Observation List
Get a list of Observation objects.
GET /api/v3/observations/?format=api&offset=1800
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This collection contains ozone profiles data obtained from Aberystwyth using ozonesondes and LIDAR for the period between 1996 and 1998." } ], "responsiblepartyinfo_set": [ 48472, 48471, 48470, 48475, 48478, 48479, 48495, 48474, 48473, 48476, 48477, 48480 ], "onlineresource_set": [ 6975 ] }, { "ob_id": 12696, "uuid": "6d9a74e917d04cde9f0f7fa5fb3a9dd4", "title": "NERC Mesosphere-Stratosphere-Troposphere (MST) Radar: stratospheric and tropospheric structure and dynamics observations, version 3", "abstract": "The Natural Environment Research Council (NERC) Mesosphere-Stratosphere-Troposphere (MST) Radar is operated by the Science and Technology Facilities Council at the Radar Facility's (MSTRF's) site in Capel Dewi, near Aberystwyth, Mid-Wales. The 46.5 MHz pulsed Doppler radar is used primarily for making atmospheric observations over the approximate altitude range 2 - 20 km, i.e. over most of the troposphere and the lower stratosphere - hence the term \"ST-mode\". Additional observations are made over the approximate altitude range 56 - 96 km, i.e. covering the mesosphere - hence the term \"M-mode\" (see related dataset).\r\n\r\nThe instrument has been in operation, using the Dopppler Beam Swinging technique (see linked documentation for further details), since late 1989. It was intially operated on a campaign basis, but switched to quasi-continuous observations (i.e. close to 24-7 operation) in late 1997. \r\n\r\nThis dataset includes radial data products, i.e. range profiles along each beam pointing direction, and the \"Cartesian\" data products that are derived from them in the form of altitude profiles. The latter are used for most purposes. Data products are derived from the version 3 processing scheme, which supersedes earlier versions. Further details can be found via the linked documentation. Radial data products include:\r\n\r\nsignal power (relates to atmospheric structure)\r\nradial velocity (relates to wind speed along the beam pointing direction)\r\nspectral width (relates to turbulence intensity)\r\n\r\nCartesian data products include:\r\n\r\nhorizontal wind components (zonal and meridional)\r\nvertical wind velocity\r\nvertical beam signal power\r\ntropopause altitude\r\nvertical beam spectral width\r\nradar return aspect sensitivity\r\n\r\nNote - some files are released marked as '-suspect'. These have been released to permit early access to the data where the majority of data are known to pass quality control, but a small, limited part of the data have been identified as being 'suspect'. An internal remark about the suspect data may be found within the file's metadata 'comments' attribute.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-06-06T09:01:09", "updateFrequency": "daily", "dataLineage": "Data are acquired by the MST radar facility and sent to the BADC within an hour of acquisition. Data are then immediately ingested into the BADC archives.", "removedDataReason": "", "keywords": "MST Radar, NERC, mesosphere, SNR, echo power, spectral width", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2012-09-27T14:42:59", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 515, "bboxName": "MST radar array", "eastBoundLongitude": -4.0054698, "westBoundLongitude": -4.0054698, "southBoundLatitude": 52.424526, "northBoundLatitude": 52.424526 }, "verticalExtent": null, "result_field": { "ob_id": 12697, "dataPath": "/badc/mst/data/mst-products-v3/st-mode", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 131530358366, "numberOfFiles": 13644, "fileFormat": "Data are netCDF formatted" }, "timePeriod": { "ob_id": 1809, "startTime": "2005-04-30T23:00:00", "endTime": null }, "resultQuality": { "ob_id": 1617, "explanation": "The MST radar data quality is described by D. A. Hooper, J. Nash, T. Oakley, and M. Turp. Validation of a new signal processing scheme for the MST radar at Aberystwyth. Ann. Geophys., 26(11):3253-3268, 2008. (available from here http://www.ann-geophys.net/26/3253/2008/angeo-26-3253-2008.html)", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-07-16" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 6162, "uuid": "259919aac38e43948ba510ef58840848", "short_code": "acq", "title": "Acquisition Process for: Natural Environment Research Council (NERC) Mesosphere-Stratosphere-Troposphere (MST) Radar Facility Wind Data (V3)", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: NERC: Mesosphere-Stratosphere-Troposphere (MST) Radar; PLATFORMS: Natural Environment Research Council (NERC) Mesosphere-Stratosphere-Troposphere (MST) Radar Facility, Capel Dewi, UK; " }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 91 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 25330, "uuid": "bda9d9df0f6d4fed86102c2479ce0a93", "short_code": "proj", "title": "NERC MST Radar Facility (MSTRF)", "abstract": "The Natural Environment Research Council's Mesosphere-Stratosphere-Troposphere (MST) Radar Facility at Capel Dewi, near Aberystwyth, Ceredigion, Mid-Wales (52.42°N, 4.01°W), is an atmospheric observatory site of several observation systems for meteorological studies, managed and operated by the RAL Space department of the STFC Rutherford Appleton Laboratory on behalf of the UK's environmental science community. The facility operates a range of instruments and hosts additional instrumentation from other institutes.