Observation List
Get a list of Observation objects.
GET /api/v3/observations/?format=api&offset=5300
{ "count": 10256, "next": "https://api.catalogue.ceda.ac.uk/api/v3/observations/?format=api&limit=100&offset=5400", "previous": "https://api.catalogue.ceda.ac.uk/api/v3/observations/?format=api&limit=100&offset=5200", "results": [ { "ob_id": 25941, "uuid": "38296ae73f3b44f5b8d66dcc3ed398bd", "title": "QA4ECV Polar sea-ice spectral albedo (2000-2016)", "abstract": "The Quality Assurance for Essential Climate Variables (QA4ECV) project produced four daily polar sea-ice products, each with a different averaging time window (24 hours, 7 days, 15 days, 31 days). For each time window, the number of samples, mean and standard deviation of Multi-angle Imaging SpectroRadiometer (MISR) cloud-free sea ice albedo was calculated. These products are on a predefined polar stereographic grid at three spatial resolutions (1 km, 5 km, 25 km). The time span of the generated sea ice albedo covers the months between March and September of each year from 2000 to 2016 inclusive.\r\n\r\nIf publishing results based on this dataset, please cite the following: S. Kharbouche and J.-P. Muller, “Sea Ice Albedo from MISR and MODIS: Production, Validation, and Trend Analysis,” Remote Sensing, vol. 11,no. 1, p. 9, Dec. 2018. DOI: 10.3390/rs11010009. URL:http://www.mdpi.com/2072-4292/11/1/9", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-04-30T22:43:26", "updateFrequency": "", "dataLineage": "Data are provided by the QA4ECV project for archival with CEDA. Data are in NetCDF format.\r\n\r\nIf publishing results based on this dataset, please cite the following: S. Kharbouche and J.-P. Muller, “Sea Ice Albedo from MISR and MODIS: Production, Validation, and Trend Analysis,” Remote Sensing, vol. 11,no. 1, p. 9, Dec. 2018. DOI: 10.3390/rs11010009. URL:http://www.mdpi.com/2072-4292/11/1/9", "removedDataReason": "", "keywords": "Albedo, Polar, Climate, Sea Ice, Radiometer", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2019-01-18T13:01:13", "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": 26911, "dataPath": "/neodc/qa4ecv/data/sea_ice/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2224562524077, "numberOfFiles": 39313, "fileFormat": "These data are in NetCDF format" }, "timePeriod": { "ob_id": 7010, "startTime": "2000-03-31T23:00:00", "endTime": "2016-09-30T13:03:52" }, "resultQuality": { "ob_id": 3217, "explanation": "Data as provided by the QA4ECV project, archived at CEDA", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-01-18" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 26906, "uuid": "f967b0786f7248848f60ec6767891332", "short_code": "cmppr", "title": "Composite Process for QA4ECV Sea-ice Spectral Albedo.", "abstract": "The Multi-angle Imaging SpectroRadiometer (MISR) sensor onboard the Terra satellite deploys nine cameras each at different view angles, which allow a near-simultaneous angular sampling of the surface anisotropy. This is particularly important to measure the near-instantaneous albedo of dynamic surface features such as sea ice. However, MISR’s cloud mask over snow or sea ice is not yet sufficiently robust because MISR’s spectral bands are only located in the visible and the near infrared. This dataset was created using a specially processed MISR sea ice albedo product (that was generated at Langley Research Center using Rayleigh correction) combining this with a cloud mask of a sea ice mask product, MOD29, which is derived from the MODerate Resolution Imaging Spectroradiometer (MODIS), which is also, like MISR, onboard the Terra satellite. The accuracy of the MOD29 cloud mask has been assessed as >90% due to the fact that MODIS has a much larger number of spectral bands and covers a much wider range of the solar spectrum." }, "imageDetails": [ 210 ], "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": 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": [ 24786, 24787, 24788, 24789, 24790, 24791, 24792, 24793, 24794, 24795, 24796, 24797, 24798, 24799, 24800 ], "vocabularyKeywords": [], "identifier_set": [ 10211 ], "observationcollection_set": [ { "ob_id": 25940, "uuid": "3a9a9c2af1c3439cabcda91edc4eaf56", "short_code": "coll", "title": "QA4ECV Albedo", "abstract": "Knowledge of albedo is of critical importance to land surface monitoring and modelling, particularly with regard to considerations of climate forecasting and energy exchanges within the biosphere. When albedo is used in models, it has often been specified as a fixed number for some given land cover type. However, many years of monitoring from single instruments, such as MODIS, have shown that it can vary significantly both spatially and temporally. That said, being an angular and spectral integral, it is relatively conservative inter-annually, other than due to factors such as snow and possibly fire and dramatic land cover change (e.g. flooding, urbanisation). As particularly high changes in albedo occur due to the presence of absence of snow, modellers tend to consider these two cases separately: a snow free albedo and one with snow included.\r\n\r\nGlobal albedo data of the land surface is produced from data from 1982-2016 from European and US satellites daily and monthly with estimated uncertainties for every pixel. There are 3 data products including: 1) AVHRR+GEO Broadband Albedo at 0.5 and 0.05 degrees; 2) Spectral Albedo at 1km; and 3) Sea Ice Spectral Albedo at 1km" }, { "ob_id": 25978, "uuid": "f65252bf8ee5448baa1ae060cd07703a", "short_code": "coll", "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)." } ], "responsiblepartyinfo_set": [ 108433, 108436, 112953, 113178, 112954, 112951, 112952, 108435, 108434, 108437 ], "onlineresource_set": [ 24542, 24543, 25982 ] }, { "ob_id": 25942, "uuid": "bd2ad818ebec44748078fefa5161bd83", "title": "QA4ECV Europe Spectral albedo (1998-2000, 2005-2006)", "abstract": "European spectral albedo data of the land surface is produced from data from 1998-200 and 2005-2006 from European and US satellites daily and monthly with estimated uncertainties for every pixel. The spectral albedo is calculated at the first 6 of the MODIS spectral bands.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": null, "updateFrequency": "", "dataLineage": "Data provided ", "removedDataReason": "", "keywords": "", "publicationState": "preview", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "pending", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": null, "timePeriod": null, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 210 ], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 25937, "uuid": "130756538390418ea80ebe143542b01d", "short_code": "proj", "title": "Quality Assurance for Essential Climate Variables (QA4ECV)", "abstract": "The FP7 QA4ECV project was initiated in 2014 to demonstrate how reliable and traceable quality information can be provided for satellite and ground-based measurements of climate and air quality parameters. The project developed and applied a Quality Assurance framework on new and improved multi-decadal data records of the Land ECVs Albedo, Leaf Area Index (LAI), and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and on the Atmosphere ECVs nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO).\r\n\r\nQA4ECV provides multi-decadal satellite data records for 3 Land Essential Climate Variables (ECVs) and 3 Atmosphere ECV precursors." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 25940, "uuid": "3a9a9c2af1c3439cabcda91edc4eaf56", "short_code": "coll", "title": "QA4ECV Albedo", "abstract": "Knowledge of albedo is of critical importance to land surface monitoring and modelling, particularly with regard to considerations of climate forecasting and energy exchanges within the biosphere. When albedo is used in models, it has often been specified as a fixed number for some given land cover type. However, many years of monitoring from single instruments, such as MODIS, have shown that it can vary significantly both spatially and temporally. That said, being an angular and spectral integral, it is relatively conservative inter-annually, other than due to factors such as snow and possibly fire and dramatic land cover change (e.g. flooding, urbanisation). As particularly high changes in albedo occur due to the presence of absence of snow, modellers tend to consider these two cases separately: a snow free albedo and one with snow included.\r\n\r\nGlobal albedo data of the land surface is produced from data from 1982-2016 from European and US satellites daily and monthly with estimated uncertainties for every pixel. There are 3 data products including: 1) AVHRR+GEO Broadband Albedo at 0.5 and 0.05 degrees; 2) Spectral Albedo at 1km; and 3) Sea Ice Spectral Albedo at 1km" }, { "ob_id": 25978, "uuid": "f65252bf8ee5448baa1ae060cd07703a", "short_code": "coll", "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)." } ], "responsiblepartyinfo_set": [ 108450, 108451, 108452, 204955, 204956, 204957, 204958, 204959, 108453, 108454, 108449, 108455 ], "onlineresource_set": [ 24544, 24545 ] }, { "ob_id": 25944, "uuid": "050ab7126ebe4300b7a3dc9fce18b054", "title": "QA4ECV LAI", "abstract": "The Leaf Area Index (LAI) product is produced using a Two Stream Inversion Package (TIP) method applied to visible (VIS) and near infrared (NIR) broadband albedos (from the QA4ECV albedo product). he definition of LAI in this product is half the total canopy area per unit ground area (m2 / m2) for a homogeneous canopy of infinitesimally small Lambertian surfaces, akin to a turbid medium.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-03-21T09:47:27", "updateFrequency": "", "dataLineage": "These data", "removedDataReason": "", "keywords": "", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "pending", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": null, "verticalExtent": null, "result_field": null, "timePeriod": null, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 210 ], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 25937, "uuid": "130756538390418ea80ebe143542b01d", "short_code": "proj", "title": "Quality Assurance for Essential Climate Variables (QA4ECV)", "abstract": "The FP7 QA4ECV project was initiated in 2014 to demonstrate how reliable and traceable quality information can be provided for satellite and ground-based measurements of climate and air quality parameters. The project developed and applied a Quality Assurance framework on new and improved multi-decadal data records of the Land ECVs Albedo, Leaf Area Index (LAI), and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and on the Atmosphere ECVs nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO).\r\n\r\nQA4ECV provides multi-decadal satellite data records for 3 Land Essential Climate Variables (ECVs) and 3 Atmosphere ECV precursors." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 25943, "uuid": "597cdd6371ba410ea72bd4219181178c", "short_code": "coll", "title": "QA4ECV LAI and FAPAR", "abstract": "The Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product is produced using a Two Stream Inversion Package (TIP) method applied to visible (VIS) and near infrared (NIR) broadband albedos (from the QA4ECV albedo product).\r\n\r\nBased on the global albedo data on 0.5 degree and 0.05 degree regular grids, TIP-LAI and TIP-FAPAR are available for 1982 to 2016." } ], "responsiblepartyinfo_set": [ 108458, 108460, 204845, 204846, 204847, 204848, 204849, 204850, 108459, 108461, 108462, 108463, 108464 ], "onlineresource_set": [] }, { "ob_id": 25945, "uuid": "fb1df8ff08564616818d71d78db03f51", "title": "QA4ECV BHR-TIP FAPAR/ effective LAI (1982-2016)", "abstract": "The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product is produced using a Two Stream Inversion Package (TIP) method applied to visible (VIS) and near infrared (NIR) broadband albedos (from the QA4ECV albedo product). The definition of FAPAR in this product is the simulated absorption of the photosynthetically active radiation (estimated for the visible band) by a homogeneous canopy of infinitesimally small Lambertian surfaces, akin to a turbid medium.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2019-02-07T09:33:52", "updateFrequency": "", "dataLineage": "These data", "removedDataReason": "", "keywords": "", "publicationState": "preview", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "pending", "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": 27070, "dataPath": "/neodc/qa4ecv/data/BHR-TIP/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 874878676097, "numberOfFiles": 25991, "fileFormat": "These data are in netCDF file format." }, "timePeriod": { "ob_id": 7018, "startTime": "1982-01-01T00:00:00", "endTime": "2016-12-31T23:59:59" }, "resultQuality": null, "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": [ 53130, 53131, 69393, 69394, 69395, 69396, 69397, 69398, 69399, 69400, 69401, 69402 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 25943, "uuid": "597cdd6371ba410ea72bd4219181178c", "short_code": "coll", "title": "QA4ECV LAI and FAPAR", "abstract": "The Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product is produced using a Two Stream Inversion Package (TIP) method applied to visible (VIS) and near infrared (NIR) broadband albedos (from the QA4ECV albedo product).\r\n\r\nBased on the global albedo data on 0.5 degree and 0.05 degree regular grids, TIP-LAI and TIP-FAPAR are available for 1982 to 2016." }, { "ob_id": 25978, "uuid": "f65252bf8ee5448baa1ae060cd07703a", "short_code": "coll", "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)." } ], "responsiblepartyinfo_set": [ 108465, 108466, 143621, 143622, 143623, 143624, 143625, 143626, 108467, 108468, 108469, 108470, 108471 ], "onlineresource_set": [] }, { "ob_id": 25947, "uuid": "5587614793674fa680a8e6e5b93c6bff", "title": "QA4ECV DHR-FAPAR (1982-2006)", "abstract": "The Joint Research Centre (JRC) are currently producing a new Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product which ingests Advanced Very High Resolution Radiometer (AVHRR) data. The estimation of a state variable from the signals measured by a given sensor is constructed from sensor-specific simulated data sets, representative of various land surfaces, using radiative transfer models of the coupled surface atmosphere system. This approach defines a large number of simulated radiance fields, which can be sampled by a virtual instrument similar to the actual one in terms of the spectral and angular observing schemes. Similarly, the corresponding FAPAR values for the various terrestrial systems under investigation can be simultaneously estimated. The simulations of FAPAR values have been made by assuming that the spectral properties of leaves and soil correspond to the Photosynthesis Active Radiation (PAR) region which is between 400 nm and 700 nm. In this case, simulations are made with a homogeneous canopy model (Gobron et al. 1997) representing land surfaces.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": null, "updateFrequency": "", "dataLineage": "These data", "removedDataReason": "", "keywords": "", "publicationState": "preview", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "pending", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": null, "timePeriod": null, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 210 ], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 25937, "uuid": "130756538390418ea80ebe143542b01d", "short_code": "proj", "title": "Quality Assurance for Essential Climate Variables (QA4ECV)", "abstract": "The FP7 QA4ECV project was initiated in 2014 to demonstrate how reliable and traceable quality information can be provided for satellite and ground-based measurements of climate and air quality parameters. The project developed and applied a Quality Assurance framework on new and improved multi-decadal data records of the Land ECVs Albedo, Leaf Area Index (LAI), and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and on the Atmosphere ECVs nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO).\r\n\r\nQA4ECV provides multi-decadal satellite data records for 3 Land Essential Climate Variables (ECVs) and 3 Atmosphere ECV precursors." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 25946, "uuid": "6e8371d872574bcb801011ace6bf393d", "short_code": "coll", "title": "QA4ECV AVHRR FAPAR", "abstract": "Need some more information here." }, { "ob_id": 25978, "uuid": "f65252bf8ee5448baa1ae060cd07703a", "short_code": "coll", "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)." } ], "responsiblepartyinfo_set": [ 108474, 108475, 200395, 200396, 200397, 200398, 200399, 200400, 108481, 108482, 108483 ], "onlineresource_set": [] }, { "ob_id": 25950, "uuid": "a3e0f0848a144484bdea833ef01ec834", "title": "Arctic Cloud Summer Expedition (ACSE): carbon dioxide and water vapour measurements from the University of Leeds LI-COR Li-7500 gas analyzer on board Icebreaker Oden", "abstract": "This dataset contains carbon dioxide and water vapour concentration measurements from the University of Leeds' LI-COR LI-7500 open path gas analyser mounted on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThe instrument's sensing head was located on the foremast of Icebreaker Oden, approximately 1 m forward of the sonic anemometer. Note the LiCOR LI-7500 CO2 data are generally not suitable for flux measurements at sea. Only the water vapour signal has been used for flux analysis.\r\n\r\nData times were truncated to match those from the sonic anemometer and the internal lag was corrected for.\r\n\r\nUsers should also note that the instrument's temperature and pressure measurements are made inside the interface box. Temperature is thus likely to be high due to solar heating of box, and pressure will be biased low (box is ~3 m below sensor) and may be subject to dynamic pressure fluctuations resulting from airflow around pressure inlet.\r\n\r\nMeasurements are made at 20 Hz frequency.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T03:06:45", "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": "CO2, H2O, water vapour, carbon dioxide", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "final", "dataPublishedTime": "2018-04-14T12:59:52", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2195, "bboxName": "ACSE voyage bounding box", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": 69.66, "northBoundLatitude": 85.23 }, "verticalExtent": null, "result_field": { "ob_id": 25949, "dataPath": "/badc/acse/data/leeds-licor-7500", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 9405431097, "numberOfFiles": 1823, "fileFormat": "Data are CF-compliant netCDF formatted" }, "timePeriod": { "ob_id": 7017, "startTime": "2014-07-10T13:02:00", "endTime": "2014-10-02T22:57:59" }, "resultQuality": { "ob_id": 3193, "explanation": "Data quality were checked by the ACSE project data author before supplying to CEDA. 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ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF).\r\n\r\nSWERUS-C3 was initiated as a Knut and Alice Wallenberg funded research project. The project was developed into a multi-disciplinary international research program focused on investigating the historical functioning of the Climate-Cryosphere-Carbon (C3) system of the East Siberian Arctic Ocean." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 4385, 54754, 56591, 56592, 56593, 56594, 56595, 56596, 56597, 56598 ], "vocabularyKeywords": [], "identifier_set": [ 10098 ], "observationcollection_set": [ { "ob_id": 25948, "uuid": "e75e1e57932d4b95831fa7b56a2016e1", "short_code": "coll", "title": "Arctic Cloud Summer Expedition (ACSE): surface and boundary layer meteorological measurements on board the Icebreaker Oden", "abstract": "This dataset collection contains a number of observational datasets (mainly from the NERC funded contribution, but others too) of surface and boundary layer meteorological measurements collected on board the Icebreaker Oden during its voyage for the Arctic Cloud Summer Expedition (ACSE).\r\n\r\nACSE was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES (the Cooperative Institute for Research In Environmental Sciences). ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." } ], "responsiblepartyinfo_set": [ 108496, 108497, 108499, 108500, 108501, 108502, 108503, 108498, 108504, 108505 ], "onlineresource_set": [ 25741, 25742, 94869 ] }, { "ob_id": 25951, "uuid": "bfa8b9457e1a4cb6aa506316295564b2", "title": "Arctic Cloud Summer Expedition (ACSE): turbulence wind and sonic temperature measurements from the University of Leeds Metek USA-100 sonic anemometer on board Icebreaker Oden", "abstract": "This dataset contains turbulent winds and sonic temperature measurements by the University of Leeds' Metek USA-100 sonic anemometer during the Arctic Cloud Summer Expedition (ACSE). The ACSE cruise took place in the Arctic during summer 2014. These data were obtained to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nMeasurements were made at 20Hz from which 20-minute average fluxes were then derived.\r\n\r\nThe sonic anemometer was located on the foremast of the Icebreaker Oden ship at 20.58 m above the waterline. Data here includes the raw measurements and fully corrected turbulent winds (motion correction, flow distortion correction, etc), along with sonic temperature. For details of motion and flow distortion see the linked documentation. \r\n\r\nNote that while the Metek anemometer uses a left-handed reference frame, all measurements have been transformed to a right-handed frame here. The anemometer x-axis was rotated 30 deg anticlockwise from ship bow.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). 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ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF).\r\n\r\nSWERUS-C3 was initiated as a Knut and Alice Wallenberg funded research project. The project was developed into a multi-disciplinary international research program focused on investigating the historical functioning of the Climate-Cryosphere-Carbon (C3) system of the East Siberian Arctic Ocean." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 4385, 54754, 56603, 56604, 56605, 56606, 56607, 56608, 56609, 56610 ], "vocabularyKeywords": [], "identifier_set": [ 10092 ], "observationcollection_set": [ { "ob_id": 25948, "uuid": "e75e1e57932d4b95831fa7b56a2016e1", "short_code": "coll", "title": "Arctic Cloud Summer Expedition (ACSE): surface and boundary layer meteorological measurements on board the Icebreaker Oden", "abstract": "This dataset collection contains a number of observational datasets (mainly from the NERC funded contribution, but others too) of surface and boundary layer meteorological measurements collected on board the Icebreaker Oden during its voyage for the Arctic Cloud Summer Expedition (ACSE).\r\n\r\nACSE was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES (the Cooperative Institute for Research In Environmental Sciences). ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." } ], "responsiblepartyinfo_set": [ 108513, 108506, 108508, 108510, 108511, 108512, 108515, 108507, 108514, 108509 ], "onlineresource_set": [ 24550, 24551, 24552, 25739, 25740, 91754, 91755, 91756, 91757, 91758 ] }, { "ob_id": 25953, "uuid": "f2566ac78a664a58a23a42e9e45da788", "title": "Arctic Cloud Summer Expedition (ACSE): University of Leeds Mobotix camera imagery on board Icebreaker Oden", "abstract": "This dataset contains digital imagery from the University of Leed's three 'Mobotix MX-M24M IP' cameras mounted on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These imagery were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThe three camera units were mounted pointing in the following directions:\r\n\r\n - Camera 1: pointing to starboard,\r\n - Camera 2: pointing to bow,\r\n - Camera 3: pointing to port.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF).", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-03-22T16:13:19.106982", "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": "cruise, imagery, sea-ice", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "final", "dataPublishedTime": "2018-04-14T11:52:20", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2195, "bboxName": "ACSE voyage bounding box", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": 69.66, "northBoundLatitude": 85.23 }, "verticalExtent": null, "result_field": { "ob_id": 25954, "dataPath": "/badc/acse/data/leeds-mobotix-cameras", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 209920948188, "numberOfFiles": 342158, "fileFormat": "Images are JPEG formatted." }, "timePeriod": { "ob_id": 7008, "startTime": "2014-07-04T12:57:48", "endTime": "2014-10-03T06:16:17" }, "resultQuality": { "ob_id": 3193, "explanation": "Data quality were checked by the ACSE project data author before supplying to CEDA. 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ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF).\r\n\r\nSWERUS-C3 was initiated as a Knut and Alice Wallenberg funded research project. The project was developed into a multi-disciplinary international research program focused on investigating the historical functioning of the Climate-Cryosphere-Carbon (C3) system of the East Siberian Arctic Ocean." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [ 10086 ], "observationcollection_set": [ { "ob_id": 25948, "uuid": "e75e1e57932d4b95831fa7b56a2016e1", "short_code": "coll", "title": "Arctic Cloud Summer Expedition (ACSE): surface and boundary layer meteorological measurements on board the Icebreaker Oden", "abstract": "This dataset collection contains a number of observational datasets (mainly from the NERC funded contribution, but others too) of surface and boundary layer meteorological measurements collected on board the Icebreaker Oden during its voyage for the Arctic Cloud Summer Expedition (ACSE).\r\n\r\nACSE was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES (the Cooperative Institute for Research In Environmental Sciences). ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." } ], "responsiblepartyinfo_set": [ 108516, 108518, 108519, 108520, 108521, 108522, 108523, 108517, 108524, 109258 ], "onlineresource_set": [ 24546, 24547, 91812, 91813, 91814, 91815, 91816, 91817, 91818, 91819, 91820 ] }, { "ob_id": 25955, "uuid": "f2f4675203d04e4eb269e230633d03db", "title": "Arctic Cloud Summer Expedition (ACSE): high resolution ship motion data from the University of Leeds XSENS MTi-G-700 attitude and heading reference system on board Icebreaker Oden", "abstract": "This dataset contains high resolution attitude and motion measurements of the Icebreaker Oden ship's motion by the University of Leeds' XSENS MTi-G-700 attitude and heading reference system during the Arctic Cloud Summer Expedition (ACSE). The ACSE cruise took place in the Arctic during summer 2014. These data were obtained to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (Swedish-Russian-US Investigation) holdings - see online resources linked to this record.\r\n\r\nMeasurements were made at 40Hz for inertial measurements and 4Hz for GPS measurements. Though the inertial measurements were used at 20Hz when merged with sonic anemometer, 20 minute final fluxes (see related data within the parent data collection).\r\n\r\nThe XSens MTi-G-700 measures 3-axis accelerations, rotation rates, and magnetic field components as well as GPS position. Internal algorithm calculate 3-axis velocity, tilt angles and heading. However, users of these data should note that it is often not possible to calibrate magnetic field for local platform induced distortions (soft iron and hard iron corrections) resulting in errors in magnetic field and calculated outputs. Additionally, the heading measurements were found to unreliable on the ship.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. 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ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. 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This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T03:12:19", "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": "temperature, relative humidity", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "final", "dataPublishedTime": "2018-04-14T12:49:32", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2195, "bboxName": "ACSE voyage bounding box", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": 69.66, "northBoundLatitude": 85.23 }, "verticalExtent": null, "result_field": { "ob_id": 25969, "dataPath": "/badc/acse/data/misu-rotronic-met", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 492646663, "numberOfFiles": 2, "fileFormat": "Data are CF-compliant netCDF" }, "timePeriod": { "ob_id": 7014, "startTime": "2014-07-04T09:47:35", "endTime": "2014-10-01T11:59:58" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 25971, "uuid": "ddc703802e2a4c1583d88edde518d0fc", "short_code": "acq", "title": "ACSE: MISU misu-rotronic-met measurements on board Icebreaker Oden", "abstract": "ACSE: MISU misu-rotronic-met measurements on board Icebreaker Oden" }, "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": 24932, "uuid": "f4d0cf8f90d240c8bc9556ca4ee075d2", "short_code": "proj", "title": "Arctic Cloud Summer Expedition (ACSE)", "abstract": "The Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES (the Cooperative Institute for Research In Environmental Sciences). ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF).\r\n\r\nSWERUS-C3 was initiated as a Knut and Alice Wallenberg funded research project. The project was developed into a multi-disciplinary international research program focused on investigating the historical functioning of the Climate-Cryosphere-Carbon (C3) system of the East Siberian Arctic Ocean." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 4385, 54754, 60866, 60867, 60868, 60869, 60870, 60871 ], "vocabularyKeywords": [], "identifier_set": [ 10093 ], "observationcollection_set": [ { "ob_id": 25948, "uuid": "e75e1e57932d4b95831fa7b56a2016e1", "short_code": "coll", "title": "Arctic Cloud Summer Expedition (ACSE): surface and boundary layer meteorological measurements on board the Icebreaker Oden", "abstract": "This dataset collection contains a number of observational datasets (mainly from the NERC funded contribution, but others too) of surface and boundary layer meteorological measurements collected on board the Icebreaker Oden during its voyage for the Arctic Cloud Summer Expedition (ACSE).\r\n\r\nACSE was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES (the Cooperative Institute for Research In Environmental Sciences). ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." } ], "responsiblepartyinfo_set": [ 108598, 108595, 108597, 108599, 108600, 108601, 108602, 108596, 108604, 109268 ], "onlineresource_set": [ 25751, 25752, 91715, 91716, 91717, 91718, 91719, 91720, 91721, 91722, 91723 ] }, { "ob_id": 25973, "uuid": "ef63d8590dd7445c8783df00f0ba654b", "title": "QA4ECV MODIS spectral BRDF climatology (2000-2016)", "abstract": "Spectral BRDF climatology from merge of snow and nosnow products upscaled at 0.05º derived from 17 records (one for each year form 2000..2016) for each land surface pixel for each day of year. each pixel has an estimated uncertainty based on a weighting of the MODIS MCD43A2 Quality bit flags. This dataset represents a global climatology in the 7 MODIS spectral bands and is used within the QA4ECV for regularisation purposes as the \"prior\" for spectral inversions.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-03-23T08:57:47", "updateFrequency": "", "dataLineage": "These data are provided in netCDF4 format.", "removedDataReason": "", "keywords": "", "publicationState": "preview", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "pending", "dataPublishedTime": null, "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": null, "verticalExtent": null, "result_field": null, "timePeriod": null, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 210 ], "discoveryKeywords": [], "permissions": [], "projects": [ { "ob_id": 25937, "uuid": "130756538390418ea80ebe143542b01d", "short_code": "proj", "title": "Quality Assurance for Essential Climate Variables (QA4ECV)", "abstract": "The FP7 QA4ECV project was initiated in 2014 to demonstrate how reliable and traceable quality information can be provided for satellite and ground-based measurements of climate and air quality parameters. The project developed and applied a Quality Assurance framework on new and improved multi-decadal data records of the Land ECVs Albedo, Leaf Area Index (LAI), and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and on the Atmosphere ECVs nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO).\r\n\r\nQA4ECV provides multi-decadal satellite data records for 3 Land Essential Climate Variables (ECVs) and 3 Atmosphere ECV precursors." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 25978, "uuid": "f65252bf8ee5448baa1ae060cd07703a", "short_code": "coll", "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)." } ], "responsiblepartyinfo_set": [ 108616, 108618, 108622, 204993, 204994, 204995, 204996, 204997, 108617, 108619, 108620, 108621 ], "onlineresource_set": [] }, { "ob_id": 25974, "uuid": "de33ae6e5b724a41be34d0f107a65ce2", "title": "HadISDH: gridded global monthly land surface humidity data version 4.0.0.2017f", "abstract": "This is the 4.0.0.2017f version of the HadISDH land data. These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2017. \r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in either NetCDF or ASCII format.\r\n\r\nThis version extends the 3.0.0.2016p version to the end of 2017 and constitutes a major update to HadISDH due to a change to using the 1981-2010 period as its climatological reference period both to make it more consistent with other monitoring products and to maximise station coverage now that it uses the larger station database of HadISD2. Users are advised to read the update document in the docs section for full details. This version now uses the 1981-2010 period as its climatological reference period both to make it more consistent with other monitoring products and to maximise station coverage now that it uses the larger station database of HadISD2. \r\n\r\nAdditionally, there has been a small methodological change. Stations with large adjustments made during homogenisation are removed based on thresholds for q (>3g/kg), RH (>15%rh), T (>5degC) and Td (>5degC) rather than just T and Td. This results in 54 stations being removed as opposed to 29 last year. All other processing steps for HadISDH remain identical. \r\n\r\nThe new version of HadISD2 (2.0.2.2017p) has pulled through some historical changes to stations which are passed on to HadISDH. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data. \r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014. \r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more detail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-04-10T03:21:16", "updateFrequency": "notPlanned", "dataLineage": "HadISDH is a global land surface humidity dataset and is produced by the Met Office Hadley Centre in collaboration with Maynooth University, NOAA NCEI, NPL and CRU. It is based on the quality controlled sub-daily HadISD from the Met Office Hadley Centre which is in turn based on the ISD dataset from NOAA's NCEI. It is passed to the BADC for archiving and distribution.", "removedDataReason": "", "keywords": "humidity, surface, land, gridded,", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2018-04-11T14:18:04", "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": 25975, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISDH/mon/HadISDHTable/r1/v4-0-0-2017f/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 658599872, "numberOfFiles": 29, "fileFormat": "These data are provided in NetCDF and ASCII formats, descriptors of the file formats are included in Docs." }, "timePeriod": { "ob_id": 7015, "startTime": "1973-01-01T00:00:00", "endTime": "2017-12-31T23:59:59" }, "resultQuality": { "ob_id": 3043, "explanation": "Uncertainty estimates are provided as part of the dataset both at the station and gridbox level, this includes information covering station uncertainty (climatological, homogenisation and measurement uncertainty), gridbox spatial and temporal sampling uncertainty and combined station and sampling uncertainty. See dataset associated documentation for full details.", "passesTest": true, "resultTitle": "HadISDH Data Quality Statement", "date": "2016-06-14" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 13526, "uuid": "02d903686bc9471a866e6b0d7c19f727", "short_code": "comp", "title": "HadISDH.land: gridded global land surface humidity dataset produced by the Met Office Hadley Centre", "abstract": "HadISDH.land utilises simultaneous subdaily temperature and dew point temperature data from over 3000 quality controlled HadISD stations that have sufficiently long records. All humidity variables are calculated at hourly resolution and monthly means are created. \r\n\r\nMonthly means are homogenised to detect and adjust for features within the data that do not appear to be of climate origin. While unlikely to be perfect, this process does help remove large errors from the data an improve robustness of long-term climate monitoring. The NCEI's Pairwise Homogenisation Algorithm has been used directly on DPD and T. An indirect PHA method (ID PHA) is used whereby changepoints detected in DPD and T are used to make adjustments to q, e, Tw and RH. Changepoints from DPD are also applied to T. Td is derived from homogenised T and DPD. See Docs 'HadISDH.land process diagram'.\r\n\r\nStation measurement, climatological and homogeneity adjustment uncertainties are estimated for each month. Climatological averages are calculated (the climatological period is dependent on product version) and monthly mean climate anomalies obtained. These anomalies (in addition to climatological mean and standard deviation, actual values and uncertainty components) are then averaged over 5° by 5° gridboxes centred on -177.5°W and -87.5°S to 177.5°E and 87.5°N. Given the uneven distribution of stations over time and space, sampling uncertainty is estimated for each gridbox month.\r\n\r\nFor greater detail please see:\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014. \r\n\r\nand\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013.\r\n\r\nDocs contains links to both these publications" }, "procedureCompositeProcess": null, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2561, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 32, "licenceURL": "http://www.nationalarchives.gov.uk/doc/non-commercial-government-licence/version/2/", "licenceClassifications": [ { "ob_id": 6, "classification": "personal" }, { "ob_id": 4, "classification": "academic" }, { "ob_id": 5, "classification": "policy" } ] } } ], "projects": [ { "ob_id": 13164, "uuid": "ce252c81a7bd4717834055e31716b265", "short_code": "proj", "title": "Met Office Hadley Centre - Observations and Climate", "abstract": "The Met Office Hadley Centre is one of the UK's foremost climate change research centres.\r\n\r\nThe Hadley Centre produces world-class guidance on the science of climate change and provide a focus in the UK for the scientific issues associated with climate science.\r\n\r\nLargely co-funded by Department of Energy and Climate Change (DECC) and Defra (the Department for Environment, Food and Rural Affairs), the centre provides in-depth information to, and advise, the Government on climate science issues.\r\n\r\nAs one of the world's leading centres for climate science research, the Hadley Centre scientists make significant contributions to peer-reviewed literature and to a variety of climate science reports, including the Assessment Report of the IPCC. The Hadley Centre climate projections were the basis for the Stern Review on the Economics of Climate Change." