c83a419caf2ddce1d5f0bb20", "short_code": "cmppr", "title": "Composite Process for: Level 1 data from the Sentinel 1A C-band Synthetic Aperture Radar (SAR), Interferometric Wide (IW), Instrument Processing Facility (IPF) v3", "abstract": "Composite process for Level 1 data from the C-band Synthetic Aperture Radar (SAR) deployed on Sentinel 1. 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": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12314, "uuid": "06d1c86f906e42f58172de32c2640be2", "short_code": "coll", "title": "Sentinel 1A: 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 1A satellite. Sentinel 1A was launched on 3rd April 2014 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 optimised for emergency response and operational applications with Europe’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 user." }, { "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": [ 146325, 146318, 146320, 146324, 146323, 146322, 146319, 146321, 146328, 146327, 146326 ], "onlineresource_set": [ 42941, 42942, 42938, 42939, 42940, 42943 ] }, { "ob_id": 32785, "uuid": "67b646c363fc4f9289486ffd8c4c6b07", "title": "Sentinel 3A Synthetic Aperture Radar Altimeter (SRAL) Level 1A data", "abstract": "This dataset contains level 1a altimetry data from the Synthetic Aperture Radar Altimeter (SRAL) aboard the European Space Agency (ESA) Sentinel 3A Satellite. Sentinel 3A was launched on the 16th of February 2016. These data contain geo-located bursts of echoes with all calibrations applied. Level 1A (L1A) is an intermediate output of the Synthetic Aperture Radar (SAR) processor. L1A complex waveforms should be fully calibrated (including both instrumental gains and calibration corrections) and aligned in range within each burst. The time tag is given at the surface (that is when the middle of the burst reaches the surface). L1A is the starting point for the SAR processing which provides high-resolution products. Data are provided by ESA and are made available via CEDA to any registered user.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2020-04-17T12:05:22", "updateFrequency": "continual", "dataLineage": "Data collected and prepared by European Space Agency (ESA). Downloaded from the Sentinel hubs for use by the CEDA community.", "removedDataReason": "", "keywords": "Sentinel, Synthetic Aperture Radar Altimeter, SRAL", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2022-12-19T15:36:13", "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": 32786, "dataPath": "/neodc/sentinel3a/data/SRAL/L1_SRA_A__/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 11349097935027, "numberOfFiles": 13802, "fileFormat": "Data are provided by ESA in zipped SAFE format." }, "timePeriod": { "ob_id": 9014, "startTime": "2018-02-01T00:00:00", "endTime": null }, "resultQuality": { "ob_id": 3218, "explanation": "Data provided by ESA. CEDA download the data from the Collaborative or open access data hubs to make available on the CEDA archive.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-01-22" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 32824, "uuid": "33712e8a0e0741a7b16f891a6a26b984", "short_code": "cmppr", "title": "Composite Process for: Level 1A data from the Sentinel 3 Synthetic Aperture Radar Altimeter (SRAL)", "abstract": "Composite process for Level 1 data from the Synthetic Aperture Radar Altimeter (SRAL) deployed on Sentinel 3. This consists of the Acquisition process for raw data from the Sentinel 3 SRAL and the computation component to produce processed Level 1A 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": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 32818, "uuid": "0bcc2457250548abb51a90f96772c374", "short_code": "coll", "title": "Sentinel 3A data", "abstract": "This dataset collection contains data products from all of the instruments on the European Space Agency (ESA) Sentinel 3A satellite. Sentinel 3A was launched on 16th February 2016.\r\n\r\nThe Sentinel 3 satellites have 3 main instruments on board: Sea and Land Surface Temperature Radiometer (SLSTR), Ocean and Land Colour Instrument (OLCI) and SAR Radar Altimeter (SRAL).\r\n\r\nData are provided by the European Space Agency (ESA) and are made available via CEDA to any registered user." }, { "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": [ 146376, 146377, 146378, 146379, 146380, 146381, 146382, 146384, 146375, 146383, 146385 ], "onlineresource_set": [ 42947, 42948 ] }, { "ob_id": 32787, "uuid": "41526384c3dd463eb0fc0117b87d08f6", "title": "Sentinel 3A Synthetic Aperture Radar Altimeter (SRAL) Level 1B-S data", "abstract": "This dataset contains level 1b (L1B-S) altimetry data from the Synthetic Aperture Radar Altimeter (SRAL) aboard the European Space Agency (ESA) Sentinel 3A Satellite. Sentinel 3A was launched on the 16th of February 2016. These data are fully SAR-processed and calibrated High-Resolution (HR) complex echoes arranged in stacks after slant range correction and prior to echo multi-look (multi-look processing reduces noise by averaging of adjacent pixels, and thereby reduces the standard deviation of the noise level).\r\n\r\nThe L1B-S HR product contains information from Doppler beams data. Hence, it has only been defined for the Synthetic Aperture Radar (SAR) processing chain. The Doppler beams associated with a given surface location (also called stack data) are formed through the selection of all the beams that illuminate a given surface location, and that contribute to each L1B HR waveform. Beams are the result of applying Doppler processing to the waveform bursts, which allows division of the conventional altimeter footprint into a certain number of stripes, thus creating a Delay Doppler Map (DDM). With this, contributions coming from different stripes can be identified and collected separately. When all the contributions from different bursts are collected, a stack is formed. The stack waveforms are provided in In-phase (I) and Quadrature-phase (I/Q) samples (complex waveforms) in the frequency domain. Apart from the Doppler processing, the beams of a stack have also been fully calibrated and range aligned. The L1B-S also includes characterisation parameters about the stack itself. The time tag is given at each surface location (defined throughout the L1 processing chain).\r\n\r\nData are provided by ESA and are made available via CEDA to any registered user.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-04-30T23:54:46", "updateFrequency": "continual", "dataLineage": "Data collected and prepared by European Space Agency (ESA). Downloaded from the Sentinel hubs for use by the CEDA community.", "removedDataReason": "", "keywords": "Sentinel, Synthetic Aperture Radar Altimeter, SRAL, SAR, Sentinel3", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-07-01T16:06:40", "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": 32788, "dataPath": "/neodc/sentinel3a/data/SRAL/L1_SRA_BS_/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 5415290909817, "numberOfFiles": 9688, "fileFormat": "Data are provided by ESA in zipped SAFE format." }, "timePeriod": { "ob_id": 9015, "startTime": "2018-02-01T00:00:00", "endTime": null }, "resultQuality": { "ob_id": 3218, "explanation": "Data provided by ESA. CEDA download the data from the Collaborative or open access data hubs to make available on the CEDA archive.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-01-22" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 19018, "uuid": "ed75ee9f51144d5bbd6a971101f92211", "short_code": "cmppr", "title": "Composite Process for: Level 1 data from the Sentinel 3 Synthetic Aperture Radar Altimeter (SRAL)", "abstract": "Composite process for Level 1 data from the Synthetic Aperture Radar Altimeter (SRAL) deployed on Sentinel 3. This consists of the Acquisition process for raw data from the Sentinel 3 SRAL and the computation component to produce processed Level 1 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": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 32818, "uuid": "0bcc2457250548abb51a90f96772c374", "short_code": "coll", "title": "Sentinel 3A data", "abstract": "This dataset collection contains data products from all of the instruments on the European Space Agency (ESA) Sentinel 3A satellite. Sentinel 3A was launched on 16th February 2016.\r\n\r\nThe Sentinel 3 satellites have 3 main instruments on board: Sea and Land Surface Temperature Radiometer (SLSTR), Ocean and Land Colour Instrument (OLCI) and SAR Radar Altimeter (SRAL).\r\n\r\nData are provided by the European Space Agency (ESA) and are made available via CEDA to any registered user." }, { "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": [ 146387, 146388, 146389, 146390, 146391, 146392, 146393, 146394, 146386, 146395, 146396 ], "onlineresource_set": [ 42949, 42950 ] }, { "ob_id": 32789, "uuid": "ab33998624364d63be7471a30cee635b", "title": "Sentinel 1A C-band Synthetic Aperture Radar (SAR): Wave (WV) mode Ocean (OCN) Level 2 data, Instrument Processing Facility (IPF) v3", "abstract": "This dataset contains Level-2, Wave mode (WV) Ocean (OCN) C-band Synthetic Aperture Radar (SAR) data from the European Space Agency (ESA) Sentinel 1A satellite. Level-2 data consists of geolocated geophysical products derived from Level-1. \r\n\r\nFrom WV modes, the OCN product will only contain Ocean Swell Spectra (OSW) and Surface Radial Velocity (RVL). \r\n\r\nThe OSW component is a two-dimensional ocean surface swell spectrum and includes an estimate of wind speed and direction per swell spectrum. The OSW component provides continuity measurement of SAR swell spectra at C-band. OSW is estimated from Sentinel-1 SLC images by inversion of the corresponding image cross-spectra.\r\n\r\nThe OSW is generated from Stripmap and Wave modes only and is not available from the TOPSAR IW and EW modes. For Stripmap mode, there are multiple spectra derived from the Level-1 SLC image. For Wave mode, there is one spectrum per vignette.\r\n\r\nOcean wave height spectra are provided in units of m4 and given on a polar grid of wavenumber in rad/m and direction in degrees with respect to North.\r\n\r\nThe OSW product also contains one estimate of the wind speed in m/s and direction in degrees (meteorological convention) per ocean wave spectrum, as well as parameters derived from the ocean wave spectra (integrated wave parameters) and from the imagette (image statistics).\r\n\r\nThe spatial coverage of the OSW product is equal to the spatial coverage of the corresponding Level-1 WV SLC or Level-1 SM SLC product, limited to ocean areas.\r\n\r\nThe RVL surface radial velocity component is a ground range gridded difference between the measured Level-2 Doppler grid and the Level-1 calculated geometrical Doppler. The RVL component provides continuity of the ASAR Doppler grid. The RVL estimates are produced on a ground-range grid.\r\n\r\nThe Level-2 Doppler is computed on a grid similar to the OWI component grid and provides an estimate of the Doppler frequency and the Doppler spectral width. For TOPS, one grid is provided by swath (additional dimension in the NetCDF). The uncertainties of the estimates are also provided for both the Doppler and radial velocity. The Doppler frequency and the Doppler spectral width are estimated based on fitting the azimuth spectral profile of the data to the antenna model taking into account additive noise, aliasing, and sideband effects. The Doppler frequency provided in the product is the pure Doppler frequency estimated from the SLC data without correcting for geometry and mispointing errors.