\r\n\r\nThe principal instrument is the NERC Mesosphere-Stratosphere-Troposphere (MST) Radar, the UK's most powerful and most versatile wind-profiling instrument from which wind data are operationally assimilated by a number of European meteorological services (including the UK's Met Office) for the purposes of numerical weather prediction. The MSTRF also operates a number of auxiliary instruments, including those for measuring surface wind, temperature, pressure, humidity, and rainfall at the site as well as surface wind speed and direction at the nearby Fron Goch site and a noctilucent cloud camera located at the Chilbolton Observatory in Hampshire (to allow images of such clouds to be seen at similar latitudes as the MSTRF site).\r\n\r\nHosted instrumentation has varied over time, but has included or continues to include instruments operated by the University of Manchester Centre for Atmospheric Science, the Met Office, the National Centre for Atmospheric Science (NCAS) Atmospheric Measurement Facility (AMF) and the RAL SPace department of the STFC Rutherford Appleton Laboratory.\r\n\r\nThe facility makes its main data products open-access (i.e. freely available) through the Centre for Environmental Data Analysis (CEDA) to all registered users, and may additionally assist users to access, to analyse, and to interpret the data as well as producing bespoke data products. Enquiries for further information about additional support form the facility should be addresses directly to the facility manager. Data from other instruments hosted by the site may be available under alternative access conditions and may not necessarily be available through CEDA." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 22318, 57072, 57073, 57075, 57076, 57077, 57078, 57079, 57080, 57081, 57082, 57083, 57084, 57085, 57086, 57087, 57088, 57089, 57090, 57091, 57092, 57093, 57094, 57095, 57096, 57097, 57098, 57099, 57100, 57101, 57102, 57103, 57104, 57105, 57106, 57107, 57108, 57109, 57110, 57111, 57112, 57113, 57114, 57115, 57116, 57117, 57118, 92248, 92249, 92250, 92251, 92252 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 6117, "uuid": "bd095d86e4a9f0c706b08058dbad3b31", "short_code": "coll", "title": "Natural Environment Research Council (NERC) Mesosphere-Stratosphere-Troposphere (MST) Radar Facility: surface and upper air meteorology measurements from Aberystwyth, mid-Wales", "abstract": "This collection contains data from the Natural Environment Research Council (NERC) Mesosphere-Stratosphere-Troposphere (MST) Radar Facility at Capel Dewi, near Aberystwyth in West Wales.\r\n\r\nThe principal measurements made by the MST radar, a 46.5 MHz pulsed Doppler radar), ideally suited for studied of atmospheric winds, waves and turbulence. It is run predominantly in the ST mode (approximately 2 - 20 km altitude) for which MST radars are unique in their ability to give continuous measurements of the three dimensional wind vector at high resolution (typically 2 - 3 minutes in time and 300 m in altitude). Under certain circumstances they can additionally provide information about humidity, static stability (thus allowing monitoring of the altitude and sharpness of the tropopause) and turbulence of at least moderate intensity. Surface meteorological measurements from the radar site, ceilometer data, sky camera images and wind speed and direction recorded from a 10m tower located at Frongoch (6km away) are also available. Other instruments at the facility have included one of the Met Office's boundary layer wind profilers and, on occasion, the NCAS's boundary layer wind profiler. \r\n\r\nThe collection also includes high-resolution radiosonde data from RAF Aberporth, approximately 45 km to the south-west of the radar site, are available for the period April 1990 - June 2000 and data from the RAL Cloud Radar. Facility data are available to all registered users under the UK Open Government License; Met Office data are available under the NERC-Met Office agreement and the RAL Cloud Radar is restricted to registered users at present.\r\n\r\n" }, { "ob_id": 11000, "uuid": "c8bd3f965b40dbc9a2f3b5c5611375d4", "short_code": "coll", "title": "Temperature, Humidity and Winds near the Tropopause (THAW) campaign: aircraft and radar data", "abstract": "The THAW (Temperature, Humidity and Winds near the Tropopause) project was led by Prof. Geraint Vaghaun (NCAS, University of Manchester) utilising a combination of vertically pointing Doppler radar data from the MST radar near Aberystwyth and a series of radiosonde and research aircraft flights in the tropopause region. The project used the FAAM BAE 146 aircraft to:\r\n\r\n• Measure fine-scale vertical temperature structure in the vicinity of the tropopause, to test a model for VHF radar reflection being developed at Manchester.\r\n\r\n• Compare wind and turbulence measurements with the MST radar, to better enable quantitative derivation of turbulence parameters from the radar echo spectra.