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 50416, 56886, 56887, 56888, 56889, 56890, 56891, 56892, 56893, 56894, 56895, 69439, 69440, 69441, 69442, 69443, 69444, 69445, 69446, 69447, 69448, 69449 ], "vocabularyKeywords": [], "identifier_set": [ 9551 ], "observationcollection_set": [ { "ob_id": 13522, "uuid": "251474c7b09449d8b9e7aeaf1461858f", "short_code": "coll", "title": "HadISDH: global surface humidity data", "abstract": "HadISDH (Integrated Surface Database Humidity) is a monthly 5° by 5° gridded global surface humidity climate monitoring dataset created from in-situ sub-daily synoptic data. The data have been quality controlled and homogenised (land), bias adjusted (marine) and buddy checked (marine). \r\n\r\nMonthly mean climate anomalies are provided alongside uncertainty estimates, actual values, climatological means and standard deviations for specific humidity, relative humidity, vapour pressure, dew point temperature, wet bulb temperature, dew point depression in addition to the simultaneously observed temperature." } ], "responsiblepartyinfo_set": [ 108623, 108624, 108626, 108627, 108628, 108630, 108625, 108764, 108631, 108629, 168126, 108632, 168127, 168128, 108633, 108634, 108635 ], "onlineresource_set": [ 24560, 24557, 24554, 24555, 24556, 24561, 24562, 24563, 24558, 24559, 91821, 91822, 91823, 91824, 91825, 91826, 91827, 91828, 91829, 91830, 94871 ] }, { "ob_id": 25976, "uuid": "acee665e3e664a73b8ad247e99b343d5", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2017, v2.0.2.2017f", "abstract": "This is version 2.0.2.2017f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data that extends HadISD v2.0.1.2016p to include 2017 and so spans 1931-2017, it replaces the preliminary version (v2.0.2.2017p) as the ISD data for 2017 are now finalised.\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20171231_v2-0-2-2017f.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nFor a more detailed description of precipitation see: http://hadisd.blogspot.co.uk/2018/03/precipitation-in-hadisd.html\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2018-06-05T03:23:23", "updateFrequency": "notPlanned", "dataLineage": "HadISD the global sub-daily station dataset was produced by the Met Office Hadley Centre. It was derived from the Integrated Surface Dataset (ISD) from NOAA's National Climatic Data Center (NCDC). HadISD has been passed to the Centre for Environmental Data Analysis (CEDA) for archiving and distribution.", "removedDataReason": "", "keywords": "temperature, dewpoint, pressure, wind, speed, direction, cloud, precipitation", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2018-03-28T10:17:13", "doiPublishedTime": "2018-03-28T10:18:31", "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": 25977, "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISD/subdaily/HadISDTable/r1/v2-0-2-2017f", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 41328211196, "numberOfFiles": 8118, "fileFormat": "The data are NetCDF formatted.\r\n" }, "timePeriod": { "ob_id": 6980, "startTime": "1931-01-01T00:00:00", "endTime": "2017-12-31T23:59:59" }, "resultQuality": { "ob_id": 3104, "explanation": "CF-Compliant NetCDF, see documentation for quality control processes used to produce these data. These data are quality controlled by the data provider, the Met Office Hadley Centre (MOHC) and not the Centre for Environmental Data Analysis (CEDA)", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2018-02-19" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 20043, "uuid": "32eff53af32442d1a347da2cc45bb9db", "short_code": "comp", "title": "HadISD station data processing performed at the Met Office Hadley Centre", "abstract": "The HadISD station data were produced by the Met Office Hadley Centre. Individual station data within the ISD were selected selected on the basis of their length of record and reporting frequency. A merging algorithm using their location, elevation and station name identified candidates suitable to combine together. All stations were passed through a suite of automated quality control tests designed to remove bad data whilst keeping the extremes. None of the ISD flags were used in this process. The QC tests focussed on the temperature, dewpoint temperature and sea-level pressure variables, although some were applied to the wind speed and direction and cloud data. The data files also contain other variables which were pulled through from the raw ISD record, but have had no QC applied (e.g. cloud base and precipitation depth). \r\n\r\nNotes:\r\n1. These data have not yet been homogenised and so trend fitting should be undertaken with caution. The homogeneity has been assessed and results are available from the Met Office Hadley Centre HadISD website: http://www.metoffice.gov.uk/hadobs/hadisd/. \r\n2. A long-standing bug (affecting versions v2.0.2_2017p through to v3.3.0.2022f), was discovered in autumn 2023 whereby the neighbour checks (and associated [un]flagging for some other tests) were not being implemented. This was corrected for the later version v3.4.0.2023f to HadISD. For more details see the posts on the HadISD blog: https://hadisd.blogspot.com/2023/10/bug-in-buddy-checks.html & https://hadisd.blogspot.com/2024/01/hadisd-v3402023f-future-look.html(v2.0.2_2017p through to v3.3.0.2022f), and as noted this has been fixed for v3.4.02023f.\r\n\r\n\r\nFor further details see: \r\nDunn, R. J. H., et al., (2016), Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geoscientific Instrumentation, Methods and Data Systems, and Dunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations\r\nfrom 1973-2011, Climate of the Past.\r\nDunn, R. J. H., et al. (2014), Pairwise Homogeneity Assessment of HadISD, Climate of the Past, 10, 1501-1522 (see Docs for links to publications)." }, "procedureCompositeProcess": null, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2561, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 32, "licenceURL": "http://www.nationalarchives.gov.uk/doc/non-commercial-government-licence/version/2/", "licenceClassifications": [ { "ob_id": 6, "classification": "personal" }, { "ob_id": 4, "classification": "academic" }, { "ob_id": 5, "classification": "policy" } ] } } ], "projects": [ { "ob_id": 13164, "uuid": "ce252c81a7bd4717834055e31716b265", "short_code": "proj", "title": "Met Office Hadley Centre - Observations and Climate", "abstract": "The Met Office Hadley Centre is one of the UK's foremost climate change research centres.\r\n\r\nThe Hadley Centre produces world-class guidance on the science of climate change and provide a focus in the UK for the scientific issues associated with climate science.\r\n\r\nLargely co-funded by Department of Energy and Climate Change (DECC) and Defra (the Department for Environment, Food and Rural Affairs), the centre provides in-depth information to, and advise, the Government on climate science issues.\r\n\r\nAs one of the world's leading centres for climate science research, the Hadley Centre scientists make significant contributions to peer-reviewed literature and to a variety of climate science reports, including the Assessment Report of the IPCC. The Hadley Centre climate projections were the basis for the Stern Review on the Economics of Climate Change." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 54776, 54777, 54778, 54779, 54780, 54781, 54782, 54783, 54784, 54785, 54786, 54787, 54788, 54789, 54790, 54793, 54794, 54795, 61314, 71791, 71792 ], "vocabularyKeywords": [], "identifier_set": [ 9536 ], "observationcollection_set": [ { "ob_id": 13521, "uuid": "f579035b3c954475922e4b13705a7669", "short_code": "coll", "title": "HadISD: global sub-daily station data for climate extremes", "abstract": "HadISD is a station based dataset comprising 6103 stations covering 1973-present. These stations are a subset of the stations available in the Integrated Surface Database (ISD), and are ones selected to be those most useful for climate studies (long records and high reporting frequency). Individual stations within the ISD were composited when it was appropriate to do so to improve the coverage.\r\n \r\nHadISD is a multi-variate dataset, where the following fields are available: temperature, dewpoint temperature, sea-level pressure, wind speed, wind direction and cloud data (total, low, mid and high levels). These variables are all quality controlled using an automatic suite of tests, the code for which is available on request. The QC tests were designed to remove bad data whilst keeping true extremes. A number of other variables are also carried through to the final NetCDF files, but have not been quality controlled (e.g. precipitation period, precipitation depth, sunshine duration)." } ], "responsiblepartyinfo_set": [ 108638, 108639, 108640, 108642, 108643, 108637, 108636, 108754, 108644, 108641, 108645, 168123, 168124, 168125 ], "onlineresource_set": [ 24564, 24565, 24566, 24567, 24581, 24568, 24569, 24570, 24571, 91831, 91832, 91833, 91834, 91835 ] }, { "ob_id": 25979, "uuid": "0af02f899ac14c218706295d3c6d1c4d", "title": "Arctic Cloud Summer Expedition (ACSE): surface meteorology and radiation measurements from the Stockholm University's automatic weather station on board Icebreaker Oden", "abstract": "This dataset contains surface meteorological measurements including air temperature, relative humidity, surface irradiation and wind measurements from the Meteorologiska Institutionen Stockholms Universitet (MISU) weather station on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThese data came from an automatic weather station installed on the 7th deck of the Icebreaker Oden, approximately 25m above the surface, measuring at 1 Hz frequency. The system was operated by Joe Sedlar who also undertook data quality control and there are several flag variables for T/RH and radiation measurements documenting known data issues - notably when primary measurements have been replaced with those from other sensors, or corrections applied. This version of the dataset was then prepared for archiving with the Centre for Environmental Data Analysis by Ian Brooks, University of Leeds.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. 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Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF).\r\n\r\nSWERUS-C3 was initiated as a Knut and Alice Wallenberg funded research project. The project was developed into a multi-disciplinary international research program focused on investigating the historical functioning of the Climate-Cryosphere-Carbon (C3) system of the East Siberian Arctic Ocean." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 54754, 60870, 60871, 62767, 80008, 80012, 80013, 80018, 80023, 80024, 87078, 87079, 87080, 87081, 87082, 87083, 87084, 87085, 87086, 87087, 87088, 87089, 87090, 87091, 87092, 87093, 87094, 87095, 87096 ], "vocabularyKeywords": [], "identifier_set": [ 10096 ], "observationcollection_set": [ { "ob_id": 25948, "uuid": "e75e1e57932d4b95831fa7b56a2016e1", "short_code": "coll", "title": "Arctic Cloud Summer Expedition (ACSE): surface and boundary layer meteorological measurements on board the Icebreaker Oden", "abstract": "This dataset collection contains a number of observational datasets (mainly from the NERC funded contribution, but others too) of surface and boundary layer meteorological measurements collected on board the Icebreaker Oden during its voyage for the Arctic Cloud Summer Expedition (ACSE).\r\n\r\nACSE was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES (the Cooperative Institute for Research In Environmental Sciences). 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The filters were then analysed for metals using X-ray fluorescence (XRF) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS), and for ion species using Ion Chromatography. Quartz filters were collected by Tisch high vol, samplers and then were analysed for organic and elemental carbons using the DRI Model 2015 Multiwavelength Thermal/Optical Carbon Analyser, and organic tracers using Gas chromatography–mass spectrometry (GC-MS).", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-03-27T15:52:35.514388", "updateFrequency": "", "dataLineage": "Data produced by Atmospheric Pollution & Human Health (APHH) project participants at University of Birmingham and uploaded to Centre for Environmental Data Anaylsis (CEDA) archive.", "removedDataReason": "", "keywords": "PM2.5, China, pollution, APHH", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2018-03-29T10:59:55", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1856, "bboxName": "IAP-Beijing", "eastBoundLongitude": 116.371, "westBoundLongitude": 116.371, "southBoundLatitude": 39.974, "northBoundLatitude": 39.974 }, "verticalExtent": null, "result_field": { "ob_id": 26001, "dataPath": "/badc/aphh/data/beijing/birm-filters", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 12841, "numberOfFiles": 2, "fileFormat": "Data NASA Ames formatted" }, "timePeriod": { "ob_id": 7016, "startTime": "2016-11-09T00:00:00", "endTime": "2016-12-11T23:59:59" }, "resultQuality": { "ob_id": 3122, "explanation": "Data is 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": "2018-03-29" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 25985, "uuid": "822bf0f5f870461eb668a5650e0611df", "short_code": "acq", "title": "APHH: Chemical composition measurements in PM2.5 made at the IAP-Beijing site during the summer and winter campaigns", "abstract": "APHH: Chemical composition measurements in PM2.5 made at the IAP-Beijing site during the summer and winter 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." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 56833 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 24817, "uuid": "648246d2bdc7460b8159a8f9daee7844", "short_code": "coll", "title": "APHH: Atmospheric measurements and model results for the Atmospheric Pollution & Human Health in a Chinese Megacity", "abstract": "The Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) Programme includes several projects making groundbased observations of meteorology, atmospheric chemical species and particulates in and around the city of Beijing. Due to the close working and exchange between the projects and overlap of instruments, this dataset collection contains measurements and related modelling study output produced by all these projects." } ], "responsiblepartyinfo_set": [ 108676, 108677, 108678, 108684, 108680, 108681, 108682, 108679, 108683 ], "onlineresource_set": [] }, { "ob_id": 25996, "uuid": "ce693b9c237d4e8cb7968ef76dfc9584", "title": "Arctic Cloud Summer Expedition (ACSE): composite lidar wind profile data from the NCAS AMF Halo Doppler lidar on board Icebreaker Oden", "abstract": "This dataset contains composite lidar wind profile data from the NCAS AMF Halo Doppler lidar mounted on a motion stabilised platform on board the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. 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ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." } ], "responsiblepartyinfo_set": [ 108708, 108709, 108711, 108712, 108713, 108714, 108715, 108710, 108716, 109266, 108717, 109267 ], "onlineresource_set": [ 25753, 25754, 91685, 91686, 91687, 91688, 91689, 91690, 91691, 91692, 91693, 91694, 91695, 91696, 91697, 91698, 91699, 91700 ] }, { "ob_id": 26002, "uuid": "4c2aaf6a80864d70b105e62e3ddbe797", "title": "APHH: Particle number size distribution measurements made at the IAP-Beijing site during the summer campaign", "abstract": "This dataset contains particle number size distribution (PNSD) measurements made at the Institute of Atmospheric Physics land station, Beijing (IAP-Beijing) site during the summer APHH-Beijing campaign for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. A University of Birmingham Particle Size Magnifier (PSM) and 2 Scanning Mobility Particle Size Spectrometer (SMPS) systems were deployed to measure PNSD from 1.5 to 615 nm.\r\n\r\nThis dataset contains two files. The number file shows the concentration of particles in each size bin, whilst the dN/dlogDp file shows the data as a lognormal function of diameter.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T03:13:54", "updateFrequency": "", "dataLineage": "Data produced by Atmospheric Pollution & Human Health (APHH) project participants at University of Birmingham and uploaded to Centre for Environmental Data Anaylsis (CEDA) archive", "removedDataReason": "", "keywords": "Particle number size, China, pollution, APHH", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2018-03-29T10:50:20", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1856, "bboxName": "IAP-Beijing", "eastBoundLongitude": 116.371, "westBoundLongitude": 116.371, "southBoundLatitude": 39.974, "northBoundLatitude": 39.974 }, "verticalExtent": null, "result_field": { "ob_id": 26006, "dataPath": "/badc/aphh/data/beijing/birm-smps", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 12607588, "numberOfFiles": 3, "fileFormat": "Data are NASA Ames formatted" }, "timePeriod": { "ob_id": 7020, "startTime": "2017-05-21T23:00:00", "endTime": "2017-06-26T22:59:59" }, "resultQuality": { "ob_id": 3119, "explanation": "Research data as provided by project team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2018-03-27" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26004, "uuid": "714a28a6b76349d490aa8da699cab3ad", "short_code": "acq", "title": "APHH: Particle number size distribution measurements at the IAP-Beijing site during the summer and winter campaigns", "abstract": "APHH: Particle number size distribution measurements at the IAP-Beijing site during the summer and winter 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." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 52353 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 24817, "uuid": "648246d2bdc7460b8159a8f9daee7844", "short_code": "coll", "title": "APHH: Atmospheric measurements and model results for the Atmospheric Pollution & Human Health in a Chinese Megacity", "abstract": "The Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) Programme includes several projects making groundbased observations of meteorology, atmospheric chemical species and particulates in and around the city of Beijing. Due to the close working and exchange between the projects and overlap of instruments, this dataset collection contains measurements and related modelling study output produced by all these projects." } ], "responsiblepartyinfo_set": [ 108736, 108737, 108739, 108740, 108741, 108742, 108743, 108744, 108738, 108751 ], "onlineresource_set": [] }, { "ob_id": 26007, "uuid": "61cd9961ecef43edadae89f842598f47", "title": "Arctic Cloud Summer Expedition (ACSE): composite temperature, humidity and wind profiles and derived variables from the NCAS AMF radiosondes launched from Icebreaker Oden", "abstract": "This dataset contains composite temperature, humidity and wind profiles, plus derived products, from the National Centre for Atmospheric Science's Atmospheric Measurement Facility (NCAS AMF) radiosondes launched from the Swedish Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThese data consist of individual radiosonde profiles as 2D time/height fields, with all profiles interpolated onto a fixed vertical grid for ease of analysis/plotting across the outward (leg 1) and return (leg 2) parts of the expedition.\r\n\r\nThe vertical grid used is: 1m step to 5km, 10m step between 5 and 12 km, 50m step between 12 and 20 km. The data also includes derived variables (potential temperature etc).\r\n\r\nBarbara Brooks (NCAS AMF) was responsible for the radiosonde ascents during the voyage and for the original data, whilst Ian Brookes prepared these data for archiving.\r\n\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-03-27T10:29:00.097164", "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": "temperature, humidity, winds, profiles", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "final", "dataPublishedTime": "2018-04-14T12:55:24", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2195, "bboxName": "ACSE voyage bounding box", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": 69.66, "northBoundLatitude": 85.23 }, "verticalExtent": null, "result_field": { "ob_id": 26008, "dataPath": "/badc/acse/data/ncas-radiosonde-2_composites/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 71005182, "numberOfFiles": 3, "fileFormat": "Data are CF-compliant NetCDF formatted." }, "timePeriod": { "ob_id": 7021, "startTime": "2014-07-06T10:25:27", "endTime": "2014-10-01T10:32:33" }, "resultQuality": { "ob_id": 3193, "explanation": "Data quality were checked by the ACSE project data author before supplying to CEDA. 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ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF).\r\n\r\nSWERUS-C3 was initiated as a Knut and Alice Wallenberg funded research project. The project was developed into a multi-disciplinary international research program focused on investigating the historical functioning of the Climate-Cryosphere-Carbon (C3) system of the East Siberian Arctic Ocean." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 4385, 54744, 54745, 54746, 54747, 54748, 54749, 54750, 54751, 54752, 54753, 54754, 54755, 54756, 54757, 54758, 54759 ], "vocabularyKeywords": [], "identifier_set": [ 10094 ], "observationcollection_set": [ { "ob_id": 25948, "uuid": "e75e1e57932d4b95831fa7b56a2016e1", "short_code": "coll", "title": "Arctic Cloud Summer Expedition (ACSE): surface and boundary layer meteorological measurements on board the Icebreaker Oden", "abstract": "This dataset collection contains a number of observational datasets (mainly from the NERC funded contribution, but others too) of surface and boundary layer meteorological measurements collected on board the Icebreaker Oden during its voyage for the Arctic Cloud Summer Expedition (ACSE).\r\n\r\nACSE was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES (the Cooperative Institute for Research In Environmental Sciences). ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." } ], "responsiblepartyinfo_set": [ 108773, 108766, 108767, 108770, 108769, 108771, 108772, 108768, 108774, 109270, 108775 ], "onlineresource_set": [ 91701, 25747, 25748, 91702, 91703, 91704, 91705, 91706, 91707, 91708, 91709, 91710, 91711, 91712, 91713, 91714 ] }, { "ob_id": 26010, "uuid": "d23f1cdf560f4ae185d1e008d1eef4b7", "title": "Arctic Cloud Summer Expedition (ACSE): SPRS Icebreaker Oden ship navigation data", "abstract": "This dataset contains ship navigation data, including speed over group, course, heading etc, fomr the Swedish Polar Research Secretariat's (SPRS) Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThese data are provided as supportive data for use with the other datasets within this collection, helping to account for ship movement during the expedition for later data analysis. These data were prepared for archiving as NetCDF data at the Centre for Environmental Data Analysis (CEDA) by Ian Brooks, University of Leeds.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T03:12:10", "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": "ship position, speed, course, winds", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "final", "dataPublishedTime": "2018-04-14T12:57:17", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2195, "bboxName": "ACSE voyage bounding box", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": 69.66, "northBoundLatitude": 85.23 }, "verticalExtent": null, "result_field": { "ob_id": 26011, "dataPath": "/badc/acse/data/sprs-oden-shipnav/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 134975964, "numberOfFiles": 2, "fileFormat": "Data are CF-compliant NetCDF formatted" }, "timePeriod": { "ob_id": 7021, "startTime": "2014-07-06T10:25:27", "endTime": "2014-10-01T10:32:33" }, "resultQuality": { "ob_id": 3193, "explanation": "Data quality were checked by the ACSE project data author before supplying to CEDA. 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The project was developed into a multi-disciplinary international research program focused on investigating the historical functioning of the Climate-Cryosphere-Carbon (C3) system of the East Siberian Arctic Ocean." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 4385, 54754, 59041, 59042, 62025, 62026, 62027, 62028, 62029, 62030, 62031 ], "vocabularyKeywords": [], "identifier_set": [ 10095 ], "observationcollection_set": [ { "ob_id": 25948, "uuid": "e75e1e57932d4b95831fa7b56a2016e1", "short_code": "coll", "title": "Arctic Cloud Summer Expedition (ACSE): surface and boundary layer meteorological measurements on board the Icebreaker Oden", "abstract": "This dataset collection contains a number of observational datasets (mainly from the NERC funded contribution, but others too) of surface and boundary layer meteorological measurements collected on board the Icebreaker Oden during its voyage for the Arctic Cloud Summer Expedition (ACSE).\r\n\r\nACSE was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES (the Cooperative Institute for Research In Environmental Sciences). 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Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." } ], "responsiblepartyinfo_set": [ 108782, 108779, 108781, 108783, 108784, 108785, 108786, 108780, 108787, 109271 ], "onlineresource_set": [ 25745, 25746, 91547, 91548, 91549, 91550, 91551, 91552, 91553, 91554, 91555, 91556, 91557, 91558, 91559, 91560 ] }, { "ob_id": 26016, "uuid": "9b204cb345994797b9197744d0ef619c", "title": "UKCP18 Future Simulations of Gridded Sea Surface Elevation around the UK for 2007-2100", "abstract": "The data are simulated instantaneous sea surface elevations above time-mean sea level due to tides alone (tideAnom) and due to tide and meteorological surge (tideSurgeAnom). The data were produced by the Met Office Hadley Centre, using data made available by the Swedish Meteorological and Hydrological Institute (SMHI) and the Climate Model Intercomparison Project, phase 5 (CMIP5). The data were produced to investigate the impact of simulated atmospheric storminess change on extreme sea levels. To produce the data, atmospheric winds and pressure from the SMHI Regional Atmospheric Model RCA4 was used to drive the CS3 continental shelf model. The data are the resulting simulated sea surface elevations. Five CMIP5 RCP8.5 simulations were downscaled in this way: EC-EARTH, HadGEM2-ES, MPI-ESM-LR, IPSL-CM5A-MR, CNRM-CM5. The data covers the period 2007 to 2099, and applies to the UK coast.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2024-03-09T03:08:07", "updateFrequency": "asNeeded", "dataLineage": "Data provided by the UK Met Office", "removedDataReason": "", "keywords": "UKCP18, Marine, Tide Surge, Projections, RCP8.5", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2209, "bboxName": "", "eastBoundLongitude": 1.75, "westBoundLongitude": -10.58, "southBoundLatitude": 49.17, "northBoundLatitude": 60.83 }, "verticalExtent": null, "result_field": { "ob_id": 26146, "dataPath": "/badc/ukcp18/data/marine-sim/bulk-proj/rcp85", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 390557078739, "numberOfFiles": 559, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 7058, "startTime": "2007-01-01T00:00:00", "endTime": "2099-12-30T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26147, "uuid": "9032579f10874f809874165cca38bde5", "short_code": "comp", "title": "UKCP18 Future Simulations of Gridded Sea Surface Elevation in UK Waters", "abstract": "The future sea surface elevation simulations for UK waters are driven with data from five CMIP5 models: \nEC-EARTH, HadGEM2-ES, MPI-ESM-LR, IPSL-CM5A-MR, CNRM-CM5,\nThe driving models were themselves forced with the high forcing CMIP5 scenario RCP8.5." }, "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": [ 50512, 56584, 56585, 56586 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26018, "uuid": "5fcae68057ea43259d0a4530d34e4ba5", "short_code": "coll", "title": "UKCP18 Simulations of Sea Surface Elevation for UK Waters", "abstract": "Historical and future simulations of sea surface elevation for UK waters for 1970-2100 produced by the Met Office for UK Climate Projections 2018 (UKCP2018). The data is available at hourly temporal resolution." } ], "responsiblepartyinfo_set": [ 110955, 111102, 111103, 111104, 111106, 111108, 111105, 193359, 111107 ], "onlineresource_set": [ 25957, 27345, 94588 ] }, { "ob_id": 26017, "uuid": "610a8d5b32fc4c51b8a2ed64de95ed73", "title": "UKCP18 Historical Simulations of Gridded Sea Surface Elevation around the UK for 1970-2006", "abstract": "\"The data are simulated instantaneous sea surface elevations above time-mean sea level due to tides alone (tideAnom) and due to tide and meteorological surge (tideSurgeAnom). The data were produced by the Met Office Hadley Centre, using data made available by the Swedish Meteorological and Hydrological Institute (SMHI) and the Climate Model Intercomparison Project, phase 5 (CMIP5). The data were produced to investigate the impact of simulated atmospheric storminess change on extreme sea levels. To produce the data, atmospheric winds and pressure from the SMHI Regional Atmospheric Model RCA4 was used to drive the CS3 continental shelf model. The data are the resulting simulated sea surface elevations. Five CMIP5 historical simulations were downscaled in this way: EC-EARTH, HadGEM2-ES, MPI-ESM-LR, IPSL-CM5A-MR, CNRM-CM5. The data covers the period 1970 to 2005, and applies to the UK coast.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2018-11-21T15:08:17", "updateFrequency": "asNeeded", "dataLineage": "Data provided by the UK Met Office", "removedDataReason": "", "keywords": "UKCP18, Marine, Tide Surge, Historical, Simulations", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2208, "bboxName": "", "eastBoundLongitude": 1.75, "westBoundLongitude": -10.58, "southBoundLatitude": 49.17, "northBoundLatitude": 60.83 }, "verticalExtent": null, "result_field": { "ob_id": 26144, "dataPath": "/badc/ukcp18/data/marine-sim/bulk-proj/historical", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 146983849105, "numberOfFiles": 211, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 7057, "startTime": "1969-12-31T23:00:00", "endTime": "2006-12-30T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26145, "uuid": "c53f486d8034465ca923104d81933db3", "short_code": "comp", "title": "UKCP18 Historical Simulations of Gridded Sea Surface Elevation in UK Waters", "abstract": "The historical sea surface elevation simulations for UK waters are driven with data from five CMIP5 models: \nEC-EARTH, HadGEM2-ES, MPI-ESM-LR, IPSL-CM5A-MR, CNRM-CM5,\nThe driving models were themselves forced with the historical CMIP5 forcings." }, "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": [ 50512, 56584, 56585, 56586 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26018, "uuid": "5fcae68057ea43259d0a4530d34e4ba5", "short_code": "coll", "title": "UKCP18 Simulations of Sea Surface Elevation for UK Waters", "abstract": "Historical and future simulations of sea surface elevation for UK waters for 1970-2100 produced by the Met Office for UK Climate Projections 2018 (UKCP2018). The data is available at hourly temporal resolution." } ], "responsiblepartyinfo_set": [ 110954, 111095, 111096, 111097, 111099, 111101, 111098, 143632, 111100 ], "onlineresource_set": [ 25956, 27337, 94587 ] }, { "ob_id": 26019, "uuid": "58c393f773504caaad48cdb6310e17b2", "title": "UKCP18 Short Event Case Studies of Historical and Future Sea Surface Elevation around the UK", "abstract": "The data are simulated instantaneous sea surface elevations above time-mean sea level due to tides alone (tideAnom) and due to tide and meteorological surge (tideSurgeAnom). The data were produced by the Met Office Hadley Centre, using data made available by the Swedish Meteorological and Hydrological Institute (SMHI) and the Climate Model Intercomparison Project, phase 5 (CMIP5). The data were produced to investigate the impact of simulated atmospheric storminess change on extreme sea levels. To produce the data, atmospheric winds and pressure from the SMHI Regional Atmospheric Model RCA4 was used to drive the CS3 continental shelf model. The data are the resulting simulated sea surface elevations. Five CMIP5 RCP8.5 simulations were downscaled in this way: EC-EARTH, HadGEM2-ES, MPI-ESM-LR, IPSL-CM5A-MR, CNRM-CM5. The data covers the period 2007 to 2099, and applies to the UK coast.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2018-11-21T16:12:32", "updateFrequency": "asNeeded", "dataLineage": "Data provided by the UK Met Office", "removedDataReason": "", "keywords": "UKCP18, Marine, Tide Surge, Historical, Projections, Case Studies", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2210, "bboxName": "", "eastBoundLongitude": 1.75, "westBoundLongitude": -10.58, "southBoundLatitude": 49.17, "northBoundLatitude": 60.83 }, "verticalExtent": null, "result_field": { "ob_id": 26148, "dataPath": "/badc/ukcp18/data/marine-sim/event-proj", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 4519981012, "numberOfFiles": 7, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 7024, "startTime": "1969-12-31T23:00:00", "endTime": "2100-01-01T00:00:00" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26149, "uuid": "4e1ad382198b4c4d84c512385d7a4e81", "short_code": "comp", "title": "UKCP18 Short Event Case Studies of Historical and Future Sea Surface Elevation Around the UK", "abstract": "The POLCS3 storm surge model was used to produce a simulation of three historical storm surge events, with the mean sea level artificially increased by zero, 0.5, 1, 2,or 3 metres. The data show the sea surface elevation (tide-only and tide-plus-surge) relative to the imposed mean sea level." }, "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": [ 56584, 56585, 56586, 56763, 62353, 83093 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26160, "uuid": "0dc7d552eb674036800670241fa31dcf", "short_code": "coll", "title": "UKCP18 High Temporal Resolution Short-term Events for Marine Case Studies", "abstract": "Short event case studies for UK waters produced by the Met Office for UK Climate Projections 2018 (UKCP2018). Data is available at 6-minute and 15-minute temporal resolution." } ], "responsiblepartyinfo_set": [ 110956, 111109, 111110, 111111, 111113, 111115, 111112, 143635, 111114 ], "onlineresource_set": [ 25958, 27327, 94589 ] }, { "ob_id": 26020, "uuid": "e5297a0c0329426380d4cd6e58c48f45", "title": "UKCP18 Simulated Impact of Mean Sea Level Change on Tidal Characteristics around the UK", "abstract": "The data are simulated instantaneous sea surface elevations above time-mean sea level due to tides alone. The data were produced by the Met Office Hadley Centre. The data were produced to investigate the impact of simulated mean sea level increase on UK coastal tides. To produce the data, the CS3 continental shelf model was used to simulate the tides under various different amounts of mean sea level increase (simulated by simply increasing the bathymetry). The data are the resulting simulated sea surface elevations above the mean sea level. The data covers a period of about 28 days (one spring-neap cycle), and applies to the UK coast.\r\n\r\nThere are several caveats which should be noted when using the ‘UKCP18 Simulated Impact of Mean Sea Level Change on Tidal Characteristics around the UK’ dataset:\r\n1.\tThe spin-up period has been included in the data. It takes about 48 hours to spin up to a realistic tide so users should remove the first 48 hours of data, or conduct their own analysis to assess how much spin-up time to remove, in order to get a realistic representation of the tide.\r\n2.\tA land-sea mask has not been applied to the data so users should take care to ensure they are only using data from sea locations.\r\n3.\tThere is a rim of zeros around the edge of the data which should be ignored.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2018-11-21T16:13:30", "updateFrequency": "asNeeded", "dataLineage": "Data provided by the UK Met Office", "removedDataReason": "", "keywords": "UKCP18, Marine, Tide Surge, Historical, Projections, Case Studies", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2211, "bboxName": "", "eastBoundLongitude": 1.75, "westBoundLongitude": -10.58, "southBoundLatitude": 49.17, "northBoundLatitude": 60.83 }, "verticalExtent": null, "result_field": { "ob_id": 26150, "dataPath": "/badc/ukcp18/data/marine-sim/tide-proj", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 5389618282, "numberOfFiles": 22, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 7024, "startTime": "1969-12-31T23:00:00", "endTime": "2100-01-01T00:00:00" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26151, "uuid": "31bd70cdd7fa4083ab41237c7ec87460", "short_code": "comp", "title": "UKCP18 Simulated Impact of Mean Sea Level Change on Tidal Characteristics Around the UK", "abstract": "The POLCS3 storm surge model was used to produce a simulation of the tides around the UK with mean sea level artificially increased by zero, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 3, 4.5, 5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5 or 10 metres. The data show the sea surface elevation relative to the imposed mean sea level. No atmospheric forcing is included: the simulation is tide only (no storm surge)." }, "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": [ 51186, 51187, 56586, 56763, 62353 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26160, "uuid": "0dc7d552eb674036800670241fa31dcf", "short_code": "coll", "title": "UKCP18 High Temporal Resolution Short-term Events for Marine Case Studies", "abstract": "Short event case studies for UK waters produced by the Met Office for UK Climate Projections 2018 (UKCP2018). Data is available at 6-minute and 15-minute temporal resolution." } ], "responsiblepartyinfo_set": [ 110957, 111116, 111117, 111118, 111120, 111122, 111119, 143648, 111121 ], "onlineresource_set": [ 25959, 27347, 95107 ] }, { "ob_id": 26021, "uuid": "da84490d169246d381f59bccdfd143f1", "title": "Arctic Cloud Summer Expedition (ACSE): composite ship motion data for Icebreaker Oden from on board ship navigation data and University of Leeds' XSens motion sensor package.", "abstract": "This dataset contains combined measurements of platform motion and final velocity and attitude corrections for turbulence measurements on the foremast of Icebreaker Oden utilising data from the ship's navigation unit alongside data from the University of Leeds' XSens motion and heading sensory package. These data include ship speed over group, course, heading etc, for Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThe XSens motion pack was mounted at the base of the sonic anemometer, in the same reference frame (rotated 30 deg to port from bow). Rotation angles given in the dataset are with respect to the earth frame, with x-axis positive to east. \r\n\r\nCorrections combine high rate data from the Xsens package with low rate data from the ship navigation system (heading and speed) to derive the full earth-relative platform motion at 20Hz. The motion calculation follows Edson et al. (1988) and Prytherch et al. (2015) - see linked documentation.\r\n\r\nThese data are provided as supportive data for use with the other datasets within this collection, helping to account for ship movement during the expedition for later data analysis. These data were prepared for archiving as NetCDF data at the Centre for Environmental Data Analysis (CEDA) by Ian Brooks, University of Leeds.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T03:20:42", "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": "ship position, speed, course, winds", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "final", "dataPublishedTime": "2018-04-14T12:14:48", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2195, "bboxName": "ACSE voyage bounding box", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": 69.66, "northBoundLatitude": 85.23 }, "verticalExtent": null, "result_field": { "ob_id": 26022, "dataPath": "/badc/acse/data/composite-shipmotion", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 7582196718, "numberOfFiles": 1836, "fileFormat": "Data are CF-compliant NetCDF formatted." }, "timePeriod": { "ob_id": 7025, "startTime": "2014-07-10T13:02:00", "endTime": "2014-10-02T22:57:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26023, "uuid": "9d2dbd64aff542e0b412f628b91ee316", "short_code": "acq", "title": "ACSE: ship motion of Icebreaker Oden", "abstract": "ACSE: ship motion of Icebreaker Oden from on board ship nav and Leeds XSens package" }, "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": 24932, "uuid": "f4d0cf8f90d240c8bc9556ca4ee075d2", "short_code": "proj", "title": "Arctic Cloud Summer Expedition (ACSE)", "abstract": "The Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES (the Cooperative Institute for Research In Environmental Sciences). ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF).\r\n\r\nSWERUS-C3 was initiated as a Knut and Alice Wallenberg funded research project. The project was developed into a multi-disciplinary international research program focused on investigating the historical functioning of the Climate-Cryosphere-Carbon (C3) system of the East Siberian Arctic Ocean." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 4385, 54754, 56471, 56472, 56473, 56474, 56475, 56476 ], "vocabularyKeywords": [], "identifier_set": [ 10088 ], "observationcollection_set": [ { "ob_id": 25948, "uuid": "e75e1e57932d4b95831fa7b56a2016e1", "short_code": "coll", "title": "Arctic Cloud Summer Expedition (ACSE): surface and boundary layer meteorological measurements on board the Icebreaker Oden", "abstract": "This dataset collection contains a number of observational datasets (mainly from the NERC funded contribution, but others too) of surface and boundary layer meteorological measurements collected on board the Icebreaker Oden during its voyage for the Arctic Cloud Summer Expedition (ACSE).\r\n\r\nACSE was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES (the Cooperative Institute for Research In Environmental Sciences). ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." } ], "responsiblepartyinfo_set": [ 108818, 108819, 108821, 108822, 108823, 108824, 108825, 108820, 108826, 109260 ], "onlineresource_set": [ 25735, 25736, 25760, 25761, 91800, 91801, 91802, 91803, 91804, 91805, 91806, 91807, 91808, 91809, 91810, 91811 ] }, { "ob_id": 26024, "uuid": "e58fdade3a6c46bbaae7c53e948dd6d0", "title": "Arctic Cloud Summer Expedition (ACSE): composite flux data for Icebreaker Oden", "abstract": "This dataset contains provides the final best estimates of fluxes, mean environmental variables and derived transfer coefficient estimates, along with asociated quality control flags, during the Icebreaker Oden voyage durning the Arctic Cloud Summer Expedition (ACSE) in summer 2014. These were calculated based on instrumentation data from the University of Leeds' Metek sonic anemometer, Licor LI-7500 gas analyzer and XSENS MTi-G-700 motion pack, plus mean surface meteorology data provided from the automatic weather station operated on board by the Department of Meteorology, Stockholm University (MISU).\r\n\r\nOther data from the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.\r\n\r\nThe document \"ACSE_turbulent_fluxes_readme.txt\" in the archive contains fuller details of the flux calculations. The final data, prepared for archiving as NetCDF data at the Centre for Environmental Data Analysis (CEDA) by Ian Brooks, University of Leeds, contain:\r\n\r\n1) The final quality controlled best estimates of 20-min averaged dynamic fluxes, associated mean environmental variables (10m wind, etc), transfer coefficients, and quality control flags.\r\n\r\n2) The raw kinematic fluxes, etc that go into generating (1), along with the quality control variables used in generating the QC flags, and the QC flags.\r\n\r\n3) Other environmental variables (in some cases with duplicates from multiple different sensors) averaged onto the same time base as the flux estimates.\r\n\r\nThe authors note that in all cases a lot of work has been done on quality control and applying suitable corrections to raw measurements. In many cases other choices could have been made, and additional QC measures may need to be applied.\r\n\r\nMost of the work on the flux data processing has been done by John Prytherch, with additional input from Ian Brooks and Dominic Salisbury. Additional work on ancillary data was undertaken by other members of the ACSE science team.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-03-22T15:23:31.706987", "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": "turbulent fluxes, meteorology, winds, wind speed", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "final", "dataPublishedTime": "2018-04-14T12:59:34", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2195, "bboxName": "ACSE voyage bounding box", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": 69.66, "northBoundLatitude": 85.23 }, "verticalExtent": null, "result_field": { "ob_id": 26025, "dataPath": "/badc/acse/data/composite-flux-data", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 4462682, "numberOfFiles": 3, "fileFormat": "Data are CF-compliant NetCDF formatted" }, "timePeriod": { "ob_id": 7026, "startTime": "2014-07-10T13:11:59", "endTime": "2014-10-02T22:48:00" }, "resultQuality": { "ob_id": 3123, "explanation": "Data quality control flagging follows the methodology described in: - Foken et al. 2012, Ch4 of 'Eddy Covariance: A Practical Guide to Measurement and Data Analysis', ed. M. Aubinet, T. Vesala, D. Papale; Springer. - Wichura and Foken 1995; Foken and Wichura 1996; and Vickers and Mahrt 1997. Some of the code implementing these was adapted from the EDDY CALC suite: http://www.swissfluxnet.ch/eddycalc/html/Eddycalc_LI7200.html", "passesTest": true, "resultTitle": "ACSE final fluxes Data Quality Statement", "date": "2018-04-04" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26023, "uuid": "9d2dbd64aff542e0b412f628b91ee316", "short_code": "acq", "title": "ACSE: ship motion of Icebreaker Oden", "abstract": "ACSE: ship motion of Icebreaker Oden from on board ship nav and Leeds XSens package" }, "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": 24932, "uuid": "f4d0cf8f90d240c8bc9556ca4ee075d2", "short_code": "proj", "title": "Arctic Cloud Summer Expedition (ACSE)", "abstract": "The Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES (the Cooperative Institute for Research In Environmental Sciences). ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF).\r\n\r\nSWERUS-C3 was initiated as a Knut and Alice Wallenberg funded research project. The project was developed into a multi-disciplinary international research program focused on investigating the historical functioning of the Climate-Cryosphere-Carbon (C3) system of the East Siberian Arctic Ocean." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 4385, 24616, 24654, 54754, 56483, 56484, 56485, 56486, 56487, 56488, 56489, 56490, 56491, 56492, 56493, 56494, 56495, 56497, 56498, 56499, 56500, 56501, 56502, 56503, 56504, 56505, 56506, 56507, 56508, 56509, 56510, 56511, 56512, 56513, 56514, 56515, 56516, 56517, 56518, 56519, 56520, 56521, 56522, 56523, 56524, 56525, 56526, 56527, 56528, 56529, 56530, 56531, 56532, 56533, 56534, 56535, 56536, 56537, 56538, 56539, 56540, 56541, 56542, 56543, 56544, 56545, 56546, 56547, 56548, 56549, 56550, 56551, 56552, 56553, 56554, 56555, 56556, 56557, 56558, 56559, 56560, 56561, 56562, 56563, 56564, 56565, 56566, 56567, 56568, 56569, 56570, 56571, 56572, 56573, 56574, 56575, 56576, 89163 ], "vocabularyKeywords": [], "identifier_set": [ 10097 ], "observationcollection_set": [ { "ob_id": 25948, "uuid": "e75e1e57932d4b95831fa7b56a2016e1", "short_code": "coll", "title": "Arctic Cloud Summer Expedition (ACSE): surface and boundary layer meteorological measurements on board the Icebreaker Oden", "abstract": "This dataset collection contains a number of observational datasets (mainly from the NERC funded contribution, but others too) of surface and boundary layer meteorological measurements collected on board the Icebreaker Oden during its voyage for the Arctic Cloud Summer Expedition (ACSE).\r\n\r\nACSE was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES (the Cooperative Institute for Research In Environmental Sciences). ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." } ], "responsiblepartyinfo_set": [ 108831, 108834, 108833, 108835, 108836, 108837, 108838, 108832, 108840, 108839, 109269 ], "onlineresource_set": [ 25749, 25750, 91724, 91725, 91726, 91727, 91728, 91729, 91730, 91731, 91732, 91733, 91734, 91735, 91736, 91737 ] }, { "ob_id": 26026, "uuid": "3b1effa4b6554366b9ad571fc32a6f7d", "title": "Arctic Cloud Summer Expedition (ACSE): composite cloud layer data for Icebreaker Oden", "abstract": "This dataset contains derived cloud layer measurements of Icebreaker Oden utilising data from the National Centre for Atmospheric Science's Atmospheric Measurement Facility's (NCAS AMF) Halo Doppler lidar and NOAA cloud radar on board Icebreaker Oden durning Arctic Cloud Summer Expedition (ACSE). ACSE took place in the Arctic during summer 2014. These measurements were used to complement a suite of other observations taken during the cruise. Those of the UK contribution, as well as selected other data, are available within the associated data collection in the Centre for Environmental Data Analysis (CEDA) archives. Other cruise data may be available in the NOAA ACSE and The Bolin Centre for Climate Research SWERUS (SWEdish-Russian-US) holdings - see online resources linked to this record.\r\n\r\nThe data provide altitudes of cloud base and top for the first two cloud layers. Cloud base was established from the laser ceilometer (base of liquid cloud) whist he cloud top was established from the cloud radar data. \r\n\r\nWhere fog was detected, the fog top altitude from the radar data is given. Note: it was possible for the radar to detect a cloud top where the laser ceilometer was not able to detecte a cloud base.\r\n\r\nThese data were prepared for archiving as NetCDF data at the Centre for Environmental Data Analysis (CEDA) by Ian Brooks, University of Leeds.\r\n\r\nThe Arctic Cloud Summer Expedition (ACSE) was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES. ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-03-22T15:23:31.663237", "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": "turbulent fluxes, meteorology, winds, wind speed", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "final", "dataPublishedTime": "2018-04-14T12:59:56", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2195, "bboxName": "ACSE voyage bounding box", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": 69.66, "northBoundLatitude": 85.23 }, "verticalExtent": null, "result_field": { "ob_id": 26027, "dataPath": "/badc/acse/data/composite-cloud-layer-data", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 6374365, "numberOfFiles": 2, "fileFormat": "Data are CF-compliant NetCDF formatted." }, "timePeriod": { "ob_id": 7027, "startTime": "2014-07-05T23:00:00", "endTime": "2014-09-28T22:59:59" }, "resultQuality": { "ob_id": 3193, "explanation": "Data quality were checked by the ACSE project data author before supplying to CEDA. 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ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF).\r\n\r\nSWERUS-C3 was initiated as a Knut and Alice Wallenberg funded research project. The project was developed into a multi-disciplinary international research program focused on investigating the historical functioning of the Climate-Cryosphere-Carbon (C3) system of the East Siberian Arctic Ocean." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 4385, 54754, 56478, 56479, 56480, 56481, 56482 ], "vocabularyKeywords": [], "identifier_set": [ 10099 ], "observationcollection_set": [ { "ob_id": 25948, "uuid": "e75e1e57932d4b95831fa7b56a2016e1", "short_code": "coll", "title": "Arctic Cloud Summer Expedition (ACSE): surface and boundary layer meteorological measurements on board the Icebreaker Oden", "abstract": "This dataset collection contains a number of observational datasets (mainly from the NERC funded contribution, but others too) of surface and boundary layer meteorological measurements collected on board the Icebreaker Oden during its voyage for the Arctic Cloud Summer Expedition (ACSE).\r\n\r\nACSE was a collaboration between the University of Leeds, the University of Stockholm, and NOAA-CIRES (the Cooperative Institute for Research In Environmental Sciences). ACSE aimed to study the response of Arctic boundary layer cloud to changes in surface conditions in the Arctic Ocean as a working package of the larger Swedish-Russian-US Investigation of Climate, Cryosphere and Carbon interaction (SWERUS-C3) Expedition in Summer 2014. This expedition was a core component to the overall SWERUS-C3 programme and was supported by the Swedish Polar Research Secretariat.\r\n\r\nACSE took place during a 3-month cruise of the Swedish Icebreaker Oden from Tromso, Norway to Barrow, Alaska and back over the summer of 2014. During this cruise ACSE scientists measured surface turbulent exchange, boundary layer structure, and cloud properties. Many of the measurements used remote sensing approaches - radar, lidar, and microwave radiometers - to retrieve vertical profiles of the dynamic and microphysical properties of the lower atmosphere and cloud.\r\n\r\nThe UK participation of ACSE was funded by the Natural Environment Research Council (NERC, grant: NE/K011820/1) and involved instrumentation from the Atmospheric Measurement Facility of the UK's National Centre for Atmospheric Science (NCAS AMF). This dataset collection contains data mainy from the UK contribution with some additional data from other institutes also archived to complement the suite of meteorological measurements." } ], "responsiblepartyinfo_set": [ 108848, 108841, 108842, 108844, 108845, 108846, 108847, 108843, 109264, 108849, 109265 ], "onlineresource_set": [ 25755, 25756, 91738, 91739, 91740, 91741, 91742, 91743, 91744, 91745, 91746, 91747, 91748, 91749, 91750, 91751, 91752, 91753 ] }, { "ob_id": 26036, "uuid": "655866af94cd4fa6af67809657b275c3", "title": "EUSTACE/GlobTemperature: Global clear-sky land surface temperature data from MODIS Terra on the satellite swath with estimates of uncertainty components, v2.1, 2000-2016", "abstract": "This dataset consists of Land Surface Temperature (LST) data with uncertainty estimates, from the MODIS instrument on NASA's Terra satellite. It forms part of the collection of datasets from the EUSTACE (EU Surface Temperature for All Corners of Earth) project, which is producing publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques. \r\n\r\nThe Level 2 Land Surface Temperature data in this dataset has been retrieved from MODIS Collection 6 L1B calibrated radiances, in the context of the GlobTemperature project, but new uncertainty estimates have been added as part of the EUSTACE project. This version of the LST dataset is v2.1 of the GT_MOG_2P product, with earlier versions produced under the GlobTemperature project. It consists of a complete set of LST and accompanying auxiliary (AUX) datafiles for the MODIS-Terra mission for the period 2000 to 2016. An equivalent dataset is also available for MODIS-Aqua.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2025-01-07T01:51:44", "updateFrequency": "notPlanned", "dataLineage": "Data are provided and archived for the EU EUSTACE project, which has received funding by the European Union's Horizon 2020 research and inovation programme under grant agreement no 640171.\r\nThe Land Surface Temperature data was originally retrieved in the context of the ESA DUE GlobTemperature project, but new uncertainty estimates have been added in the context of the EUSTACE project. The MODIS data was acquired from the NASA Land Processes Distributed Active Archive Center (LP DAAC).", "removedDataReason": "", "keywords": "eustace, land surface temperature, LST", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "1km at nadir", "status": "completed", "dataPublishedTime": "2019-03-18T12:07:46", "doiPublishedTime": "2019-03-18T12:14:26", "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": 26508, "dataPath": "/neodc/eustace/data/satellite_skin_temperature/UOL/land/MODIS_Terra/L2/GT_MOG_2P/v2.1/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 32049822808365, "numberOfFiles": 3406978, "fileFormat": "Data are in NetCDF" }, "timePeriod": { "ob_id": 7029, "startTime": "2000-03-05T00:00:00", "endTime": "2016-12-31T23:59:59" }, "resultQuality": { "ob_id": 3124, "explanation": "Data format checked ", "passesTest": true, "resultTitle": "Eustace Data Compliance Checker", "date": "2018-01-01" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 26037, "uuid": "cc40ad68b5bb434bad66c3324c885427", "short_code": "cmppr", "title": "Eustace: Land Surface Temperature retrieval from the MODIS-Terra satellite instrument", "abstract": "Land Surface Temperature (LST) has been derived from calibrated radiance data from the MODIS instrument on the Terra Satellite. It has been retrieved using the GlobTemperature Level-2 MODIS LST algorithm from the University of Leicester." }, "imageDetails": [ 214 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2526, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 19556, "uuid": "a52b2cc065a847b8a77a93896880349f", "short_code": "proj", "title": "EUSTACE (EU Surface Temperature for All Corners of Earth)", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is producing publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques.\r\n\r\nDay-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. Satellite data can be used to estimate temperatures at locations where no ground (or in situ) observations are available. To achieve this, we must develop an understanding of the relationships between traditional (land and marine) surface air temperature measurements and satellite measurements, i.e. land surface temperature, ice surface temperature, sea surface temperature and lake surface water temperature. These relationships can be derived either empirically, or with the help of physical understanding.\r\n\r\nTo achieve this the EUSTACE project is using new statistical techniques to provide information on higher spatial and temporal scales than are currently available, making optimum use of the information in data-rich eras. The final and intermediate products of EUSTACE (e.g. satellite skin temperature retrievals over all domains with consistent uncertainty estimates; station time series with discontinuities identified; information on the relationship between skin and air temperature over different domains and different seasons) will be interesting for many applications.\r\n\r\nThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 640171." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 54670, 54671, 54674, 54675, 57596, 57599, 69213, 69214, 69215, 69216, 69217, 69218, 69219, 69220, 69221, 69222, 69223, 69224, 69225, 69226 ], "vocabularyKeywords": [], "identifier_set": [ 10500 ], "observationcollection_set": [ { "ob_id": 20098, "uuid": "7ebff7be4c0149d082ca9a32ec8df4da", "short_code": "coll", "title": "EUSTACE: Collection of products from the EUSTACE (EU Surface Temperature for All Corners of Earth) project", "abstract": "The EUSTACE (EU Surface Temperature for All Corners of Earth) project is an EU Horizon 2020 project, producing daily estimates of surface air temperature since 1850 across the globe for the first time, by combining surface and satellite data using novel statistical techniques. \r\n\r\nThe data are publically available and consists of a number of different products: satellite skin temperature retrievals over all surface types; global surface air temperature derived from satellite skin temperature retrievals; homogonised surface meteorological station records for Europe and a European in filled analysis; global surface meteorological station records with discontinuities identified; and global analyses of daily surface air temperature going back to 1850, derived from both satellite and meteorological station data." }, { "ob_id": 30128, "uuid": "7fe9f59731ab47b6a20e792e0cba4641", "short_code": "coll", "title": "National Centre for Earth Observation (NCEO) partnered datasets", "abstract": "The National Centre for Earth Observation (NCEO) has a proud tradition of being involved with some of the most successful international collaborations in the Earth observation. This Collection contains dataset generated and/or archived with the support of NCEO resource or scientific expertise. Some notable collaboration which generated data within this collection are as follows:\r\n\r\nThe European Space Agency (ESA)'s Climate Change Initiative (CCI) program. The program goal is to provide stable, long-term, satellite-based Essential Climate Variable (ECV) data products for climate modelers and researchers.\r\n\r\nThe EUSTACE (EU Surface Temperature for All Corners of Earth) project is produced publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques.\r\n\r\nFIDUCEO has created new climate datasets from Earth Observations with a rigorous treatment of uncertainty informed by the discipline of metrology. This response to the need for enhanced credibility for climate data, to support rigorous science, decision-making and climate services. The project approach was to develop methodologies for generating Fundamental Climate Data Records (FCDRs) and Climate Data Records (CDRs) that are widely applicable and metrologically rigorous. \r\n\r\nThe “BACI” project translates satellite data streams into novel “essential biodiversity variables” by integrating ground-based observations. The trans-disciplinary project offers new insights into the functioning and state of ecosystems and biodiversity. BACI enables the user community to detect abrupt and transient changes of ecosystems and quantify the implications for regional biodiversity.\r\n\r\nThe UK Natural Environment Research Council has established a knowledge transfer network called NCAVEO (Network for Calibration and Validation of EO data - NCAVEO) which has as its aim the promotion and support of methodologies based upon quantitative, traceable measurements in Earth observation. \r\n\r\nThe Geostationary Earth Radiation Budget 1 & 2 instruments (GERB-1 and GERB-2) make accurate measurements of the Earth Radiation Budget. They are specifically designed to be mounted on a geostationary satellite and are carried onboard the Meteosat Second Generation satellites operated by EUMETSAT. They were produced by a European consortium led by the UK (NERC) together with Belgium, Italy, and EUMETSAT, with funding from national agencies.\r\n\r\nGloboLakes analysed 20 years of data from more than 1000 large lakes across the globe to determine 'what controls the differential sensitivity of lakes to environmental perturbation'. This was an ambitious project that was only possible by bringing together a consortium of scientists with complementary skills. These include expertise in remote sensing of freshwaters and processing large volumes of satellite images, collation and analysis of large-scale environmental data, environmental statistics and the assessment of data uncertainty, freshwater ecology and mechanisms of environmental change and the ability to produce lake models to forecast future lake conditions.\r\n\r\nThis SPEI collaboration consists of high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset over the whole of Africa at different time scales from 1 month to 48 months. It is calculated based on precipitation estimates from the satellite-based Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and potential evaporation estimates by the Global Land Evaporation Amsterdam Model (GLEAM)." } ], "responsiblepartyinfo_set": [ 108985, 108986, 108989, 108990, 111390, 108991, 193350, 193351, 108988, 108987, 111389 ], "onlineresource_set": [ 24598, 26558 ] }, { "ob_id": 26039, "uuid": "7bd4a1539085456e8d282379086516e9", "title": "CRUTEM3 Global mean monthly temperature time series from the historical land-only surface temperature", "abstract": "This dataset contains CRUTEM3 Global mean monthly temperature time series from the historical land-only surface temperature, produced in 2006 for the period: 1850-2010. The global temperature is calculated as the mean of the Northern and Southern Hemisphere time series (to stop the better sampled Northern Hemisphere from dominating the average). Data represent temperature anomalies with respect to the 1961-1990 mean. \r\n\r\nA new version of the CRUTEM data set, CRUTEM3, has been produced, benefiting from improvements to the station records which provide the land temperature data. CRUTEM3 no longer infills missing grid box values using data from surrounding grid boxes but rather attributes an uncertainty to each grid box value. \r\n", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-04-16T09:23:16", "updateFrequency": "", "dataLineage": "Data archived by the IPCC DDC held at the Centre for Environmental Data Anaylsis", "removedDataReason": "", "keywords": "CRITEM3, temperature, land", "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": null, "timePeriod": null, "resultQuality": null, "validTimePeriod": { "ob_id": 7030, "startTime": "1850-01-01T00:00:00", "endTime": "2010-12-31T23:59:59" }, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26038, "uuid": "7a4e8ea849d147b3a63c6bc9c574b1f2", "short_code": "comp", "title": "CRUTEM3 Global mean monthly temperature time series from the historical land-only surface temperature", "abstract": "The global temperature is calculated as the mean of the Northern and Southern Hemisphere time series (to stop the better sampled Northern Hemisphere from dominating the average). Data represent temperature anomalies with respect to the 1961-1990 mean." }, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [], "permissions": [], "projects": [], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12165, "uuid": "eeabb5e1ff2140f48e76ea1ffda6bb48", "short_code": "coll", "title": "CRUTEM datasets", "abstract": "CRUTEM is a dataset derived from air temperatures near to the land surface recorded at weather stations across all continents of Earth. It has been developed and maintained by the Climatic Research Unit (CRU) since the early 1980s, with funding provided mostly by the US Department of Energy. Since the early 2000s, the Met Office Hadley Centre (MOHC) have also been involved, especially in the regular updating of the operational version of CRUTEM (current version CRUTEM5) and in the development of the CRUTEM uncertainty model. The lead scientist for most of this work was Professor Phil Jones, but for CRUTEM5 it is Professor Tim Osborn. CRUTEM has been combined with the MOHC's dataset of sea surface temperatures to provide a near-global dataset of temperatures across Earth's surface, called HadCRUT. These datasets have been widely used for assessing anthropogenic climate change." } ], "responsiblepartyinfo_set": [ 108995, 108997, 108998, 108999, 109001, 109002, 109003, 109004, 109000, 108996 ], "onlineresource_set": [ 24599, 24600 ] }, { "ob_id": 26044, "uuid": "262f973ce9e0445bb4158266ff535f11", "title": "DEEP-C: Derived surface net downward energy and absorbed radiation", "abstract": "This dataset contains derived surface net downward energy and absorbed radiation in support of the Diagnosing Earth's Energy Pathways in the Climate system (DEEP-C) NERC funded project (grant reference NE/K004387/1). The energy fluxes at the top of the atmosphere and surface are reconstructed using satellite observations, ERA-Interim reanalysis, and atmospheric simulations. The data period is from 1985-2015.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-04-18T14:41:29.424291", "updateFrequency": "", "dataLineage": "Data produced by Diagnosing Earth's Energy Pathways in the Climate system (DEEP-C) and delivered to the Centre for Environmental Data Analysis (CEDA) for archiving.", "removedDataReason": "", "keywords": "DEEP-C, Energy fluxes, radiation", "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": 26041, "dataPath": "/badc/deposited2018/deep-c/data", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 765525083, "numberOfFiles": 8, "fileFormat": "Data are netCDF formatted" }, "timePeriod": { "ob_id": 7032, "startTime": "1985-01-01T00:00:00", "endTime": "2015-05-31T22:59:59" }, "resultQuality": { "ob_id": 3125, "explanation": "Data is 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": "2018-04-18" }, "validTimePeriod": { "ob_id": 7031, "startTime": "1985-01-01T00:00:00", "endTime": "2015-05-31T22:59:59" }, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26043, "uuid": "1d4eb12ed3d540bbb741e52439bed363", "short_code": "comp", "title": "DEEP-C: Derived surface net downward energy and absorbed radiation", "abstract": "Using satellite observations, ERA-Interim reanalysis, and atmospheric simulations" }, "procedureCompositeProcess": null, "imageDetails": [ 2 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2522, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 12146, "uuid": "f905b0ed03b9405b945d0e035c2642b7", "short_code": "proj", "title": "Diagnosing Earth's Energy Pathways in the Climate system (DEEP-C)", "abstract": "The DEEP-C project was funded by the Natural Environment Research Council (NERC) with the grant reference - NE/K004387/1 - led by Professor Richard Allen (University of Reading) and Dr Elaine McDonagh (National Oceanographic Centre). \r\n\r\nA global warming trend since the 1970s has slowed over the most recent 10-15 years despite the continuing build up of carbon dioxide in the atmosphere (due primarily to the burning of fossil fuels). This research sought to understand the reasons for this \"hiatus\" in global warming and in particular the roles of the ocean and atmosphere in contributing to this hiatus through movement of energy around the climate system. This project has helped us monitor changes in climate and understand the processes that are important in enabling us to predict climate change more accurately over the coming decades. \r\n\r\nWarming of the planet is caused by a small yet persistent imbalance between the amount of sunlight absorbed by the Earth and the outgoing flow of thermal (infra-red) radiative energy constantly emanating from our planet to space: if more energy is arriving than leaving then the climate heats up. To understand why the heating has apparently slowed required a detailed assessment of the flows of energy arriving from space, how this energy is transported by the atmosphere, taken up by the surface ocean and subducted deep below the sea surface. Previously, scientists had identified a discrepancy between these energy flows, or \"missing energy\" in the climate. A primary objective of this research program was to resolve the discrepancy between these energy flows and understand the root causes of the hiatus in the warming of the Earth's surface. \r\n\r\nThe project combined the latest, improved satellite measurements of Earth's radiative energy imbalance (reflected sunlight and emitted thermal radiation) with the best estimates of energy flows in the atmosphere (from reanalysis simulations) and detailed 3-dimensional ocean heating measurements made by thousands of automated floating buoys, to determine the observed flows of energy in the climate system. The project combined these measurements with state-of-the-art depictions of Earth's climate from sophisticated computer simulations to understand the mechanisms by which the build up of energy due to greenhouse gas increases are redistributed into the oceans. \r\n\r\nIt is plausible that increased amounts of reflective aerosols in the atmosphere (due to human activities or naturally through emissions by volcanic eruptions) may have diminished the heating of the planet. However, preliminary analyses lead to the hypothesis that in fact more heat has been entering the deep ocean rather than heating the planets surface. Getting to the bottom of this question was vital for understanding current climate variability and future change over the coming 10 years or more. The project considered that the research is also important for understanding regional sea level rise (since warmer water occupies a larger volume leading to rising sea level), fluctuations in clouds and whether they magnify or reduce warming tendencies (climate feedbacks) and simulating the ocean circulation and heat uptake, crucial for representing climate change over the coming decades. \r\n\r\nThis research was only possible by combining the expertise from three institutions (the University of Reading, the National Oceanography Centre Southampton and the Met Office) covering satellite data, reanalyses of the atmosphere and ocean, ocean measurements and numerical computer simulations of the climate system. The current planetary changes are unusual and present a timely opportunity for understanding how our climate system works: to discover the cause of the global warming hiatus and to understand and simulate the mechanisms important in representing climate variability and change over the coming decades.\r\n\r\nThe primary objective of the project was to quantify Earth's Energy Imbalance, its variability and implications for climate change over the coming decades. The driving goal was to observe, understand and explain the slow rates of surface warming since 2000 using satellite data, atmospheric reanalyses, in situ observations of ocean heat content and climate simulations and to elucidate physical mechanisms operating during \"hiatus\" decades of slow surface warming rates through the following specific objectives: \r\n\r\n1) Combine CERES satellite radiation budget measurements with ERA Interim reanalysis and additional datasets, providing improved 2D estimates of surface heat fluxes entering the ocean surface since 2000 \r\n2) Develop and compute global 3D ocean heat and freshwater content and its changes since 2003 using ARGO observations, leading to improved understanding of energy propagation through the climate system \r\n3) Conduct multi-model assessment of simulated variability in ocean heat content, freshwater content and steric sea-level and evaluate the processes fundamental for ocean heat uptake and redistribution \r\n4) Provide accurate estimate of Earth's net radiative energy balance and its variability over the period 2000-2015 by combining results from (1-3) and compare with state-of-the-art CMIP5 climate simulations. \r\n5) Quantify and understand lags between OHC and top of atmosphere radiation involving additional minor energy storage terms in the climate system \r\n6) Characterise spatial signatures and mechanisms of ocean and atmospheric heat re-distribution during the period 2000-2015 using observations and multi-model simulations of variability in ocean heat content, freshwater content and steric sea-level \r\n\r\nMeeting these objectives also resulted in: \r\n\r\n7) Explain the previously documented discrepancy between energy flows (or\"missing energy\") in the climate system \r\n8) Generate legacy software and methodologies for monitoring changes in Earth's radiative imbalance \r\n\r\nAdditional outputs that stemmed from the project were: \r\n\r\n9) Computations of ocean-basin scale estimates of energy budget, \r\n10) Identification of key regions of energy subduction into the ocean on interannual-decadal time-scales \r\n11) Explore the potential for using deep hydrographic sections for quantifying changes deeper than 2000m and evaluate their significance. \r\n12) New knowledge for regional sea level, climate feedback and reanalysis/climate modelling communities (see Academic Beneficiaries)" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 22483, 22484, 22485, 22486, 50416, 50559, 50561 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 109013, 109014, 109015, 109016, 109018, 109019, 109020, 109021, 109017, 109237 ], "onlineresource_set": [ 24605, 24704 ] }, { "ob_id": 26047, "uuid": "c0c7998800414e46b6823dc75751bb4c", "title": "Envelope field of Northern hemispheric upper tropospheric (300 hPa) quasi-stationary waves (June 1979 to August 2015)", "abstract": "This dataset comprises 12 hourly data of the envelope field of Northern hemispheric upper tropospheric (300 hPa) quasi-stationary waves calculated between1979-06-01 and 2015-08-31. The data were derived as part of the NERC funded ODYSEA project (Ocean Dynamics as Driver of Seasonal to Decadal European Atmospheric variability).\r\n\r\nThe envelope field in this dataset is a phase-independent measure of the wave amplitude and is derived from the meridional wind at 300 hPa of the ERA-Interim reanalysis data. To remove the faster transient signals a 15-day lowpass filter was applied to the meridional wind and then subtracted from a daily climatology. The envelope field allows for the identification of a slowly evolving stationary or slowly moving wave packet.\r\n\r\nFull details of the method are described in the methodology statement that can be found in the docs section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-04-19T13:32:06.729942", "updateFrequency": "", "dataLineage": "The data were produced as part of the NERC project Ocean Dynamics as Driver of Seasonal to Decadal European Atmospheric variability (ODYSEA; NE/M006107/1) and passed to the Centre for Environmental Data Analysis (CEDA) for archival and distribution.", "removedDataReason": "", "keywords": "quasi-stationary waves, wave packet, NE/M006107/1", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2018-04-20T07:56:19", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 741, "bboxName": "Northern Hemisphere", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": 0.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 26045, "dataPath": "/badc/deposited2018/odysea/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 827302534, "numberOfFiles": 2, "fileFormat": "The data are provided in a single NetCDF file. " }, "timePeriod": { "ob_id": 7033, "startTime": "1976-05-31T23:00:00", "endTime": "2015-12-31T12:00:00" }, "resultQuality": { "ob_id": 3126, "explanation": "The data were quality controlled by the project team and no quality control has been performed by the Centre for Environmental Data Analysis (CEDA)", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2018-04-19" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26046, "uuid": "c310df6bc12b4ff8a541c1577c8bc298", "short_code": "comp", "title": "Calculation of the envelope field of Northern hemispheric upper tropospheric (300 hPa) quasi-stationary waves ( June 1979 to August 2015)", "abstract": "The data are calculated from the meridional wind in ERA-Interim. A lowpass filter of 15-days is applied and the daily climatology (also lowpass filtered) subtracted. The method of Zimin et al. 2003 with a latitude dependent wavenumber range is then applied. The description of this method and the discussion about the climatology of quasi-stationary waves (this dataset) and their connection to European temperature anomalies and extreme events can be found in the attached methodology statement." }, "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": 26048, "uuid": "1c815f9fdd8d4c1cbddd502af8b6291f", "short_code": "proj", "title": "ODYSEA: Ocean dynamics as driver of seasonal to decadal European atmospheric variability", "abstract": "ODYSEA: Ocean dynamics as driver of seasonal to decadal European atmospheric variability is a NERC funded research project (NE/M006107/1) investigating the impact of the ocean on the variability and predictability of European weather and climate. ODYSEA combines novel and existing numerical simulations (including hindcasts from the latest generation of the UK Met Office’s seasonal and decadal forecasting systems) and observations to provide new process-level understanding for European atmospheric variability by identifying the physical mechanisms through which the ocean modulates the variability of European climate. The project began in 2015." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 51981, 59154, 59155, 70812, 70813 ], "vocabularyKeywords": [], "identifier_set": [ 9554 ], "observationcollection_set": [ { "ob_id": 26049, "uuid": "1cec31b7f73d429d8d273064d0a8f824", "short_code": "coll", "title": "ODYSEA: Ocean Dynamics as Driver of Seasonal to Decadal European Atmospheric variability project data", "abstract": "A collection of data products produced by the NERC project ODYSEA: Ocean Dynamics as Driver of Seasonal to Decadal European Atmospheric variability." } ], "responsiblepartyinfo_set": [ 109022, 109027, 109028, 109031, 109034, 109026, 109029, 109030, 109033, 109032, 109023, 148630, 109024, 109025 ], "onlineresource_set": [ 24607, 87779 ] }, { "ob_id": 26050, "uuid": "7a349024c0eb4bd5a05e7cf75cec16af", "title": "ECMWF ERA-Interim: reduced N256 Gaussian gridded monthly mean of daily mean analysed pressure level parameter data (ggap)", "abstract": "ERA-Interim is the latest European Centre for Medium-Range Weather Forecasts (ECMWF) global atmospheric reanalysis of the period 1979 to August 2019. This follows on from the ERA-15 and ERA-40 re-analysis projects. \r\n\r\nThe dataset includes monthly mean of daily mean pressure level data on a reduced N256 Gaussian grid.