\r\n\r\nSentinel 1A was launched on 3rd April 2014 and provides continuous all-weather, day and night imaging radar data. These data are available via CEDA to any registered CEDA user.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2023-11-02T00:01:12", "updateFrequency": "asNeeded", "dataLineage": "Data collected and prepared by European Space Agency (ESA). Downloaded from the Collaborative Hub for use by CEDA users.", "removedDataReason": "", "keywords": "Sentinel, radar, Synthetic Aperture Radar, SAR, Wave, WV, OCN", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2023-05-04T10:46:29", "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": 32790, "dataPath": "/neodc/sentinel1a/data/WV/L2_OCN/IPF_v3/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1591499378956, "numberOfFiles": 158861, "fileFormat": "Data are provided in SAFE format. With the data products inside the SAFE zip in NetCDF." }, "timePeriod": { "ob_id": 9002, "startTime": "2019-06-26T00:00:00", "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": 32793, "uuid": "82df069ac1ad48ae8e548aaae496acf3", "short_code": "cmppr", "title": "Composite Process for: Level 1 data from the Sentinel 1A C-band Synthetic Aperture Radar (SAR), Wave (WV) mode, Instrument Processing Facility (IPF) v3", "abstract": "Composite process for Level 1 data from the C-band Synthetic Aperture Radar (SAR) deployed on Sentinel 1. 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": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12314, "uuid": "06d1c86f906e42f58172de32c2640be2", "short_code": "coll", "title": "Sentinel 1A: 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 1A satellite. Sentinel 1A was launched on 3rd April 2014 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 optimised for emergency response and operational applications with Europe’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 user." }, { "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": [ 146397, 146398, 146399, 146400, 146401, 146402, 146403, 146404, 146407, 146406, 146405 ], "onlineresource_set": [ 42951, 42952, 42953, 42954, 42955 ] }, { "ob_id": 32795, "uuid": "e9df102eeac54d04b24686fc026c63f9", "title": "Sentinel 1B C-band Synthetic Aperture Radar (SAR): Wave (WV) mode Ocean (OCN) Level 2 data, Instrument Processing Facility (IPF) v2", "abstract": "This dataset contains Level-2, Wave mode (WV) Ocean (OCN) C-band Synthetic Aperture Radar (SAR) data from the European Space Agency (ESA) Sentinel 1B satellite. Level-2 data consists of geolocated geophysical products derived from Level-1. \r\n\r\nFrom WV modes, the OCN product will only contain Ocean Swell Spectra (OSW) and Surface Radial Velocity (RVL). \r\n\r\nThe OSW component is a two-dimensional ocean surface swell spectrum and includes an estimate of wind speed and direction per swell spectrum. The OSW component provides continuity measurement of SAR swell spectra at C-band. OSW is estimated from Sentinel-1 SLC images by inversion of the corresponding image cross-spectra.\r\n\r\nThe OSW is generated from Stripmap and Wave modes only and is not available from the TOPSAR IW and EW modes. For Stripmap mode, there are multiple spectra derived from the Level-1 SLC image. For Wave mode, there is one spectrum per vignette.\r\n\r\nOcean wave height spectra are provided in units of m4 and given on a polar grid of wavenumber in rad/m and direction in degrees with respect to North.\r\n\r\nThe OSW product also contains one estimate of the wind speed in m/s and direction in degrees (meteorological convention) per ocean wave spectrum, as well as parameters derived from the ocean wave spectra (integrated wave parameters) and from the imagette (image statistics).\r\n\r\nThe spatial coverage of the OSW product is equal to the spatial coverage of the corresponding Level-1 WV SLC or Level-1 SM SLC product, limited to ocean areas.\r\n\r\nThe RVL surface radial velocity component is a ground range gridded difference between the measured Level-2 Doppler grid and the Level-1 calculated geometrical Doppler. The RVL component provides continuity of the ASAR Doppler grid. The RVL estimates are produced on a ground-range grid.\r\n\r\nThe Level-2 Doppler is computed on a grid similar to the OWI component grid and provides an estimate of the Doppler frequency and the Doppler spectral width. For TOPS, one grid is provided by swath (additional dimension in the NetCDF). The uncertainties of the estimates are also provided for both the Doppler and radial velocity. The Doppler frequency and the Doppler spectral width are estimated based on fitting the azimuth spectral profile of the data to the antenna model taking into account additive noise, aliasing, and sideband effects. The Doppler frequency provided in the product is the pure Doppler frequency estimated from the SLC data without correcting for geometry and mispointing errors.\r\n\r\nSentinel 1B was launched on 25th April 2016 and provides continuous all-weather, day and night imaging radar data. These data are available via CEDA to any registered CEDA user.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2020-04-30T23:13:41", "updateFrequency": "asNeeded", "dataLineage": "Data collected and prepared by European Space Agency (ESA). Downloaded from the Collaborative Hub for use by CEDA users.", "removedDataReason": "", "keywords": "Sentinel, radar, Synthetic Aperture Radar, SAR, Wave, WV, OCN", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2023-05-04T10:47:11", "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": 27466, "dataPath": "/neodc/sentinel1b/data/WV/L2_OCN/IPF_v2/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 879324274087, "numberOfFiles": 135608, "fileFormat": "Data are provided in SAFE format. With the data products inside the SAFE zip in NetCDF." }, "timePeriod": { "ob_id": 9003, "startTime": "2016-09-26T00:00:00", "endTime": "2019-06-25T23:59:59" }, "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": 32796, "uuid": "540c178877e94c4082492e210954716d", "short_code": "cmppr", "title": "Composite Process for: Level 1 data from the Sentinel 1B C-band Synthetic Aperture Radar (SAR), Wave (WV) mode, Instrument Processing Facility (IPF) v2", "abstract": "Composite process for Level 1 data from the C-band Synthetic Aperture Radar (SAR) deployed on Sentinel 1. 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": [], "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": [ 146414, 146415, 146416, 146417, 146418, 146419, 146420, 146421, 146424, 146423, 146422 ], "onlineresource_set": [ 42962, 42963, 42960, 42959, 42961 ] }, { "ob_id": 32798, "uuid": "4ecd5242cde24b2bb9c0572218da9861", "title": "Sentinel 1B C-band Synthetic Aperture Radar (SAR): Wave (WV) mode Ocean (OCN) Level 2 data, Instrument Processing Facility (IPF) v3", "abstract": "This dataset contains Level-2, Wave mode (WV) Ocean (OCN) C-band Synthetic Aperture Radar (SAR) data from the European Space Agency (ESA) Sentinel 1B satellite. Level-2 data consists of geolocated geophysical products derived from Level-1. \r\n\r\nFrom WV modes, the OCN product will only contain Ocean Swell Spectra (OSW) and Surface Radial Velocity (RVL). \r\n\r\nThe OSW component is a two-dimensional ocean surface swell spectrum and includes an estimate of wind speed and direction per swell spectrum. The OSW component provides continuity measurement of SAR swell spectra at C-band. OSW is estimated from Sentinel-1 SLC images by inversion of the corresponding image cross-spectra.\r\n\r\nThe OSW is generated from Stripmap and Wave modes only and is not available from the TOPSAR IW and EW modes. For Stripmap mode, there are multiple spectra derived from the Level-1 SLC image. For Wave mode, there is one spectrum per vignette.\r\n\r\nOcean wave height spectra are provided in units of m4 and given on a polar grid of wavenumber in rad/m and direction in degrees with respect to North.\r\n\r\nThe OSW product also contains one estimate of the wind speed in m/s and direction in degrees (meteorological convention) per ocean wave spectrum, as well as parameters derived from the ocean wave spectra (integrated wave parameters) and from the imagette (image statistics).\r\n\r\nThe spatial coverage of the OSW product is equal to the spatial coverage of the corresponding Level-1 WV SLC or Level-1 SM SLC product, limited to ocean areas.\r\n\r\nThe RVL surface radial velocity component is a ground range gridded difference between the measured Level-2 Doppler grid and the Level-1 calculated geometrical Doppler. The RVL component provides continuity of the ASAR Doppler grid. The RVL estimates are produced on a ground-range grid.\r\n\r\nThe Level-2 Doppler is computed on a grid similar to the OWI component grid and provides an estimate of the Doppler frequency and the Doppler spectral width. For TOPS, one grid is provided by swath (additional dimension in the NetCDF). The uncertainties of the estimates are also provided for both the Doppler and radial velocity. The Doppler frequency and the Doppler spectral width are estimated based on fitting the azimuth spectral profile of the data to the antenna model taking into account additive noise, aliasing, and sideband effects. The Doppler frequency provided in the product is the pure Doppler frequency estimated from the SLC data without correcting for geometry and mispointing errors.\r\n\r\nSentinel 1A was launched on 25th April 2016 and provides continuous all-weather, day and night imaging radar data. These data are available via CEDA to any registered CEDA user.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-12-23T23:06:00", "updateFrequency": "asNeeded", "dataLineage": "Data collected and prepared by European Space Agency (ESA). Downloaded from the Collaborative Hub for use by CEDA users.", "removedDataReason": "", "keywords": "Sentinel, radar, Synthetic Aperture Radar, SAR, Wave, WV, OCN", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2023-05-04T10:47:35", "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": 32799, "dataPath": "/neodc/sentinel1b/data/WV/L2_OCN/IPF_v3/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1099563983359, "numberOfFiles": 110186, "fileFormat": "Data are provided in SAFE format. With the data products inside the SAFE zip in NetCDF." }, "timePeriod": { "ob_id": 9004, "startTime": "2019-06-25T00:00:00", "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": 32800, "uuid": "d6eea898cc2048198e842f081f17070e", "short_code": "cmppr", "title": "Composite Process for: Level 1 data from the Sentinel 1B C-band Synthetic Aperture Radar (SAR), Wave (WV) mode, Instrument Processing Facility (IPF) v3", "abstract": "Composite process for Level 1 data from the C-band Synthetic Aperture Radar (SAR) deployed on Sentinel 1. 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": [], "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": [ 146431, 146432, 146433, 146434, 146435, 146436, 146429, 146430, 146439, 146438, 146437 ], "onlineresource_set": [ 42968, 42964, 42967, 42965, 42966 ] }, { "ob_id": 32801, "uuid": "8305ad215f0f48c994bdb37df1bcf773", "title": "Sentinel 1B C-band Synthetic Aperture Radar (SAR): SM mode SLC Level 1 data, Instrument Processing Facility (IPF) v2", "abstract": "This dataset contains Stripmap Mode (SM) C-band Synthetic Aperture Radar (SAR) Single Look Complex (SLC) 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 SM mode is used only on special request for extraordinary events such as emergency management. The SM mode supports single (HH or VV) and dual (HH+HV or VV+VH) polarisation. \r\n\r\nStripmap SLCs contain one image per polarisation band from one of six overlapping beams. Each beam covers 80.1 km, covering a combined range of 375 km. Pixel spacing is determined, in azimuth by the pulse repetition frequency (PRF), and in range by the radar range sampling frequency, providing natural pixel spacing.