\r\n\r\n• Characterise the performance of the Buck research CR-2 hygrometer in the upper troposphere, with special emphasis on measuring supersaturation in the vicinity of the cirrus clouds.\r\n\r\nThe MST radar was operated in two modes during this period with higher vertical resolution measurements at 150 m resolution interspersed with the 300 m vertical resolution data - these are available in the standard MST radar version 3 dataset linked within this collection." } ], "responsiblepartyinfo_set": [ 48488, 48487, 48490, 48486, 48493, 48491, 48492, 48489, 48494 ], "onlineresource_set": [ 15972, 15977, 15978 ] }, { "ob_id": 12698, "uuid": "e6a20b90d06b4bc6b40e54e770f7ede6", "title": "ACSOE OXICOA OZPROF-98: Aberystwyth Ozone Profiles Data from Ozonesonde and Ozone DIAL LIDAR", "abstract": "The Atmospheric Chemistry Studies in the Oceanic Environment (ACSOE) OXIdising Capacity of the Ocean Atmosphere (OXICOA) Ozone Profile Experiment 97 (OZPROF-96) Aberystwyth Ozone Profiles Data from Ozonesonde and Ozone DIAL LIDAR contains tropospheric ozone data from balloon-launched ozonesodes and ground-based Ozone DIAL LIDAR in 1998.\r\nThe level of ozone at high altitude on 6 December, 1998 was too low to be measured by the ozonesonde.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "1999-01-20T09:57:33", "updateFrequency": "notPlanned", "dataLineage": "Data collected by instruments on Aberystwyth. Data acquired by BADC for archiving as programme was underway.", "removedDataReason": "", "keywords": "ACSOE, OXICOA, OZPROF, Ozone", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2007-03-23T19:25:18", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 740, "bboxName": "Capel Dewi and Frongoch", "eastBoundLongitude": -4.0054698, "westBoundLongitude": -4.0540051, "southBoundLatitude": 52.423569, "northBoundLatitude": 52.424526 }, "verticalExtent": null, "result_field": { "ob_id": 12700, "dataPath": "/badc/acsoe/data/ozprof/aberystwyth/98", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2238247, "numberOfFiles": 53, "fileFormat": "The data files are NASA-Ames formatted." }, "timePeriod": { "ob_id": 3420, "startTime": "1998-01-06T00:00:00", "endTime": "1998-12-30T23:59:59" }, "resultQuality": { "ob_id": 1596, "explanation": "Data files archived as is. 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This collection contains ozone profiles data obtained from Aberystwyth using ozonesondes and LIDAR for the period between 1996 and 1998." } ], "responsiblepartyinfo_set": [ 48498, 48499, 48502, 48505, 48508, 48497, 48506, 48500, 48501, 48503, 48504, 48507 ], "onlineresource_set": [ 6976 ] }, { "ob_id": 12701, "uuid": "08ce7ca3941446ab9f66315d28a73631", "title": "ECMWF ERA-40: T159 spherical harmonic gridded model level forecast data (spfm)", "abstract": "This dataset contains T159 spherical harmonics gridded, model level, forecast timestep data from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA) 40 program from January 1958 to December 2001. ERA-40 followed on from the ERA-15 re-analysis project. Access limited to UK based academic researchers only. 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The data overlaps with the earlier ECMWF ERA-15 Re-analysis project (1979-1993). \r\n\r\nThis dataset collection contains both initialised and uninitialised T106 spectral upper air data (approximately 1 degree resolution) on model levels and standard pressure levels. Corresponding surface parameters are held on a reduced Gaussian N80 grid. Regular 2.5 degree x 2.5 degree gridded data are also stored on standard pressure levels and at the surface." } ], "responsiblepartyinfo_set": [ 48527, 48528, 48526, 48530, 48531, 48532, 48533, 48529 ], "onlineresource_set": [ 6137, 6136 ] }, { "ob_id": 12702, "uuid": "348248028eb74138a867ed5b1ec0112f", "title": "ECMWF ERA-40: reduced N80 Gaussian gridded model level forecast data (ggfm)", "abstract": "ERA-40 was a European Centre for Medium-Range Weather Forecasts (ECMWF) global atmospheric reanalysis project covering the period September 1957 to August 2002. This follows on from the ERA-15 re-analysis project. 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. Access limited to UK based academic researchers only", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-05-29T22:57:24", "updateFrequency": "notPlanned", "dataLineage": "Data were generated by the ERA-40 project at European Centre for Medium-Range Weather Forecasts (ECMWF) and stored within ECMWF's archives. 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"vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_jason1", "resolvedTerm": "Jason-1" }, { "ob_id": 10105, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org08", "resolvedTerm": "Collecte Localisation Satellites" }, { "ob_id": 10491, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_jason", "resolvedTerm": "JASON" }, { "ob_id": 10365, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_ers", "resolvedTerm": "ERS" }, { "ob_id": 10111, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org06", "resolvedTerm": "Centre National d'Etudes Spatiales" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12684, "uuid": "56c94cb1410f4f2b8a41729c0e558617", "short_code": "coll", "title": "ESA Sea Level Climate Change Initiative (Sea Level CCI) dataset collection", "abstract": "As part of the European Space Agency's (ESA) Climate Change Initiative (CCI) programme, the Sea Level CCI project has produced a set of gridded multi-satellite merged products relating to the Sea Level Essential Climate Variable (ECV). These consist of a) a time series of monthly gridded Sea Level Anomalies (SLA) and b) Oceanic Indicators describing the evolution of the sea level anomalies.