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2019-10-26T01:05:30", "updateFrequency": "notPlanned", "dataLineage": "Data are generated by the ERA-Interim project at European Centre for Medium-Range Weather Forecasts (ECMWF) before being prepared by ECMWF and uploaded to BADC for ingestion into the archive.", "removedDataReason": "", "keywords": "ECMWF, ERA, ERA, Interim, reanalysis, surface, model, Gaussian, N256, analysis, pressure level, monthly-mean", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2020-04-24T13:44:21", "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": 26062, "dataPath": "/badc/ecmwf-era-interim/data/monthly-means/gg/ap", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 151469918949, "numberOfFiles": 489, "fileFormat": "Data are CF-compliant netCDF formatted" }, "timePeriod": { "ob_id": 1834, "startTime": "1979-01-01T00:00:00", "endTime": "2019-08-31T23:59:59" }, "resultQuality": { "ob_id": 1669, "explanation": "ECMWF quality controlled data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-08-26" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 6306, "uuid": "64ed8e22930b447998e54f619a54cff5", "short_code": "comp", "title": "ECMWF ERA-Interim Re-analysis Model deployed on ECMWF Computer", "abstract": "This computation involved: ECMWF ERA-Interim Re-analysis Model deployed on ECMWF Computer. The data assimilation system used to produce ERA-Interim is based on a 2006 release of the IFS (Cy31r2). The system includes a 4-dimensional variational analysis (4D-Var) with a 12-hour analysis window. The spatial resolution of the data set is approximately 80 km (T255 spectral) on 60 vertical levels from the surface up to 0.1 hPa." }, "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": 6305, "uuid": "3ffd77b96c15d3e96db104aa34a5e782", "short_code": "proj", "title": "ECMWF ERA-Interim Re-analysis project", "abstract": "The objectives of the European Centre for Medium-Range Weather Forecasts ERA-Interim 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. 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The dataset includes data on surface, PV, potential temperature and pressure surfaces. Model level data available as GRIB formatted data on spectral and reduced Gaussian grids. \r\n\r\nMonthly mean of daily mean and synoptic monthly mean data are also available as part of this collection.\r\n\r\nAdditional datasets derived from these data are also available." } ], "responsiblepartyinfo_set": [ 109168, 109161, 109167, 109166, 109165, 109162, 109163, 109164, 109189 ], "onlineresource_set": [ 24688, 24690, 24692, 24693, 24691 ] }, { "ob_id": 26073, "uuid": "029e04488a314c9e8fea9cb7543037c9", "title": "ECMWF ERA-Interim: reduced N256 Gaussian gridded synoptic monthly mean analysed pressure level parameter data (hgap)", "abstract": "ERA-Interim is the latest European Centre for Medium-Range Weather Forecasts (ECMWF) global atmospheric reanalysis of the period 1979 to August 2019. This follows on from the ERA-15 and ERA-40 re-analysis projects. \r\n\r\nThe dataset includes synoptic monthly mean analysed pressure level data on a reduced N256 Gaussian grid. Data are available at the 00, 06, 12 and 18 UT analysis times.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2019-10-26T01:08:16.137715", "updateFrequency": "notPlanned", "dataLineage": "Data are generated by the ERA-Interim project at European Centre for Medium-Range Weather Forecasts (ECMWF) before being prepared by ECMWF and uploaded to BADC for ingestion into the archive.", "removedDataReason": "", "keywords": "ECMWF, ERA, ERA, Interim, reanalysis, surface, model, Gaussian, N256, analysis, pressure level, monthly-mean", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2020-04-09T15:34:38", "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": 26074, "dataPath": "/badc/ecmwf-era-interim/data/monthly-means/hg/ap", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 605879673076, "numberOfFiles": 1953, "fileFormat": "Data are CF-compliant NetCDF formatted." }, "timePeriod": { "ob_id": 1837, "startTime": "1979-01-01T00:00:00", "endTime": "2019-08-31T23:59:59" }, "resultQuality": { "ob_id": 1672, "explanation": "ECMWF quality controlled data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-08-26" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 6306, "uuid": "64ed8e22930b447998e54f619a54cff5", "short_code": "comp", "title": "ECMWF ERA-Interim Re-analysis Model deployed on ECMWF Computer", "abstract": "This computation involved: ECMWF ERA-Interim Re-analysis Model deployed on ECMWF Computer. The data assimilation system used to produce ERA-Interim is based on a 2006 release of the IFS (Cy31r2). The system includes a 4-dimensional variational analysis (4D-Var) with a 12-hour analysis window. 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Model level data available as GRIB formatted data on spectral and reduced Gaussian grids. \r\n\r\nMonthly mean of daily mean and synoptic monthly mean data are also available as part of this collection.\r\n\r\nAdditional datasets derived from these data are also available." } ], "responsiblepartyinfo_set": [ 109169, 109175, 109174, 109173, 109176, 109170, 109171, 109172, 109177 ], "onlineresource_set": [ 24696, 24698, 24699, 24694, 24697 ] }, { "ob_id": 26093, "uuid": "100dd91da981445fa4a350cc9cfe60bf", "title": "Re-analysis ERA-20C European winter extra-tropical cyclone tracks 1900-2010", "abstract": "This dataset contains winter (October-March) extra-tropical cyclone tracks generated by TRACK (Hodges 1994, 1995, 1999) that pass through a Western European domain from the ERA-20C (1900-2010). The tracks were filtered to retain those that travelled 1000km and lasted 2 days. Fields referenced to the tracks are: mean sea-level pressure (min within 5 degrees), 925hPa windspeed (max within 6 degrees), precipitation (max within 5 degrees), 700hPa vertical velocity (min within 5 degrees), 925hPa land-windspeed (max within 6 degrees), precipitation (area average over 5 degrees).\r\n\r\nThis data was collected as part of Robust Spatial Projections for the Real World (Real Projections) NERC (Natural Environment Research Council) NE/N018486/1.\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip.new_1000km2dayfiltered[_RealProjregion2filtered_maxlandwindsinregion].txt\r\n\r\n\r\nThe track files contain a 5 line header. The information in the body of the file gives:\r\n1. Date and time (YYYYMMDDHH).\r\n2. Longitude of relative vorticity maximum (degrees).\r\n3. Latitude of relative vorticity maximum (degrees).\r\n4. Relative vorticty at T42 resolution (x10-5 s-1).\r\n5. Longitude of associated MSLP minimum (degrees).\r\n6. Latitude of associated MSLP minimum (degrees).\r\n7. MSLP minimum (hPa).\r\n8. Longitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n9. Latitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n10. 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (ms-1).\r\n11. Longitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n12. Latitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n13. Precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n14. Longitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n15. Latitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n16. 700hPa vertical velocity minimum within a 5 degree radius of vorticity maximum (ms-1)\r\n17. Longitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n18. Latitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n19. 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (ms-1).\r\n20. Precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)\r\n\r\nThe [_RealProjregion2filtered_maxlandwindsinregion] refers to data that has been filtered to those storms that have their maximum 925hPa windspeed over land in the region. The add[field] refers to which field, and the order, in which the meteorological fields have been referenced to the vorticity centres.\r\n\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip_addmax5cmorph_addavg5cmorph.new_1000km2dayfiltered_RealProjregion2filtered_maxlandwindsinregion.txt\r\n\r\n(i.e. these include two additional fields for a smaller temporal range)\r\n\r\nThe same track information as above in included, plus:\r\n\r\n21. Longitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n22. Latitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n23. CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n24. CMORPH precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-06-07T14:56:49.178004", "updateFrequency": "", "dataLineage": "Data delivered to the Centre for Environmental Data Analysis (CEDA) for archiving by the project team.", "removedDataReason": "", "keywords": "extra-tropical, cyclone, European, track, tracks, ETC, storm, storms", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2018-06-15T13:07:30", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2202, "bboxName": "winter storm", "eastBoundLongitude": 50.0, "westBoundLongitude": -100.0, "southBoundLatitude": 30.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 26167, "dataPath": "/badc/deposited2018/robust-storm-track/data/era-20c", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2659023853, "numberOfFiles": 23, "fileFormat": "Data are txt formatted" }, "timePeriod": { "ob_id": 7048, "startTime": "1900-01-01T00:00:00", "endTime": "2010-03-31T22:59:59" }, "resultQuality": { "ob_id": 3128, "explanation": "Data is 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": "2018-05-10" }, "validTimePeriod": { "ob_id": 7045, "startTime": "1900-01-01T00:00:00", "endTime": "2010-12-31T23:59:59" }, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26097, "uuid": "a688e159a7264bc4960577edcce8871e", "short_code": "comp", "title": "Re-analysis (ERA-20C, ERA-Interim, NCEP-CFS) European winter extra-tropical cyclone tracks 1900/1979-2010", "abstract": "The data was downloaded from either the ECMWF MARS server (ERA-20C, ERA-Interim) or the NOAA server (NCEP-CFS). The tracking was then performed using the TRACK software (Hodges 1994, 1995, 1999), with the storm selection and filtering method, and the variables associated with the tracks discussed in the paper currently in preparation." }, "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": 26098, "uuid": "97ca58a7570f4e169473953f3d694e45", "short_code": "proj", "title": "Robust Spatial Projections for the Real World (Real Projections)", "abstract": "This project produced quantitative projections of the real-world spatial patterns of future climate change. Two interlinked frameworks were developed; one to advance our basic understanding of climate change processes through targeted and idealized model experiments; and the other to optimally combine the information from climate models with observations and the new understanding to produce projections of the real world. The frameworks were rigorously tested by application to three key problems in climate projection; (i) tropical and subtropical land-ocean temperature contrast and precipitation change, (ii) northern hemisphere mid-latitude storms and blocking and (iii) polar temperature and precipitation change and sea-ice feedbacks." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [ 9606 ], "observationcollection_set": [ { "ob_id": 26096, "uuid": "8ec7ddba554844b4ad1a600ff2196e1c", "short_code": "coll", "title": "Re-analysis (ERA-20C, ERA-Interim, NCEP-CFS) European winter extra-tropical cyclone tracks 1900/1979-2010", "abstract": "This dataset collection contains winter (October - March) extra-tropical cyclone tracks generated by TRACK (Hodges 1994, 1995, 1999) that pass through a Western European domain from three re-analysis datasets: ERA-20C (1900-2010), ERA-Interim (1979-2010) and NCEP-CFS (1979-2010). The tracks were filtered to retain those that travelled 1000km and lasted 2 days. Fields referenced to the tracks are: mean sea-level pressure (min within 5 degrees), 925hPa windspeed (max within 6 degrees), precipitation (max within 5 degrees), 700hPa vertical velocity (min within 5 degrees), 925hPa land-windspeed (max within 6 degrees), precipitation (area average over 5 degrees).\r\n\r\nThis data was collected as part of Robust Spatial Projections for the Real World (Real Projections) NERC (Natural Environment Research Council) NE/N018486/1." } ], "responsiblepartyinfo_set": [ 109238, 109243, 109244, 109245, 109246, 109248, 109249, 109250, 109247, 168801, 109239, 109240, 109241, 109242 ], "onlineresource_set": [ 24733, 94831, 94832 ] }, { "ob_id": 26094, "uuid": "421688bf376b41b884246b34bd274356", "title": "Re-analysis ERA-Interim European winter extra-tropical cyclone tracks 1979-2010", "abstract": "This dataset contains winter (October-March) extra-tropical cyclone tracks generated by TRACK (Hodges 1994, 1995, 1999) that pass through a Western European domain from the ERA-Interim (1979-2010). The tracks were filtered to retain those that travelled 1000km and lasted 2 days. Fields referenced to the tracks are: mean sea-level pressure (min within 5 degrees), 925hPa windspeed (max within 6 degrees), precipitation (max within 5 degrees), 700hPa vertical velocity (min within 5 degrees), 925hPa land-windspeed (max within 6 degrees), precipitation (area average over 5 degrees).\r\n\r\nThis data was collected as part of Robust Spatial Projections for the Real World (Real Projections) NERC (Natural Environment Research Council) NE/N018486/1.\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip.new_1000km2dayfiltered[_RealProjregion2filtered_maxlandwindsinregion].txt\r\n\r\n\r\nThe track files contain a 5 line header. The information in the body of the file gives:\r\n1. Date and time (YYYYMMDDHH).\r\n2. Longitude of relative vorticity maximum (degrees).\r\n3. Latitude of relative vorticity maximum (degrees).\r\n4. Relative vorticty at T42 resolution (x10-5 s-1).\r\n5. Longitude of associated MSLP minimum (degrees).\r\n6. Latitude of associated MSLP minimum (degrees).\r\n7. MSLP minimum (hPa).\r\n8. Longitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n9. Latitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n10. 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (ms-1).\r\n11. Longitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n12. Latitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n13. Precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n14. Longitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n15. Latitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n16. 700hPa vertical velocity minimum within a 5 degree radius of vorticity maximum (ms-1)\r\n17. Longitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n18. Latitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n19. 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (ms-1).\r\n20. Precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)\r\n\r\nThe [_RealProjregion2filtered_maxlandwindsinregion] refers to data that has been filtered to those storms that have their maximum 925hPa windspeed over land in the region. The add[field] refers to which field, and the order, in which the meteorological fields have been referenced to the vorticity centres.\r\n\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip_addmax5cmorph_addavg5cmorph.new_1000km2dayfiltered_RealProjregion2filtered_maxlandwindsinregion.txt\r\n\r\n(i.e. these include two additional fields for a smaller temporal range)\r\n\r\nThe same track information as above in included, plus:\r\n\r\n21. Longitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n22. Latitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n23. CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n24. CMORPH precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2024-03-09T01:56:50", "updateFrequency": "notPlanned", "dataLineage": "Data delivered to the Centre for Environmental Data Analysis (CEDA) for archiving by the project team.", "removedDataReason": "", "keywords": "extra-tropical, cyclone, European, track, tracks, ETC, storm, storms", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2018-06-15T13:08:38", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2202, "bboxName": "winter storm", "eastBoundLongitude": 50.0, "westBoundLongitude": -100.0, "southBoundLatitude": 30.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 26168, "dataPath": "/badc/deposited2018/robust-storm-track/data/era-interim", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 284636020, "numberOfFiles": 5, "fileFormat": "Data are txt formatted" }, "timePeriod": { "ob_id": 7047, "startTime": "1979-01-01T00:00:00", "endTime": "2010-12-31T23:59:59" }, "resultQuality": { "ob_id": 3128, "explanation": "Data is 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": "2018-05-10" }, "validTimePeriod": { "ob_id": 7046, "startTime": "1979-01-01T00:00:00", "endTime": "2010-12-31T23:59:59" }, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26097, "uuid": "a688e159a7264bc4960577edcce8871e", "short_code": "comp", "title": "Re-analysis (ERA-20C, ERA-Interim, NCEP-CFS) European winter extra-tropical cyclone tracks 1900/1979-2010", "abstract": "The data was downloaded from either the ECMWF MARS server (ERA-20C, ERA-Interim) or the NOAA server (NCEP-CFS). The tracking was then performed using the TRACK software (Hodges 1994, 1995, 1999), with the storm selection and filtering method, and the variables associated with the tracks discussed in the paper currently in preparation." }, "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": 26098, "uuid": "97ca58a7570f4e169473953f3d694e45", "short_code": "proj", "title": "Robust Spatial Projections for the Real World (Real Projections)", "abstract": "This project produced quantitative projections of the real-world spatial patterns of future climate change. Two interlinked frameworks were developed; one to advance our basic understanding of climate change processes through targeted and idealized model experiments; and the other to optimally combine the information from climate models with observations and the new understanding to produce projections of the real world. The frameworks were rigorously tested by application to three key problems in climate projection; (i) tropical and subtropical land-ocean temperature contrast and precipitation change, (ii) northern hemisphere mid-latitude storms and blocking and (iii) polar temperature and precipitation change and sea-ice feedbacks." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [ 9607 ], "observationcollection_set": [ { "ob_id": 26096, "uuid": "8ec7ddba554844b4ad1a600ff2196e1c", "short_code": "coll", "title": "Re-analysis (ERA-20C, ERA-Interim, NCEP-CFS) European winter extra-tropical cyclone tracks 1900/1979-2010", "abstract": "This dataset collection contains winter (October - March) extra-tropical cyclone tracks generated by TRACK (Hodges 1994, 1995, 1999) that pass through a Western European domain from three re-analysis datasets: ERA-20C (1900-2010), ERA-Interim (1979-2010) and NCEP-CFS (1979-2010). The tracks were filtered to retain those that travelled 1000km and lasted 2 days. Fields referenced to the tracks are: mean sea-level pressure (min within 5 degrees), 925hPa windspeed (max within 6 degrees), precipitation (max within 5 degrees), 700hPa vertical velocity (min within 5 degrees), 925hPa land-windspeed (max within 6 degrees), precipitation (area average over 5 degrees).\r\n\r\nThis data was collected as part of Robust Spatial Projections for the Real World (Real Projections) NERC (Natural Environment Research Council) NE/N018486/1." } ], "responsiblepartyinfo_set": [ 109280, 109272, 109273, 109274, 109276, 109277, 109278, 109279, 109275, 168803, 109281, 109282, 109283, 109284 ], "onlineresource_set": [ 24731, 94827, 94828 ] }, { "ob_id": 26095, "uuid": "994193d395314c9fa33bdd38364f5171", "title": "Re-analysis NCEP-CFS European winter extra-tropical cyclone tracks 1979-2010", "abstract": "This dataset contains winter (October-March) extra-tropical cyclone tracks generated by TRACK (Hodges 1994, 1995, 1999) that pass through a Western European domain from NCEP-CFS (1979-2010). The tracks were filtered to retain those that travelled 1000km and lasted 2 days. Fields referenced to the tracks are: mean sea-level pressure (min within 5 degrees), 925hPa windspeed (max within 6 degrees), precipitation (max within 5 degrees), 700hPa vertical velocity (min within 5 degrees), 925hPa land-windspeed (max within 6 degrees), precipitation (area average over 5 degrees).\r\n\r\nThis data was collected as part of Robust Spatial Projections for the Real World (Real Projections) NERC (Natural Environment Research Council) NE/N018486/1.\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip.new_1000km2dayfiltered[_RealProjregion2filtered_maxlandwindsinregion].txt\r\n\r\n\r\nThe track files contain a 5 line header. The information in the body of the file gives:\r\n1. Date and time (YYYYMMDDHH).\r\n2. Longitude of relative vorticity maximum (degrees).\r\n3. Latitude of relative vorticity maximum (degrees).\r\n4. Relative vorticty at T42 resolution (x10-5 s-1).\r\n5. Longitude of associated MSLP minimum (degrees).\r\n6. Latitude of associated MSLP minimum (degrees).\r\n7. MSLP minimum (hPa).\r\n8. Longitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n9. Latitude of 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (degrees).\r\n10. 925hPa windspeed maximum within a 6 degree radius of vorticity maximum (ms-1).\r\n11. Longitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n12. Latitude of precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n13. Precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n14. Longitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n15. Latitude of 700hPa minimum vertical velocity within a 5 degree radius of vorticity maximum (degrees)\r\n16. 700hPa vertical velocity minimum within a 5 degree radius of vorticity maximum (ms-1)\r\n17. Longitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n18. Latitude of 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (degrees).\r\n19. 925hPa windspeed maximum over European and Scandinavian land within a 6 degree radius of vorticity maximum (ms-1).\r\n20. Precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)\r\n\r\nThe [_RealProjregion2filtered_maxlandwindsinregion] refers to data that has been filtered to those storms that have their maximum 925hPa windspeed over land in the region. The add[field] refers to which field, and the order, in which the meteorological fields have been referenced to the vorticity centres.\r\n\r\n\r\nFor files with the naming convention:\r\n\r\n[Dataset]_tr_trs_VOR850_[yearstart][yearend]_pos.addmslp_addspeed_addprecip_addomega_addlandwinds_addavgprecip_addmax5cmorph_addavg5cmorph.new_1000km2dayfiltered_RealProjregion2filtered_maxlandwindsinregion.txt\r\n\r\n(i.e. these include two additional fields for a smaller temporal range)\r\n\r\nThe same track information as above in included, plus:\r\n\r\n21. Longitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n22. Latitude of CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (degrees)\r\n23. CMORPH precipitation maximum within a 5 degree radius of vorticity maximum (mmhr-1)\r\n24. CMORPH precipitation area averaged over a 5 degree radius of vorticity maximum (mmhr-1)", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-06-07T15:04:40.370528", "updateFrequency": "", "dataLineage": "Data delivered to the Centre for Environmental Data Analysis (CEDA) for archiving by the project team.", "removedDataReason": "", "keywords": "extra-tropical, cyclone, European, track, tracks, ETC, storm, storms", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2018-06-15T13:11:57", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2202, "bboxName": "winter storm", "eastBoundLongitude": 50.0, "westBoundLongitude": -100.0, "southBoundLatitude": 30.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 26169, "dataPath": "/badc/deposited2018/robust-storm-track/data/ncep-cfs", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 307311552, "numberOfFiles": 5, "fileFormat": "Data are txt formatted" }, "timePeriod": { "ob_id": 7049, "startTime": "1979-09-30T23:00:00", "endTime": "2010-03-31T22:59:59" }, "resultQuality": { "ob_id": 3128, "explanation": "Data is 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": "2018-05-10" }, "validTimePeriod": { "ob_id": 7046, "startTime": "1979-01-01T00:00:00", "endTime": "2010-12-31T23:59:59" }, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26097, "uuid": "a688e159a7264bc4960577edcce8871e", "short_code": "comp", "title": "Re-analysis (ERA-20C, ERA-Interim, NCEP-CFS) European winter extra-tropical cyclone tracks 1900/1979-2010", "abstract": "The data was downloaded from either the ECMWF MARS server (ERA-20C, ERA-Interim) or the NOAA server (NCEP-CFS). The tracking was then performed using the TRACK software (Hodges 1994, 1995, 1999), with the storm selection and filtering method, and the variables associated with the tracks discussed in the paper currently in preparation." }, "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": 26098, "uuid": "97ca58a7570f4e169473953f3d694e45", "short_code": "proj", "title": "Robust Spatial Projections for the Real World (Real Projections)", "abstract": "This project produced quantitative projections of the real-world spatial patterns of future climate change. Two interlinked frameworks were developed; one to advance our basic understanding of climate change processes through targeted and idealized model experiments; and the other to optimally combine the information from climate models with observations and the new understanding to produce projections of the real world. The frameworks were rigorously tested by application to three key problems in climate projection; (i) tropical and subtropical land-ocean temperature contrast and precipitation change, (ii) northern hemisphere mid-latitude storms and blocking and (iii) polar temperature and precipitation change and sea-ice feedbacks." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [ 9605 ], "observationcollection_set": [ { "ob_id": 26096, "uuid": "8ec7ddba554844b4ad1a600ff2196e1c", "short_code": "coll", "title": "Re-analysis (ERA-20C, ERA-Interim, NCEP-CFS) European winter extra-tropical cyclone tracks 1900/1979-2010", "abstract": "This dataset collection contains winter (October - March) extra-tropical cyclone tracks generated by TRACK (Hodges 1994, 1995, 1999) that pass through a Western European domain from three re-analysis datasets: ERA-20C (1900-2010), ERA-Interim (1979-2010) and NCEP-CFS (1979-2010). The tracks were filtered to retain those that travelled 1000km and lasted 2 days. Fields referenced to the tracks are: mean sea-level pressure (min within 5 degrees), 925hPa windspeed (max within 6 degrees), precipitation (max within 5 degrees), 700hPa vertical velocity (min within 5 degrees), 925hPa land-windspeed (max within 6 degrees), precipitation (area average over 5 degrees).\r\n\r\nThis data was collected as part of Robust Spatial Projections for the Real World (Real Projections) NERC (Natural Environment Research Council) NE/N018486/1." } ], "responsiblepartyinfo_set": [ 109291, 109292, 109285, 109286, 109293, 109288, 109289, 109290, 109287, 109294, 168804, 109295, 109296, 109297 ], "onlineresource_set": [ 24732, 94829, 94830 ] }, { "ob_id": 26102, "uuid": "cf97ccc802d348ec8a3b6f2995dfbbff", "title": "Daily MODIS (MODerate Imaging Spectroradiometer) derived cloud droplet number concentration global dataset for 2003-2015", "abstract": "Daily global cloud droplet number concentrations (Nd) have been calculated at 1x1 degree resolution from pixel-level MODIS (MODerate Imaging Spectroradiometer) Collection 5.1 Joint Level-2 (Aqua satellite) optical depth (tau) and the 3.7 micron effective radius (reff) data (and other supporting data) using the adiabatic cloud assumption (liquid water content increases linearly with height, Nd is constant throughout the cloud depth and the ratio of the volumne mean radius to the effective radius is assumed constant). \r\n\r\nThe Nd data is contained in separate NetCDF files for each year for the period 2003-2015. Nd is contained in the \"Nd\" variable and has units of cm^{-3}. This is a 360x180xNdays (lon x lat x Ndays) sized array, where Ndays is the number of days in the year. The lon x lat grid is a regular 1x1 degree grid. The time is provided as both a 1D array of size Ndays (\"time\") with units of days since 1st Jan, 1970 and an array of size Ndays x 3 (\"time_vec\") that contains numbers for the year month and day for each of the Ndays entries.\r\n \r\nA number of filters have been applied to the data in order to remove retrievals that are likely to be problematic, or to violate the adiabatic cloud assumptions. Data is only included if:\r\n\r\n 1) Pixels are determined to be liquid pixels by MODIS.\r\n 2) The 1x1 degree mean cloud top height (calculated using the MODIS cloud top temperature and the sea surface temperature) is below 3.2km.\r\n 3) The 1x1 degree liquid cloud fraction was larger than 80%.\r\n 4) The 1x1 degree mean solar zenith angle was 65 degrees or less to avoid biases at high angles (Grosvenor and Wood, 2014).\r\n\t\t\t\t\t\t\r\n Note, that the filtering is different to that described in Grosvenor, AMTD, 2018 in the following ways :-\r\n\r\n 1) 1km resolution tau and reff are used to calculate Nd, which is then aggregated to 1x1 degree resolution (rather than using 1x1 degree tau and reff).\r\n 2) Only Nd based on the 3.7 micron reff retrieval is provided here.\r\n 3) No filtering for the presence of sea-ice is done here - it is recommended that this is done if using for high latitudes.\r\n 4) The data here is not restricted to tau>5.\r\n\t\t\t\t\t\t\t\t\t\t\t\t\r\nAlso note that the vertical penetration bias correction described in Grosvenor, AMTD, 2018 is NOT applied here. In addition, as described in the latter paper, further pixel-level screening is performed in order to select high quality data.\r\n\r\nDetails on the reasons for restricting to low solar zenith angles can be found in Grosvenor and Wood, ACP, 2014. Information on the pixel level filtering applied can be found in Grosvenor et al., AMTD, 2018 (noting the differences explained above). A comparison of this dataset with others can be found in Grosvenor et al., Reviews of Geophysics, 2018.\r\n\r\nThis dataset calculates a product that is not provided as standard by MODIS. It uses improved optical depth and effective radius data compared to the standard MODIS Level-3 data since situations (e.g., high solar zenith angles, broken clouds) that have been shown to cause retrieval issues have been filtered out at the Level-2 stage before being averaged into Level-3 droplet concentration data.\r\n", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T03:05:58", "updateFrequency": "notPlanned", "dataLineage": "The data upon which this dataset was based was downloaded in the form of Collection 5.1 Joint Level-2 cloud product swaths (MYDATML files) from the MODIS-Aqua satellite instrument via the MODIS FTP service. They were then processed using Matlab following the methods described above onto a regular 1x1 degree grid with separate values stored for each overpass of a given gridbox. Overpasseses with a solar zenith angles larger than 65 degrees were not included in the subsequent averaging to daily values.\r\n", "removedDataReason": "", "keywords": "", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2018-05-23T15:54:22", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2203, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 26100, "dataPath": "/badc/deposited2018/grosvenor_modis_droplet_conc/data", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2461071312, "numberOfFiles": 14, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 7051, "startTime": "2003-01-01T00:00:00", "endTime": "2015-12-31T23:59:59" }, "resultQuality": { "ob_id": 3129, "explanation": "Research Data", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2018-05-18" }, "validTimePeriod": { "ob_id": 7050, "startTime": "2003-01-01T00:00:00", "endTime": "2015-12-31T23:59:59" }, "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": [], "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": 26101, "uuid": "373db968ae0a4cb2bc0293c12d4f7807", "short_code": "proj", "title": "University of Washington postdoctoral work for Rob Wood.", "abstract": "Postdoctoral work with Rob Wood funded by the University of Washington." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 3894, 18405, 18408, 24302, 24303 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 30129, "uuid": "3b0630c7fa264164868d4da5c9f90bed", "short_code": "coll", "title": "National Centre for Earth Observation (NCEO) Third Party Data", "abstract": "The National Centre for Earth Observation (NCEO) Third Party data contains a broad range remotely sensed data acquired by satellite for use by the Earth Observation Scientific community supported by NCEO. The Centre for Environmental Data Analysis (CEDA) has archived and provides access to extensive Earth observation datasets under strict licensing conditions. Please see the individual dataset records for conditions of use." } ], "responsiblepartyinfo_set": [ 109316, 109318, 109319, 109320, 109322, 109323, 109324, 109321, 109317 ], "onlineresource_set": [ 24705, 24706, 24707 ] }, { "ob_id": 26112, "uuid": "9f8dfaf790644dbcb2c3f69f409a70d6", "title": "UKCP18 Probabilistic Projections on a 25km grid over the UK for 1961-2100", "abstract": "This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe data represents anomalies with respect to the baseline periods 1961-1990, 1981-2000 and 1981-2010, and cover the period 1 Dec 1960 to 30 Nov 2099. Gridded data on a 25km grid over the United Kingdom, the Isle of Man and the Channel Islands is provided. Further information on this dataset and UKCP18 can be found under UK Climate Projections (UKCP18) guidance and reports in the documentation section.\r\n\r\nThe Probabilistic Projections were updated on 4th August 2022, to make improvements to the methodology to improve: consistency between maximum, minimum and mean temperature; consistency in the downscaling; statistical treatment of precipitation particularly at the wet and dry extremes; representation of annual and decadal variability; and adjustment of the data in the 1981-2000 baseline period to ensure the anomalies average to zero. The combination of the improvements means that all variables are modified to some degree. For more information, please refer to the UKCP news article and the documents it links to under UK Climate Projections News in the documentation section.\r\n\r\nOn 11th February 2025, the Probabilistic Projections were updated to include information at global warming levels. This information is available for each of the RCP scenarios as cumulative distribution frequency data. Further information about this global warming levels data and approach can be found in the relevant UKCP news article and the guidance document it links to under UK Climate Projections News in the documentation section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-02-11T09:52:53", "updateFrequency": "asNeeded", "dataLineage": "Data provided by the UK Met Office", "removedDataReason": "", "keywords": "UK, Climate, Projections, UKCP18, Probabilistic, Uncertainty", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2218, "bboxName": "", "eastBoundLongitude": 4.59, "westBoundLongitude": -12.61, "southBoundLatitude": 48.83, "northBoundLatitude": 60.57 }, "verticalExtent": null, "result_field": { "ob_id": 26124, "dataPath": "/badc/ukcp18/data/land-prob/uk/25km", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 7260791807012, "numberOfFiles": 93036, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 7052, "startTime": "1961-01-01T00:00:00", "endTime": "2100-12-30T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26113, "uuid": "a3ff0eb099e34980a0d694cd57100a7b", "short_code": "comp", "title": "UKCP18 Probabilistic Climate Projections for the UK on a 25km grid", "abstract": "The probabilistic projections combine information from several collections of earth system climate models, including the HadCM3 family of Met Office Hadley Centre climate models, and earth system climate models from other climate centres contributing to CMIP5 (Coupled Model Intercomparison Project Phase 5) and the 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, 2013).\n\nThe leading sources of modelling uncertainty in the atmosphere, land surface, ocean, sulphur cycle, and terrestrial carbon cycle components of the climate system are sampled, and simulated responses are weighted by the likelihood for predicting a large multivariate set of climate observables. Observationally constrained uncertainty estimates for ranges of future climate are provided in the form of probability distribution functions or large sets of probabilistic realizations, for the RCP2.6, RCP4.5, RCP6.0, RCP8.5 and SRES-A1B emission-driven scenarios." }, "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": 26111, "uuid": "b94590a87114418281a859d391ab5641", "short_code": "proj", "title": "UKCP18: The Land Component of the UK Climate Projections 2018", "abstract": "The land component of the UKCP18 project is comprised of:\r\nA set of probabilistic projections over the UK for multiple scenarios at various temporal and spatial scales.\r\nGlobal and UK-scale simulations at global climate model resolution.\r\nUK-scale simulations at regional climate model resolution." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6023, 11484, 11485, 11486, 50510, 50512, 50515, 50516, 50517, 50518, 50529, 50530, 50531, 50532, 50533, 50534, 50535, 50536, 50537, 50538, 50542, 50543, 51188, 51189, 57971, 57972, 57973, 57974, 57975, 57976, 57977, 57978, 57979, 57980, 57981, 57982, 57983 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26156, "uuid": "9842e395f2d04f48a177c3550756bf98", "short_code": "coll", "title": "UKCP18 Probabilistic Climate Projections", "abstract": "Probabalistic climate projections for the UK from 1961-2100 produced by the Met Office for UK Climate Projections 2018 (UKCP18). The data is available on a 25km OSGB grid." } ], "responsiblepartyinfo_set": [ 110941, 110999, 111000, 111001, 111003, 111005, 111034, 148002, 111004 ], "onlineresource_set": [ 25942, 27329, 52687, 94576 ] }, { "ob_id": 26114, "uuid": "8eca5b80ee244d9486162e699c5197f5", "title": "UKCP18 Probabilistic Projections by Administrative Regions over the UK for 1961-2100", "abstract": "\"This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe data represents anomalies with respect to the baseline period 1981-2000, and cover the period 1 Dec 1960 to 30 Nov 2099. Data for 16 administrative regions in the UK is provided. Further information on this dataset and UKCP18 can be found in the documentation section.\r\n\r\nThe Probabilistic Projections were updated on 4th August 2022, to make improvements to the methodology to improve: consistency between maximum, minimum and mean temperature; consistency in the downscaling; statistical treatment of precipitation particularly at the wet and dry extremes; representation of annual and decadal variability; and adjustment of the data in the 1981-2000 baseline period to ensure the anomalies average to zero. The combination of the improvements means that all variables are modified to some degree. For more information, please refer to the UKCP news article and the documents it links to under UK Climate Projections (UKCP18) news in the documentation section.