\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": "2020-06-12T11:48:04", "updateFrequency": "", "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, Stripmap, Single Look Complex", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-07-02T09:51:28", "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": 32802, "dataPath": "/neodc/sentinel1b/data/SM/L1_SLC/IPF_v2/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1427172708154, "numberOfFiles": 2336, "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": 9005, "startTime": "2017-06-18T00:00:00", "endTime": "2019-06-19T23:59:59" }, "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": 32812, "uuid": "05fbcb5c4c2b440e9949b05f03de17b7", "short_code": "cmppr", "title": "Composite Process for: Level 1 data from the Sentinel 1B C-band Synthetic Aperture Radar (SAR), Stripmap (SM) mode, Instrument Processing Facility (IPF) v2", "abstract": "Composite process for Level 1 data from the C-band Synthetic Aperture Radar (SAR) deployed on Sentinel 1. 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": [], "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": [ 146447, 146448, 146449, 146450, 146451, 146446, 146452, 146453, 146454, 146455 ], "onlineresource_set": [ 42971, 42969, 42970 ] }, { "ob_id": 32803, "uuid": "7a5529a8758041eb83b9c32f8461e50d", "title": "CRU CY4.05: Climatic Research Unit year-by-year variation of selected climate variables by country version 4.05 (Jan. 1901 - Dec. 2020)", "abstract": "The Climatic Research Unit (CRU) Country (CY) data version 4.05 dataset consists of ten climate variables for country averages at a monthly, seasonal and annual frequency: including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure, potential evapotranspiration and wet day frequency. This version uses the updated set of country definitions, please see the appropriate Release Notes.\r\n\r\nThis dataset was produced in 2021 by CRU at the University of East Anglia and extends the CRU CY4.04 data to include 2020. 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 CY4.05 is derived directly from the CRU time series (TS) 4.05 dataset. CRU CY version 4.05 spans the period 1901-2020 for 292 countries.\r\n\r\nTo understand the CRU CY4.05 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS4.05. It is therefore recommended that all users read the Harris et al, 2020 paper and the CRU TS4.05 release notes 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": "2024-03-09T02:07:26", "updateFrequency": "notPlanned", "dataLineage": "The Climatic Research Unit (CRU) CY data are derived directly from the CRU TS data, and version numbering is matched between the two datasets. The CRU CY data are produced by the CRU unit at the University of East Anglia and passed to the Centre for Environmental Data Analysis (CEDA) for long term archival and distribution. Previous releases of CRU CY include:\r\n\r\nCRU CY 4.05 data were passed to CEDA for archival and distribution by CRU in June 2021.\r\n\r\nCRU CY 4.04 data were passed to CEDA for archival and distribution by CRU in October 2020.\r\n\r\nCRU CY 4.03 data were passed to CEDA for archival and distribution by CRU in May 2019.\r\n\r\nCRU CY 4.02 data were passed to CEDA for archival and distribution by CRU in November 2018.\r\n\r\nCRU CY 4.01 data were passed to CEDA for archival and distribution by CRU in September 2017.\r\n\r\nCRU CY 4.00 data were passed to CEDA for archival and distribution by CRU in March 2017.\r\n\r\nCRU CY 3.24.01 data files supplied to CEDA for long term archival by CRU in January 2017.\r\n\r\nThe CRU CY 3.24 data were withdrawn by CRU and CEDA in January 2017 due to known issues with the data.\r\n\r\nCRU CY 3.24 data files supplied to CEDA for long term archival by CRU in October 2016.", "removedDataReason": "", "keywords": "CRU, CRU CY, CY, climate", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "0.5x0.5 degree grid", "status": "completed", "dataPublishedTime": "2021-07-02T11:54:39", "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": 32823, "dataPath": "/badc/cru/data/cru_cy/cru_cy_4.05/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 50992332, "numberOfFiles": 2924, "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": 9006, "startTime": "1901-01-01T00:00:00", "endTime": "2020-12-31T23:59:59" }, "resultQuality": { "ob_id": 3080, "explanation": "CRU CY data are quality controlled by the Climatic Research Unit (CRU) at the University of East Anglia. Details are given in the paper Harris et al. 2014 and the release notes, links to both can be found in the documentation.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2017-04-07" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 20388, "uuid": "81842aa686174647ae132a4c841d73b6", "short_code": "comp", "title": "UEA Climatic Research Unit (CRU) high resolution gridding software deployed on UEA CRU computer system for v4.00", "abstract": "This computation involved: UEA Climate Research Unit (CRU) High Resolution gridding software deployed on UEA Climate Research Unit (CRU) computer system. For details about the production of CRU TS and CRU CY datasets, please refer to Harris et al. (2020) - see Details/Docs tab, moderated by the Release Notes for v4.00 (which outline the new gridding process)" }, "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": 27835, "uuid": "a5fc25a8153148b9872f24ab889f64a9", "short_code": "coll", "title": "Climatic Research Unit (CRU): Year-by-Year Variation of Selected Climate Variables by CountrY (CY) v4", "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 v4.03, as it is based on CRU TS v4.03. 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": [ 146457, 146462, 146456, 146460, 146461, 146459, 146458, 146463, 146464, 146465, 148555, 146466, 168467, 146467 ], "onlineresource_set": [ 42977, 42972, 42975, 42973, 42974, 42976, 42978, 43010 ] }, { "ob_id": 32804, "uuid": "c26a65020a5e4b80b20018f148556681", "title": "CRU TS4.05: Climatic Research Unit (CRU) Time-Series (TS) version 4.05 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2020)", "abstract": "The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.05 data are month-by-month variations in climate over the period 1901-2020, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia and funded by the UK National Centre for Atmospheric Science (NCAS), a NERC collaborative centre.\r\n\r\nThe CRU TS4.05 variables are cloud cover, diurnal temperature range, frost day frequency, wet day frequency, potential evapotranspiration (PET), precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period January 1901 - December 2020.\r\n\r\nThe CRU TS4.05 data were produced using angular-distance weighting (ADW) interpolation. All versions prior to 4.00 used triangulation routines in IDL. Please see the release notes for full details of this version update. \r\n\r\nThe CRU TS4.05 data are monthly gridded fields based on monthly observational data 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. The NetCDF versions contain an additional integer variable, ’stn’, which provides, for each datum in the main variable, a count (between 0 and 8) of the number of stations used in that interpolation. The missing value code for 'stn' is -999.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-06-30T13:50:30", "updateFrequency": "notPlanned", "dataLineage": "The CRU TS data are produced by the Climatic Research Unit (CRU) at the University of East Anglia and are passed to the Centre for Environmental Data Analysis (CEDA) for long-term archival and distribution. Previous releases of the CRU TS data include:\r\n\r\nCRU TS 4.05 was provided to CEDA for archival in June 2021.\r\n\r\nCRU TS 4.04 was provided to CEDA for archival in April 2020.\r\n\r\nCRU TS 4.03 was provided to CEDA for archival in May 2019. \r\n\r\nCRU TS 4.02 was provided to CEDA for archival in December 2018. \r\n\r\nCRU TS 4.01 was provided to CEDA for archival in September 2017. \r\n\r\nCRU TS 4.00 was provided to CEDA for archival in March 2017. \r\n\r\nCRU TS 3.24.01 was provided to CEDA for archival in January 2017. This is the latest version available and is a replacement of the withdrawn dataset 3.24, it supersedes 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), v3.24 has been withdrawn.\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 3.22 was provided to CEDA for archival in July 2014 by CRU.\r\n\r\nCRU TS 3.21 was provided to CEDA for archival in July 2013 by CRU.\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 3.10.01 In 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 3.00 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.", "removedDataReason": "", "keywords": "CRU, CRU TS, 4.05, CRU TS4.05, CRU TS 4, CRU TS 4.05,atmosphere, earth science, climate,", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "0.5x0.5 degree grid", "status": "completed", "dataPublishedTime": "2021-07-02T11:41:45", "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": 32822, "dataPath": "/badc/cru/data/cru_ts/cru_ts_4.05", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 6911362666, "numberOfFiles": 379, "fileFormat": "Data are provided in ASCII and NetCDF formats." }, "timePeriod": { "ob_id": 9011, "startTime": "1901-01-01T00:00:00", "endTime": "2020-12-31T23:59:59" }, "resultQuality": { "ob_id": 3416, "explanation": "The data are quality controlled by the Climatic Research Unit (CRU) at the University of East Anglia. Details are given in the paper Harris et al. 2020 and the release notes, links to both can be found in the documentation.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2020-05-21" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 20388, "uuid": "81842aa686174647ae132a4c841d73b6", "short_code": "comp", "title": "UEA Climatic Research Unit (CRU) high resolution gridding software deployed on UEA CRU computer system for v4.00", "abstract": "This computation involved: UEA Climate Research Unit (CRU) High Resolution gridding software deployed on UEA Climate Research Unit (CRU) computer system. For details about the production of CRU TS and CRU CY datasets, please refer to Harris et al. (2020) - see Details/Docs tab, moderated by the Release Notes for v4.00 (which outline the new gridding process)" }, "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": 27513, "uuid": "3587430e588b491e8a795664466a27d1", "short_code": "coll", "title": "Climatic Research Unit (CRU): Time-series (TS) datasets of variations in climate with variations in other phenomena v4", "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\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": [ 146473, 146468, 146472, 146471, 146470, 146469, 146475, 146474, 146476, 146477, 148556, 146478, 168465, 146479 ], "onlineresource_set": [ 42979, 42980, 42981, 42984, 42990, 42982, 42983, 42987, 42988, 42989, 42986 ] }, { "ob_id": 32807, "uuid": "d69ef5ff221a45f38c35cd77c0ca9352", "title": "Sentinel 1B C-band Synthetic Aperture Radar (SAR): Interferometric Wide (IW) mode Single Look Complex (SLC) Level 1 data, Instrument Processing Facility (IPF) v3", "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": "2021-06-29T12:23:40", "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": 32810, "dataPath": "/neodc/sentinel1b/data/IW/L1_SLC/IPF_v3/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1514497644380227, "numberOfFiles": 1834079, "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": 9010, "startTime": "2019-04-10T00:00:00", "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": 32811, "uuid": "dda769b3edc247b19fac1828052001cd", "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) v3", "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": [], "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": [ 146485, 146486, 146484, 146487, 146491, 146490, 146489, 146493, 146488, 146492, 146494 ], "onlineresource_set": [ 42994, 42995, 42996, 42997, 42993 ] }, { "ob_id": 32809, "uuid": "f088e7a33a25409197ea9b6aa3b90864", "title": "CCMI-2022: refD1 data produced by the SOCOL model at ETH-PMOD", "abstract": "This dataset contains model data for CCMI-2022 experiment refD1 produced by the SOCOL (SOlar Climate Ozone Links) model run by the modelling team at ETH-PMOD (Swiss Federal Institute of Technology Zurich and the Physical-Meteorology Observatory Davos).