\r\n\r\nSea surface heights are measured above (or below) some reference level by altimeter satellites, surface height being the difference between a satellites position in orbit with respect to an arbitrary reference surface (the Earth's centre or a rough approximation of the Earth's surface: the reference ellipsoid) and the satellite-to-surface range (calculated by measuring the time taken for the signal to make the round trip). Through sending a microwave pulse to the ocean's surface, the satellites measured the surface heights through measuring the time taken for the pulse to return. \r\n\r\nThe current version is v1.1, and covers the period January 1993 - December 2014, and has been derived from the main altimeter missions: ERS-1, ERS-2, Envisat, TOPEX/Poseidon, Jason-1, Jason-2 and Geosat-Follow-On. A detailed description of the SL CCI project and the products can be found in Ablain et al., 2014, and further information is also provided in the Product User Guide. \r\n\r\nThe following DOI can be used to reference the product database (all products in the V1.1 release (as of December 2015)): DOI:10.5270/esa-sea_level_cci-1993_2014-v_1.1-201512. \r\n\r\n When using or referring to the SL_cci products, please mention the associated DOI (see above and the individual datasets) and also use the following citation where a detailed description of the SL_cci project and products can be found:\r\n\r\nAblain, M., Cazenave, A., Larnicol, G., Balmaseda, M., Cipollini, P., Faugère, Y., Fernandes, M. J., Henry, O., Johannessen, J. A., Knudsen, P., Andersen, O., Legeais, J., Meyssignac, B., Picot, N., Roca, M., Rudenko, S., Scharffenberg, M. G., Stammer, D., Timms, G., and Benveniste, J.: Improved sea level record over the satellite altimetry era (1993–2010) from the Climate Change Initiative project, Ocean Sci., 11, 67-82, doi:10.5194/os-11-67-2015, 2015.\r\n\r\nFor further information on the Sea Level CCI products, and to register your interest with the CCI team please email: info-sealevel@esa-sealevel-cci.org" } ], "responsiblepartyinfo_set": [ 48671, 48692, 48693, 104819, 105021, 105212, 48691, 50957, 52475 ], "onlineresource_set": [ 6189, 6192, 8900, 8901, 15826, 16532 ] }, { "ob_id": 12736, "uuid": "effd70debeb84e75a30cb98a76a48226", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): Oceanic Indicators of Mean Sea Level Changes, Version 1.1", "abstract": "As part of the European Space Agency's (ESA) Sea Level Climate Change Initiative (CCI) project, a number of oceanic indicators of mean sea level changes have been produced from merging satellite altimetry measurements of sea level anomalies. The oceanic indicators dataset consists of static files covering the whole altimeter period, describing the evolution of the project's monthly sea level anomaly gridded product (see separate dataset record).\r\n\r\nA number of indicators are provided including:\r\n- the temporal evolution of the global mean sea level (MSL) with the global slope DOI: DOI: 10.5270/esa-sea_level_cci-IND_MSL_MERGED-1993_2014-v_1.1-201512\r\n- the geographical distribution of MSL trends DOI: 10.5270/esa-sea_level_cci-IND_MSLTR_MERGED-1993_2014-v_1.1-201512\r\n- Maps of the amplitude and phase of the main periodic signals (annual, semi-annual) DOI: 10.5270/esa-sea_level_cci-IND_MSLAMPH_MERGED-1993_2014-v_1.1-201512\r\n\r\nThe complete collection of v1.1 products from the Sea Level CCI project can be referenced using the following DOI:10.5270/esa-sea_level_cci-1993_2014-v_1.1-201512.\r\n\r\nWhen using or referring to the SL_cci products, please mention the associated DOIs and also use the following citation where a detailed description of the SL_cci project and products can be found:\r\n\r\nAblain, M., Cazenave, A., Larnicol, G., Balmaseda, M., Cipollini, P., Faugère, Y., Fernandes, M. J., Henry, O., Johannessen, J. A., Knudsen, P., Andersen, O., Legeais, J., Meyssignac, B., Picot, N., Roca, M., Rudenko, S., Scharffenberg, M. G., Stammer, D., Timms, G., and Benveniste, J.: Improved sea level record over the satellite altimetry era (1993–2010) from the Climate Change Initiative project, Ocean Sci., 11, 67-82, doi:10.5194/os-11-67-2015, 2015.