\r\n\r\nOn 11th February 2025, the Probabilistic Projections were updated to include information at global warming levels. This information is available for each of the RCP scenarios as cumulative distribution frequency data. Further information about this global warming levels data and approach can be found in the relevant UKCP news article and the guidance document it links to under UK Climate Projections (UKCP18) news in the documentation section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-02-11T10:02:34", "updateFrequency": "asNeeded", "dataLineage": "Data provided by the UK Met Office", "removedDataReason": "", "keywords": "UK, Climate, Projections, UKCP18, Probabilistic, Uncertainty", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2018-06-06T11:00:00", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2219, "bboxName": "", "eastBoundLongitude": 1.76, "westBoundLongitude": -8.18, "southBoundLatitude": 49.86, "northBoundLatitude": 60.86 }, "verticalExtent": null, "result_field": { "ob_id": 26125, "dataPath": "/badc/ukcp18/data/land-prob/uk/region", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 56654336542, "numberOfFiles": 3981, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 7053, "startTime": "1961-01-01T00:00:00", "endTime": "2100-12-30T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26141, "uuid": "6e6bf8ba72b9495398b444e10d68b6e8", "short_code": "comp", "title": "UKCP18 Probabilistic Climate Projections for the UK Administrative Regions", "abstract": "The probabilistic projections combine information from several collections of earth system climate models, including the HadCM3 family of Met Office Hadley Centre climate models, and earth system climate models from other climate centres contributing to CMIP5 (Coupled Model Intercomparison Project Phase 5) and the 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, 2013).\n\nThe leading sources of modelling uncertainty in the atmosphere, land surface, ocean, sulphur cycle, and terrestrial carbon cycle components of the climate system are sampled, and simulated responses are weighted by the likelihood for predicting a large multivariate set of climate observables. 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The data is available on a 25km OSGB grid." } ], "responsiblepartyinfo_set": [ 110942, 111006, 111007, 111008, 111010, 111012, 111035, 143638, 111011 ], "onlineresource_set": [ 24814, 24815, 24816, 24817, 24818, 52689, 94578, 85298, 85299, 85297 ] }, { "ob_id": 26115, "uuid": "10538cf7a8d84e5e872883ea09a674f3", "title": "UKCP18 Probabilistic Projections by UK River Basins for 1961-2100", "abstract": "This data represents the probabilistic climate projections component of the past (observed) and future climate scenario projections data, produced as part of the UK Climate Projections 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe data represents anomalies with respect to the baseline period 1981-2000, and cover the period 1 Dec 1960 to 30 Nov 2099. Data for 23 river basin regions in the UK is provided.\r\n\r\nThe Probabilistic Projections were updated on 4th August 2022, to make improvements to the methodology to improve: consistency between maximum, minimum and mean temperature; consistency in the downscaling; statistical treatment of precipitation particularly at the wet and dry extremes; representation of annual and decadal variability; and adjustment of the data in the 1981-2000 baseline period to ensure the anomalies average to zero. The combination of the improvements means that all variables are modified to some degree. For more information, please refer to the UKCP news article and the documents it links to.\r\n\r\nOn 11th February 2025, the Probabilistic Projections were updated to include information at global warming levels. This information is available for each of the RCP scenarios as cumulative distribution frequency data. 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Data for 8 'country' regions in the UK is provided: Channel Islands, England, England and Wales, Isle of Man, Northern Ireland, Scotland, United Kingdom, Wales. Further information on this dataset and UKCP18 can be found in the documentation section.\r\n\r\nThe Probabilistic Projections were updated on 4th August 2022, to make improvements to the methodology to improve: consistency between maximum, minimum and mean temperature; consistency in the downscaling; statistical treatment of precipitation particularly at the wet and dry extremes; representation of annual and decadal variability; and adjustment of the data in the 1981-2000 baseline period to ensure the anomalies average to zero. The combination of the improvements means that all variables are modified to some degree. 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Further information about this global warming levels data and approach can be found in the relevant UKCP news article and the guidance document it links to under UK Climate Projections (UKCP18) news in the documentation section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-02-11T09:56:33", "updateFrequency": "asNeeded", "dataLineage": "Data provided by the UK Met Office", "removedDataReason": "", "keywords": "UK, Climate, Projections, UKCP18, Probabilistic, Uncertainty", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2018-06-06T11:00:00", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2221, "bboxName": "", "eastBoundLongitude": 1.76, "westBoundLongitude": -8.18, "southBoundLatitude": 49.16, "northBoundLatitude": 60.86 }, "verticalExtent": null, "result_field": { "ob_id": 26127, "dataPath": "/badc/ukcp18/data/land-prob/uk/country", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 28418507566, "numberOfFiles": 3982, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 7055, "startTime": "1961-01-01T00:00:00", "endTime": "2100-12-30T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26143, "uuid": "6dd83819d5954787815b4e2c849b07ad", "short_code": "comp", "title": "UKCP18 Probabilistic Climate Projections for UK Countries", "abstract": "The probabilistic projections combine information from several collections of earth system climate models, including the HadCM3 family of Met Office Hadley Centre climate models, and earth system climate models from other climate centres contributing to CMIP5 (Coupled Model Intercomparison Project Phase 5) and the 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, 2013).\n\nThe leading sources of modelling uncertainty in the atmosphere, land surface, ocean, sulphur cycle, and terrestrial carbon cycle components of the climate system are sampled, and simulated responses are weighted by the likelihood for predicting a large multivariate set of climate observables. 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The data is available on a 25km OSGB grid." } ], "responsiblepartyinfo_set": [ 110944, 111020, 111021, 111022, 111024, 111026, 111037, 143633, 111025 ], "onlineresource_set": [ 24826, 24827, 24828, 24825, 24824, 27373, 52686, 94577 ] }, { "ob_id": 26117, "uuid": "97bc0c622a24489aa105f5b8a8efa3f0", "title": "UKCP18 Global Projections at 60km Resolution for 1900-2100", "abstract": "Global climate model projections for the CMIP5 RCP8.5 emissions scenario produced as part of the UK Climate Projection 2018 (UKCP18) project. Data has been produced by the UK Met Office Hadley Centre, and provides information on changes in 21st century climate for the UK, helping to inform adaptation to a changing climate. \r\n\r\nThe set of 28 projections is a combination of 15 coupled model simulations produced by the Met Office Hadley Centre, and 13 coupled simulations from CMIP5 contributed by different climate modelling centres.\r\n\r\nThis data set provides information on changes in climate across the entire globe from 1900 to 2100 for RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across many climate variables at different times and spatial locations.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2020-12-25T01:57:57", "updateFrequency": "asNeeded", "dataLineage": "Data provided by the UK Met Office", "removedDataReason": "", "keywords": "UK, Climate, Projections, UKCP18, Global, Simulation, Model, Runs, RCP8.5, rcp85", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2018-11-26T09:00:00", "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": 26128, "dataPath": "/badc/ukcp18/data/land-gcm/global/60km", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 29925429832525, "numberOfFiles": 17114, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 7056, "startTime": "1900-01-01T00:00:00", "endTime": "2100-12-30T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26118, "uuid": "09449d597ed64c119a1e150e4fd1e9fe", "short_code": "comp", "title": "UKCP18 Global Projections", "abstract": "The data is provided at 60km resolution, the native resolution of the 15 Met Office Hadley Centre projections. \n\nThe CMIP5 projections have been regridded to this resolution. The Met Office Hadley Centre projections are all variants of the global coupled models HadGEM3-GC3.05, differing only in the choice of values assigned to 52 model parameters that control the strength of processes that affect the climate system and how it responds to anthropogenic emissions. The set of parameters to perturb was chosen by expert elicitation. A subset of these HadGEM3-3.05 projections were used to drive the UKCP18 Regional Projections. \n\nThe model is configured to run using a N216 Gaussian grid which has a 60km resolution over the UK." }, "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": 26111, "uuid": "b94590a87114418281a859d391ab5641", "short_code": "proj", "title": "UKCP18: The Land Component of the UK Climate Projections 2018", "abstract": "The land component of the UKCP18 project is comprised of:\r\nA set of probabilistic projections over the UK for multiple scenarios at various temporal and spatial scales.\r\nGlobal and UK-scale simulations at global climate model resolution.\r\nUK-scale simulations at regional climate model resolution." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6023, 9042, 9043, 9045, 19043, 50416, 50498, 50510, 50517, 51184, 51185, 51186, 51187, 51190, 51191, 51192, 51193, 51194, 51195, 51196, 51197, 51198, 51199, 51200, 51201, 51202, 51203, 51204, 54707, 56769, 56770, 56771, 56772, 56773, 56774, 56775, 56776, 56777 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26157, "uuid": "f1a2fc3c120f400396a92f5de84d596a", "short_code": "coll", "title": "UKCP18 Global Climate Model Projections for the entire globe", "abstract": "Global climate model runs from 1900-2100 produced by the Met Office for UK Climate Projections 2018 (UKCP18) using the HadGEM3 climate model. The data is available at daily and monthly temporal resolutions on a N216 Gaussian grid which has a 60km resolution over the UK." } ], "responsiblepartyinfo_set": [ 110945, 111027, 111028, 111029, 111031, 111033, 111038, 143645, 111032 ], "onlineresource_set": [ 25943, 27365, 94565 ] }, { "ob_id": 26119, "uuid": "fd2eb396a33247aa9945d61e88e63c88", "title": "UKCP18 Time-series Analyses of Sea Surface Elevation around the UK for 2007-2100", "abstract": "The data are simulated 21st century trends in the one-year return level (i.e. the location parameter) of skew surge due to simulated atmospheric storminess change only. No mean sea level change is included. The data were produced to investigate the magnitude of this component of extreme sea level change and to give an estimate of the minimum uncertainty in this component. To produce the data, atmospheric storminess data from five CMIP5 models was downscaled by the Swedish Meteorological and Hydrological Institute regional climate model RCA4 and used to drive the National Oceanography Centre/Met Office storm surge model CS3. The 5 largest simulated skew surges in each year were identified and a 4-parameter joint probability distribution (including a linear trend in location parameter over time) was fitted. The data given here are the trends in the location parameter from 2007 to 2099. By construction the scale parameter does not change and so the same trend applies to all return periods. The data covers the UK coast.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2018-11-21T16:12:36", "updateFrequency": "asNeeded", "dataLineage": "Data provided by the UK Met Office", "removedDataReason": "", "keywords": "", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2212, "bboxName": "", "eastBoundLongitude": 1.75, "westBoundLongitude": -10.58, "southBoundLatitude": 49.17, "northBoundLatitude": 60.83 }, "verticalExtent": null, "result_field": { "ob_id": 26152, "dataPath": "/badc/ukcp18/data/marine-sim/skew-trend", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 418201, "numberOfFiles": 2, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 7059, "startTime": "2007-01-01T00:00:00", "endTime": "2100-12-30T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26153, "uuid": "c21af5504e98474e9e4ed8f481013f98", "short_code": "comp", "title": "UKCP18 Time-series Analyses of Sea Surface Elevation Around the UK", "abstract": "The POLCS3 storm surge model was driven by climate model simulations of the 21st century under RCP8.5. Five different climate models were used. Each has first been downscaled by the SMHI regional atmospheric model RCA4. A statistical methid was used to identify trends in the most extreme storm surges. The data show these trends for various sites around the UK coastline." }, "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": [ 7026, 7028, 21657, 21658 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [], "responsiblepartyinfo_set": [ 110958, 111123, 111124, 111125, 111127, 111129, 111126, 143636, 111128 ], "onlineresource_set": [ 25960, 27377, 95106 ] }, { "ob_id": 26120, "uuid": "0f8d27b1192f41088cd6983e98faa46e", "title": "UKCP18 21st century time-mean sea level projections around the UK for 2007-2100", "abstract": "The UKCP18 21st century sea level projections are provided as spatially a continuous dataset around the UK coastline. The projections are rooted in CMIP5 climate model simulations and the process-based methods described in IPCC AR5 (Church et al, 2013). 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 1981-2000. Projections are available for the RCP2.6, RCP4.5 and RCP8.5 climate change scenarios (Meinshausen et al, 2011). Nine percentiles are provided to characterise the projection uncertainty. The 5th, 50th and 95th percentiles are equivalent to the IPCC AR5 lower, central, and upper estimate of projected sea level change, based on underlying modelling uncertainty.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section.\r\n\r\nThis dataset was updated in March 2023 to correct a minor processing error in the earlier version of the UKCP18 site-specific sea level projections relating to the adjustment applied to convert from the IPCC AR5 baseline of 1986-2005 to the baseline period of 1981-2000. The update results in about a 1 cm increase compared to the original data release for all UKCP18 site-specific sea level projections at all timescales. Further details can be found in the accompanying technical note.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2023-03-14T10:06:41", "updateFrequency": "asNeeded", "dataLineage": "Data provided by the UK Met Office", "removedDataReason": "", "keywords": "", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2213, "bboxName": "", "eastBoundLongitude": 1.75, "westBoundLongitude": -10.58, "southBoundLatitude": 49.17, "northBoundLatitude": 60.83 }, "verticalExtent": null, "result_field": { "ob_id": 26154, "dataPath": "/badc/ukcp18/data/marine-sim/msl-proj", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 479836787, "numberOfFiles": 10, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 7060, "startTime": "2007-01-01T00:00:00", "endTime": "2100-12-30T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26121, "uuid": "8d419dad0cbe41febb1f4d5ec137d82a", "short_code": "comp", "title": "UKCP18 regional time-mean sea level projections for the 21st Century", "abstract": "The UKCP18 21st Century regional time-mean sea level projections are based on CMIP5 climate model simulations of global ocean thermal expansion and global average surface temperature (GST) change. 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). 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 the UK through use of: (i) sea level fingerprints for mass components provided by Aimee Slangen and Giorgio Spada; (ii) regression relationships around the UK and across CMIP5 models for the oceanographic component; (iii) an ensemble of estimates of the relative sea level change from glacial isostatic adjustment from the NERC BRITICE_CHRONO project. Following the approach of Church et al (2013), 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. Please refer to UKCP18 documentation for detailed methods." }, "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": [ 51186, 51187, 51662, 63010, 91958 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26163, "uuid": "72407f08415c4b868c85b934033691b3", "short_code": "coll", "title": "UKCP18 Time-mean Sea Level Projections", "abstract": "Time-mean Sea Level Projections for the UK produced by the Met Office for UK Climate Projections 2018 (UKCP2018). Data has been produced by standard and exploratory methods." } ], "responsiblepartyinfo_set": [ 110959, 111130, 111131, 111132, 111134, 111136, 111133, 143639, 111135 ], "onlineresource_set": [ 24829, 25961, 27369, 83122, 95102 ] }, { "ob_id": 26122, "uuid": "a077f4058cda4cd4b37ccfbdf1a6bd29", "title": "UKCP18 exploratory extended time-mean sea level projections around the UK for 2007-2300", "abstract": "The UKCP18 exploratory extended time-mean sea level projections are provided as spatially a continuous dataset around the UK coastline for the period 2007-2300. These exploratory projections have been devised to be used seamlessly with the UKCP18 21st Century projections and provide very similar values for the period up to 2100. Users should be aware that post-2100 projections have a far greater degree of uncertainty than the 21st Century projections and should therefore be treated as illustrative of the potential future changes. Note that we cannot rule out substantially larger sea level rise in the coming centuries than is represented in the projections presented here. 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 1981-2000. Projections are available for the RCP2.6, RCP4.5 and RCP8.5 climate change scenarios (Meinshausen et al, 2011). As with the 21st Century projections, nine percentiles are provided to characterise the projection uncertainty, based on underlying modelling uncertainty. However, users should view these uncertainties with a much lower degree of confidence for the period post-2100.\r\n\r\nFurther information on this dataset and UKCP18 can be found in the documentation section.\r\n\r\nThis dataset was updated in March 2023 to correct a minor processing error in the earlier version of the UKCP18 site-specific sea level projections relating to the adjustment applied to convert from the IPCC AR5 baseline of 1986-2005 to the baseline period of 1981-2000. The update results in about a 1 cm increase compared to the original data release for all UKCP18 site-specific sea level projections at all timescales. Further details can be found in the accompanying technical note.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2023-03-14T10:09:54", "updateFrequency": "asNeeded", "dataLineage": "Data provided by the UK Met Office", "removedDataReason": "", "keywords": "", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2018-11-26T09:00:00", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2214, "bboxName": "", "eastBoundLongitude": 1.75, "westBoundLongitude": -10.58, "southBoundLatitude": 49.17, "northBoundLatitude": 60.83 }, "verticalExtent": null, "result_field": { "ob_id": 26155, "dataPath": "/badc/ukcp18/data/marine-sim/msl-proj-expl", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1500450043, "numberOfFiles": 10, "fileFormat": "Data are NetCDF formatted" }, "timePeriod": { "ob_id": 7061, "startTime": "2007-01-01T00:00:00", "endTime": "2300-12-30T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26123, "uuid": "8c04cc69ec674540bc44428e80b01ae0", "short_code": "comp", "title": "UKCP18 exploratory extended regional time-mean sea level projections", "abstract": "The UKCP18 exploratory regional time-mean sea level projections are based on a two-layer energy balance model (e.g. Gregory et al, 2015) fit to individual CMIP5 climate models. This model framework is used to provide extended projections of global thermal expansion and global average surface temperature (GST) change to 2300. 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). Global sea level contributions for dynamic ice discharge for Greenland and Antarctica are based on extrapolation of IPCC AR5 projections to 2100 and the modelling work of Levermann et al (2014), respectively. Estimates of land water storage changes follow those reported in IPCC AR5 for the 21st Century extrapolated to 2300. These global components are regionalised for the UK through use of: (i) sea level fingerprints for mass components provided by Aimee Slangen and Giorgio Spada; (ii) regression relationships around the UK and across CMIP5 models for the oceanographic component; (iii) an ensemble of estimates of the relative sea level change from glacial isostatic adjustment from the NERC BRITICE_CHRONO project. 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Data has been produced by standard and exploratory methods." } ], "responsiblepartyinfo_set": [ 110960, 111137, 111138, 111139, 111141, 111143, 111140, 143634, 111142 ], "onlineresource_set": [ 24830, 25962, 27375, 83121, 95103 ] }, { "ob_id": 26130, "uuid": "0a2f8f3d1b2c4c818f9b8f55f2eeb3e8", "title": "FAAM C074 Instrument Test flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects (Instrument) project.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2023-01-11T09:55:58", "updateFrequency": "asNeeded", "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).", "removedDataReason": "", "keywords": "Instrument, FAAM, airborne, atmospheric measurments", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2018-04-18T13:19:16.734876", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2215, "bboxName": "", "eastBoundLongitude": -0.3630272448062897, "westBoundLongitude": -5.7465596199035645, "southBoundLatitude": 50.38112258911133, "northBoundLatitude": 52.37362289428711 }, "verticalExtent": null, "result_field": { "ob_id": 26129, "dataPath": "/badc/faam/data/2018/c074-jan-18", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1314321886, "numberOfFiles": 23, "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted." }, "timePeriod": { "ob_id": 7062, "startTime": "2018-01-18T00:00:00", "endTime": "2018-01-18T23:59:59" }, "resultQuality": { "ob_id": 3074, "explanation": "Data collected by flight participants before preparation for archival with the Centre for Environmental Data Analysis (CEDA).", "passesTest": true, "resultTitle": "FAAM to CEDA Data Quality Statement", "date": "2015-09-03" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26131, "uuid": "3637a3a0e3ea4a029403feb1040f9b87", "short_code": "acq", "title": "FAAM Flight C074 Acquisition", "abstract": "FAAM Flight C074 Acquisition" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2522, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 12946, "uuid": "718a0508440b4ee4b965c6d4e5843bc5", "short_code": "proj", "title": "FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects.", "abstract": "Some flights made on board the the FAAM (Facility for Airborne Atmospheric Measurement) BAe-146 aircraft are for instrument testing, calibration or training purposes, as well as non-science demonstration flights. This flying differs from regular flights which are conducted for a specific project." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 1633, 3220, 3221, 3222, 3223, 3224, 3225, 3226, 3227, 3228, 3229, 3230, 3231, 3232, 3233, 3234, 3235, 3236, 3237, 3238, 3239, 3240, 3241, 3242, 3243, 3244, 3245, 3246, 3247, 3248, 3249, 3250, 3251, 3252, 3253, 3254, 3255, 3256, 3257, 3258, 3259, 3260, 3261, 3262, 3263, 3264, 3265, 3266, 3267, 3268, 3269, 3270, 3271, 3272, 3273, 3274, 3275, 3276, 3277, 3278, 3279, 3280, 3281, 3282, 3283, 3284, 3285, 3286, 3287, 3288, 3289, 3290, 3291, 3292, 3293, 3294, 3295, 3307, 3315, 3316, 3317, 3318, 3319, 3320, 3321, 3322, 3323, 3324, 3325, 3326, 3327, 3328, 3329, 3330, 3331, 3332, 3333, 3334, 3335, 3336, 3337, 3338, 3339, 3340, 3341, 3342, 3343, 3344, 3345, 14474, 14836, 14837, 14838, 14840, 14841, 14842, 14843, 14845, 14846, 14847, 14848, 14849, 14850, 14851, 14857, 14859, 14860, 14861, 14863, 14864, 14865, 14866, 14868, 14869, 14870, 14871, 14872, 14873, 14874, 14880, 14882, 14883, 14885, 14887, 14890, 14893, 14894, 14895, 14900, 14901, 14905, 14906, 14912, 14916, 14917, 14919, 14921, 14924, 14927, 14928, 14935, 14946, 15022, 15023, 15029, 15030, 15040, 15041, 15047, 15048, 15283, 15324, 15325, 15338, 15339, 15342, 15344, 15812, 15813, 15816, 15818, 15819, 15820, 15821, 15822, 15823, 15824, 15825, 15836, 16210, 16211, 16219, 16220, 16658, 17108, 17109, 18977, 20656, 20657, 20658, 20659, 20660, 20662, 20663, 20664, 20665, 20666, 20667, 20668, 20669, 20670, 20671, 20672, 20673, 20676, 20677, 20678, 20679, 20680, 20681, 20683, 20684, 20685, 20686, 20687, 20688, 20689, 20690, 20691, 20692, 20693, 20694, 20695, 20696, 20697, 22362, 22363, 22364, 22365, 22366, 22369, 22370, 22371, 22372, 22373, 22374, 22375, 22376, 22377, 22378, 22379, 22380, 22381, 25783, 25784, 25785, 25786, 25787, 25788, 25789, 25790, 25791, 25792, 25793, 25794, 25795, 25796, 25797, 25798, 25799, 25800, 25801, 25802, 25803, 25804, 25805, 25806, 25807, 25808, 25809, 25810, 25811, 25812, 25813, 25814, 25815, 25816, 25817, 25818, 25819, 25820, 25821, 25822, 25823, 25824, 25825, 25826, 25827, 25828, 25830, 25831, 25832, 25834, 26158 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 5782, "uuid": "affe775e8d8890a4556aec5bc4e0b45c", "short_code": "coll", "title": "Facility for Airborne Atmospheric Measurements (FAAM) flights", "abstract": "The FAAM is a large atmospheric research BAE-146 aircraft, run by the NERC (jointly with the UK Met Office until 2019). It has been in operation since March 2004 and is at the scientists' disposal through a scheme of project selection. \r\n\r\nData collected by this aircraft is stored in the FAAM data archive and includes \"core\" data, provided by the FAAM as a support to all flight campaigns, and \"non-core\" data, the nature of which depends on the scientific goal of the campaign.\r\n\r\nFAAM instruments provide four types of data: \r\n\r\n- parameters required for aircraft navigation; \r\n- meteorology; \r\n- cloud physics; \r\n- chemical composition. \r\n\r\nThe data are accompanied by extensive metadata, including flight logs. The FAAM apparatus includes a number of core instruments permanently onboard and operated by FAAM staff members, and a variety of other instruments, grouped into chemistry kit and cloud physics kit, that can be fitted onto the aircraft on demand. \r\nFAAM is also a member of the EUropean Facility for Airborne Research (EUFAR) fleet of research aircraft.\r\n\r\nAs per NERC data policy (see documents), FAAM data are openly available upon registration with the CEDA archive (anyone can register) under the Open Government Licence. Raw data are retained for longterm preservation but are not intended for general use." } ], "responsiblepartyinfo_set": [ 109337, 109338, 109339, 109342, 109343, 109344, 109345, 109346, 109340, 109341 ], "onlineresource_set": [ 24722, 24720, 24721 ] }, { "ob_id": 26135, "uuid": "9dace73ad8654298aea626b8bde0a782", "title": "Optimised global monthly mean surface flux of ethane (2008-2014) produced using the INVICAT 4D-Var inverse model", "abstract": "This data file contains two sets of optimised global surface fluxes of ethane (C2H6), produced through variational inverse methods using the TOMCAT chemical transport model, and the INVICAT inverse transport model. Emissions were produced using an iterative method of optimisation, known as 4D-Var, which minimised the model-observation differences.\r\n\r\nThese surface fluxes are produced as monthly mean values on the (approximately) 5.6 degree horizontal model grid. The associated uncertainty for the flux from each gridcell is also included. \r\n\r\nThe fluxes and uncertainties are global, and cover the period Jan 2008 - Dec 2014.\r\n \r\nThere are two alternative emissions sets, labelled EMIS_ALL and EMIS_ANTH, whilst the uncertainties are labelled ERROR_ALL and ERROR_ANTH, respectively. The two optimised emission estimates are produced through iterative minimisation of model-observation error in INVICAT. In all cases the observations are surface flask samples of ethane produced by by the National Oceanic and Atmospheric Administration’s Global Monitoring Division (NOAA GMD) and the University of Colorado’s Institute of Arctic and Alpine Research (INSTAAR). Whole air samples in flasks are collected weekly to bi-weekly at each site and C2H6 is measured using gas chromatography with a flame ionization detection method.\r\n \r\nThe EMIS_ALL fluxes are produced through variation of all surface emission types (anthropogenic, biomass burning, oceanic and biospheric), whilst the EMIS_ANTH fluxes are produced by only allowing the surface anthropogenic emissions to vary, with prior estimates of other emission types then added back on.\r\n\r\nFlux and uncertainty units are kg(C2H6)/m2/s, and time units are days since January 1st 2008. These emissions show improved performance relative to independent observations when included in the TOMCAT model. Further details about the data can be found in the PDF documentation stored along side this data, as well as in Monks et al., 2018.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2018-05-29T15:12:55", "updateFrequency": "notPlanned", "dataLineage": "Produced by C. Wilson using the INVICAT inverse model, developed at the University of Leeds, Leeds, UK. INVICAT is based on the TOMCAT chemical transport model, which was developed by M. P. 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Chipperfield, also now at the University \r\nof Leeds." }, "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": [ 1319, 1320, 4385, 24201, 24203, 57658, 57659 ], "vocabularyKeywords": [], "identifier_set": [ 9587 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 109351, 109358, 109359, 109360, 109362, 109363, 109364, 109361, 109352, 109353, 109354, 109355, 109356, 109357 ], "onlineresource_set": [ 24724, 25669 ] }, { "ob_id": 26136, "uuid": "489e9b2a0abd43a491d5afdd0d97c1a4", "title": "RAL Infrared Microwave Sounder (IMS) temperature, water vapour, ozone and surface spectral emissivity", "abstract": "The Rutherford Appleton Laboratory (RAL) Infrared Microwave Sounder (IMS) data set contains vertical profiles of temperature, water vapour, and ozone as well as surface spectral emissivity spanning infrared and microwave, surface temperature, cloud fraction and height. Data are retrieved from co-located measurements by the Infrared Atmospheric Sounding Interferometer (IASI), the Microwave Humidity Sounder (MHS) and the Advanced Microwave Sounding Unit (AMSU) on board the Eumetsat Metop satellites.\r\n\r\nDevelopment of the IMS scheme and data production were funded by the UK’s National Centre for Earth Observation (NCEO) under the Natural Environment Research Council (NERC), with additional funding from EUMETSAT contract EUM/CO/13/4600001252/THH.\r\n\r\nData were produced by the Remote Sensing Group (RSG) at the Rutherford Appleton Laboratory (RAL).\r\n\r\nThis first public release consists of a full processing of the Metop A mission from 2007 to the end of 2016, using version 2.1 of the algorithm.\r\n\r\nIMS data are produced with the horizontal sampling of IASI, ~25 x 25 km", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-10-31T01:57:21", "updateFrequency": "notPlanned", "dataLineage": "Data produced by the Rutherford Appleton Laboratory (RAL) Remote Sensing Group (RSG). The development of the Infrared Atmospheric Sounding Interferometer (IASI) IMS data was funded by the Natural Environment Research Council (NERC) through its National Centre for Earth Observation (NCEO).", "removedDataReason": "", "keywords": "IASI, MHS, AMSU, IMS retrieval, temperature, water vapour, surface emissivity, ozone", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2018-09-11T15:03:34", "doiPublishedTime": "2018-06-28T15:08:08", "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 26218, "dataPath": "/neodc/metop_ims_ral/data/v2.1/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 5448896138598, "numberOfFiles": 741201, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 7133, "startTime": "2007-05-31T23:00:00", "endTime": "2016-12-31T23:59:59" }, "resultQuality": { "ob_id": 1, "explanation": "See dataset associated documentation", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2012-08-15" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26250, "uuid": "13df5ddb2ca5479eb3697507763f6d3b", "short_code": "comp", "title": "METOP IMS RAL computation process", "abstract": "The RAL Infrared Microwave Sounder (IMS) retrieval scheme jointly retrieves height-resolved temperature, water vapour, and ozone, as well as surface spectral emissivity, effective cloud fraction, effective cloud ice fraction, and effective cloud top height, from three instruments on board the MetOp platform: the Infrared Atmospheric Sounding Interferometer (IASI), the Advanced Microwave Sounding Unit (AMSU), and the Microwave Humidity Sounder (MHS). The IMS scheme is a modified version of the EUMETSAT 1DVar IASI L2 retrieval, resulting from the study “Optimal Estimation Method retrievals with IASI, AMSU and MHS measurements” (R. Siddans et al., 2015). The IMS scheme differs from the EUMETSAT L2 scheme through the addition of microwave channels from AMSU and MHS to the measurement vector, and the addition of surface spectral emissivity and cloud to the state vector. There are also differences in the prior assumptions made by the retrieval and RTTOV coefficients used.\r\n\r\nThe IMS scheme measurement vector comprises the same subset of 139 IASI channels as the EUMETSAT L2 scheme (700-1900 cm-1), all (functioning) AMSU channels, and all MHS channels. The forward model used is RTTOV (Matricari, 2009) with v9 coefficients to allow the modelling of spatial and seasonal variation and trends in greenhouse gases.\r\n\r\nThe IMS retrieval state vector is expressed in terms of PC weights of a climatological global zonal mean covariance matrix, with 28 PC weights for the atmospheric temperature profile, 18 for the water vapour profile, 10 for the ozone profile and 20 for surface spectral emissivity. In the output files, profiles are reported on the 101 level RTTOV fixed pressure grid. \r\n\r\nA climatological zonal mean prior, scaled to match NWP, is used for temperature, water vapour and ozone, and is interpolated linearly to the latitude of each measurement. \r\n\r\nFor the retrieval of surface spectral emissivity, PCs were computed from the global covariance of the RTTOV implementation of the University of Wisconsin global infrared land surface emissivity database (Borbas and Ruston, 2010) and RTTOV microwave spectral emissivity models. Prior covariances for surface spectral emissivity are defined for the first 6 patterns using the combined RTTOV infrared and microwave atlases. Spectral correlations between the infrared and microwave emissivities are included (derived from the RTTOV representation of the spatial covariance of infrared and microwave emissivity).\r\n\r\nInitial cloud screening of IASI scenes is performed by implementing a threshold on the brightness temperature difference between observations and cloud-free simulations (based on ECMWF) at 11 microns. Scenes containing partial, thin or very-low cloud are processed by the retrieval and characterised by the retrieved cloud variables.\r\n\r\nsee documentations for additional details\r\n" }, "procedureCompositeProcess": null, "imageDetails": [ 130 ], "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": 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": [ 58082, 58083, 69637, 69638, 69639, 69640, 69641, 69642, 69643, 69644, 69645, 69646, 69647, 69648, 69649, 69650, 69651, 69652, 69653, 69654, 69655, 69656, 69657, 69658, 69659, 69660, 69661, 69662, 69663, 69664, 69665, 69666, 69667, 69668, 69669, 69670, 69671, 69672, 69673, 69674, 69675, 69676, 69677, 69678, 69679, 69680, 69681, 69682, 69683, 69684, 69685, 69686, 69687, 69688, 69689, 69690, 69691, 69692, 69693, 69694, 69695, 69696, 69697, 69698, 69699, 69700, 69701, 69702, 69703, 69704, 69705, 69706, 69707 ], "vocabularyKeywords": [], "identifier_set": [ 9618 ], "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": [ 109366, 110278, 110784, 110786, 110785, 109370, 109368, 109371, 109660, 109381, 109380, 109375, 109377, 109376, 109658, 109813 ], "onlineresource_set": [ 25055, 87457 ] }, { "ob_id": 26140, "uuid": "bf4fb57ac7f9461db27dab77c8c97cf2", "title": "Forcing files for the ECMWF Integrated Forecasting System (IFS) Single Column Model (SCM) over Indian Ocean/Tropical Pacific derived from a 10-day high resolution simulation", "abstract": "This data set consisting of initial conditions, boundary conditions and forcing profiles for the Single Column Model (SCM) version of the European Centre for Medium-range Weather Forecasts (ECMWF) model, the Integrated Forecasting System (IFS). The IFS SCM is freely available through the OpenIFS project, on application to ECMWF for a licence. The data were produced and tested for IFS CY40R1, but will be suitable for earlier model cycles, and also for future versions assuming no new boundary fields are required by a later model. The data are archived as single time-stamp maps in netCDF files. If the data are extracted at any lat-lon location and the desired timestamps concatenated (e.g. using netCDF operators), the resultant file is in the correct format for input into the IFS SCM. \r\n\r\nThe data covers the Tropical Indian Ocean/Warm Pool domain spanning 20S-20N, 42-181E. The data are available every 15 minutes from 6 April 2009 0100 UTC for a period of ten days. The total number of grid points over which an SCM can be run is 480 in the longitudinal direction, and 142 latitudinally. With over 68,000 independent grid points available for evaluation of SCM simulations, robust statistics of bias can be estimated over a wide range of boundary and climatic conditions. \r\n \r\nThe initial conditions and forcing profiles were derived by coarse-graining high resolution (4 km) simulations produced as part of the NERC Cascade project, dataset ID xfhfc (also available on CEDA). The Cascade dataset is archived once an hour. The dataset was linearly interpolated in time to produce the 15-minute resolution required by the SCM. The resolution of the coarse-grained data corresponds to the IFS T639 reduced gaussian grid (approx 32 km). The boundary conditions are as used in the operational IFS at resolution T639. The coarse graining procedure by which the data were produced is detailed in Christensen, H. M., Dawson, A. and Holloway, C. E., 'Forcing Single Column Models using High-resolution Model Simulations', in review, Journal of Advances in Modeling Earth Systems (JAMES).\r\n \r\nFor full details of the parent Cascade simulation, see Holloway et al (2012). In brief, the simulations were produced using the limited-area setup of the MetUM version 7.1 (Davies et al, 2005). The model is semi-Lagrangian and non-hydrostatic. Initial conditions were specified from the ECMWF operational analysis. A 12 km parametrised convection run was first produced over a domain 1 degree larger in each direction, with lateral boundary conditions relaxed to the ECMWF operational analysis. The 4 km run was forced using lateral boundary conditions computed from the 12 km parametrised run, via a nudged rim of 8 model grid points. The model has 70 terrain-following hybrid levels in the vertical, with vertical resolution ranging from tens of metres in the boundary layer, to 250 m in the free troposphere, and with model top at 40 km. The time step was 30 s.\r\n \r\nThe Cascade dataset did not include archived soil variables, though surface sensible and latent heat fluxes were archived. When using the dataset, it is therefore recommended that the IFS land surface scheme be deactivated and the SCM forced using the surface fluxes instead. The first day of Cascade data exhibited evidence of spin-up. It is therefore recommended that the first day be discarded, and the data used from April 7 - April 16.