\r\n\r\nThe refD1 experiment is a hindcast of the atmospheric state, using a prescribed evolution of sea surface temperature and sea ice from observations along with forcings for the extra-terrestrial solar flux, long-lived greenhouse gases and ozone depleting substances, stratospheric aerosols and an imposed quasi-biennial oscillation that approximate the observed variations over the historical period to the fullest extent possible.\r\n\r\nThe CCMI-2022 Chemistry-climate model initiative is a set of model experiments focused on the stratosphere, with the goals of providing updated projections towards the future evolution of the ozone layer and improving our understanding of chemistry-climate interactions from models.\r\n\r\n------------------------------------------\r\nSources of additional information\r\n------------------------------------------\r\nThe following web links are provided in the Details/Docs section of this catalogue record:\r\n- Atmosphere-Ocean-Aerosol-Chemistry-Climate Model SOCOLv4.0: description and evaluation.\r\n- A new set of Chemistry-Climate Model Initiative (CCMI) Community Simulations to Update the Assessment of Models and Support Upcoming Ozone Assessment Activities, David Plummer and Tatsuya Nagashima and Simone Tilmes and Alex Archibald and Gabriel Chiodo and Suvarna Fadnavis and Hella Garny and Beatrice Josse and Joowan Kim and Jean-Francois Lamarque and Olaf Morgenstern and Lee Murray and Clara Orbe and Amos Tai and Martyn Chipperfield and Bernd Funke and Martin Juckes and Doug Kinnison and Markus Kunze and Beiping Luo and Katja Matthes and Paul A. Newman and Charlotte Pascoe and Thomas Peter (2021), SPARC Newsletter, volume 57, pp 22-30", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-06-28T21:32:38", "updateFrequency": "", "dataLineage": "Data were generated using the SOCOLv4.0 model at T63 horizontal resolution over the global domain. CCMI-2022 data has been converted to CF-netCDF by the model team using CDO and CMOR3 then passed on to the CEDA for archiving.", "removedDataReason": "", "keywords": "CCMI-2022, refD1, Hindcast, Scenario, SOCOL, ETH-PMOD, APARC", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "T63", "status": "completed", "dataPublishedTime": "2024-11-11T15:47:52", "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": 32806, "dataPath": "/badc/ccmi/data/post-cmip6/ccmi-2022/ETH-PMOD/SOCOL/refD1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 361060547370, "numberOfFiles": 426, "fileFormat": "netCDF" }, "timePeriod": { "ob_id": 9009, "startTime": "1960-01-01T00:00:00", "endTime": "2018-12-31T23:59:59" }, "resultQuality": { "ob_id": 3704, "explanation": "Data checked by provider prior to archiving. Data passed CEDA quality control procedure, ceda-cc.", "passesTest": true, "resultTitle": "CCMI-2022 Data and Metadata Quality Statement", "date": "2021-06-28" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32808, "uuid": "feb90994cd0c439384bf1819eaa575ff", "short_code": "comp", "title": "CCM SOCOLv4.0 deployed on CSCS Piz Daint computer", "abstract": "CCM SOCOLv4.0 deployed on CSCS Piz Daint computer" }, "procedureCompositeProcess": null, "imageDetails": [ 146 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2544, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "ccmi-2022", "label": "restricted: ccmi-2022 group", "licence": { "ob_id": 21, "licenceURL": "https://artefacts.ceda.ac.uk/licences/rugl_versions/rugl_v1-0.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 32805, "uuid": "92dddf542adc44b5898f535be4179705", "short_code": "proj", "title": "CCMI-2022 Chemistry-climate model initiative, phase 2", "abstract": "CCMI-2022 Chemistry-climate model initiative, phase 2 is a World Climate Research Programme (WCRP) Stratosphere-Troposphere Processes and their Role in Climate (SPARC) project to study the evolution of the ozone layer using chemistry-climate model simulations. CCMI-2022 data will support the World Meteorologcial Organisation (WMO)/ United Nations Environment Programme (UNEP) Scientific Assessment of Ozone Depletion Report 2022." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6021, 6022, 6023, 50415, 50417, 50418, 50419, 50420, 50421, 50422, 50423, 50424, 50425, 50426, 50427, 50428, 50429, 50430, 50431, 50432, 50433, 50434, 50435, 50436, 50437, 50438, 50439, 50440, 50441, 50442, 50443, 50444, 50445, 50446, 50447, 50448, 50449, 50450, 50451, 50452, 50453, 50454, 50455, 50456, 50457, 50459, 50460, 50461, 50462, 50463, 50464, 50465, 50466, 50467, 50468, 50469, 50470, 50471, 50472, 50473, 50474, 50475, 50477, 50478, 50479, 50481, 50482, 50483, 50484, 50485, 50486, 50489, 50490, 50491, 50492, 50493, 50494, 50495, 50496, 50498, 50499, 50500, 50501, 50502, 50503, 50504, 50505, 50506, 50507, 50508, 50555, 50566, 50590, 50591, 50596, 50598, 50622, 51210, 51211, 53111, 54366, 54369, 54378, 59920, 59921, 59922, 60402, 60403, 60438, 61535, 61536, 61589, 61594, 61614, 66084, 66396, 71572, 71613, 71614, 71619, 71634, 71691, 71782, 71783, 71926, 74528 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 32820, "uuid": "4d9554592924473281d0c90f5688989b", "short_code": "coll", "title": "CCMI-2022 data produced by the SOCOL model at ETH-PMOD", "abstract": "Data for CCMI-2022 produced by the SOCOL (SOlar Climate Ozone Links) model run by the modelling team at ETH-PMOD (Swiss Federal Institute of Technology Zurich and the Physical-Meteorology Observatory Davos).\r\n\r\nCCMI-2022 Chemistry-climate model initiative, phase 2 is a project to study the evolution of the ozone layer using chemistry-climate model simulations.\r\n\r\nThe SOCOL (SOlar Climate Ozone Links) model contribution to the CCMI-2022 set of experiments defined by the APARC- and IGAC-supported Chemistry-Climate Model Initiative.\r\n\r\nThe CCMI-2022 set of model experiments focus on the stratosphere, with the goals of providing updated projections of the future evolution of ozone and improving our understanding of chemistry-climate interactions and how they are represented in models.\r\n\r\nThe SOCOL chemistry-climate model is run by the modelling team at ETH-PMOD (Swiss Federal Institute of Technology Zurich and the Physical-Meteorology Observatory Davos) and configured to follow forcings as laid out in the CCMI2022 founding document (Plummer et al., 2021).\r\n\r\nAPARC (formerly SPARC) and IGAC projects coordinate international research in atmospheric chemistry. APARC (Atmospheric Processes And their Role in Climate) is a core project of the World Climate Research Programme (WCRP). IGAC is the International Global Atmospheric Chemistry which currently operates under the umbrella of Future Earth." } ], "responsiblepartyinfo_set": [ 146497, 146498, 146499, 146500, 146501, 146502, 146503, 146504, 146505 ], "onlineresource_set": [ 43011, 52164 ] }, { "ob_id": 32814, "uuid": "171d5d0e6ef44fc3addad6ba45c8fb17", "title": "Sentinel 1B C-band Synthetic Aperture Radar (SAR): SM mode SLC Level 1 data, Instrument Processing Facility (IPF) v3", "abstract": "This dataset contains Stripmap Mode (SM) C-band Synthetic Aperture Radar (SAR) Single Look Complex (SLC) 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 SM mode is used only on special request for extraordinary events such as emergency management. The SM mode supports single (HH or VV) and dual (HH+HV or VV+VH) polarisation. \r\n\r\nStripmap SLCs contain one image per polarisation band from one of six overlapping beams. Each beam covers 80.1 km, covering a combined range of 375 km. Pixel spacing is determined, in azimuth by the pulse repetition frequency (PRF), and in range by the radar range sampling frequency, providing natural pixel spacing.\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": "2022-06-10T22:00:26", "updateFrequency": "", "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, Stripmap, Single Look Complex", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-07-02T09:53:15", "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": 32815, "dataPath": "/neodc/sentinel1b/data/SM/L1_SLC/IPF_v3/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 3727643585008, "numberOfFiles": 6621, "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": 9012, "startTime": "2019-05-16T00:00:00", "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": 32816, "uuid": "772b1c2ca7254513bd19d05ea8c25a53", "short_code": "cmppr", "title": "Composite Process for: Level 1 data from the Sentinel 1B C-band Synthetic Aperture Radar (SAR), Stripmap (SM) mode, Instrument Processing Facility (IPF) v3", "abstract": "Composite process for Level 1 data from the C-band Synthetic Aperture Radar (SAR) deployed on Sentinel 1. 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": [], "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." }, { "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." } ], "responsiblepartyinfo_set": [ 146516, 146517, 146518, 146519, 146520, 146521, 146514, 146515, 146523, 146522 ], "onlineresource_set": [ 42998, 42999, 43000 ] }, { "ob_id": 32817, "uuid": "4bdf41fc10af4caaa489b14745c665a6", "title": "CRU JRA v2.2: A forcings dataset of gridded land surface blend of Climatic Research Unit (CRU) and Japanese reanalysis (JRA) data; Jan.1901 - Dec.2020.", "abstract": "The CRU JRA V2.2 dataset is a 6-hourly, land surface, gridded time series of ten meteorological variables produced by the Climatic Research Unit (CRU) at the University of East Anglia (UEA), and is intended to be used to drive models. The variables are provided on a 0.5 deg latitude x 0.5 deg longitude grid, the grid is near global but excludes Antarctica (this is same as the CRU TS grid, though the set of variables is different). The data are available at a 6 hourly time-step from January 1901 to December 2020.\r\n\r\nThe dataset is constructed by regridding data from the Japanese Reanalysis data (JRA) produced by the Japanese Meteorological Agency (JMA), adjusting where possible to align with the CRU TS 4.05 data (see the Process section and the ReadMe file for full details).\r\n\r\nThe CRU JRA data consists of the following ten meteorological variables: 2-metre temperature, 2-metre maximum and minimum temperature, total precipitation, specific humidity, downward solar radiation flux, downward long wave radiation flux, pressure and the zonal and meridional components of wind speed (see the ReadMe file for further details).