\r\n\r\nFor further information on the Sea Level CCI products, and to register your interest with the CCI team please email: info-sealevel@esa-sealevel-cci.org\r\n\r\n", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-03-08T14:43:20.975142", "updateFrequency": "", "dataLineage": "Data was produced by the ESA SL CCI team and was transferred to CEDA as part of the ESA CCI Open Data Portal project. ", "removedDataReason": "", "keywords": "ESA, CCI, Sea Level Indicators", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "lat 0.25 x lon 0.25 degrees", "status": "completed", "dataPublishedTime": "2016-03-08T16:39:11", "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": 12735, "dataPath": "/neodc/esacci/sea_level/data/IND/v1.1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 27707687, "numberOfFiles": 11, "fileFormat": "ECV products are stored using the NetCDF (Network Common Data Form) format and CF (Climate\r\nand Forecast) metadata conventions" }, "timePeriod": { "ob_id": 3436, "startTime": "1993-01-01T00:00:00", "endTime": 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"vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_jason1", "resolvedTerm": "Jason-1" }, { "ob_id": 10105, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org08", "resolvedTerm": "Collecte Localisation Satellites" }, { "ob_id": 10491, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_jason", "resolvedTerm": "JASON" }, { "ob_id": 10365, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_ers", "resolvedTerm": "ERS" }, { "ob_id": 10111, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org06", "resolvedTerm": "Centre National d'Etudes Spatiales" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12684, "uuid": "56c94cb1410f4f2b8a41729c0e558617", "short_code": "coll", "title": "ESA Sea Level Climate Change Initiative (Sea Level 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These consist of a) a time series of monthly gridded Sea Level Anomalies (SLA) and b) Oceanic Indicators describing the evolution of the sea level anomalies.\r\n\r\nSea surface heights are measured above (or below) some reference level by altimeter satellites, surface height being the difference between a satellites position in orbit with respect to an arbitrary reference surface (the Earth's centre or a rough approximation of the Earth's surface: the reference ellipsoid) and the satellite-to-surface range (calculated by measuring the time taken for the signal to make the round trip). Through sending a microwave pulse to the ocean's surface, the satellites measured the surface heights through measuring the time taken for the pulse to return. \r\n\r\nThe current version is v1.1, and covers the period January 1993 - December 2014, and has been derived from the main altimeter missions: ERS-1, ERS-2, Envisat, TOPEX/Poseidon, Jason-1, Jason-2 and Geosat-Follow-On. A detailed description of the SL CCI project and the products can be found in Ablain et al., 2014, and further information is also provided in the Product User Guide. \r\n\r\nThe following DOI can be used to reference the product database (all products in the V1.1 release (as of December 2015)): DOI:10.5270/esa-sea_level_cci-1993_2014-v_1.1-201512. \r\n\r\n When using or referring to the SL_cci products, please mention the associated DOI (see above and the individual datasets) and also use the following citation where a detailed description of the SL_cci project and products can be found:\r\n\r\nAblain, M., Cazenave, A., Larnicol, G., Balmaseda, M., Cipollini, P., Faugère, Y., Fernandes, M. J., Henry, O., Johannessen, J. A., Knudsen, P., Andersen, O., Legeais, J., Meyssignac, B., Picot, N., Roca, M., Rudenko, S., Scharffenberg, M. G., Stammer, D., Timms, G., and Benveniste, J.: Improved sea level record over the satellite altimetry era (1993–2010) from the Climate Change Initiative project, Ocean Sci., 11, 67-82, doi:10.5194/os-11-67-2015, 2015.\r\n\r\nFor further information on the Sea Level CCI products, and to register your interest with the CCI team please email: info-sealevel@esa-sealevel-cci.org" } ], "responsiblepartyinfo_set": [ 55960, 48696, 48695, 48694, 104818, 105020, 105211, 48672, 52474 ], "onlineresource_set": [ 6197, 6199, 8898, 8899, 15825, 16531 ] }, { "ob_id": 12742, "uuid": "3829ddbb0ec045ac881f3c520ddadcf2", "title": "ECMWF ERA-40: 6-hourly monthly average reduced N80 Gaussian gridded model level analysis time data (ggam)", "abstract": "This dataset contains 6-hourly monthly average, N80 Gaussian gridded, model level, analysis time step parameters from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA) 40 program from August 1958 to September 2002. ERA-40 followed on from the ERA-15 re-analysis project. Access limited to UK based academic researchers only. These data are GRIB formatted.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2003-12-17T09:48:41", "updateFrequency": "notPlanned", "dataLineage": "Data were generated by the ERA-40 project at European Centre for Medium-Range Weather Forecasts (ECMWF) and stored within ECMWF's archives. The BADC then obtained a copy from the ECMWF archived and ingested into the BADC archives to aid wider academic use of these data.", "removedDataReason": "", "keywords": "ECMWF, ERA, ERA-40, reanalysis, surface, model, Gaussian, N80, analysis, potential temperature level, monthly, average", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2006-12-10T03:17:46", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 12743, "dataPath": "/badc/ecmwf-e40/data/mm/gg/am", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 