\r\n \r\nThe software used to produce this dataset are freely available to interested users;\r\n 1. \"cg-cascade\"; NCL software to produce OpenIFS forcing fields from a high-resolution MetUM simulation and necessary ECMWF boundary files.\r\n https://github.com/aopp-pred/cg-cascade\r\n Furthermore, software to facilitate the use of this dataset are also available, consisting of;\r\n 2. \"scmtiles\"; Python software to deploy many independent SCMs over a domain. \r\n https://github.com/aopp-pred/scmtiles\r\n 3. \"openifs-scmtiles\"; Python software to deploy the OpenIFS SCM using scmtiles.\r\n https://github.com/aopp-pred/openifs-scmtiles\r\n ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-03-02T10:24:11", "updateFrequency": "notPlanned", "dataLineage": "The high-resolution parent simulation was produced under the NERC Cascade project using the limited-area setup of the MetUM version 7.1 (Davies et al, 2005). This parent simulation was used to derive initial conditions and forcing profiles for the Single Column Model version of the Integrated Forecasting System. The data were produced for, and tested on, IFS CY40R1, but will be suitable for earlier model cycles, and also for future versions assuming no new boundary fields are required by a later model. Delivered to the CEDA Archive by the author.", "removedDataReason": "", "keywords": "NERC CASCADE", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2018-06-05T15:18:56", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2217, "bboxName": "", "eastBoundLongitude": -179.0, "westBoundLongitude": 42.0, "southBoundLatitude": -20.0, "northBoundLatitude": 20.0 }, "verticalExtent": null, "result_field": { "ob_id": 26137, "dataPath": "/badc/deposited2018/scm_in/data", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 459132246474, "numberOfFiles": 954, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 7066, "startTime": "2009-04-06T00:00:00", "endTime": "2009-04-16T22:59:59" }, "resultQuality": { "ob_id": 3131, "explanation": "Research Data", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2018-06-01" }, "validTimePeriod": { "ob_id": 7065, "startTime": "2009-04-06T00:00:00", "endTime": "2009-04-16T22:59:59" }, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26138, "uuid": "e8fe9f46c3e24a85afd29dde48856fd1", "short_code": "comp", "title": "MetUM version 7.1", "abstract": "The parent simulation was produced with the limited area version of MetUM version 7.1. This simulation was processed to produce IFS CY40R1 SCM input fields using the 'cg-cascade' software available at https://github.com/aopp-pred/cg-cascade. " }, "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": 26139, "uuid": "e33464858fd04cd0950fb33f520c4193", "short_code": "proj", "title": "Reliable Climate Projections; the Final Frontier for Stochastic Parametrisations", "abstract": "Reliable Climate Projections: the Final Frontier for Stochastic Parametrisations is a NERC-funded project studying the development of new stochastic parametrisation schemes for use in climate models. Grant number NE/P018238/1" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 51629, 51630, 51631, 51632, 51633, 51634, 51635, 51636, 51637, 51638, 51639, 51640, 51641, 51642, 51643, 51644, 51645, 51646, 51647, 51648, 51649, 51650, 51651, 51652, 51653, 51654, 51655, 51656, 51657, 51658, 51659, 51660, 51661, 51662, 51663, 51664, 51665, 51666, 51667, 51668, 51669, 51670, 51671, 51672, 51673, 51674, 51675, 51676, 51677 ], "vocabularyKeywords": [], "identifier_set": [ 9594 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 109384, 109387, 109388, 109389, 109391, 109392, 109393, 109390, 109385, 109394, 109386 ], "onlineresource_set": [ 24727, 24728, 24729, 24730, 94870 ] }, { "ob_id": 26173, "uuid": "0f4570c780ba41b19a362e774509c883", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Combined' Product, Version 03.3", "abstract": "The Soil Moisture CCI 'Combined' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these being respectively fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. \r\n\r\nThe v03.3 Combined product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T12:59:05", "updateFrequency": "notPlanned", "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project.\r\nThis dataset forms part of the v03.3 Soil Moisture CCI data (doi:10.5285/b810601740bd4848b0d7965e6d83d26c. http://dx.doi.org/10.5285/b810601740bd4848b0d7965e6d83d26c )", "removedDataReason": "", "keywords": "ESA, Soil Moisture, CCI, Combined", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2018-06-25T13:23:48", "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": 26231, "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/COMBINED/v03.3/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 12075789740, "numberOfFiles": 13942, "fileFormat": "Data is in NetCDF format" }, "timePeriod": { "ob_id": 7084, "startTime": "1978-11-01T00:00:00", "endTime": "2016-12-31T23:59:59" }, "resultQuality": { "ob_id": 3145, "explanation": "as provided by the CCI Soil Moisture team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2018-06-25" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2535, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 15, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_soilmoisture_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13332, "uuid": "c256fcfeef24460ca6eb14bf0fe09572", "short_code": "proj", "title": "ESA Soil Moisture Climate Change Initiative Project", "abstract": "The European Space Agency Soil Moisture Climate Change Initiative (Soil_Moisture_cci) project is part of the ESA Climate Change Initiative (CCI) programme, which aims to produce datasets of Essential Climate Variables (ECV's) from satellite datasets.\r\n\r\nThe Soil Moisture CCI project was set up to :\r\n - Analyse the needs of the climate research community in terms of soil moisture data.\r\n - Adapt soil moisture satellite measurements for their use by the climate research community.\r\n - Create a long-term consistent soil moisture time series, based on active and passive data, suitable for climate change studies." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 50512, 52664, 52665, 54641, 54643, 54646, 54647, 54648, 54649, 54650, 54651 ], "vocabularyKeywords": [ { "ob_id": 10246, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_soilMst", "resolvedTerm": "soil moisture" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12877, "uuid": "6e4abd45503d44f09c74ee3a0e8fefb7", "short_code": "coll", "title": "ESA Soil Moisture (SM) Climate Change Initiative (CCI) Dataset Collection", "abstract": "As part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project, three surface soil moisture datasets have been created. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP (dependent on version). The 'Combined Product' is then a blended product based on the former two data sets. The Ancillary datasets involved in their production are also available. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2017-12-31 and the Active product covering 1991-08-05 to 2017-12-31 (dependent on version). The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD) or the papers cited below. Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using the complete references as follows:\r\nVersion 2.1 and v2.2\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321\r\n\r\nVersion 3.2 onwards:\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 26166, "uuid": "b810601740bd4848b0d7965e6d83d26c", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 03.3 data collection", "abstract": "Soil Moisture data (version 03.3) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT satellite instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS. The 'Combined Product' is then a blended product based on the former two data sets. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31 and the Active product covering 1991-08-05 to 2016-12-31. The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" } ], "responsiblepartyinfo_set": [ 109475, 109476, 109477, 109478, 109479, 109480, 110068, 109481, 109483, 110069, 110070, 110071, 110072, 110073, 110074, 110075, 110076, 110077 ], "onlineresource_set": [ 24838, 24839, 24840, 24845, 24843, 24844, 24918, 24919, 24920, 25086, 25088, 25085, 25087, 24842, 42143 ] }, { "ob_id": 26174, "uuid": "bb339ff791814fc6a8b9a93d339f5bc1", "title": "APHH: Fluorescence Assay Gas Expansion measurements of OH, HO2 and RO2 made at the IAP-Beijing site during the winter and summer campaigns.", "abstract": "This dataset contains Fluorescence Assay Gas Expansion measurements of OH, HO2 and RO2 made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the winter and summer APHH-Beijing campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nThe measurements were taken using the FAGE (Fluorescence Assay by Gas Expansion) technique which is a LIF (laser induced fluorescence) that measures on-resonance fluorescence at 308 nm. HO2 and RO2 are converted to OH via reaction with NO and NO + CO respectively. \r\n\r\nThe instrument is calibrated by photolysis of known concentration of water vapour at 185 nm to generate know concentrations of OH and HO2, same method used for HO2 but NO is injected into the flow to convert HO2 to OH. RO2 is calibrated by photolysing water vapur at 185 nm to generate OH but CH4 is added to convert OH to CH3O2, then CH3O2 is converted to OH using CO and NO. The calibration was preform every three days on campaign, and from this we can convert counts measured into concentration. The units for OH, HO2 and RO2 and there associated errors is molecules cm-3. The data has been filtered for instabilities in data collection including unstable pressure, unstable online, low laser power and not going online correctly. The data has been flagged for when the values were below limit of detection.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-06-15T16:41:57.449063", "updateFrequency": "", "dataLineage": "Data produced by Atmospheric Pollution & Human Health (APHH) project participants at University of Leeds and uploaded to Centre for Environmental Data Anaylsis (CEDA) archive.", "removedDataReason": "", "keywords": "OH, HO2, RO2, China, pollution, APHH", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2018-07-26T15:52:44", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1856, "bboxName": "IAP-Beijing", "eastBoundLongitude": 116.371, "westBoundLongitude": 116.371, "southBoundLatitude": 39.974, "northBoundLatitude": 39.974 }, "verticalExtent": null, "result_field": { "ob_id": 26230, "dataPath": "/badc/aphh/data/beijing/leeds-fage/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 547061, "numberOfFiles": 3, "fileFormat": "Data are NASA Ames formatted" }, "timePeriod": { "ob_id": 7070, "startTime": "2016-11-08T00:00:00", "endTime": "2017-06-25T22:59:59" }, "resultQuality": { "ob_id": 3122, "explanation": "Data is 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": "2018-03-29" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26175, "uuid": "0220b962282a499eba90413e79e67844", "short_code": "acq", "title": "APHH: Fluorescence Assay Gas Expansion measurements of OH, HO2 and RO2 made at the IAP-Beijing site during the winter campaign", "abstract": "APHH: Fluorescence Assay Gas Expansion measurements of OH, HO2 and RO2 made at the IAP-Beijing site during the winter campaign" }, "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." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 88514 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 24817, "uuid": "648246d2bdc7460b8159a8f9daee7844", "short_code": "coll", "title": "APHH: Atmospheric measurements and model results for the Atmospheric Pollution & Human Health in a Chinese Megacity", "abstract": "The Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) Programme includes several projects making groundbased observations of meteorology, atmospheric chemical species and particulates in and around the city of Beijing. Due to the close working and exchange between the projects and overlap of instruments, this dataset collection contains measurements and related modelling study output produced by all these projects." } ], "responsiblepartyinfo_set": [ 109485, 109487, 109488, 109489, 109490, 109491, 109492, 109484, 109486, 109495 ], "onlineresource_set": [ 25302 ] }, { "ob_id": 26177, "uuid": "76b4ad364d71465d8f8b61e302eb2c4c", "title": "APHH: Solar actinic UV flux photolysis rates made at the IAP-Beijing site during the summer and winter campaigns", "abstract": "This dataset contains direct measurement of solar actinic UV flux from which photolysis frequencies are calculated made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the summer and winter APHH-Beijing campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nPhotolysis rates were derived from the product of absorption cross-section of the precursor molecule, the quantum yield of the photo-product and the actinic flux density (cm-2s-1nm-1). The actinic flux is measured between 280 - 650 nm (<1 nm resolution) using a spectral radiometer attached to a quartz receiver optic. Absorption cross sections and quantum yields are taken from the latest IUPAC recommendations. The instrument was calibrated between 250 - 750 nm using a spectral Irradiance of Standard Tungsten-Halogen lamp before and after the campaign.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T03:05:59", "updateFrequency": "", "dataLineage": "Data produced by Atmospheric Pollution & Human Health (APHH) project participants at University of Leeds and uploaded to Centre for Environmental Data Anaylsis (CEDA) archive.", "removedDataReason": "", "keywords": "spectroradiometer, photolysis frequencies, UV, actinic flux, China, APHH", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2018-07-26T15:48:05", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1856, "bboxName": "IAP-Beijing", "eastBoundLongitude": 116.371, "westBoundLongitude": 116.371, "southBoundLatitude": 39.974, "northBoundLatitude": 39.974 }, "verticalExtent": null, "result_field": { "ob_id": 26191, "dataPath": "/badc/aphh/data/beijing/leeds-specrad", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 13113945, "numberOfFiles": 3, "fileFormat": "Data are NASA Ames formatted" }, "timePeriod": { "ob_id": 7071, "startTime": "2016-11-08T00:00:00", "endTime": "2017-06-25T22:59:59" }, "resultQuality": { "ob_id": 3122, "explanation": "Data is 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": "2018-03-29" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26179, "uuid": "4429d82822a3466eb726acc5f7a71105", "short_code": "acq", "title": "APHH: Solar actinic UV flux photolysis rates made at the IAP-Beijing site during the summer campaign", "abstract": "APHH: Solar actinic UV flux photolysis rates made at the IAP-Beijing site during the summer campaign" }, "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." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 57657 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 24817, "uuid": "648246d2bdc7460b8159a8f9daee7844", "short_code": "coll", "title": "APHH: Atmospheric measurements and model results for the Atmospheric Pollution & Human Health in a Chinese Megacity", "abstract": "The Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) Programme includes several projects making groundbased observations of meteorology, atmospheric chemical species and particulates in and around the city of Beijing. Due to the close working and exchange between the projects and overlap of instruments, this dataset collection contains measurements and related modelling study output produced by all these projects." } ], "responsiblepartyinfo_set": [ 109513, 109515, 109506, 109508, 109509, 109510, 109511, 109512, 109507, 109514 ], "onlineresource_set": [ 25301 ] }, { "ob_id": 26181, "uuid": "8ed84f3c770544c49329df9b068ab662", "title": "APHH: Laser induced fluorescence (LIF) OH reactivity measurements made at the IAP-Beijing site during the winter and summer campaigns", "abstract": "This dataset contains Laser induced fluorescence (LIF) OH reactivity measurements made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the winter and summer APHH-Beijing campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nThe Leeds OH reactivity instrument measures OH reactivity by photolysing ozone at 266 nm to produce OH, decay of OH with ambient air is measured with LIF (laser induced fluorescence) at 308 nm. The results generate a bi-exponential curve and a line of best fit can be used to calculate OH lifetime. The instrument is calibrated by flowing air zero through the instrument. The units for OH reactivity is in s-1. The data has been filtered for instrument instabilities such as pressure, laser power, high background (laser scatter) and laser alignment", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-06-14T12:20:34", "updateFrequency": "", "dataLineage": "Data produced by Atmospheric Pollution & Human Health (APHH) project participants at University of Leeds and uploaded to Centre for Environmental Data Anaylsis (CEDA) archive.", "removedDataReason": "", "keywords": "OH, China, pollution, APHH", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2018-07-26T15:43:30", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1856, "bboxName": "IAP-Beijing", "eastBoundLongitude": 116.371, "westBoundLongitude": 116.371, "southBoundLatitude": 39.974, "northBoundLatitude": 39.974 }, "verticalExtent": null, "result_field": { "ob_id": 26217, "dataPath": "/badc/aphh/data/beijing/leeds-lif", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 594072, "numberOfFiles": 3, "fileFormat": "Data are NASA Ames formatted" }, "timePeriod": { "ob_id": 7072, "startTime": "2016-11-16T00:00:00", "endTime": "2017-05-25T22:59:59" }, "resultQuality": { "ob_id": 3122, "explanation": "Data is 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": "2018-03-29" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26182, "uuid": "e2cdea6a9a954413a021572ab147eb07", "short_code": "acq", "title": "APHH: Laser induced fluorescence (LIF) OH reactivity measurements made at the IAP-Beijing site during the winter and summer campaign", "abstract": "APHH: Laser induced fluorescence (LIF) OH reactivity measurements made at the IAP-Beijing site during the winter and summer campaign" }, "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." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 3356 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 24817, "uuid": "648246d2bdc7460b8159a8f9daee7844", "short_code": "coll", "title": "APHH: Atmospheric measurements and model results for the Atmospheric Pollution & Human Health in a Chinese Megacity", "abstract": "The Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) Programme includes several projects making groundbased observations of meteorology, atmospheric chemical species and particulates in and around the city of Beijing. Due to the close working and exchange between the projects and overlap of instruments, this dataset collection contains measurements and related modelling study output produced by all these projects." } ], "responsiblepartyinfo_set": [ 109541, 109532, 109534, 109535, 109536, 109537, 109538, 109539, 109540, 109533 ], "onlineresource_set": [ 24849, 25299, 25300 ] }, { "ob_id": 26183, "uuid": "7b9c3b7d3f554f48b9082bc4dcc9607c", "title": "APHH: Formaldehyde (HCHO) measurements made at the IAP-Beijing site during the winter and summer campaigns", "abstract": "This dataset contains measurements of formaldehyde using laser induced fluorescence (LIF) made at the Institute of Atmospheric Physics land station (IAP), Beijing site during the winter and summer campaigns for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. \r\n\r\nFormaldehyde concentration measurements in pptv were made using the Leeds Formaldehyde instrument which uses off-resonance laser induced fluorescence at 353 nm to detect ambient formaldehyde. The instrument was calibrated at regular intervals during the campaign using a commercial permatube containing paraformaldehyde.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-06-11T16:11:26.546484", "updateFrequency": "", "dataLineage": "Data produced by Atmospheric Pollution & Human Health (APHH) project participants at University of Leeds and uploaded to Centre for Environmental Data Anaylsis (CEDA) archive.", "removedDataReason": "", "keywords": "Formaldehyde, HCHO, Laser induced fluorescence, LIF, APHH", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2018-07-26T15:56:58", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1856, "bboxName": "IAP-Beijing", "eastBoundLongitude": 116.371, "westBoundLongitude": 116.371, "southBoundLatitude": 39.974, "northBoundLatitude": 39.974 }, "verticalExtent": null, "result_field": { "ob_id": 26190, "dataPath": "/badc/aphh/data/beijing/leeds-hcho", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2366262, "numberOfFiles": 3, "fileFormat": "Data are NASA Ames formatted" }, "timePeriod": { "ob_id": 7073, "startTime": "2016-11-09T00:00:00", "endTime": "2017-06-24T22:59:59" }, "resultQuality": { "ob_id": 3122, "explanation": "Data is 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": "2018-03-29" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26185, "uuid": "ea238adb694c4d53859ff23ca74da6d3", "short_code": "acq", "title": "APHH: Formaldehyde (HCHO) measurements made at the IAP-Beijing site during the winter and summer campaign", "abstract": "APHH: Formaldehyde (HCHO) measurements made at the IAP-Beijing site during the winter and summer campaign" }, "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." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 51678 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 24817, "uuid": "648246d2bdc7460b8159a8f9daee7844", "short_code": "coll", "title": "APHH: Atmospheric measurements and model results for the Atmospheric Pollution & Human Health in a Chinese Megacity", "abstract": "The Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) Programme includes several projects making groundbased observations of meteorology, atmospheric chemical species and particulates in and around the city of Beijing. Due to the close working and exchange between the projects and overlap of instruments, this dataset collection contains measurements and related modelling study output produced by all these projects." } ], "responsiblepartyinfo_set": [ 109544, 109546, 109547, 109548, 109549, 109550, 109551, 109552, 109545, 109564, 109565, 109553 ], "onlineresource_set": [ 25303 ] }, { "ob_id": 26187, "uuid": "065f6040ef08485db989cbd89d536167", "title": "ESA Fire Climate Change Initiative (Fire_cci): Small Fire Dataset (SFD) Burned Area pixel product for Sub-Saharan Africa, version 1.1", "abstract": "The ESA Fire Disturbance Climate Change Initiative (Fire_cci) project has produced maps of global burned area developed from satellite observations. The Small Fire Dataset (SFD) pixel products have been obtained by combining spectral information from Sentinel-2 MSI data and thermal information from MODIS MOD14MD Collection 6 active fire products.\r\n\r\nThis dataset is part of v1.1 of the Small Fire Dataset (also known as FireCCISFD11), which covers Sub-Saharan Africa for the year 2016. Data is available here at pixel resolution (0.00017966259 degrees, corresponding to approximately 20m at the Equator). Gridded data products are also available in a separate dataset.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2020-04-30T21:49:08", "updateFrequency": "notPlanned", "dataLineage": "Data was produced by the ESA Fire CCI team as part of the ESA Climate Change Initiative (CCI) and is being held on the CEDA (Centre for Environmental Data Analysis) archive as part of the ESA CCI Open Data Portal project.", "removedDataReason": "", "keywords": "ESA, CCI, Pixel, Burned Area, Fire Disturbance, Climate Change, GCOS", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "0.00017966259 degrees (~20m at Equator)", "status": "completed", "dataPublishedTime": "2018-10-12T08:43:45", "doiPublishedTime": "2018-10-12T16:00:00", "removedDataTime": null, "geographicExtent": { "ob_id": 2288, "bboxName": "CCI Fire SFD 1.1", "eastBoundLongitude": 55.0, "westBoundLongitude": -20.0, "southBoundLatitude": -35.0, "northBoundLatitude": 25.0 }, "verticalExtent": null, "result_field": { "ob_id": 26617, "dataPath": "/neodc/esacci/fire/data/burned_area/SFD/Africa/Sentinel2/pixel/v1.1/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 41917713485, "numberOfFiles": 1395, "fileFormat": "The product is a set of three single-layer GeoTIFF files (labelled JD, CL and LC in the filenames for layers 1 to 3 respectively).\r\n\r\nLayer 1 (JD): Date of the first detection; Pixel Spacing = 0.00017966259deg (approx. 20m); Pixel value = Day of the year, from 1 to 365 (or 366) . A value of 0 is included when the pixel is not burned in the month; a value of -1 is allocated to pixels that are not observed in the month; a value of -2 is allocated to pixels that are not burnable (build up areas, bare areas, , snow and/or ice, open water). Data type = Integer; Number of layers = 1; Data depth = 16\r\n\r\nLayer 2: Confidence Level; Pixel Spacing = 0.00017966259deg (approx. 20m); Pixel value = 0 to 100, where the value is the probability in percentage that the pixel is actually burned, as a result of thedifferent steps of the burned area classification. The higher the value, the higher the confidence that the pixel is actually burned. A value of 0 is allocated to pixels that are not observed in the month, or not taken into account in the burned area processing (non burnable). Data type = Byte; Number of layers = 1; Data depth = 8\r\n\r\nLayer 3: Land cover of that pixel, extracted from the CCI S2 prototype Land Cover map at 20m of Africa 2016. N is the number of the land cover categories in the reference map. It is only valid when layer 1 > 0. Pixel value is 0 to N under the following codes: 1 – Trees cover area; 2 – Shrubs cover area; 3 – Grassland; 4 – Cropland; 5 – Vegetation aquatic or regularly flooded; 6 – Lichen Mosses / Sparse vegetation; Pixel Spacing = 0.00017966259deg (approx. 20m); Datatype = Byte; Number of layers = 1; Data depth = 8" }, "timePeriod": { "ob_id": 7162, "startTime": "2016-01-01T00:00:00", "endTime": "2016-12-31T23:59:59" }, "resultQuality": { "ob_id": 3166, "explanation": "Validated by the Fire CCI team (see Product User Guide for further information)", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2018-10-04" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 26618, "uuid": "c633b45849c244f3968d450612502ffb", "short_code": "cmppr", "title": "ESA Fire_cci Burned Area SFD product, v1.1", "abstract": "The MODIS Fire_CCI Burned Area Small Fires Dataset v1.1 has been produced from Sentinel 2 data for Sub-Saharan Africa." }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "permissions": [ { "ob_id": 2539, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 19, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_fire_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13255, "uuid": "6c3584d985bd484e8beb23ff0df91292", "short_code": "proj", "title": "ESA Fire Climate Change Initiative Project (Fire CCI)", "abstract": "The European Space Agency (ESA) Fire Climate Change Initiative (Fire CCI) project, led by University of Alcala (Spain), is part of ESA's Climate Change Initiative (CCI) to produce long term datasets of Essential Climate Variables derived from global satellite data.\r\n\r\nThe Fire CCI focuses on the following issues relating to Fire Disturbance: Analysis and specification of scientific requirements relating to climate; Development and improvement of pre-processing and burned area algorithms; Inter-comparison and selection of burned area algorithms; System prototyping and production of burned area datasets; Product validation and product assessment\r\n" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [ { "ob_id": 10213, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_fire", "resolvedTerm": "fire" }, { "ob_id": 10663, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_fire", "resolvedTerm": "fire" }, { "ob_id": 11140, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_msi", "resolvedTerm": "MSI (Sentinel-2)" }, { "ob_id": 10909, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_sentinel2a", "resolvedTerm": "Sentinel-2A" } ], "identifier_set": [ 9684, 9686 ], "observationcollection_set": [ { "ob_id": 12683, "uuid": "bcef9e87740e4cbabc743d295afbe849", "short_code": "coll", "title": "ESA Fire Climate Change Initiative (Fire CCI) Dataset Collection", "abstract": "The ESA Fire Climate Change Initiative (Fire_cci) project is producing long-term datasets of burned area information from satellites, as part of the ESA Climate Change Initiative. The data is of use for those interested in historical burned patterns, fire management and emissions analysis and climate change research, by providing a consistent burned area time series. \r\n\r\nCurrent datasets consist of maps of global burned area for the years 1982 to 2019. Products are available at different spatial resolutions: the Pixel product (at the original resolution of the sensor data) and the Grid product (0.25 degrees resolution), the latter of which is produced from the Pixel product. They are based upon spectral information from different sensors, and in many cases also thermal information from active fires.\r\n\r\nGlobal products: \r\n\r\nFireCCI41: Medium Resolution Imaging Spectrometer (MERIS) reflectance, on board the ENVISAT ESA satellite, 300m spatial resolution, and MODIS active fires. Temporal resolution: 2005 – 2011.\r\nFireCCI50: Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and active fires, on board the TERRA satellite, 250m spatial resolution, temporal resolution: 2001 – 2016.\r\nFireCCI51: Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and active fires, on board the TERRA satellite, 250m spatial resolution, temporal resolution: 2001 – 2019.\r\n\r\nFireCCILT10 (beta product): Advanced Very High Resolution Radiometer (AVHRR) Land Long Term Data Record (LTDR) reflectance. Provided only as grid product. Temporal resolution: 1982-2017.\r\n\r\nContinental products:\r\n\r\nFireCCISFD11: Multispectral Instrument (MSI) reflectance, on board the Sentinel-2A satellite, 20 spatial resolution, and MODIS active fires. Temporal resolution: 2016, spatial coverage: Sub-Saharan Africa." } ], "responsiblepartyinfo_set": [ 109572, 109573, 109574, 109597, 109571, 142473, 142474, 109570, 109575, 109598, 109577, 109578, 109588, 109580 ], "onlineresource_set": [ 24867, 24866, 24865, 24864, 87453, 87454, 87455 ] }, { "ob_id": 26188, "uuid": "4f377defc2454db9b2a6d032abfd0cbd", "title": "ESA Fire Climate Change Initiative (Fire_cci): AVHRR-LTDR Burned Area Grid product, version 1.0", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. The AVHRR - LTDR Grid v1.0 product described here contains gridded data of global burned area derived from spectral information from the AVHRR (Advanced Very High Resolution Radiometer) Land Long Term Data Record (LTDR) v5 dataset produced by NASA.\r\n\r\nThe dataset provides monthly information on global burned area on a 0.25 x 0.25 degree resolution grid from 1982 to 2017. The year 1994 is omitted as there was not enough input data for this year. For further information on the product and its format see the product user guide.\r\n\r\nThis v1.0 product is released as a beta version; only the gridded version of the data is available.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-12-17T17:01:46", "updateFrequency": "notPlanned", "dataLineage": "Data was produced by the ESA Fire CCI team as part of the ESA Climate Change Initiative (CCI) and is being held on the CEDA (Centre for Environmental Data Analysis) archive as part of the ESA CCI Open Data Portal project. \r\n\r\nData has been derived from spectral infomration from the AVHRR Land Long Term Data Record (LTDR) product version 5 dataset (https://ltdr.modaps.eosdis.nasa.gov/cgi-bin/ltdr/ltdrPage.cgi)", "removedDataReason": "", "keywords": "ESA, CCI, Pixel, Burned Area, Fire Disturbance, Climate Change, GCOS Essential Climate Variable", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "0.25 degree", "status": "superseded", "dataPublishedTime": "2019-03-12T10:50:15", "doiPublishedTime": "2019-03-12T10:56:27", "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": 27394, "dataPath": "/neodc/esacci/fire/data/burned_area/AVHRR-LTDR/grid/v1.0/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 40555281206, "numberOfFiles": 457, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 7349, "startTime": "1982-01-01T00:00:00", "endTime": "2017-12-31T23:59:59" }, "resultQuality": { "ob_id": 3271, "explanation": "This dataset is provided as a beta product.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-03-06" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 27395, "uuid": "21f6fbc65f78425292369fd24697f3c6", "short_code": "cmppr", "title": "ESA Fire_cci AVHRR-LTDR Burned Area Grid product", "abstract": "The AVHRR-LTDR Burned Area Grid product has been produced from data from the AVHRR series of instruments using the AVHRR Land Long Term Data Record (LTDR) product version 5 dataset (https://ltdr.modaps.eosdis.nasa.gov/cgi-bin/ltdr/ltdrPage.cgi) \r\n\r\nGridded burned area products have been produced using an algorithm from the ESA Climate Change Initiative Fire project." }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2539, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 19, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_fire_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13255, "uuid": "6c3584d985bd484e8beb23ff0df91292", "short_code": "proj", "title": "ESA Fire Climate Change Initiative Project (Fire CCI)", "abstract": "The European Space Agency (ESA) Fire Climate Change Initiative (Fire CCI) project, led by University of Alcala (Spain), is part of ESA's Climate Change Initiative (CCI) to produce long term datasets of Essential Climate Variables derived from global satellite data.\r\n\r\nThe Fire CCI focuses on the following issues relating to Fire Disturbance: Analysis and specification of scientific requirements relating to climate; Development and improvement of pre-processing and burned area algorithms; Inter-comparison and selection of burned area algorithms; System prototyping and production of burned area datasets; Product validation and product assessment\r\n" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 1050, 6021, 6022, 6023, 6337, 6338, 11747, 18512, 18514, 18515, 18516, 18517, 22894, 22895 ], "vocabularyKeywords": [ { "ob_id": 10663, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_fire", "resolvedTerm": "fire" } ], "identifier_set": [ 10498, 10499 ], "observationcollection_set": [ { "ob_id": 12683, "uuid": "bcef9e87740e4cbabc743d295afbe849", "short_code": "coll", "title": "ESA Fire Climate Change Initiative (Fire CCI) Dataset Collection", "abstract": "The ESA Fire Climate Change Initiative (Fire_cci) project is producing long-term datasets of burned area information from satellites, as part of the ESA Climate Change Initiative. The data is of use for those interested in historical burned patterns, fire management and emissions analysis and climate change research, by providing a consistent burned area time series. \r\n\r\nCurrent datasets consist of maps of global burned area for the years 1982 to 2019. Products are available at different spatial resolutions: the Pixel product (at the original resolution of the sensor data) and the Grid product (0.25 degrees resolution), the latter of which is produced from the Pixel product. They are based upon spectral information from different sensors, and in many cases also thermal information from active fires.\r\n\r\nGlobal products: \r\n\r\nFireCCI41: Medium Resolution Imaging Spectrometer (MERIS) reflectance, on board the ENVISAT ESA satellite, 300m spatial resolution, and MODIS active fires. Temporal resolution: 2005 – 2011.\r\nFireCCI50: Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and active fires, on board the TERRA satellite, 250m spatial resolution, temporal resolution: 2001 – 2016.\r\nFireCCI51: Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and active fires, on board the TERRA satellite, 250m spatial resolution, temporal resolution: 2001 – 2019.\r\n\r\nFireCCILT10 (beta product): Advanced Very High Resolution Radiometer (AVHRR) Land Long Term Data Record (LTDR) reflectance. Provided only as grid product. Temporal resolution: 1982-2017.\r\n\r\nContinental products:\r\n\r\nFireCCISFD11: Multispectral Instrument (MSI) reflectance, on board the Sentinel-2A satellite, 20 spatial resolution, and MODIS active fires. Temporal resolution: 2016, spatial coverage: Sub-Saharan Africa." } ], "responsiblepartyinfo_set": [ 109601, 109602, 109603, 109600, 109626, 142206, 142207, 109599, 109627, 109604, 114501, 109617, 109609 ], "onlineresource_set": [ 24871, 24868, 24869, 24870, 87520 ] }, { "ob_id": 26189, "uuid": "4b0773a84e8142c688a628c9ce62d4ec", "title": "ESA Fire Climate Change Initiative (Fire_cci): Small Fire Database (SFD) Burned Area grid product for Sub-Saharan Africa, version 1.1", "abstract": "The ESA Fire Disturbance Climate Change Initiative (Fire_cci) project has produced maps of global burned area developed from satellite observations. The Small Fire Database (SFD) pixel products have been obtained by combining spectral information from Sentinel-2 MSI data and thermal information from MODIS MOD14MD Collection 6 active fire products.\r\n\r\nThis gridded dataset has been derived from the Small Fire Database (SFD) Burned Area pixel product for Sub-Saharan Africa, v1.1 (also available), which covers Sub-Saharan Africa for the year 2016, by summarising its burned area information into a regular grid covering the Earth at 0.25 x 0.25 degrees resolution and at monthly temporal resolution.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2019-01-29T10:31:39.120085", "updateFrequency": "notPlanned", "dataLineage": "Data was produced by the ESA Fire CCI team as part of the ESA Climate Change Initiative (CCI) and is being held on the CEDA (Centre for Environmental Data Analysis) archive as part of the ESA CCI Open Data Portal project.", "removedDataReason": "", "keywords": "ESA, CCI, Grid, Burned Area, Fire Disturbance, Climate Change, GCOS Essential Climate Variable", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "0.25 degrees", "status": "completed", "dataPublishedTime": "2019-02-08T14:48:44", "doiPublishedTime": "2019-02-08T14:51:09", "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": 27005, "dataPath": "/neodc/esacci/fire/data/burned_area/SFD/Africa/Sentinel2/grid/v1.1/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 555110314, "numberOfFiles": 15, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 7269, "startTime": "2016-01-01T00:00:00", "endTime": "2016-12-31T23:59:59" }, "resultQuality": { "ob_id": 3224, "explanation": "Validated by the Fire CCI team (see Product User Guide for further information)", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2019-01-29" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 26618, "uuid": "c633b45849c244f3968d450612502ffb", "short_code": "cmppr", "title": "ESA Fire_cci Burned Area SFD product, v1.1", "abstract": "The MODIS Fire_CCI Burned Area Small Fires Dataset v1.1 has been produced from Sentinel 2 data for Sub-Saharan Africa." }, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1140, "name": "ESACCI" } ], "permissions": [ { "ob_id": 2539, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 19, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_fire_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13255, "uuid": "6c3584d985bd484e8beb23ff0df91292", "short_code": "proj", "title": "ESA Fire Climate Change Initiative Project (Fire CCI)", "abstract": "The European Space Agency (ESA) Fire Climate Change Initiative (Fire CCI) project, led by University of Alcala (Spain), is part of ESA's Climate Change Initiative (CCI) to produce long term datasets of Essential Climate Variables derived from global satellite data.