\r\n\r\nThe CRU JRA dataset is intended to be a replacement of the CRU NCEP forcing dataset. The CRU JRA dataset follows the style of Nicolas Viovy's original CRU NCEP dataset rather than that which is available from UCAR. A link to the CRU NCEP documentation for comparison is provided in the documentation section. \r\n\r\nIf this dataset is used in addition to citing the dataset as per the data citation string users must also cite the following:\r\n\r\nHarris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS\r\nmonthly high-resolution gridded multivariate climate dataset.\r\nSci Data 7, 109 (2020). https://doi.org/10.1038/s41597-020-0453-3\r\n\r\nHarris, I., Jones, P.D., Osborn, T.J. and Lister, D.H. (2014), Updated\r\nhigh-resolution grids of monthly climatic observations - the CRU TS3.10\r\nDataset. International Journal of Climatology 34, 623-642.\r\n\r\nKobayashi, S., et. al., The JRA-55 Reanalysis: General Specifications and\r\nBasic Characteristics. J. Met. Soc. Jap., 93(1), 5-48\r\nhttps://dx.doi.org/10.2151/jmsj.2015-001", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-06-29T18:21:33", "updateFrequency": "notPlanned", "dataLineage": "The CRU JRA data are produced by the Climatic Research Unit (CRU) at the University of East Anglia and are passed to the Centre for Environmental Data Analysis (CEDA) for long-term archival and distribution.", "removedDataReason": "", "keywords": "CRU, JRA, CRUJRA, atmosphere, earth science, climate", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "0.5x0.5 degree grid", "status": "completed", "dataPublishedTime": "2021-07-02T12:33:42", "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": 32821, "dataPath": "/badc/cru/data/cru_jra/cru_jra_2.2/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 406024456466, "numberOfFiles": 1202, "fileFormat": "The data are provided as gzipped NetCDF files, with one file per variable, per year." }, "timePeriod": { "ob_id": 9013, "startTime": "1901-01-01T00:00:00", "endTime": "2020-12-31T23:59:59" }, "resultQuality": { "ob_id": 3075, "explanation": "The data are quality controlled by the Climatic Research Unit (CRU) at the University of East Anglia. Details are given in the paper Harries et al. 2014 and the release notes, links to both can be found in the documentation.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2017-02-14" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 27185, "uuid": "9692143d57aa413eab1277193361de77", "short_code": "comp", "title": "Climatic Research Unit (CRU) procedure to produce the CRU JRA data.", "abstract": "The CRU JRA (Japanese reanalysis) data is a replacement to the CRU NCEP dataset, CRU JRA data follows the style of Nicolas Viovy's original dataset rather than that which is available from UCAR.\r\n\r\nThe CRU JRA dataset is based on the JRA-55 reanalysis dataset and aligned where appropriate with the CRU TS dataset version 3.26 (1901-2017).\r\n\r\nAll JRA variables are regridded from their native TL319 Gaussian grid to the CRU regular 0.5° x 0.5° grid, using the g2fsh spherical harmonics routine from NCL (NCAR Command Language), based on the 'Spherepack' code. The exception is precipitation, which is regridded using ESMF 'nearest neighbour': all other algorithms tried exhibited unwanted artifacts.\r\n\r\nThe JRA-55 reanalysis dataset starts in 1958. The years 1901-1957 are constructed using randomly-selected years between 1958 and 1967. Where alignment with CRU TS occurs, the relevant CRU TS data is used.\r\n\r\nOf the ten variables listed above, the last four do not have analogs in the CRU TS dataset. These are simply regridded, masked for land only, and output as CRUJRA. The other six are aligned with CRU TS as follows:\r\n\r\nTMP is aligned with CRU TS TMP. A monthly mean for the JRA data is\r\ncalculated and compared with the equivalent CRU TS mean. The difference\r\nbetween the means is added to every JRA value.\r\n\r\n---\r\n\r\nTMAX and TMIN are aligned with CRUJRA TMP and CRU TS DTR. Firstly, at\r\neach time step, the TMAX-TMP-TMIN triplets are checked and adjusted so\r\nthat TMAX is always >= TMP, and TMIN is always <= TMP. This triplet\r\nalignment is prioritised above DTR alignment. Secondly, monthly JRA DTR\r\nis calculated by first establishing the daily maxima and minima (max and\r\nmin of the subdaily values in TMAX and TMIN respectively), then monthly\r\nmaxima and minima, (means of the daily DTR values), giving JRA monthly\r\nDTR. This is compared with CRU TS DTR and the fractional difference\r\n(factor) calculated as (CRU TS DTR) / (JRA monthly DTR). This factor is\r\nthen used to adjust the DTR of each pair of subdaily TMAX and TMIN\r\nvalues, though not if the triplet alignment would be broken.\r\n\r\n---\r\n\r\nPRE is aligned with CRU TS PRE and WET (rain day counts). Firstly, the\r\nmonthly total precipitation is calculated for JRA and compared to CRU TS\r\nPRE; an adjustment factor is acquired (crupre/jrapre) and all values\r\nadjusted. Precipitation amounts are now aligned at a monthly level, and\r\nthis alignment is prioritised above WET alignment. Secondly, the number\r\nof rain days is calculated for JRA: a day is declared wet if the total\r\nprecipitation is equal to, or exceeds, 0.1mm (the same threshold as CRU\r\nTS WET). If JRA has more wet days than CRU TS, then the driest of those\r\nare reduced to a random amount below 0.1 (an adjustment factor is\r\ncalculated and applied to each time step, to preserve the subdaily\r\ndistribution). If JRA has fewer wet days than CRU TS, then sufficient\r\ndry days are set to a random amount equal to or closely above 0.1mm,\r\nagain using an adjustment factor to preserve the subdaily distribution. \r\nWhere wet day alignment threatens precipitation alignment, the process\r\nis abandoned and the cell/month reverts to the previously-aligned\r\nprecip version. Exception handling is very complicated and cannot be\r\nsummarised here.\r\n\r\n---\r\n\r\nSPFH is aligned with CRU TS VAP. VAP is converted to SPFH, and JRA mean\r\nmonthly SPFH is calculated. The fractional difference (factor) is\r\ncalculated as (CRU TS SPFH) / (JRA monthly SPFH), this factor is then\r\napplied to the JRA subdaily humidity values.\r\n\r\n---\r\n\r\nDSWRF is aligned with CRU TS CLD. CLD is converted to shortwave\r\nradiation, and JRA mean monthly DSWRF is calculated. The fractional\r\ndifference (factor) is calculated as (CRU TS SWR) / (JRA monthly DSWRF),\r\nthis factor is then applied to the JRA subdaily radiation values.\r\n\r\n---\r\n\r\nWhere appropriate, CRUJRA values are kept within physically-appropriate\r\nconstraints (such as negative precipitation), which could result from\r\nregridding as well as adjustments." }, "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": 26851, "uuid": "863a47a6d8414b6982e1396c69a9efe8", "short_code": "coll", "title": "CRU JRA: Collection of CRU JRA forcing datasets of gridded land surface blend of Climatic Research Unit (CRU) and Japanese reanalysis (JRA) data.", "abstract": "This is a collection of the University of East Anglia Climatic Research Unit (CRU) Japanese Reanalysis (JRA) data. The CRU JRA data are 6-hourly, land surface, gridded time series of ten meteorological variables produced by the Climatic Research Unit (CRU) at the University of East Anglia (UEA), and is intended to be used to drive models.\r\n\r\nThe dataset is constructed by combining data from the Japanese Reanalysis data produced by the Japanese Meteorological Agency (JMA) and adjusted where possible to align with the CRU TS data (these 'ten meteorological variables' are not the same ten available from CRU TS).\r\n\r\nThe CRU JRA dataset is intended to be a replacement of the CRUNCEP forcing dataset. The CRU JRA dataset follows the style of Nicolas Viovy's original CRUNCEP dataset rather than that which is available from UCAR." } ], "responsiblepartyinfo_set": [ 146531, 146526, 146528, 146527, 146533, 146532, 146529, 146530, 148557, 146535, 146534, 168464 ], "onlineresource_set": [ 43001, 43002, 43003, 43004, 43005, 43006, 43008, 43009 ] }, { "ob_id": 32841, "uuid": "7da8723b16e94771be1a2717d8a6e2fe", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Monthly sea surface salinity product, v03.21, for 2010 to 2020", "abstract": "The ESA Sea Surface Salinity Climate Change Initiative (CCI) consortium has produced global, level 4, multi-sensor Sea Surface Salinity maps covering the 2010-2020 period.\r\n\r\nThis dataset provides Sea Surface Salinity (SSS) data at a spatial resolution of 25 km and a time resolution of 1 month. This has been spatially sampled on a 25 km EASE (Equal Area Scalable Earth) grid and 15 days of time sampling. A weekly product is also available. In addition to salinity, information on errors are provided. For more information, see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page.\r\n\r\nCompared to the previous version of the data, version 3 SSS and associated uncertainties are more precise and cover a longer period (Jan 2010-sept 2020); version 3 SSS are provided closer to land than version 2 SSS, with a possible degraded quality. Users might remove these additional near land data by using the lsc_qc flag.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-09-16T09:56:48", "updateFrequency": "notPlanned", "dataLineage": "Data are provided by the Sea Surface Salinity project as part of the ESA Climate Change Initiative programme, and delivered for long-term archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "ESA Climate Change Initiative, CCI, Sea Surface Salinity", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2021-10-08T13:22:22", "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": 33082, "dataPath": "/neodc/esacci/sea_surface_salinity/data/v03.21/30days", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1312695041, "numberOfFiles": 258, "fileFormat": "Data are netCDf formatted." }, "timePeriod": { "ob_id": 9156, "startTime": "2010-01-01T00:00:00", "endTime": "2020-09-30T23:59:59" }, "resultQuality": { "ob_id": 3529, "explanation": "Data are as provided by the CCI Sea Surface Salinity project team. Estimates of uncertainty are provided in the data files, see documentation for further information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2020-09-04" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 29942, "uuid": "31c2d365861f4a7f87a56a0178321034", "short_code": "cmppr", "title": "CCI Sea Surface Salinity retrieval process", "abstract": "The ESA CCI Climate Change Initiate Sea Surface Salinity project has derived salinity data from the SMOS, SMAP and Aquarius Satellite instruments." }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "permissions": [ { "ob_id": 2550, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 43, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_salinity_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 28235, "uuid": "d64aaf9ca941488d90ba0ad3e339977d", "short_code": "proj", "title": "ESA Sea Surface Salinity Climate Change Initiative", "abstract": "The ESA Sea Surface Salinity (SSS) Climate Change Initiative project is part of the European Space Agency's Climate Change Initiative programme. It aims to provide data products that are specifically adapted to climate applications (i.e. include information on accuracy and uncertainty within the data). Furthermore, this project will explore the need to improve the performance of current SSS algorithm retrievals and directly contribute to climate science studies submitted to the next International Panel on Climate Change (IPCC) Annual Review for climate change in 2020." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 1050, 6019, 6020, 28227, 28228, 28230, 28231, 29289, 29290, 40158, 40159 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 32840, "uuid": "5920a2c77e3c45339477acd31ce62c3c", "short_code": "coll", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): weekly and monthly sea surface salinity products, v03.21, for 2010 to 2020", "abstract": "The European Space Agency (ESA) Sea Surface Salinity Climate Change Initiative (CCI) consortium has produced global, level 4, multi-sensor Sea Surface Salinity maps covering the 2010-2020 period.\r\n\r\nThis dataset collection contains Sea Surface Salinity (SSS) v03.21 data at a spatial resolution of 50km and a time resolution of 1 week. It has been spatially sampled on a 25km EASE (Equal Area Scalable Earth) grid and 1 day of time sampling.\r\n\r\nA monthly product is also available, at a spatial resolution of 25 km and a time resolution of 1 month. This has been spatially sampled on a 25 km EASE (Equal Area Scalable Earth) grid and 15 days of time sampling.\r\n\r\n In addition to salinity, information on errors are provided. For more information, see the user guide and product documentation available on the Sea Surface Salinity CCI web page (linked below).\r\n\r\nCompared to the previous version of the data, version 3 SSS and associated uncertainties are more precise and cover a longer period (Jan 2010-sept 2020); version 3 SSS are provided closer to land than version 2 SSS, with a possible degraded quality. Users might remove these additional near land data by using the lsc_qc flag." } ], "responsiblepartyinfo_set": [ 146634, 146626, 146627, 146628, 146629, 146630, 146633, 146631, 146632, 146636, 146635, 146637, 146638, 146639, 146640, 146641, 146642, 146643, 146644, 146645, 146646, 146647, 146648, 146649, 146650, 146651, 146652, 146653, 146654, 146655, 146656, 146657, 146658, 146659, 146660 ], "onlineresource_set": [ 43026, 43028, 43502, 43627, 51662 ] }, { "ob_id": 32842, "uuid": "fad2e982a59d44788eda09e3c67ed7d5", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Weekly sea surface salinity product, v03.21, for 2010 to 2020", "abstract": "The ESA Sea Surface Salinity Climate Change Initiative (CCI) consortium has produced global, level 4, multi-sensor Sea Surface Salinity maps covering the 2010-2020 period.\r\n\r\nThis dataset contains Sea Surface Salinity (SSS) v03.21 data at a spatial resolution of 50 km and a time resolution of 1 week. It has been spatially sampled on a 25 km EASE (Equal Area Scalable Earth) grid and 1 day of time sampling. A monthly product is also available. In addition to salinity, information on errors are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page).\r\n\r\nCompared to the previous version of the data, version 3 SSS and associated uncertainties are more precise and cover a longer period (Jan 2010-sept 2020); version 3 SSS are provided closer to land than version 2 SSS, with a possible degraded quality. Users might remove these additional near land data by using the lsc_qc flag.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-10-05T12:58:45", "updateFrequency": "notPlanned", "dataLineage": "Data have been produced by the Sea Surface Salinity project as part of the ESA Climate Change Initiative programme and delivered for long-term archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "ESA Climate Change Initiative, CCI, Sea Surface Salinity", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2021-10-08T13:24:06", "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": 33081, "dataPath": "/neodc/esacci/sea_surface_salinity/data/v03.21/7days/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 19354665239, "numberOfFiles": 3917, "fileFormat": "Data are netCDF formatted." }, "timePeriod": { "ob_id": 9084, "startTime": "2010-01-01T00:00:00", "endTime": "2020-12-31T23:59:59" }, "resultQuality": { "ob_id": 3530, "explanation": "Data are as provided by the CCI Sea Surface Salinity project team. Estimates of uncertainty are provided in the data files, see documentation for further information", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2020-09-04" }, "validTimePeriod": { "ob_id": 9157, "startTime": "2010-01-01T00:00:00", "endTime": "2020-09-30T23:59:59" }, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 29942, "uuid": "31c2d365861f4a7f87a56a0178321034", "short_code": "cmppr", "title": "CCI Sea Surface Salinity retrieval process", "abstract": "The ESA CCI Climate Change Initiate Sea Surface Salinity project has derived salinity data from the SMOS, SMAP and Aquarius Satellite instruments." }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "permissions": [ { "ob_id": 2550, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 43, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_salinity_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 28235, "uuid": "d64aaf9ca941488d90ba0ad3e339977d", "short_code": "proj", "title": "ESA Sea Surface Salinity Climate Change Initiative", "abstract": "The ESA Sea Surface Salinity (SSS) Climate Change Initiative project is part of the European Space Agency's Climate Change Initiative programme. It aims to provide data products that are specifically adapted to climate applications (i.e. include information on accuracy and uncertainty within the data). Furthermore, this project will explore the need to improve the performance of current SSS algorithm retrievals and directly contribute to climate science studies submitted to the next International Panel on Climate Change (IPCC) Annual Review for climate change in 2020." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 1050, 6019, 6020, 28227, 28228, 28230, 28231, 29289, 29290, 40158, 40159 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 32840, "uuid": "5920a2c77e3c45339477acd31ce62c3c", "short_code": "coll", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): weekly and monthly sea surface salinity products, v03.21, for 2010 to 2020", "abstract": "The European Space Agency (ESA) Sea Surface Salinity Climate Change Initiative (CCI) consortium has produced global, level 4, multi-sensor Sea Surface Salinity maps covering the 2010-2020 period.\r\n\r\nThis dataset collection contains Sea Surface Salinity (SSS) v03.21 data at a spatial resolution of 50km and a time resolution of 1 week. It has been spatially sampled on a 25km EASE (Equal Area Scalable Earth) grid and 1 day of time sampling.\r\n\r\nA monthly product is also available, at a spatial resolution of 25 km and a time resolution of 1 month. This has been spatially sampled on a 25 km EASE (Equal Area Scalable Earth) grid and 15 days of time sampling.\r\n\r\n In addition to salinity, information on errors are provided. For more information, see the user guide and product documentation available on the Sea Surface Salinity CCI web page (linked below).\r\n\r\nCompared to the previous version of the data, version 3 SSS and associated uncertainties are more precise and cover a longer period (Jan 2010-sept 2020); version 3 SSS are provided closer to land than version 2 SSS, with a possible degraded quality. Users might remove these additional near land data by using the lsc_qc flag." } ], "responsiblepartyinfo_set": [ 146667, 146668, 146669, 146661, 146662, 146663, 146664, 146665, 146666, 146670, 146671, 146672, 146673, 146674, 146675, 146676, 146677, 146678, 146679, 146680, 146681, 146682, 146683, 146684, 146685, 146686, 146687, 146688, 146689, 146690, 146691, 146692, 146693, 146694, 146695 ], "onlineresource_set": [ 43030, 43501, 43626, 51663, 43029 ] }, { "ob_id": 32844, "uuid": "2e982e6692e3427dbe35e64ad9dee12d", "title": "1/12 degree Nucleus for European Modelling of the Ocean (NEMO) model of the Southern Ocean: CORE2 normal year forced control run (1951-1987)", "abstract": "The dataset is a 37 year control run of a NEMO-based 1/12 degree grid spacing model of the Southern Ocean as part of the ORCHESTRA LTS-M project. It uses the NEMO \"extended\" grid, although ice cavities are closed. The model was run on Archer, the national HPC platform. The dataset covers the full length of the model run (excluding a three year spinup period) and includes regular (5 day mean) output of the model state, as well as more frequent (1 day mean) output of surface variables and fluxes and 1 month mean of more extensive transport diagnostics.\r\n\r\nForced by the GFDL (Geophysical Fluid Dynamics Laboratory) CORE2 (corrected normal year forcing version 2.0) normal year forcing. With some additional forcing as supplied by the UK Met Office (freshwater runoff, tidal friction, geothermal heating) and additional freshwater runoff to suppress polynya formation. Initialised from January of a climatology of ECCOv4r2 (Estimating the Circulation and Climate of the Ocean) in nominal year 1948.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-04-12T12:20:28", "updateFrequency": "notPlanned", "dataLineage": "Data were generated using a Nucleus for European Modelling of the Ocean (NEMO) based model run on Archer, the national HPC platform. Data were submitted to the British Oceanographic Data Centre (BODC, NOC) and then archived at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "oceans, climatologyMeteorologyAtmosphere", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1/12 degree", "status": "completed", "dataPublishedTime": "2021-09-03T14:46:38", "doiPublishedTime": "2021-09-17T09:20:20", "removedDataTime": null, "geographicExtent": { "ob_id": 2807, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -86.0, "northBoundLatitude": -3.5 }, "verticalExtent": null, "result_field": { "ob_id": 32845, "dataPath": "/bodc/BAS210039/CORE2NYF-ORCH0083-LIM3", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 39378733805708, "numberOfFiles": 66605, "fileFormat": "Data are CF-compliant NetCDF formatted" }, "timePeriod": { "ob_id": 9019, "startTime": "1951-01-01T00:00:00", "endTime": "1987-12-31T23:59:59" }, "resultQuality": { "ob_id": 3732, "explanation": "The data are provided as-is with no quality control undertaken by the British Oceanographic Data Centre (BODC). The data suppliers have not indicated if any quality control has been undertaken on these data.", "passesTest": true, "resultTitle": "BODC Data Quality Statement", "date": "2021-07-02" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 33039, "uuid": "90d3d4ea198c4f0c9cfeb1ee740cc566", "short_code": "comp", "title": "1/12deg Nucleus for European Modelling of the Ocean (NEMO) model of the Southern Ocean", "abstract": "This computation involved: NEMO-based 1/12 degree grid spacing model of the Southern Ocean as part of the ORCHESTRA LTS-M project. It uses the NEMO \"extended\" grid, although ice cavities are closed. The model was run on Archer, the national HPC platform." }, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2526, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 32626, "uuid": "c21cf5fb28c84cb2820a4785c503ea8c", "short_code": "proj", "title": "ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports", "abstract": "The Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports (ORCHESTRA) is a £8.4 million, five year (2016-2021) research programme funded by the Natural Environment Research Council (NERC). The aim of the research is to to advance the understanding of, and capability to predict, the Southern Ocean's impact on climate change via its uptake and storage of heat and carbon. The programme will significantly reduce uncertainties concerning how this uptake and storage by the ocean influences global climate, by conducting a series of unique fieldwork campaigns and innovative model developments.