\r\n\r\nThe Fire CCI focuses on the following issues relating to Fire Disturbance: Analysis and specification of scientific requirements relating to climate; Development and improvement of pre-processing and burned area algorithms; Inter-comparison and selection of burned area algorithms; System prototyping and production of burned area datasets; Product validation and product assessment\r\n" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6021, 6022, 6023, 50416, 57314, 57317, 59231, 59233, 59234, 59235, 59236, 59237, 68093, 68094 ], "vocabularyKeywords": [ { "ob_id": 10663, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_fire", "resolvedTerm": "fire" }, { "ob_id": 11140, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_msi", "resolvedTerm": "MSI (Sentinel-2)" }, { "ob_id": 10909, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_sentinel2a", "resolvedTerm": "Sentinel-2A" } ], "identifier_set": [ 10212, 10220 ], "observationcollection_set": [ { "ob_id": 12683, "uuid": "bcef9e87740e4cbabc743d295afbe849", "short_code": "coll", "title": "ESA Fire Climate Change Initiative (Fire CCI) Dataset Collection", "abstract": "The ESA Fire Climate Change Initiative (Fire_cci) project is producing long-term datasets of burned area information from satellites, as part of the ESA Climate Change Initiative. The data is of use for those interested in historical burned patterns, fire management and emissions analysis and climate change research, by providing a consistent burned area time series. \r\n\r\nCurrent datasets consist of maps of global burned area for the years 1982 to 2019. Products are available at different spatial resolutions: the Pixel product (at the original resolution of the sensor data) and the Grid product (0.25 degrees resolution), the latter of which is produced from the Pixel product. They are based upon spectral information from different sensors, and in many cases also thermal information from active fires.\r\n\r\nGlobal products: \r\n\r\nFireCCI41: Medium Resolution Imaging Spectrometer (MERIS) reflectance, on board the ENVISAT ESA satellite, 300m spatial resolution, and MODIS active fires. Temporal resolution: 2005 – 2011.\r\nFireCCI50: Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and active fires, on board the TERRA satellite, 250m spatial resolution, temporal resolution: 2001 – 2016.\r\nFireCCI51: Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and active fires, on board the TERRA satellite, 250m spatial resolution, temporal resolution: 2001 – 2019.\r\n\r\nFireCCILT10 (beta product): Advanced Very High Resolution Radiometer (AVHRR) Land Long Term Data Record (LTDR) reflectance. Provided only as grid product. Temporal resolution: 1982-2017.\r\n\r\nContinental products:\r\n\r\nFireCCISFD11: Multispectral Instrument (MSI) reflectance, on board the Sentinel-2A satellite, 20 spatial resolution, and MODIS active fires. Temporal resolution: 2016, spatial coverage: Sub-Saharan Africa." } ], "responsiblepartyinfo_set": [ 109630, 109631, 109632, 109629, 109655, 142475, 142476, 109628, 109656, 109633, 109635, 109636, 109646, 109638 ], "onlineresource_set": [ 24873, 24874, 24875, 24872 ] }, { "ob_id": 26192, "uuid": "7ebab0df1a794d1fae245256af7de633", "title": "UKCP18 Global Projections by Administrative Regions over the UK for 1899-2099", "abstract": "Global climate model projections for the CMIP5 RCP8.5 emissions scenario produced as part of the UK Climate Projection 2018 (UKCP18) project. 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The data is available at various temporal resolutions: daily, monthly, seasonal and annual and various spatial resolutions: on a 12km OSGB grid, for major UK river catchments and each of the countries of the United Kingdom." } ], "responsiblepartyinfo_set": [ 110951, 111075, 111076, 111078, 111080, 111074, 111077, 143642, 111079 ], "onlineresource_set": [ 25953, 27349, 94581 ] }, { "ob_id": 26210, "uuid": "22a3c9e91b4446df9569a44e43bbfffc", "title": "UKCP18 Regional Projections by UK River Basins for 1980-2080", "abstract": "Regional climate model projections produced as part of the UK Climate Projection 2018 (UKCP18) project. The data produced by the Met Office Hadley Centre provides information on changes in climate for the UK until 2080, downscaled to a high resolution (12km), helping to inform adaptation to a changing climate. \r\n\r\nThe projections cover Europe and a 100-year period, 01/12/1980-30/11/2080, for a high emissions scenario, RCP8.5. Each projection provides an example of climate variability in a changing climate, which is consistent across climate variables at different times and spatial locations. \r\n\r\nThis dataset contains regional averages for 23 river basin regions across the UK. 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The data is available at various temporal resolutions: daily, monthly, seasonal and annual and various spatial resolutions: on a 12km OSGB grid, for major UK river catchments and each of the countries of the United Kingdom." } ], "responsiblepartyinfo_set": [ 110952, 111081, 111082, 111083, 111085, 111087, 111084, 143641, 111086 ], "onlineresource_set": [ 25954, 27361, 94583 ] }, { "ob_id": 26213, "uuid": "589211abeb844070a95d061c8cc7f604", "title": "UKCP18 Regional Projections on a 12km grid over the UK for 1980-2080", "abstract": "\"Regional climate model projections produced as part of the UK Climate Projection 2018 (UKCP18) project. The data produced by the Met Office Hadley Centre provides information on changes in climate for the UK until 2080, downscaled to a high resolution (12km), helping to inform adaptation to a changing climate. \r\n\r\nThe projections cover Europe and a 100-year period, 01/12/1980-30/11/2080, for a high emissions scenario, RCP8.5. 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All models are configurations of the Unified Model.\n\nThe regional climate model data has been interpolated using a conservative regridding scheme to the Ordnance Survey's British National grid.\n\nThere are discontinuities in the data on 1st Dec 2020 and 1st Dec 2060, due to the simulations being conducted as three separate time slices." }, "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": 26111, "uuid": "b94590a87114418281a859d391ab5641", "short_code": "proj", "title": "UKCP18: The Land Component of the UK Climate Projections 2018", "abstract": "The land component of the UKCP18 project is comprised of:\r\nA set of probabilistic projections over the UK for multiple scenarios at various temporal and spatial scales.\r\nGlobal and UK-scale simulations at global climate model resolution.\r\nUK-scale simulations at regional climate model resolution." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6023, 11484, 11485, 11486, 50510, 50515, 50517, 51184, 51185, 51186, 51187, 51188, 51189, 51190, 51191, 51192, 51193, 51194, 51195, 51196, 51197, 51198, 51199, 51200, 51201, 51202, 51203, 51204, 54031, 54032, 54035, 54036, 62353 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26216, "uuid": "b4d24b3df3754b9d9028447eb3cd89c6", "short_code": "coll", "title": "UKCP18 Regional Climate Model Projections for the UK", "abstract": "UK-scale data from regional climate model for the UK from North-West Europe regional climate model runs from 1980-2080 produced by the Met Office for UK Climate Projections 2018 (UKCP18). The data is available at various temporal resolutions: daily, monthly, seasonal and annual and various spatial resolutions: on a 12km OSGB grid, for major UK river catchments and each of the countries of the United Kingdom." } ], "responsiblepartyinfo_set": [ 110953, 111088, 111089, 111090, 111092, 111094, 111091, 143647, 111093 ], "onlineresource_set": [ 25955, 27331, 94580 ] }, { "ob_id": 26221, "uuid": "b43ce022c8f94f79b5c3b3ede7aad975", "title": "DEMON: Simulation output from ensemble assimilation of Synthetic Aperture Radar (SAR) water level observations into the Lisflood-FP flood forecast model ", "abstract": "This dataset contains simulation results from ensemble assimilation of Synthetic Aperture Radar (SAR) water level observation into Lisflood-FP flood forecast model for the the lower Severn-Avon rivers in the South West United Kingdom. This was run over a 30.6 x 49.8 km (1524 km2) domain, as part of Developing enhanced impact models for integration with next generation NWP and climate outputs (DEMON) project (NE/I005242/1).\r\n\r\nCOSMO-Skymed Synthetic Aperture Radar (CSK-SAR) data were acquired processed and transformed into Water Level Observations (WLOs) by crossing with LiDAR Digital Terrain Model. Data from Environment Agency (EA) rain gauges were used to estimate precipitation and combined with potential evapotranspiration data from the Met Office's Met Office Rainfall and Evapo-transpiration Calculation System (MORECS) to generate forcings within the \"topHSPF\" catchment-scale rainfall-runoff hydrologic model. These were used in tern to generate simulated runoff forecast used as the forcing for the coupled Lisflood-FP v5.9 inundation model. \r\n\r\nCSK-SAR based WLO were assimilated into ensemble simulations using the Lisflood-FP v5.9 model, run with perturbed physics (friction parameters, bathymetric errors) and runoff inputs from the topHSPF hydrologic model", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-02-07T09:48:44", "updateFrequency": "notPlanned", "dataLineage": "Data were delivered by the project team to be archived at the Centre for Environmental Data Analysis (CEDA)", "removedDataReason": "", "keywords": "DEMON, Synthetic Aperture Radar, Flood forecast, Assimilation, Ensemble Kalman Filter", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2018-06-28T13:11:37", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2234, "bboxName": "river severn", "eastBoundLongitude": -1.942119, "westBoundLongitude": -2.391243, "southBoundLatitude": 51.94913, "northBoundLatitude": 52.39685 }, "verticalExtent": null, "result_field": { "ob_id": 26280, "dataPath": "/badc/deposited2018/demon", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 9742783131, "numberOfFiles": 458, "fileFormat": "Data are R binary formatted" }, "timePeriod": { "ob_id": 7082, "startTime": "2012-11-01T00:00:00", "endTime": "2012-12-31T23:59:59" }, "resultQuality": { "ob_id": 3134, "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": "2018-06-15" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26220, "uuid": "eea5f87c81a84857a2950268713c5881", "short_code": "comp", "title": "Lisflood-FP v5.9, subgrid compset", "abstract": "LISFLOOD-FP is a two-dimensional hydrodynamic model specifically designed to simulate floodplain inundation in a computationally efficient manner over complex topography. It is capable of simulating grids up to 106 cells for dynamic flood events and can take advantage of new sources of terrain information from remote sensing techniques such as airborne laser altimetry and satellite interferometric radar.\r\n\r\nThe model predicts water depths in each grid cell at each time step, and hence can simulate the dynamic propagation of flood waves over fluvial, coastal and estuarine floodplains. It is a non-commercial, research code developed as part of an effort to improve our fundamental understanding of flood hydraulics, flood inundation prediction and flood risk assessment.\r\n\r\nIn this project the COSMO-Skymed Synthetic Aperture Radar (CSK-SAR) were acquired processed and transformed into Water Level Observations (WLOs) by crossing with LiDAR Digital Terrain Model. Environment Agency (EA) rain gauges were used to estimate precipitation and MORECS as potential evapotranspiration to generate the forcings into a catchment-scale rainfall-runoff hydrologic model (topHSPF) to generate simulated runoff forecast, to be used as forcing for the coupled Lisflood-FP v5.9 inundation model. EA water level gauges were used for validation. CSK-SAR based WLO were assimilated into ensemble simulations with Lisflood-FP v5.9 generated with perturbed physics (friction parameters, bathymetric errors) and runoff inputs from the above mentioned hydrologic model. \r\n" }, "procedureCompositeProcess": null, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2526, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 26219, "uuid": "79e749a562f34a7790fdfe0bce2ac1fd", "short_code": "proj", "title": "Developing enhanced impact models for integration with next generation NWP and climate outputs (DEMON)", "abstract": "DEMON aimed to analyse state-of-the-art Numerical Weather Prediction precipitation forecast for online integration with flood forecast models. A key component in DEMON was the analysis of Synthetic Aperture Radar for assimilation into the flood model to keep the forecast on track. The capability of real-time operational forecast was at the heart of the project. The duration of the project took place between 2012-2015 and was funded by the Natural Environment Research Council (NERC) NE/I005242/1.\r\n\r\nObjectives: The project aimed to develop improved hydrologic and hydraulic models to translate the outputs from Numerical Weather Prediction (NWP) and climate models into more meaningful estimates of storm impact due to fluvial flow or coastal surge. These improvements in storm impact modelling were achieved through four linked objectives - \r\n1.\tDownscaling, uncertainty propagation and evaluation of hydrologic modelling structures. \r\n2.\tThe development of data assimilation and remote sensing approaches to enhance predictions from storm impact models. \r\n3.\tFully dynamically coupled extreme storm surge and fluvial modelling. \r\n4.\tThe development of a new class of hydraulic model that can be used to convert predictions of rainfall-runoff or coastal extreme water levels to estimates of flood extent and depth at the resolution of LiDAR data (~1 - 2m horizontal resolution) over whole city regions using a true momentum-conserving approach. " } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [ 9619 ], "observationcollection_set": [], "responsiblepartyinfo_set": [ 109670, 109666, 109667, 109668, 109669, 109672, 109673, 109674, 109671, 110279, 168824 ], "onlineresource_set": [ 24880, 24881, 87652 ] }, { "ob_id": 26224, "uuid": "89a34bc430834422bef1f72e2172e3b9", "title": "ACITES: Monthly global surface ozone concentration and ozone dry deposition flux fields from models", "abstract": "Monthly global surface ozone concentration and ozone dry deposition flux fields from models participating in the UN/ECE Task Force on Hemispheric Transport of Air Pollution (TF HTAP) intercomparison. Models were driven by meteorological fields for the year 2001.\r\n\r\nData are regridded to a consistent 3 x 3 degree resolution and saved in NetCDF format.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T03:06:25", "updateFrequency": "", "dataLineage": "Data are regridded to a consistent 3 x 3 degree resolution and saved in NetCDF format. 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These grants were led by Professor Mathew Evans (University of York), Dr Oliver Wild (Lancaster University) and Professor David Stevenson (University of Edinburgh). \r\n\r\nAtmospheric chemistry plays an essential role in the Earth system. Whether from the perspective of a changing radiation balance, the impact of pollutants on vegetation, the size distribution of cloud droplets or the effect of desert dust on ocean bio-geochemistry, understanding the composition and chemistry of the atmosphere is vital. The UK has a long history in atmospheric chemistry research, from the early days of sulphur smogs, through stratospheric ozone depletion to ongoing research on air quality and climate. The UK community is diverse and plays a central role in global efforts to advance understanding through laboratory, field and process modelling studies.\r\n\r\nMuch of this world-leading atmospheric chemistry research focuses on developing detailed understanding of the various processes controlling atmospheric composition. However, addressing many of society's greatest environmental problems now requires a wider 'Earth System' approach which considers the ensemble of processes occurring on the planet, from the biosphere, to the oceans, cryosphere and the atmosphere, rather than focusing on a single domain in isolation. Earth System Models represent our understanding of processes and interactions across these domains and creating such models is one of the grand challenges for science. Achieving an effective integration of state-of-the-science understanding derived from process studies into Earth System Models is a challenge. This network encouraged this integration in order to better develop the UK's capabilities in atmospheric chemistry and Earth System Modelling. \r\n\r\nThe network achieved this exchange in two main ways. The first was through a series of meetings, the second through the community undertaking two science projects. \r\n\r\nThe first activity comprised of a comprehensive series of meetings that brought together the various processes focused groups with Earth System Modelling focused groups. These included groups from universities, NERC Centres and Meteorological Services. Both large, multi-day inclusive meetings to bring together the whole community and smaller, more focused meetings were undertaken. The three large meetings discussed science topics and future directions. They identified important science topics which were then followed up with smaller focused meetings (~12). Three topics were chosen in advance of the meetings; One involved reactive carbon emissions from the biosphere and two involved the atmospheric chemistry schemes used within models of different complexities. \r\n\r\nThe network also undertook two challenging science projects supported by two PDRA posts. These focussed on developing observationally constrained metrics of two key processes for atmospheric chemistry: transport and deposition. Both of these processes need to be 'fit for purpose' for ESMs to be suitable for atmospheric chemistry studies. Groups across the country, including those running ESMs, provided relevant model simulations. Observationally based metrics were constructed and the models compared to assess their suitability. \r\n\r\nOther activities included workshops to allow process focused scientists to engage with the current generation of NERC/MO ESM; meetings to discuss technical/software/governance issues with ESMs; support for the network to engage with similar international efforts; and the creation of an Emerging Scientists network to foster the next generation of scientists.\r\n\r\nThe primary objective of the network was to enhance the UK's capability in modelling atmospheric chemistry within an Earth System perspective. This was achieved mainly through a series of workshops and meetings, and through the community working together on two challenging atmospheric chemistry focused projects.\r\n\r\nThe aims of the meetings were to identify and prioritise potential scientific projects, questions and developments in atmospheric chemistry for Earth System Modelling; to investigate synergies and intellectual pull-through across different scales and approaches to modelling; to identify links between atmospheric chemistry and other aspects of the Earth System; to bring together players from HEIs, NERC Centres and the wider science community (Met Office, JWCRP, ECMWF) to facilitate collaborative research; to link with international efforts in atmospheric chemistry; to engage with policy stakeholders and to develop the UK atmospheric chemistry community in general. \r\n\r\nThe atmospheric chemistry projects investigated two specific topics vital for representing atmospheric composition within the Earth system. The first of these addresses the requirements for the transport of atmospheric constituents for accurate representation of atmospheric chemistry and the second addresses the representation of deposition processes which govern both the composition of the lower atmosphere and the impacts it has on the biosphere at the Earth's surface.\r\n\r\nThe physics developed for Earth System Models typically targets the transport of water vapour, heat, and momentum. However mass-conservative transport of both long- and short-lived chemically-transforming tracers is less completely considered. This leads to errors in our ability to represent atmospheric composition on these larger, longer scales. This sub-project (with a funded PDRA) aimed to take advantage of the community's knowledge and experience to create observationally-based metrics of model transport to assess whether the representation of transport in models is fit for the purposes of atmospheric chemistry. \r\n\r\nThe deposition of atmospheric components to land and oceans is the ultimate fate of all compounds emitted into the atmosphere. These deposition processes can significantly impact the chemical composition of the atmosphere and an accurate representation of this deposition is a key, but under explored, component of the atmospheric chemistry system. This sub-project (again with a funded PDRA) developed observationally constrained metrics to assess the deposition schemes used in a range of the community's models and assess their suitability for atmospheric chemistry. \r\n\r\nOther activities included running workshops to introduce the process-based/observational community to the current generation of NERC/Met Office ESMs; meetings to discuss the technical/software/governance issues with ESMs and the creation of an emerging scientists network to foster the next generation of atmospheric chemists specializing in Earth System projects.\r\n\r\nThe network engaged with science partners such as the Met Office and the ECMWF, with agencies such as DEFRA and with the wider international community. Overall this network aimed to bring together the wide and diverse range of atmospheric chemistry occurring in the UK so as to support and focus atmospheric science in the UK, help define future research plans, and to encourage engagement with the wider NERC strategy." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 50559, 50561, 57905, 57910 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26222, "uuid": "43fdd19d25b44ec2a9176288d1085ef0", "short_code": "coll", "title": "Atmospheric Chemistry In The Earth System (ACITES)", "abstract": "The Atmospheric Chemistry In The Earth System (ACITES) Network has been funded by the Natural Environment Research Council to bring together the atmospheric chemistry process community and the Earth system modelling community. \r\n\r\nThe ACITES data collection includes: Monthly global surface ozone concentration and ozone dry deposition flux fields from models and observation , land cover data. The data collection also includes the python code used to create the netCDF data files." } ], "responsiblepartyinfo_set": [ 109682, 109684, 109686, 112062, 112063, 141566, 141567, 141569, 141568, 109688, 109683, 109685 ], "onlineresource_set": [ 24884, 24885, 25589, 41697, 41698 ] }, { "ob_id": 26225, "uuid": "b117e4bd7f754d22a65fc823694fa388", "title": "ACITES: Land cover data for the Olson and Global Land Cover Facility data sets", "abstract": "Model grid cell areas and land cover data for the Olson and Global Land Cover Facility. Data are regridded to a consistent 3 x 3 degree resolution and saved in NetCDF format.\r\nThe Olson land cover dataset was developed from Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI) composites covering 1992-1993.\r\nThe Global Land Cover Facility dataset was developed from monthly satellite sensor data of NDVI values for 1987.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-06-15T10:28:28.168719", "updateFrequency": "", "dataLineage": "Land cover data regridded to the same resolution\r\nas the HTAP model results, approximately 3 x 3 degrees.\r\n\r\n1. The data is in NetCDF format\r\n\r\n2. The area for each 3 x 3 degree grid cell is in area3x3.nc\r\n\r\n3. The land cover data for the Olson and Global Land Cover Facility\r\n data sets are in: lc_olson_3x3.nc and lc_umd_3x3.nc\r\n\r\n4. The original Olson land cover data set was obtained from:\r\n http://acmg.seas.harvard.edu/geos/\r\n\r\n5. The original Global Land Cover Facility data set was obtained from:\r\n http://www.landcover.org/\r\n\r\n6. See Hardacre et al., Atmos. Chem. Phys., 15, 6419-6436, 2015,\r\n doi:10.5194/acp-15-6419-2015 for further details on the data\r\n sets used in this study.", "removedDataReason": "", "keywords": "ACITES, Atmospheric Chemistry, Land Cover", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "3x3 degree", "status": "completed", "dataPublishedTime": "2018-10-16T10:24:39", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2203, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 26226, "dataPath": "/badc/acites/data/land_surface_data", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 789647, "numberOfFiles": 5, "fileFormat": "netCDF" }, "timePeriod": { "ob_id": 8772, "startTime": "1987-01-01T00:00:00", "endTime": "1993-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26229, "uuid": "d0dba8684d3f466db3a7144ca6852e2c", "short_code": "comp", "title": "ACITES: Python code used to produce the NetCDF files", "abstract": "Python code used to produce the NetCDF files in the htap_data, land_surface_data and measurement_data direc" }, "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": 12136, "uuid": "9f5271615b78455298a30f02b61b727e", "short_code": "proj", "title": "Atmospheric Chemistry In The Earth System (ACITES) Network", "abstract": "The ACITES network was funded by the Natural Environment Research Council (NERC) under the grant references - NE/K001280/1, NE/K001272/1 and NE/K001329/1. These grants were led by Professor Mathew Evans (University of York), Dr Oliver Wild (Lancaster University) and Professor David Stevenson (University of Edinburgh). \r\n\r\nAtmospheric chemistry plays an essential role in the Earth system. Whether from the perspective of a changing radiation balance, the impact of pollutants on vegetation, the size distribution of cloud droplets or the effect of desert dust on ocean bio-geochemistry, understanding the composition and chemistry of the atmosphere is vital. The UK has a long history in atmospheric chemistry research, from the early days of sulphur smogs, through stratospheric ozone depletion to ongoing research on air quality and climate. The UK community is diverse and plays a central role in global efforts to advance understanding through laboratory, field and process modelling studies.\r\n\r\nMuch of this world-leading atmospheric chemistry research focuses on developing detailed understanding of the various processes controlling atmospheric composition. However, addressing many of society's greatest environmental problems now requires a wider 'Earth System' approach which considers the ensemble of processes occurring on the planet, from the biosphere, to the oceans, cryosphere and the atmosphere, rather than focusing on a single domain in isolation. Earth System Models represent our understanding of processes and interactions across these domains and creating such models is one of the grand challenges for science. Achieving an effective integration of state-of-the-science understanding derived from process studies into Earth System Models is a challenge. This network encouraged this integration in order to better develop the UK's capabilities in atmospheric chemistry and Earth System Modelling. \r\n\r\nThe network achieved this exchange in two main ways. The first was through a series of meetings, the second through the community undertaking two science projects. \r\n\r\nThe first activity comprised of a comprehensive series of meetings that brought together the various processes focused groups with Earth System Modelling focused groups. These included groups from universities, NERC Centres and Meteorological Services. Both large, multi-day inclusive meetings to bring together the whole community and smaller, more focused meetings were undertaken. The three large meetings discussed science topics and future directions. They identified important science topics which were then followed up with smaller focused meetings (~12). Three topics were chosen in advance of the meetings; One involved reactive carbon emissions from the biosphere and two involved the atmospheric chemistry schemes used within models of different complexities. \r\n\r\nThe network also undertook two challenging science projects supported by two PDRA posts. These focussed on developing observationally constrained metrics of two key processes for atmospheric chemistry: transport and deposition. Both of these processes need to be 'fit for purpose' for ESMs to be suitable for atmospheric chemistry studies. Groups across the country, including those running ESMs, provided relevant model simulations. Observationally based metrics were constructed and the models compared to assess their suitability. \r\n\r\nOther activities included workshops to allow process focused scientists to engage with the current generation of NERC/MO ESM; meetings to discuss technical/software/governance issues with ESMs; support for the network to engage with similar international efforts; and the creation of an Emerging Scientists network to foster the next generation of scientists.\r\n\r\nThe primary objective of the network was to enhance the UK's capability in modelling atmospheric chemistry within an Earth System perspective. This was achieved mainly through a series of workshops and meetings, and through the community working together on two challenging atmospheric chemistry focused projects.\r\n\r\nThe aims of the meetings were to identify and prioritise potential scientific projects, questions and developments in atmospheric chemistry for Earth System Modelling; to investigate synergies and intellectual pull-through across different scales and approaches to modelling; to identify links between atmospheric chemistry and other aspects of the Earth System; to bring together players from HEIs, NERC Centres and the wider science community (Met Office, JWCRP, ECMWF) to facilitate collaborative research; to link with international efforts in atmospheric chemistry; to engage with policy stakeholders and to develop the UK atmospheric chemistry community in general. \r\n\r\nThe atmospheric chemistry projects investigated two specific topics vital for representing atmospheric composition within the Earth system. The first of these addresses the requirements for the transport of atmospheric constituents for accurate representation of atmospheric chemistry and the second addresses the representation of deposition processes which govern both the composition of the lower atmosphere and the impacts it has on the biosphere at the Earth's surface.\r\n\r\nThe physics developed for Earth System Models typically targets the transport of water vapour, heat, and momentum. However mass-conservative transport of both long- and short-lived chemically-transforming tracers is less completely considered. This leads to errors in our ability to represent atmospheric composition on these larger, longer scales. This sub-project (with a funded PDRA) aimed to take advantage of the community's knowledge and experience to create observationally-based metrics of model transport to assess whether the representation of transport in models is fit for the purposes of atmospheric chemistry. \r\n\r\nThe deposition of atmospheric components to land and oceans is the ultimate fate of all compounds emitted into the atmosphere. These deposition processes can significantly impact the chemical composition of the atmosphere and an accurate representation of this deposition is a key, but under explored, component of the atmospheric chemistry system. This sub-project (again with a funded PDRA) developed observationally constrained metrics to assess the deposition schemes used in a range of the community's models and assess their suitability for atmospheric chemistry. \r\n\r\nOther activities included running workshops to introduce the process-based/observational community to the current generation of NERC/Met Office ESMs; meetings to discuss the technical/software/governance issues with ESMs and the creation of an emerging scientists network to foster the next generation of atmospheric chemists specializing in Earth System projects.\r\n\r\nThe network engaged with science partners such as the Met Office and the ECMWF, with agencies such as DEFRA and with the wider international community. Overall this network aimed to bring together the wide and diverse range of atmospheric chemistry occurring in the UK so as to support and focus atmospheric science in the UK, help define future research plans, and to encourage engagement with the wider NERC strategy." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 52192, 52193, 56837, 56838, 56839, 56840, 56841, 56842, 56843, 56844, 56845, 56846, 56847, 56848, 56849, 56850, 56851, 56852, 56853 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26222, "uuid": "43fdd19d25b44ec2a9176288d1085ef0", "short_code": "coll", "title": "Atmospheric Chemistry In The Earth System (ACITES)", "abstract": "The Atmospheric Chemistry In The Earth System (ACITES) Network has been funded by the Natural Environment Research Council to bring together the atmospheric chemistry process community and the Earth system modelling community. \r\n\r\nThe ACITES data collection includes: Monthly global surface ozone concentration and ozone dry deposition flux fields from models and observation , land cover data. The data collection also includes the python code used to create the netCDF data files." } ], "responsiblepartyinfo_set": [ 109691, 109695, 109693, 112060, 112061, 141562, 141563, 141565, 141564, 109689, 109694, 109692 ], "onlineresource_set": [ 24888, 24889, 24890, 25588 ] }, { "ob_id": 26227, "uuid": "b7953003f065461c9568e3fd9a13460f", "title": "ACITES: Monthly ozone observations from European and North American sites and CASTNET data.", "abstract": "Monthly surface ozone concentration and ozone dry deposition flux fields from observations in Europe and North America and from CASTNET data saved in NetCDF format.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2018-06-15T10:28:46.555758", "updateFrequency": "", "dataLineage": "1. > o3_observation directory\r\n \r\n > SITE_mon_ave.nc\r\n Monthly average ozone dry deposition flux, surface\r\n ozone concentration (where available) and ozone deposition\r\n velocity.\r\n \r\n\r\n2. > castnet_data directory\r\n\r\n > CASTNET_mon_ave_SITE.nc\r\n Monthly average ozone dry deposition flux, surface ozone\r\n concentration and ozone deposition velocity for each year that \r\n observations were available. The ozone dry deposition flux is\r\n calculated. Note that data was not necessarily available for all\r\n of the years between 1987-2014.", "removedDataReason": "", "keywords": "ACITES, Atmospheric Chemistry, Ozone, HTAP", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "3x3 degree", "status": "completed", "dataPublishedTime": "2018-10-16T10:22:14", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2203, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 26228, "dataPath": "/badc/acites/data/measurement_data", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 429206, "numberOfFiles": 86, "fileFormat": "netCDF" }, "timePeriod": { "ob_id": 7083, "startTime": "1987-01-01T00:00:00", "endTime": "2014-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 26229, "uuid": "d0dba8684d3f466db3a7144ca6852e2c", "short_code": "comp", "title": "ACITES: Python code used to produce the NetCDF files", "abstract": "Python code used to produce the NetCDF files in the htap_data, land_surface_data and measurement_data direc" }, "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": 12136, "uuid": "9f5271615b78455298a30f02b61b727e", "short_code": "proj", "title": "Atmospheric Chemistry In The Earth System (ACITES) Network", "abstract": "The ACITES network was funded by the Natural Environment Research Council (NERC) under the grant references - NE/K001280/1, NE/K001272/1 and NE/K001329/1. These grants were led by Professor Mathew Evans (University of York), Dr Oliver Wild (Lancaster University) and Professor David Stevenson (University of Edinburgh). \r\n\r\nAtmospheric chemistry plays an essential role in the Earth system. Whether from the perspective of a changing radiation balance, the impact of pollutants on vegetation, the size distribution of cloud droplets or the effect of desert dust on ocean bio-geochemistry, understanding the composition and chemistry of the atmosphere is vital. The UK has a long history in atmospheric chemistry research, from the early days of sulphur smogs, through stratospheric ozone depletion to ongoing research on air quality and climate. The UK community is diverse and plays a central role in global efforts to advance understanding through laboratory, field and process modelling studies.\r\n\r\nMuch of this world-leading atmospheric chemistry research focuses on developing detailed understanding of the various processes controlling atmospheric composition. However, addressing many of society's greatest environmental problems now requires a wider 'Earth System' approach which considers the ensemble of processes occurring on the planet, from the biosphere, to the oceans, cryosphere and the atmosphere, rather than focusing on a single domain in isolation. Earth System Models represent our understanding of processes and interactions across these domains and creating such models is one of the grand challenges for science. Achieving an effective integration of state-of-the-science understanding derived from process studies into Earth System Models is a challenge. This network encouraged this integration in order to better develop the UK's capabilities in atmospheric chemistry and Earth System Modelling. \r\n\r\nThe network achieved this exchange in two main ways. The first was through a series of meetings, the second through the community undertaking two science projects. \r\n\r\nThe first activity comprised of a comprehensive series of meetings that brought together the various processes focused groups with Earth System Modelling focused groups. These included groups from universities, NERC Centres and Meteorological Services. Both large, multi-day inclusive meetings to bring together the whole community and smaller, more focused meetings were undertaken. The three large meetings discussed science topics and future directions. They identified important science topics which were then followed up with smaller focused meetings (~12). Three topics were chosen in advance of the meetings; One involved reactive carbon emissions from the biosphere and two involved the atmospheric chemistry schemes used within models of different complexities. \r\n\r\nThe network also undertook two challenging science projects supported by two PDRA posts. These focussed on developing observationally constrained metrics of two key processes for atmospheric chemistry: transport and deposition. Both of these processes need to be 'fit for purpose' for ESMs to be suitable for atmospheric chemistry studies. Groups across the country, including those running ESMs, provided relevant model simulations. Observationally based metrics were constructed and the models compared to assess their suitability. \r\n\r\nOther activities included workshops to allow process focused scientists to engage with the current generation of NERC/MO ESM; meetings to discuss technical/software/governance issues with ESMs; support for the network to engage with similar international efforts; and the creation of an Emerging Scientists network to foster the next generation of scientists.\r\n\r\nThe primary objective of the network was to enhance the UK's capability in modelling atmospheric chemistry within an Earth System perspective. This was achieved mainly through a series of workshops and meetings, and through the community working together on two challenging atmospheric chemistry focused projects.