\r\nORCHESTRA involves scientists from many NERC Centres. This ambitious 5 year project began in spring 2016 and will use a combination of data collection, analyses and computer simulations to radically improve our ability to understand and predict the circulation of the Southern Ocean and its role in the global climate, with particular emphasis on the way that the Southern Ocean absorbs and stores heat and carbon.\r\n\r\nThe intensive 5-year observational program will involve ORCHESTRA scientists undertaking 12 expeditions on research ships in the Southern Ocean, with US collaborators performing a 13th. Ten of these expeditions will be annual north/south transects across the Antarctic Circumpolar Current, to evaluate how the ocean changes from one year to the next. The other three will form ‘boxes’ around the Atlantic sector of the Southern Ocean so that budgets can be performed. All these data, along with historical measurements, will be combined and analysed together. The observations will be used to inform and test a range of models." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 36269, 36270, 36324, 36331, 36334, 36337, 50623, 50624, 50625, 52949, 52960, 52977, 59647, 60131, 60132, 60135, 60136, 60143, 60148, 60151, 63109, 64089, 64090, 64091, 64092, 64093, 64094, 64095, 64096, 64097, 64098, 64099, 64100, 64101, 64102, 64103, 64104, 64105, 64106, 64107, 64108, 64109, 64110, 64111, 64112, 64113, 64114, 64115, 64116, 64117, 64118, 64119, 64120, 64121, 64122, 64123, 64124, 64125, 64126, 64127, 64128, 64129, 64130, 64131, 64132, 64133, 64134, 64135, 64136, 64137, 64138, 64139, 64140, 64141, 64142, 64143, 64144, 64145, 64146, 64147, 64148 ], "vocabularyKeywords": [], "identifier_set": [ 10946 ], "observationcollection_set": [ { "ob_id": 33122, "uuid": "5297667993904b12b0f8cbd8400ab56b", "short_code": "coll", "title": "ORCHESTRA - Ocean Regulation of Climate by Heat and Carbon Sequestration and Transports: Innovative model run output", "abstract": "ORCHESTRA is a NERC-funded Long Term Science programme that involves scientists from many NERC Centres. This 5 year project began in spring 2016 and will use a combination of data collection, analyses and computer simulations to radically improve our ability to understand and predict the circulation of the Southern Ocean and its role in the global climate, with particular emphasis on the way that the Southern Ocean absorbs and stores heat and carbon.\r\nThis Collection provides the outputs of innovative model runs of the 1/12 degree Nucleus for European Modelling of the Ocean (NEMO) model of the Southern Ocean carried out within the project" } ], "responsiblepartyinfo_set": [ 146705, 146706, 146704, 146703, 146702, 146708, 146711, 146712, 146714, 146715, 146713 ], "onlineresource_set": [ 43034, 43033, 43032, 43297 ] }, { "ob_id": 32847, "uuid": "b98db73607354c7b8ba9bc9347ceb9ed", "title": "ESA Sea Level Climate Change Initiative (Sea_level_cci): Arctic Sea Level Anomalies from ENVISAT and SARAL/Altika satellite altimetry missions (by CLS/PML)", "abstract": "This dataset contains estimations of Arctic sea level anomalies produced by the ESA Sea Level Climate Change Initiative project (Sea_level_cci), based on satellite altimetry from the ENVISAT and SARAL/Altika satellites. It has been produced by Collecte Localisation Satellites (CLS) and the Plymouth Marine Laboratory (PML).\r\n\r\nThe retrieval of sea level in the Arctic sea ice covered region requires specific processing steps of the satellite altimetry measurements. For this dataset, a specific radar waveform classification method has been applied based on a neural network approach, and the waveform retracking is based on a new adaptive retracking that is able to process both open ocean and peaky echoes measured in leads without introducing any bias between the two types of surfaces. Editing and mapping processing steps have been optimized for this dataset", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-12-09T10:39:54", "updateFrequency": "", "dataLineage": "The dataset has been produced by the Sea Level project of the ESA Climate Change Initiative programme. It has been supplied to CEDA for archiving in the context of the CCI Open Data Portal.", "removedDataReason": "", "keywords": "ESA, CCI, Sea level", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2021-12-16T09:45:03", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2911, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": 50.0, "northBoundLatitude": 82.0 }, "verticalExtent": null, "result_field": { "ob_id": 33433, "dataPath": "/neodc/esacci/sea_level/data/Arctic_MSLA/20161024/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 571964358, "numberOfFiles": 3715, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 9181, "startTime": "2003-01-01T00:00:00", "endTime": "2016-09-29T23:59:59" }, "resultQuality": { "ob_id": 3810, "explanation": "Data are as provided by the Sea Level CCI project team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-12-09" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 33436, "uuid": "f529533367f445e4b024ef8d8018e44a", "short_code": "cmppr", "title": "Composite process for ESA Sea Level Climate Change Initiative (Sea_level_cci): Arctic Sea Level Anomalies from ENVISAT and SARAL/Altika satellite altimetry missions (by CLS/PML)", "abstract": "Estimations of Arctic sea level anomalies have beenproduced by the ESA Sea Level Climate Change Initiative project (Sea_level_cci), based on satellite altimetry from the ENVISAT and SARAL/Altika satellites. It has been produced by Collecte Localisation Satellites (CLS) and the Plymouth Marine Laboratory (PML).\r\n\r\nThe retrieval of sea level in the Arctic sea ice covered region requires specific processing steps of the satellite altimetry measurements. For this dataset, a specific radar waveform classification method has been applied based on a neural network approach. And the waveform retracking is based on a new adaptive retracking that is able to process both open ocean and peaky echoes measured in leads without introducing any bias between the two types of surfaces. Editing and mapping processing steps have been optimized for this dataset" }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "permissions": [ { "ob_id": 2584, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 47, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_sealevel_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13331, "uuid": "a0a6fa39470a4a7baf847e3a1751f950", "short_code": "proj", "title": "ESA Sea Level Climate Change Initiative Project", "abstract": "The European Space Agency (ESA) Sea Level Climate Change Initiative (Sea_Level_cci) project is part of the ESA's Climate Change Initiative programme. \r\n\r\nIn the first phases of the CCI programme, the Sea Level project produced and validated global sea level Essential Climate Variable (ECV) products.\r\n\r\nIn the current phase, the objective is to produce a long-term and homogeneous sea level record as close to the coast as possible in order to assess whether the coastal sea level trends experienced at the coast are similar as the observed sea level trends in the open ocean and to determine the causes of the potential discrepancies." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 67730, 67731, 67732, 67733, 67734, 67735, 67736, 67737 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12684, "uuid": "56c94cb1410f4f2b8a41729c0e558617", "short_code": "coll", "title": "ESA Sea Level Climate Change Initiative (Sea Level CCI) dataset collection", "abstract": "As part of the European Space Agency's (ESA) Climate Change Initiative (CCI) programme, the Sea Level CCI project has produced a set of gridded multi-satellite merged products relating to the Sea Level Essential Climate Variable (ECV). These consist of a) a time series of monthly gridded Sea Level Anomalies (SLA) and b) Oceanic Indicators describing the evolution of the sea level anomalies.\r\n\r\nSea surface heights are measured above (or below) some reference level by altimeter satellites, surface height being the difference between a satellites position in orbit with respect to an arbitrary reference surface (the Earth's centre or a rough approximation of the Earth's surface: the reference ellipsoid) and the satellite-to-surface range (calculated by measuring the time taken for the signal to make the round trip). Through sending a microwave pulse to the ocean's surface, the satellites measured the surface heights through measuring the time taken for the pulse to return. \r\n\r\nThe current version is v1.1, and covers the period January 1993 - December 2014, and has been derived from the main altimeter missions: ERS-1, ERS-2, Envisat, TOPEX/Poseidon, Jason-1, Jason-2 and Geosat-Follow-On. A detailed description of the SL CCI project and the products can be found in Ablain et al., 2014, and further information is also provided in the Product User Guide. \r\n\r\nThe following DOI can be used to reference the product database (all products in the V1.1 release (as of December 2015)): DOI:10.5270/esa-sea_level_cci-1993_2014-v_1.1-201512. \r\n\r\n When using or referring to the SL_cci products, please mention the associated DOI (see above and the individual datasets) and also use the following citation where a detailed description of the SL_cci project and products can be found:\r\n\r\nAblain, M., Cazenave, A., Larnicol, G., Balmaseda, M., Cipollini, P., Faugère, Y., Fernandes, M. J., Henry, O., Johannessen, J. A., Knudsen, P., Andersen, O., Legeais, J., Meyssignac, B., Picot, N., Roca, M., Rudenko, S., Scharffenberg, M. G., Stammer, D., Timms, G., and Benveniste, J.: Improved sea level record over the satellite altimetry era (1993–2010) from the Climate Change Initiative project, Ocean Sci., 11, 67-82, doi:10.5194/os-11-67-2015, 2015.\r\n\r\nFor further information on the Sea Level CCI products, and to register your interest with the CCI team please email: info-sealevel@esa-sealevel-cci.org" } ], "responsiblepartyinfo_set": [ 146717, 146718, 146719, 146720, 146721, 146722, 149269, 149270 ], "onlineresource_set": [ 43695, 43714, 43715 ] }, { "ob_id": 32848, "uuid": "65bcd04dde2e4f8383a0cca4f69ac79e", "title": "UKCP18 Local Time-Mean Sea Level Projections for selected Tide Gauge Locations around the World", "abstract": "The UKCP18 worldwide sea level projections are provided for the tide gauge locations presented in Palmer et al (2020). They follow the same methods as the UK projections with the exceptions that make use of globally complete GIA estimates and a larger set of GRD fingerprints. The data consist of annual time series of the projected change in the time-mean coastal water level relative to the average value for the period 1986-2005, consistent with the IPCC Fifth Assessment Report (AR5) and the Special Report on the Ocean and Cryosphere in a Changing Climate. Projections are available for the RCP2.6, RCP4.5 and RCP8.5 climate change scenarios (Meinshausen et al, 2011). The 5th, 50th and 95th percentile projections are provided for the total sea level change and the individual components. Further details are available in Palmer et al (2020), which can be found in the documentation section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2021-07-09T12:33:03", "updateFrequency": "asNeeded", "dataLineage": "Data provided by the UK Met Office", "removedDataReason": "", "keywords": "UKCP18, climate, projections, global, marine, sea level, CMIP5, RCP", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-07-09T11:41:59", "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": 32849, "dataPath": "/badc/ukcp18/data/marine-sim/worldwide-proj", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 12614183, "numberOfFiles": 205, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 9021, "startTime": "2007-01-01T00:00:00", "endTime": "2300-12-30T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 32850, "uuid": "fb97f236192748289c4b0f5102097ffa", "short_code": "comp", "title": "UKCP18 local time-mean sea level calculations for selected tide gauge locations around the world", "abstract": "The UKCP18 local time-mean sea level projections are based on CMIP5 climate model simulations of global ocean thermal expansion and global average surface temperature (GST) change. The extended 2300 projections make use of a simple climate model emulator tuned to CMIP5 models to generate estimates of thermal expansion and GST change beyond 2100. Global contributions from ice sheet surface mass balance and glaciers are related to GST following methods described in IPCC AR5 WG1 Chapter 13 (Church et al, 2013) and as described by Palmer et al (2020). Global sea level contributions for dynamic ice discharge for Greenland and Antarctica are based on IPCC AR5 and Levermann et al (2014), respectively. Estimates of land water storage changes follow those reported in IPCC AR5. These global components are regionalised for worldwide tide gauge locations using: (i) sea level GRD (gravitational, rotational and deformation) \"fingerprints\" for mass changes in land-based ice and water; (ii) local regression relationships across CMIP5 models for the sterodynamic component; (iii) an ensemble of estimate of the local relative sea level change from glacial isostatic adjustment. A 100,000 sample Monte Carlo is used to provide uncertainties for regional sea level change based on the 5th and 95th percentiles of the Monte Carlo sample. All projections are expressed relative to the 1986-2005 average value. Please refer to Palmer et al (2020) for detailed methods. Further details are available in Palmer et al (2020), https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019EF001413" }, "procedureCompositeProcess": null, "imageDetails": [ 212 ], "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": 26015, "uuid": "3500c35912e34566adb9948920d1216d", "short_code": "proj", "title": "UKCP18: The Marine Component of the UK Climate Projections 2018", "abstract": "The marine component of the UKCP18 project is comprised of:\r\nA multi-model ensemble of sea level projections for UK waters which extend to 2100 and include contributions from glaciers, ice sheets, freshwater reservoirs, groundwater and thermal expansion. \r\nA multi-model ensemble of historical sea level simulations for UK waters from 1970 to 2006.\r\nCase studies of three short events.\r\nSimulated impacts of mean sea level change on tidal characteristics around the UK." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 146723, 146724, 146725, 146726, 146727, 146728, 146729, 146736, 146735 ], "onlineresource_set": [ 43038, 43039, 95108, 95109 ] }, { "ob_id": 32852, "uuid": "deab4235f1ef4cd79b73d0cbf2655bd7", "title": "Sub-meter resolution digital elevation models and orthomosaics of the Kruger National Park, South Africa, v1.0, September-October 2018", "abstract": "This dataset contains sub-meter resolution digital elevation models and orthomosaics of the Kruger National Park, South Africa, generated from aerial images captured by Digital Mapping Camera (DMC) during September and October 2018.\r\n\r\n\r\nThe use of digital elevation models has proven to be crucial in a large number of studies related to savanna ecosystem research. However, the insufficient spatial resolution of the input data is often considered to be a limiting factor when conducting local to regional ecosystem analysis. The elevation models and orthorectified imagery created in this dataset represent the first wall-to-wall digital elevation products of the Kruger National Park (KNP) in South Africa at 25 cm pixel posting. In the light of regular flight campaigns carried out by the South African government, the workflow of the presented data sets can be reused to create height models and orthorectified images of a vulnerable ecosystem in the future. Flight campaigns were carried out by GeoSpace International, Pretoria. Data processing and preparation as well as validation of the final products was carried out by Kai Heckel (Friedrich Schiller University Jena, Germany) with the strong support of all co-authors of the related study.\r\n\r\nThe methodology is described in the following publication:\r\n\r\nHeckel, K.; Urban, M.; Bouffard, J.-S.; Baade, J.; Boucher, P.; Davies, A.; Hockridge, E.G.; Lück, W.; Ziemer, J.; Smit, I.; Jacobs, B.; Norris-Rogers, M.; Schmullius, C. (2021): The first sub-meter resolution digital elevation model of the Kruger National Park, South Africa. Koedoe.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2021-08-12T20:27:06", "updateFrequency": "", "dataLineage": "Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "Kruger, Digital Elevation Models, Orthomosaics", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2021-08-24T14:45:09", "doiPublishedTime": "2021-09-28T13:30:57.775657", "removedDataTime": null, "geographicExtent": { "ob_id": 2808, "bboxName": "Kruger National Park", "eastBoundLongitude": 32.03301, "westBoundLongitude": 30.88824, "southBoundLatitude": -25.52952, "northBoundLatitude": -22.32868 }, "verticalExtent": null, "result_field": { "ob_id": 32851, "dataPath": "/neodc/dem/kruger/v1.0/sep2018_oct2018/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 3633786348379, "numberOfFiles": 338, "fileFormat": "GEOtiff" }, "timePeriod": { "ob_id": 9022, "startTime": "2018-09-01T00:00:00", "endTime": "2018-10-30T00:00:00" }, "resultQuality": { "ob_id": 3724, "explanation": "Data was validated by the project team. For the validation of the vertical accuracy of the derived digital elevation models (DEMs) the authors used parameters as suggested by the American Society for Photogrammetry and Remote Sensing (ASPRS), Positional Accuracy Standards for Digital Geospatial Data. The validation of the horizontal accuracy of the orthorectified mosaics was carried out following the National Standard for Spatial Data Accuracy (NSSDA) standards. Details can be found in the related documnetation", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2021-07-28" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 33043, "uuid": "1edad8d1d7414d798ac441790d5f92ee", "short_code": "cmppr", "title": "Kruger DEM and Orthomosaics", "abstract": "The Kruger DEM and Orthomsaics" }, "imageDetails": [], "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": 33044, "uuid": "112ad38f32dc4da4bdf137471ec5ac0f", "short_code": "proj", "title": "SALDi", "abstract": "The South African Land Degradation Monitor (SALDi) supported the production of the Sub-meter resolution digital elevation models and orthomosaics of the Kruger National Park, South Africa, v1.0, September-October 2018 dataset archived at CEDA.\r\n\r\nThe SALDi project develops new approaches for the spatially explicit detection of land degradation in South Africa. The objectives of the Working Group on Soil Erosion within SALDi are:\r\n\r\n To improve the assessment of the extent of soil erosion in South Africa by means of current studies on the silting up of reservoirs.\r\n\r\n To evaluate the extent of soil erosion in relation to soil recharge rates.\r\n\r\n To improve the model-based estimation of soil erosion by water with a physically-based model.\r\n\r\n\r\nAgainst the background of widespread land degradation in South Africa, SALDi pursues the following remote sensing related objectives:\r\n\r\n Development of a permanent observation system (monitors) for ecosystem changes and degradation by satellite remote sensing.\r\n\r\n Modelling of the interactions of surface changes, weather and climate.\r\n\r\n Improvement of methods for the evaluation of soil degradation, especially soil erosion by water.\r\n\r\n Consideration of socio-economic dimensions and impacts of land degradation and evaluation of SALDi products by local actors.\r\n\r\n A main objective of TP1.3 is the development of high-resolution Spatio-temporal methods for the analysis of ecosystem changes using the latest Earth observation satellites (e.g. Sentinel-1), which serve as a basis for regional climate modelling (TP2) and synergistic intersection with other EO data (TP4). The Chair of Remote Sensing at FSU Jena has the task to analyze ecosystem changes and dynamics. The project will perform the following tasks:\r\n\r\n\r\na) Analysis of Spatio-temporal dynamics of surface moisture and mapping of vegetation structure (e.g. biomass)\r\nb) Validation of derived EO products (e.g. soil moisture) through terrain campaigns and cooperation with South African partners;\r\nc) Derivation of land degradation indicators through synergetic linking of optical and radar-based EO data.\r\n\r\nThe PI of the SALDi project is Jussi Baade and is funded by the Federal Ministry of Education and Research (BMBF) under BMBF funding code: South African Land Degradation Monitor (SALDi) (01LL1701A-A)." }, { "ob_id": 33119, "uuid": "e0fe7559b06e4f49baf9a3710e7ff5b3", "short_code": "proj", "title": "EMSAfrica", "abstract": "EMSAfrica supported the production of the Sub-meter resolution digital elevation models and orthomosaics of the Kruger National Park, South Africa, v1.0, September-October 2018 dataset archived at CEDA.\r\n\r\nEMSAfrica is a collaborative research project between South Africa and Germany. The project brings together different scientific disciplines and approaches to understand the impacts of land use and climate change on the structure and function of South African terrestrial ecosystems. The data and products are used to develop and test models and produce information relevant to ecosystem management in the region. The project uses six observation sites in South Africa established by its predecessor project ARS Africa (2014-2018). These sites represent a climatic gradient and different land management types from peri-urban to grazed and protected, natural-like environments. To disentangle the impacts of land management from the impacts of climate, the sites are \"paired\" so that the managed sites are located as close as possible to a similar site in a natural-like environment. This way, observed differences between the sites are due to land use rather than climate. Each of the project work packages conducts different measurements on these sites. By working together and integrating our data, analyses and results, it becomes possible to build models on the Southern African vegetation patterns and carbon balance. Furthermore, the aim is to scale up this information into combined models that can be used to aid land-use decision making.\",\r\n\r\nThe PI for the EMSAfrica project is Steve Higgins and received funding from the Federal Ministry of Education and Research (BMBF) under grant_number: 01LL1801." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [ 10947 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 146738, 146739, 146740, 146741, 146742, 146743, 147009, 147010, 147011, 147012, 147013, 147014, 147015, 147016, 147017, 147018, 147019, 147020, 147021, 147022 ], "onlineresource_set": [ 43333, 43334, 43335, 43404, 43405, 43406 ] } ] }