\r\n\r\nThe aims of the meetings were to identify and prioritise potential scientific projects, questions and developments in atmospheric chemistry for Earth System Modelling; to investigate synergies and intellectual pull-through across different scales and approaches to modelling; to identify links between atmospheric chemistry and other aspects of the Earth System; to bring together players from HEIs, NERC Centres and the wider science community (Met Office, JWCRP, ECMWF) to facilitate collaborative research; to link with international efforts in atmospheric chemistry; to engage with policy stakeholders and to develop the UK atmospheric chemistry community in general. \r\n\r\nThe atmospheric chemistry projects investigated two specific topics vital for representing atmospheric composition within the Earth system. The first of these addresses the requirements for the transport of atmospheric constituents for accurate representation of atmospheric chemistry and the second addresses the representation of deposition processes which govern both the composition of the lower atmosphere and the impacts it has on the biosphere at the Earth's surface.\r\n\r\nThe physics developed for Earth System Models typically targets the transport of water vapour, heat, and momentum. However mass-conservative transport of both long- and short-lived chemically-transforming tracers is less completely considered. This leads to errors in our ability to represent atmospheric composition on these larger, longer scales. This sub-project (with a funded PDRA) aimed to take advantage of the community's knowledge and experience to create observationally-based metrics of model transport to assess whether the representation of transport in models is fit for the purposes of atmospheric chemistry. \r\n\r\nThe deposition of atmospheric components to land and oceans is the ultimate fate of all compounds emitted into the atmosphere. These deposition processes can significantly impact the chemical composition of the atmosphere and an accurate representation of this deposition is a key, but under explored, component of the atmospheric chemistry system. This sub-project (again with a funded PDRA) developed observationally constrained metrics to assess the deposition schemes used in a range of the community's models and assess their suitability for atmospheric chemistry. \r\n\r\nOther activities included running workshops to introduce the process-based/observational community to the current generation of NERC/Met Office ESMs; meetings to discuss the technical/software/governance issues with ESMs and the creation of an emerging scientists network to foster the next generation of atmospheric chemists specializing in Earth System projects.\r\n\r\nThe network engaged with science partners such as the Met Office and the ECMWF, with agencies such as DEFRA and with the wider international community. Overall this network aimed to bring together the wide and diverse range of atmospheric chemistry occurring in the UK so as to support and focus atmospheric science in the UK, help define future research plans, and to encourage engagement with the wider NERC strategy." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 24561, 50559, 50561, 57905, 57906, 57907, 57908, 57909, 57910, 87813, 87814 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26222, "uuid": "43fdd19d25b44ec2a9176288d1085ef0", "short_code": "coll", "title": "Atmospheric Chemistry In The Earth System (ACITES)", "abstract": "The Atmospheric Chemistry In The Earth System (ACITES) Network has been funded by the Natural Environment Research Council to bring together the atmospheric chemistry process community and the Earth system modelling community. \r\n\r\nThe ACITES data collection includes: Monthly global surface ozone concentration and ozone dry deposition flux fields from models and observation , land cover data. The data collection also includes the python code used to create the netCDF data files." } ], "responsiblepartyinfo_set": [ 109698, 109700, 109702, 112058, 112059, 141558, 141559, 141561, 141560, 109701, 109696, 109699 ], "onlineresource_set": [ 24898, 25587 ] }, { "ob_id": 26232, "uuid": "7f320bf20d9e4c7994031c3b0a2170aa", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 03.3", "abstract": "The Soil Moisture CCI 'Active' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, and SMOS satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v03.3 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2016-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T13:04:59", "updateFrequency": "notPlanned", "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project.\r\nThis dataset forms part of the v03.3 Soil Moisture CCI data (doi:10.5285/b810601740bd4848b0d7965e6d83d26c. http://dx.doi.org/10.5285/b810601740bd4848b0d7965e6d83d26c )", "removedDataReason": "", "keywords": "ESA, Soil Moisture, CCI, Active", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2018-06-25T13:08:57", "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": 26233, "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/ACTIVE/v03.3/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 6714124499, "numberOfFiles": 9282, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 7085, "startTime": "1991-08-04T23:00:00", "endTime": "2016-12-31T23:59:59" }, "resultQuality": { "ob_id": 3143, "explanation": "as provided by the CCI Soil Moisture team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2018-06-25" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2535, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 15, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_soilmoisture_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13332, "uuid": "c256fcfeef24460ca6eb14bf0fe09572", "short_code": "proj", "title": "ESA Soil Moisture Climate Change Initiative Project", "abstract": "The European Space Agency Soil Moisture Climate Change Initiative (Soil_Moisture_cci) project is part of the ESA Climate Change Initiative (CCI) programme, which aims to produce datasets of Essential Climate Variables (ECV's) from satellite datasets.\r\n\r\nThe Soil Moisture CCI project was set up to :\r\n - Analyse the needs of the climate research community in terms of soil moisture data.\r\n - Adapt soil moisture satellite measurements for their use by the climate research community.\r\n - Create a long-term consistent soil moisture time series, based on active and passive data, suitable for climate change studies." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 50512, 52664, 52665, 54641, 54643, 54644, 54645, 54646, 54647, 54648, 54649 ], "vocabularyKeywords": [ { "ob_id": 10246, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_soilMst", "resolvedTerm": "soil moisture" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26166, "uuid": "b810601740bd4848b0d7965e6d83d26c", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 03.3 data collection", "abstract": "Soil Moisture data (version 03.3) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT satellite instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS. The 'Combined Product' is then a blended product based on the former two data sets. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31 and the Active product covering 1991-08-05 to 2016-12-31. The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" } ], "responsiblepartyinfo_set": [ 109711, 109714, 109712, 109713, 109716, 109715, 110048, 109717, 110049, 109719, 110050, 110051, 110052, 110053, 110054, 110055, 110056, 110057 ], "onlineresource_set": [ 24932, 24921, 24927, 24922, 24928, 24924, 24926, 24931, 25083, 24923, 24925, 24930, 42141 ] }, { "ob_id": 26234, "uuid": "f77cbcfbb6214448aebaa2119d829692", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 04.2", "abstract": "The Soil Moisture CCI 'Active' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, and SMOS satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v04.2 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2016-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). 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Analyse the needs of the climate research community in terms of soil moisture data.\r\n - Adapt soil moisture satellite measurements for their use by the climate research community.\r\n - Create a long-term consistent soil moisture time series, based on active and passive data, suitable for climate change studies." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 50512, 52664, 52665, 54641, 54643, 54644, 54645, 54646, 54647, 54648, 54649 ], "vocabularyKeywords": [ { "ob_id": 10955, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platformProg/plat_metop", "resolvedTerm": "Metop" }, { "ob_id": 10246, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_soilMst", "resolvedTerm": "soil moisture" }, { "ob_id": 10940, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platformProg/plat_ers", "resolvedTerm": "ERS" }, { "ob_id": 10857, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_metOpA", "resolvedTerm": "Metop-A" }, { "ob_id": 10992, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/product/prod_active", "resolvedTerm": "ACTIVE" }, { "ob_id": 10545, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/L22/current/TOOL1070/", "resolvedTerm": "Advanced SCATterometer" }, { "ob_id": 11085, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_ascat", "resolvedTerm": "ASCAT" }, { "ob_id": 10858, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_metOpB", "resolvedTerm": "Metop-B" }, { "ob_id": 11048, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_amiscat", "resolvedTerm": "AMI-SCAT" }, { "ob_id": 10680, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/freq/freq_day", "resolvedTerm": "day" }, { "ob_id": 10984, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/procLev/proc_level3", "resolvedTerm": "Level 3" }, { "ob_id": 10986, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/procLev/proc_level3S", "resolvedTerm": "Level 3S" }, { "ob_id": 10672, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_soilMst", "resolvedTerm": "soil moisture" }, { "ob_id": 10810, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_ers2", "resolvedTerm": "ERS-2" }, { "ob_id": 10809, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_ers1", "resolvedTerm": "ERS-1" }, { "ob_id": 10645, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/dataType/dtype_ssms", "resolvedTerm": "surface soil moisture degree of saturation absolute" }, { "ob_id": 10757, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/org/org70", "resolvedTerm": "Vienna University of Technology" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26170, "uuid": "3a8a94c3fa464d68b6d70df291afd457", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 04.2 data collection", "abstract": "Soil Moisture data (version 04.2) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS. The 'Combined Product' is then a blended product based on the former two data sets. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31 and the Active product covering 1991-08-05 to 2016-12-31. The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using the all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" } ], "responsiblepartyinfo_set": [ 109720, 109723, 109724, 109725, 109726, 109727, 110101, 109722, 109728, 110102, 110103, 110104, 110105, 110106, 110107, 110108, 110109, 110110 ], "onlineresource_set": [ 24933, 24935, 24938, 24939, 24941, 24943, 24944, 24937, 24940, 25100, 25101, 24942, 26045, 42170 ] }, { "ob_id": 26236, "uuid": "dd3da2570363429791b51120bdd29c02", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE Product, Version 05.2", "abstract": "The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created.\r\n\r\nThe v05.2 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2019-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T12:37:56", "updateFrequency": "notPlanned", "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project. This dataset forms part of the ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 05.2 data collection. doi: 10.5285/b11f3fa3303e46e6b0d44b058947a3f5. http://dx.doi.org/10.5285/b11f3fa3303e46e6b0d44b058947a3f5 .", "removedDataReason": "", "keywords": "ESA, Soil Moisture, CCI, Active", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2020-11-23T15:02:02", "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": 31909, "dataPath": "/neodc/esacci/soil_moisture/data/daily_files/ACTIVE/v05.2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 8378534351, "numberOfFiles": 10377, "fileFormat": "Data are netCDF formatted." }, "timePeriod": { "ob_id": 8781, "startTime": "1991-08-05T00:00:00", "endTime": "2019-12-31T23:59:59" }, "resultQuality": { "ob_id": 3571, "explanation": "See the Soil Moisture CCI documentation for information on data quality", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2020-11-13" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 32009, "uuid": "b4d82ac4e7504b268977b47d975611d2", "short_code": "cmppr", "title": "ESA Soil Moisture Climate Change Initiative: Retrieval of Soil Moisture using Active sensors for version 05.2 data.", "abstract": "The ESA Soil Moisture Climate Change Initiative is using Active and Passive Sensors to derive information on soil moisture. 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This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The ACTIVE and PASSIVE products have been created by fusing satellite scatterometer and radiometer soil moisture products respectively. In the case of the ACTIVE product, these have been derived from the AMI-WS and ASCAT satellite instruments and for the PASSIVE product from the satellite instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP. The COMBINED product is generated from the Level 2 active and passive instruments..\r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the PASSIVE and COMBINED products covering the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31 and the ACTIVE product covering 1991-08-05 to 2019-12-31. The soil moisture data for the PASSIVE and the COMBINED product are provided in volumetric units [m3 m-3], while the ACTIVE soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using the all of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" } ], "responsiblepartyinfo_set": [ 109729, 109730, 109731, 109732, 109733, 109734, 110184, 109735, 109737, 141752, 141753, 141754, 110187, 110188, 110192, 141755, 110193, 110189, 141756, 141757 ], "onlineresource_set": [ 24946, 24950, 24952, 24948, 24949, 24947, 41784, 41785, 41783 ] }, { "ob_id": 26237, "uuid": "5644c9ab30ef499ba1cc9ecfc6b6474c", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Passive' Product, Version 03.3", "abstract": "The Soil Moisture CCI 'Passive' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing radiometer soil moisture products, merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. 'Active' and 'Combined' products have also been created, the 'Active' product being a fusion of AMI-WS and ASCAT derived scatterometer products and the 'Combined Product' being a blended product based on the former two data sets. \r\n\r\nThe v03.3 Passive product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). 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This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT satellite instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS. The 'Combined Product' is then a blended product based on the former two data sets. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31 and the Active product covering 1991-08-05 to 2016-12-31. The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). 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'Active' and 'Combined' products have also been created, the 'Active' product being a fusion of AMI-WS and ASCAT derived scatterometer products and the 'Combined Product' being a blended product based on the former two data sets. \r\n\r\nThe v04.2 Passive product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). 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This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS. The 'Combined Product' is then a blended product based on the former two data sets. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31 and the Active product covering 1991-08-05 to 2016-12-31. The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using the all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" } ], "responsiblepartyinfo_set": [ 109749, 109750, 109751, 109752, 109753, 109754, 110111, 109748, 109755, 110112, 110113, 110114, 110115, 110116, 110117, 110118, 110119, 110120 ], "onlineresource_set": [ 24970, 24971, 24973, 24976, 24978, 24979, 24980, 24975, 24972, 25102, 25103, 25104, 26044 ] }, { "ob_id": 26241, "uuid": "f0580e34da524770b0a5d43c033b33dc", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE Product, Version 05.2", "abstract": "The Soil Moisture CCI PASSIVE dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v05.2 PASSIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T13:15:39", "updateFrequency": "notPlanned", "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project. 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This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The ACTIVE and PASSIVE products have been created by fusing satellite scatterometer and radiometer soil moisture products respectively. In the case of the ACTIVE product, these have been derived from the AMI-WS and ASCAT satellite instruments and for the PASSIVE product from the satellite instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP. The COMBINED product is generated from the Level 2 active and passive instruments..\r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the PASSIVE and COMBINED products covering the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31 and the ACTIVE product covering 1991-08-05 to 2019-12-31. The soil moisture data for the PASSIVE and the COMBINED product are provided in volumetric units [m3 m-3], while the ACTIVE soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using the all of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. 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The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these being respectively fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. \r\n\r\nThe v04.2 Combined product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. 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This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS. The 'Combined Product' is then a blended product based on the former two data sets. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31 and the Active product covering 1991-08-05 to 2016-12-31. The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using the all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" } ], "responsiblepartyinfo_set": [ 109768, 109769, 109770, 109771, 109772, 109765, 110153, 109767, 110154, 109773, 110155, 110156, 110157, 110158, 110159, 110160, 110161, 110162 ], "onlineresource_set": [ 24996, 24993, 24994, 24995, 24998, 25000, 25001, 25002, 25004, 24999, 25113, 25115, 25114, 25116, 26043, 42171 ] }, { "ob_id": 26244, "uuid": "057dd6c36f0741d3b97f9eee688b7835", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED Product, Version 05.2", "abstract": "The Soil Moisture CCI COMBINED dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by directly merging Level 2 scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v05.2 COMBINED product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. 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Analyse the needs of the climate research community in terms of soil moisture data.\r\n - Adapt soil moisture satellite measurements for their use by the climate research community.\r\n - Create a long-term consistent soil moisture time series, based on active and passive data, suitable for climate change studies." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 1633, 3301, 3302, 11834, 11836, 11839, 11840, 13274, 13275, 20629, 20630 ], "vocabularyKeywords": [ { "ob_id": 10246, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_soilMst", "resolvedTerm": "soil moisture" }, { "ob_id": 11048, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_amiscat", "resolvedTerm": "AMI-SCAT" }, { "ob_id": 11079, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_amsr2", "resolvedTerm": "AMSR2" }, { "ob_id": 11080, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_amsre", "resolvedTerm": "AMSRE" }, { "ob_id": 11085, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_ascat", "resolvedTerm": "ASCAT" }, { "ob_id": 11053, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_miras", "resolvedTerm": "MIRAS" }, { "ob_id": 11122, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_smap", "resolvedTerm": "SMAP" }, { "ob_id": 11123, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_smmr", "resolvedTerm": "SMMR" }, { "ob_id": 11126, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_ssmI", "resolvedTerm": "SSM/I" }, { "ob_id": 11132, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_tmi", "resolvedTerm": "TMI" }, { "ob_id": 11134, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_windSat", "resolvedTerm": "WindSat" }, { "ob_id": 10784, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_aqua", "resolvedTerm": "Aqua" }, { "ob_id": 10786, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_coriolis", "resolvedTerm": "Coriolis" }, { "ob_id": 10795, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_dmsp_F08", "resolvedTerm": "DMSP-F08" }, { "ob_id": 10798, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_dmsp_F11", "resolvedTerm": "DMSP-F11" }, { "ob_id": 10800, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_dmsp_F13", "resolvedTerm": "DMSP-F13" }, { "ob_id": 10809, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_ers1", "resolvedTerm": "ERS-1" }, { "ob_id": 10810, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_ers2", "resolvedTerm": "ERS-2" }, { "ob_id": 10811, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_gcomW1", "resolvedTerm": "GCOM-W1" }, { "ob_id": 10857, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_metOpA", "resolvedTerm": "Metop-A" }, { "ob_id": 10858, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_metOpB", "resolvedTerm": "Metop-B" }, { "ob_id": 10882, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_nimbus7", "resolvedTerm": "Nimbus-7" }, { "ob_id": 11071, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_smap", "resolvedTerm": "SMAP" }, { "ob_id": 10913, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_smos", "resolvedTerm": "SMOS" }, { "ob_id": 10927, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_trmm", "resolvedTerm": "TRMM" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26171, "uuid": "b11f3fa3303e46e6b0d44b058947a3f5", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 05.2 data collection", "abstract": "Soil Moisture data (version 05.2) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The ACTIVE and PASSIVE products have been created by fusing satellite scatterometer and radiometer soil moisture products respectively. In the case of the ACTIVE product, these have been derived from the AMI-WS and ASCAT satellite instruments and for the PASSIVE product from the satellite instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP. The COMBINED product is generated from the Level 2 active and passive instruments..\r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the PASSIVE and COMBINED products covering the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31 and the ACTIVE product covering 1991-08-05 to 2019-12-31. The soil moisture data for the PASSIVE and the COMBINED product are provided in volumetric units [m3 m-3], while the ACTIVE soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using the all of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" } ], "responsiblepartyinfo_set": [ 109774, 109775, 109776, 109777, 109778, 109779, 110204, 109780, 109782, 141758, 141759, 141760, 110207, 110208, 110212, 141761, 110213, 110209, 141762, 141763 ], "onlineresource_set": [ 25008, 25009, 25014, 25015, 25013, 25010, 25016, 41786, 41787 ] }, { "ob_id": 26245, "uuid": "1d28a3d5d74d4439a2be8938dfb550f8", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 03.3", "abstract": "These ancillary datasets were used in the production of the \"Active\", \"Passive\" and \"Combined\" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v03.3 Soil Moisture CCI data.\r\n\r\nThe \"Active\" \"Passive\" and \"Combined\" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using the complete three references as follows:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T12:59:06", "updateFrequency": "notPlanned", "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project.\r\nThis dataset forms part of the v03.3 Soil Moisture CCI data (doi:10.5285/b810601740bd4848b0d7965e6d83d26c. http://dx.doi.org/10.5285/b810601740bd4848b0d7965e6d83d26c )", "removedDataReason": "", "keywords": "ESA, Soil Moisture, CCI, Ancillary", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2018-06-25T13:34:28", "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": 26246, "dataPath": "/neodc/esacci/soil_moisture/data/ancillary/v03.3/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1630198, "numberOfFiles": 6, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 7093, "startTime": "2002-06-30T23:00:00", "endTime": "2011-10-04T22:59:59" }, "resultQuality": { "ob_id": 3146, "explanation": "as provided by the CCI Soil Moisture team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2018-06-25" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2535, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 15, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_soilmoisture_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13332, "uuid": "c256fcfeef24460ca6eb14bf0fe09572", "short_code": "proj", "title": "ESA Soil Moisture Climate Change Initiative Project", "abstract": "The European Space Agency Soil Moisture Climate Change Initiative (Soil_Moisture_cci) project is part of the ESA Climate Change Initiative (CCI) programme, which aims to produce datasets of Essential Climate Variables (ECV's) from satellite datasets.\r\n\r\nThe Soil Moisture CCI project was set up to :\r\n - Analyse the needs of the climate research community in terms of soil moisture data.\r\n - Adapt soil moisture satellite measurements for their use by the climate research community.\r\n - Create a long-term consistent soil moisture time series, based on active and passive data, suitable for climate change studies." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 12066, 52664, 52665, 54683, 54684, 54685, 54686, 60753, 60754, 63533, 63534, 63535, 63536 ], "vocabularyKeywords": [ { "ob_id": 10246, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_soilMst", "resolvedTerm": "soil moisture" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26166, "uuid": "b810601740bd4848b0d7965e6d83d26c", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 03.3 data collection", "abstract": "Soil Moisture data (version 03.3) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT satellite instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS. The 'Combined Product' is then a blended product based on the former two data sets. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31 and the Active product covering 1991-08-05 to 2016-12-31. The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" } ], "responsiblepartyinfo_set": [ 109783, 109784, 109785, 109790, 109789, 109791, 110078, 109788, 110079, 109787, 110080, 110081, 110082, 110083, 110084, 110085, 110086, 110087 ], "onlineresource_set": [ 25091, 25024, 25020, 25021, 25022, 25026, 25089, 25090, 25092, 25093, 25028, 42144 ] }, { "ob_id": 26247, "uuid": "55bff4add65d489e86c195edbae8f970", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 04.2", "abstract": "These ancillary datasets were used in the production of the \"Active\", \"Passive\" and \"Combined\" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v04.2 Soil Moisture CCI data.\r\n\r\nThe \"Active\" \"Passive\" and \"Combined\" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T12:59:19", "updateFrequency": "notPlanned", "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project.\r\nThis dataset forms part of the v04.2 Soil Moisture dataset (doi: 10.5285/3a8a94c3fa464d68b6d70df291afd457 https://doi.org/10.5285/3a8a94c3fa464d68b6d70df291afd457)", "removedDataReason": "", "keywords": "ESA, Soil Moisture, CCI, Ancillary", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2018-06-25T14:49:20", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 529, "bboxName": "Global (-180 to 180)", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 26248, "dataPath": "/neodc/esacci/soil_moisture/data/ancillary/v04.2/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1630198, "numberOfFiles": 6, "fileFormat": "Data are in NetCDF format" }, "timePeriod": { "ob_id": 7094, "startTime": "2002-06-30T23:00:00", "endTime": "2011-10-04T22:59:59" }, "resultQuality": { "ob_id": 3151, "explanation": "as provided by the CCI Soil Moisture team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2018-06-25" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2535, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 15, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_soilmoisture_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13332, "uuid": "c256fcfeef24460ca6eb14bf0fe09572", "short_code": "proj", "title": "ESA Soil Moisture Climate Change Initiative Project", "abstract": "The European Space Agency Soil Moisture Climate Change Initiative (Soil_Moisture_cci) project is part of the ESA Climate Change Initiative (CCI) programme, which aims to produce datasets of Essential Climate Variables (ECV's) from satellite datasets.\r\n\r\nThe Soil Moisture CCI project was set up to :\r\n - Analyse the needs of the climate research community in terms of soil moisture data.\r\n - Adapt soil moisture satellite measurements for their use by the climate research community.\r\n - Create a long-term consistent soil moisture time series, based on active and passive data, suitable for climate change studies." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 12066, 52664, 52665, 54684, 54685, 54686, 60753, 60754, 63533, 63534, 63535, 63536 ], "vocabularyKeywords": [ { "ob_id": 10246, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_soilMst", "resolvedTerm": "soil moisture" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26170, "uuid": "3a8a94c3fa464d68b6d70df291afd457", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 04.2 data collection", "abstract": "Soil Moisture data (version 04.2) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS. The 'Combined Product' is then a blended product based on the former two data sets. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31 and the Active product covering 1991-08-05 to 2016-12-31. The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using the all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" } ], "responsiblepartyinfo_set": [ 109793, 109794, 109795, 109798, 110166, 109799, 109796, 109800, 110167, 109797, 110168, 110169, 110170, 110171, 110172, 110173, 110174, 110175 ], "onlineresource_set": [ 25033, 25031, 25035, 25029, 25036, 25037, 25034, 25038, 25117, 25118, 25119, 42172 ] }, { "ob_id": 26249, "uuid": "91719888102e4c81b7884cb57cb2f3e3", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the ACTIVE, PASSIVE and COMBINED products, Version 05.2", "abstract": "These ancillary datasets were used in the production of the ACTIVE, PASSIVE and COMBINED soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v05.2 Soil Moisture CCI data.\r\n\r\nThe ACTIVE, PASSIVE and COMBINED soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-09-25T14:57:09", "updateFrequency": "notPlanned", "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project. This dataset forms part of the ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 05.2 data collection. doi: 10.5285/b11f3fa3303e46e6b0d44b058947a3f5. http://dx.doi.org/10.5285/b11f3fa3303e46e6b0d44b058947a3f5", "removedDataReason": "", "keywords": "ESA, Soil Moisture, CCI, Ancillary", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2020-11-26T17:08:25", "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": 31910, "dataPath": "/neodc/esacci/soil_moisture/data/ancillary/v05.2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1558808, "numberOfFiles": 6, "fileFormat": "Data are netCDF formatted." }, "timePeriod": null, "resultQuality": { "ob_id": 3547, "explanation": "Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA)", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2020-09-25" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2535, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 15, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_soilmoisture_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13332, "uuid": "c256fcfeef24460ca6eb14bf0fe09572", "short_code": "proj", "title": "ESA Soil Moisture Climate Change Initiative Project", "abstract": "The European Space Agency Soil Moisture Climate Change Initiative (Soil_Moisture_cci) project is part of the ESA Climate Change Initiative (CCI) programme, which aims to produce datasets of Essential Climate Variables (ECV's) from satellite datasets.\r\n\r\nThe Soil Moisture CCI project was set up to :\r\n - Analyse the needs of the climate research community in terms of soil moisture data.\r\n - Adapt soil moisture satellite measurements for their use by the climate research community.\r\n - Create a long-term consistent soil moisture time series, based on active and passive data, suitable for climate change studies." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 3301, 3302, 11883, 11884, 11885, 11886, 12066, 20611, 20612, 20740, 20741, 20742, 20743 ], "vocabularyKeywords": [ { "ob_id": 10246, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_soilMst", "resolvedTerm": "soil moisture" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 26171, "uuid": "b11f3fa3303e46e6b0d44b058947a3f5", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 05.2 data collection", "abstract": "Soil Moisture data (version 05.2) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside ancilliary data products. The ACTIVE and PASSIVE products have been created by fusing satellite scatterometer and radiometer soil moisture products respectively. In the case of the ACTIVE product, these have been derived from the AMI-WS and ASCAT satellite instruments and for the PASSIVE product from the satellite instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP. The COMBINED product is generated from the Level 2 active and passive instruments..\r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the PASSIVE and COMBINED products covering the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31 and the ACTIVE product covering 1991-08-05 to 2019-12-31. The soil moisture data for the PASSIVE and the COMBINED product are provided in volumetric units [m3 m-3], while the ACTIVE soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD). Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using the all of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" } ], "responsiblepartyinfo_set": [ 109801, 109802, 109803, 109807, 110214, 109808, 109806, 109805, 109809, 141764, 141765, 141766, 110217, 110218, 110222, 141767, 110223, 110219, 141768, 141769 ], "onlineresource_set": [ 25041, 25042, 25044, 25047, 25046, 25048, 41788, 41789, 41790 ] }, { "ob_id": 26258, "uuid": "440c7db6c4d34d669b7bedc4d621e48e", "title": "Met Office LIDARNET Camborne Raymetrics LR111-D300 lidar profile data", "abstract": "Range corrected lidar signal and volume depolarisation ratio data from the Met Office's Raymetrics LR111-D300 lidar located at Camborne, Cornwall. Data available from June 2018 onwards, though the instrument is only operated sporadically (see below for further details).\r\n\r\nThis instrument is one of a suite of 10 Raman lidars deployed by the Met Office around the UK to complement a wider network of ceilometers within the \"LIDARNET\" upper air monitoring network. Returns from these instruments form a range of products for use in forecasting and hazard detection. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed.\r\n\r\nThe primary aim of the Raman lidar network is the detection and quantification of volcanic ash aerosols during a volcanic event, and the network is only test fired only for a few hours each week. Outside of these times the lidars may be fired if there is a mineral dust outbreak or other such aerosol event of interest. The lidars will not fire if any precipitation is detected.\r\n\r\nRaman channel data are not presently available from this instrument in the CEDA archives.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2025-01-15T00:46:46", "updateFrequency": "asNeeded", "dataLineage": "Data were collected by the Met Office before processed through the Met Office's Hermes system. A copy of these data were then delivered by the Met Office to CEDA for archiving.", "removedDataReason": "", "keywords": "Met Office, lidar, ash, Raman, backscatter profiles", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2019-02-19T10:26:35", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 642, "bboxName": "Camborne, UK", "eastBoundLongitude": -5.327272, "westBoundLongitude": -5.327272, "southBoundLatitude": 50.217931, "northBoundLatitude": 50.217931 }, "verticalExtent": null, "result_field": { "ob_id": 26262, "dataPath": "/badc/ukmo-lidarnet/data/camborne/raymetrics-lr111-d300/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 5868941460, "numberOfFiles": 12545, "fileFormat": "Data are netCDF formatted." }, "timePeriod": { "ob_id": 7095, "startTime": "2018-06-20T07:29:00", "endTime": null }, "resultQuality": { "ob_id": 3152, "explanation": "The data are checked to make sure there are data present, and all the channels are populated etc. However, there are no quality checks in place to catch problems with the machine. Users should therefore take care to inspect the data for any obvious artefacts. For example, it has happened in the past that a filter has been left in place when it should not have been, and that data will not be scrubbed at any point (in that particular case the error will be clear to anyone using the data).", "passesTest": true, "resultTitle": "LIDARNET Data Quality Statement", "date": "2018-06-26" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 26263, "uuid": "e9440f9e52aa432cb3bf6ca508fa6733", "short_code": "acq", "title": "Raymetrics LR111-D300 lidar at Camborne", "abstract": "Raymetrics LR111-D300 lidar at Camborne" }, "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": 12429, "uuid": "9124ac0ba62d4c87990e0d5cd5c38f92", "short_code": "proj", "title": "Met Office LIDARNET system", "abstract": "Met Office operate a network of ceilometers from which they obtain both cloud base and backscatter information." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 1635, 1636, 9784, 29319, 29321, 29322, 29327, 32484, 32485, 32486, 32487, 32488, 32489, 32490, 32491, 32492 ], "vocabularyKeywords": [], "identifier_set": [ 9617 ], "observationcollection_set": [ { "ob_id": 10994, "uuid": "38a6e76871fca4c58d0f831e532bff41", "short_code": "coll", "title": "Met Office LIDARNET ceilometer network cloud base and backscatter data", "abstract": "Data from the Met Office's laser cloud base recorders network (LCBRs), or ceilometers, returns a range of products for use in forecasting and hazard detection. These include cloud base height and also backscatter profiles. The backscatter profiles can allow detection of aerosol species such as volcanic ash where suitable instrumentation is deployed. The Met Offices operational LIDARNET network consists of Vaisala CT25k and CL31 ceilometers and the Jenoptik CHM15k Nimbus. In addition, this dataset also contains data from the development ceilometers operated by the Met Office." } ], "responsiblepartyinfo_set": [ 110121, 110122, 110123, 110125, 110126, 110127, 110128, 110124, 110165 ], "onlineresource_set": [ 25105, 25106 ] }, { "ob_id": 26259, "uuid": "5b99157e20374ea0828598b8b3a24433", "title": "Met Office LIDARNET Lerwick Raymetrics LR111-D300 lidar profile data", "abstract": "Range corrected lidar signal and volume depolarisation ratio data from the Met Office's Raymetrics LR111-D300 lidar located at Lerwick, Shetland Isles. 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