18753964409, "numberOfFiles": 4226, "fileFormat": "Data are GRIB formatted" }, "timePeriod": { "ob_id": 3440, "startTime": "1958-01-01T00:00:00", "endTime": "2001-12-31T23:59:59" }, "resultQuality": { "ob_id": 1666, "explanation": "ECMWF quality controlled data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-08-26" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 6659, "uuid": "ecb41cff466f4b2384c73371b37a2219", "short_code": "comp", "title": "ECWF ERA-40 data assimilation system deployed on ECMWF Computer", "abstract": "This computation involved: ERA-40 data assimilation system deployed on ECMWF Computer." }, "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": 3809, "uuid": "15e78c00d093d2260a52867b6ecbdb93", "short_code": "proj", "title": "ECMWF ERA-40 Re-analysis project", "abstract": "The objectives of the European Centre for Medium-Range Weather Forecasts ERA-40 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 mid-1957 to August 2002. 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The ERA-40 project applies a modern Variational Data Assimilation technique (used in daily operational numerical forecasting at ECMWF) to the past conventional and satellite observations." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 1129, 4761, 6240, 6241, 6243, 6497, 6498, 6499 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 3806, "uuid": "775634f7e339b5262067e28a5d7b679d", "short_code": "coll", "title": "European Centre for Medium-Range Weather Forecasts (ECMWF) 40-year Re-Analysis (ERA-40) model data", "abstract": "The European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-40 Re-Analysis Project consists of a number of climate datasets spanning the period mid-1957 to August 2002 using a consistent model. The data overlaps with the earlier ECMWF ERA-15 Re-analysis project (1979-1993). \r\n\r\nThis dataset collection contains both initialised and uninitialised T106 spectral upper air data (approximately 1 degree resolution) on model levels and standard pressure levels. Corresponding surface parameters are held on a reduced Gaussian N80 grid. 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The data overlaps with the earlier ECMWF ERA-15 Re-analysis project (1979-1993). \r\n\r\nThis dataset collection contains both initialised and uninitialised T106 spectral upper air data (approximately 1 degree resolution) on model levels and standard pressure levels. Corresponding surface parameters are held on a reduced Gaussian N80 grid. Regular 2.5 degree x 2.5 degree gridded data are also stored on standard pressure levels and at the surface." } ], "responsiblepartyinfo_set": [ 48876, 48875, 48874, 48878, 48879, 48880, 48881, 48877 ], "onlineresource_set": [ 6253, 6254 ] }, { "ob_id": 12790, "uuid": "b0ecc01a0c244162b5c4254ae03be45a", "title": "NCAVEO: Level 3A ARSF Compact Airbone Spectrographic Imager 2 (CASI-2) data collected on board the Dornier Do228-101 D-CALM aircraft", "abstract": "As part of the Network for Calibration and Validation of Earth Observation data (NCAVEO) 2006 Field Campaign, a Dornier 228 aircraft operated by the Natural Environment Research Council (NERC) Airborne Research and Survey Facility (ARSF) collected CASI-2 data on 17th June 2006. The data was collected between 10:40 am and 12:01pm GMT over Chilbolton, the campaign's study area. The aircraft flew eight adjacent north-south flightlines to cover the whole area, and one east-west across the area, passing directly over the CFARR site. Information about data collection can be found in documentation file '168-GB06-10.pdf' in linked documentation.\r\n\r\nThe Level 3a files in this dataset have been processed using the AZGCORR software package (Azimuth Systems UK) provided by the NERC Airborne Research and Survey Facility. This produced a 2 metre pixel geo-corrected product without the use of ground control points. JPEG images of the Level 3 files are available for each flight line as band 10, 8, 6 RGB false-colour composites. The CASI data has 15 bands. The wavelength and width of these are specified in the associated metadata PDF, in linked documentation. Level 1B CASI-2 files and data collected by the Eagle instrument during the flight are also available through their separate dataset record pages, listed in linked documentation. ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T03:06:41", "updateFrequency": "notPlanned", "dataLineage": "These data were provided to NEODC by university of Southampton, who carried out work to convert formats to NASA-Ames, and write metadata documents. 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" }, "timePeriod": { "ob_id": 2252, "startTime": "2006-06-16T23:00:00", "endTime": "2006-06-16T23:00:00" }, "resultQuality": { "ob_id": 2117, "explanation": "Mostly unknown, but some quality statements are provided in metadata files archived alongside the data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-01-26" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 7859, "uuid": "01768688fb4e490fa2ba15191f68d851", "short_code": "acq", "title": "Acquisition Process for: Data from ARSF Compact Airbone Spectrographic Imager 2 (CASI-2) at Dornier Do228-101 D-CALM for the NCAVEO - Network for Calibration and Validation of EO data Campaign", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: ARSF Compact Airbone Spectrographic Imager 2 (CASI-2); PLATFORMS: Dornier Do228-101 D-CALM; " }, "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": 7827, "uuid": "97acc31e1530599d27c36d1e62afacab", "short_code": "proj", "title": "NCAVEO - Network for Calibration and Validation of EO data", "abstract": "The 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. The network currently comprises over 20 groups active in Earth observation in the UK, drawn from universities, government and the commercial sector." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64847 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 7824, "uuid": "3013f5fdcb544848bb028cb1a31178e9", "short_code": "coll", "title": "NCAVEO: Calibration and Validation Field Experiment: Aircraft and Ground Spectral Measurements, Atmospheric and Biophysical Data Collection", "abstract": "In June 2006 the NERC-funded Network for Calibration and Validation of EO data (NCAVEO) organised a cal-val field experiment in Chilbolton, north Hampshire involving 48 scientists from 20 organisations (click for list). The aim was to undertake a validation exercise based on the protocols and methods developed by the Validation of Land European Remote Sensing Instruments (VALERI) project, but modified as necessary for UK conditions. The experiment is a scoping exercise for the establishment of one or more VALERI sites in the UK as well as an opportunity to learn and share best practice amongst NCAVEO partners and the wider community.\r\n\r\nThe initial plan was to base the experiment at the Barton Bendish test site in East Anglia, but the absence of on-site instrumentation coupled with uncertainty about access to this site and its distance from the main research groups led to a search for other suitable sites. The one chosen was centred on the Services and Technology Facilities Council Chilbolton Facility for Atmospheric and Radio Research (CFARR), approximately 45 km north of Southampton (Figure 1). CFARR comprises a number of state-of-the-art instruments for measuring atmospheric properties, including the 25 metre diameter Chilbolton dish, a 3 GHz doppler-polarisation radar, 1275 MHz clear air radar and a UV vertical sounding LiDAR In addition, the site has a full suite of continuously operating meteorological instruments.\r\n\r\nDatasets collected include Digi HRG data, remotely sensed data from 2 aircrafts, ground spectral data , atmospheric data, biophysical data, and fluvial geomorphological data.\r\n" }, { "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": [ 48891, 48892, 48894, 48895, 48896, 48897, 48890, 48893 ], "onlineresource_set": [ 6262, 6263, 6264, 6265, 6309, 6310 ] }, { "ob_id": 12795, "uuid": "db06f38c6f214ecb922fa452cb2dc4e2", "title": "NCAVEO: ASD Field spectra N4406 data collected from Brockley field, near Chilbolton on the 18th June 2006", "abstract": "The reflectance spectra of the spring barley of field Brockley, near Chilbolton was collected as part of the Network for Calibration and Validation of Earth Observation data (NCAVEO) 2006 Field Campaign. This dataset compromises the data which was collected on the 18th June. Measurements were also taken on the 15th at this location, the dataset record for which is available through linked documentation. Measurements were recorded using an ASD N4406 FieldSpec Pro, measurements having been taken at 5 flags within the field. After the exclusion of noisy bands, the spectra contains 1926 bands, covering the wavelengths 350-1354 nm, 1409-1811 nm and 1952-2496 nm. For further information on the processing of the raw data please see the dataset's metadata pdf in linked documentation. Please note that all raw spectra files collected during the NCAVEO campaign with ASD N4406 have incorrect dates. The laptop computer used with the ASD had the month accidently set to JULY instead of June. The DAY of month and TIME (UTC) are correct in all cases. All other files (FSF spreadsheets and Excel/ENVI summary outputs) are marked with the correct 15-18th June 2006 dates. ", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2007-07-13T12:04:00", "updateFrequency": "notPlanned", "dataLineage": "These data were provided to NEODC by university of Southampton, who carried out work to convert formats to NASA-Ames, and write metadata documents. 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All the bands for the flag sites have been saved into an ENVI spectral library (‘BK_060618_abs_10’) and out from ENVI as a text file (‘BK_060618_abs_10.txt’)." }, "timePeriod": { "ob_id": 2258, "startTime": "2006-06-14T23:00:00", "endTime": "2006-06-17T23:00:00" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 7893, "uuid": "8c118cf88a264e3e9ac0cf7e24e74d88", "short_code": "acq", "title": "Acquisition Process for: Data from Newcastle University ASD Field spectra N4406 at Brockley field near Chilbolton for the NCAVEO - Network for Calibration and Validation of EO data Campaign", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Newcastle University ASD Field spectra N4406; PLATFORMS: Brockley field near Chilbolton; " }, "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": 7827, "uuid": "97acc31e1530599d27c36d1e62afacab", "short_code": "proj", "title": "NCAVEO - Network for Calibration and Validation of EO data", "abstract": "The 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. The network currently comprises over 20 groups active in Earth observation in the UK, drawn from universities, government and the commercial sector." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 7824, "uuid": "3013f5fdcb544848bb028cb1a31178e9", "short_code": "coll", "title": "NCAVEO: Calibration and Validation Field Experiment: Aircraft and Ground Spectral Measurements, Atmospheric and Biophysical Data Collection", "abstract": "In June 2006 the NERC-funded Network for Calibration and Validation of EO data (NCAVEO) organised a cal-val field experiment in Chilbolton, north Hampshire involving 48 scientists from 20 organisations (click for list). The aim was to undertake a validation exercise based on the protocols and methods developed by the Validation of Land European Remote Sensing Instruments (VALERI) project, but modified as necessary for UK conditions. The experiment is a scoping exercise for the establishment of one or more VALERI sites in the UK as well as an opportunity to learn and share best practice amongst NCAVEO partners and the wider community.\r\n\r\nThe initial plan was to base the experiment at the Barton Bendish test site in East Anglia, but the absence of on-site instrumentation coupled with uncertainty about access to this site and its distance from the main research groups led to a search for other suitable sites. The one chosen was centred on the Services and Technology Facilities Council Chilbolton Facility for Atmospheric and Radio Research (CFARR), approximately 45 km north of Southampton (Figure 1). CFARR comprises a number of state-of-the-art instruments for measuring atmospheric properties, including the 25 metre diameter Chilbolton dish, a 3 GHz doppler-polarisation radar, 1275 MHz clear air radar and a UV vertical sounding LiDAR In addition, the site has a full suite of continuously operating meteorological instruments.\r\n\r\nDatasets collected include Digi HRG data, remotely sensed data from 2 aircrafts, ground spectral data , atmospheric data, biophysical data, and fluvial geomorphological data.\r\n" }, { "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": [ 48916, 48917, 48922, 48915, 48920, 48921, 48919, 48918 ], "onlineresource_set": [ 6275, 6276 ] }, { "ob_id": 12799, "uuid": "714c110263864a82b3484c4351e120ca", "title": "NCAVEO: ARSF Specim AISA Eagle Level 3a data collected on board the Dornier Do228-101 D-CALM aircraft", "abstract": "As part of the Network for Calibration and Validation of Earth Observation data (NCAVEO) 2006 Field Campaign, hyperspectral measurements were collected over the study area of Shrewsbury on 17th June 2006. The measurements were recorded using a Specim Airborne Hyperspectral Imaging Systems (AISA) Eagle sensor on board a Dornier 228 aircraft operated by the Natural Environment Research Council (NERC) Airborne Research and Survey Facility (ARSF). The Eagle is a 12 bit, pushbroom, hyperspectral sensor. It covers the visible and near infra-red spectrum 400 - 970nm, has a 1000 pixel swath width and a maximum spectral resolution of 2.9nm. This dataset compromises the level 3a data which was collected by the instrument. The data was collected between 10:40 am and 12:01 pm GMT. 8 flightlines of data were acquired: 7 flown in a NW-SE azimuth and one cross-cutting flightline (08), in a SW-NE direction. A link to the record page for the level 1b dataset and CASI-2 data collected during the flight are also available in linked documentation.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T03:06:42", "updateFrequency": "notPlanned", "dataLineage": "These data were provided to NEODC by university of Southampton, who carried out work to convert formats to NASA-Ames, and write metadata documents. The metadata documents describing the processing are archived alongside the data as PDF files.", "removedDataReason": "", "keywords": "NCAVEO, ARSF, AISA EAGLE, DORNIER, CHILBOLTON", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2008-09-26T09:08:16", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 172, "bboxName": "", "eastBoundLongitude": -1.3859, "westBoundLongitude": -1.4718, "southBoundLatitude": 51.1217, "northBoundLatitude": 51.2026 }, "verticalExtent": null, "result_field": { "ob_id": 12805, "dataPath": "/neodc/ncaveo_field/data/arsf/eagleL3a", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 5216364817, "numberOfFiles": 19, "fileFormat": "Data are in BIL, HDR and HDF format." }, "timePeriod": { "ob_id": 2273, "startTime": "2006-06-16T23:00:00", "endTime": "2006-06-16T23:00:00" }, "resultQuality": { "ob_id": 2138, "explanation": "Mostly unknown, but some quality statements are provided in metadata files archived alongside the data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-01-26" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 7947, "uuid": "0c1f3f78a7d2469d938436a844ec70f6", "short_code": "acq", "title": "Acquisition Process for: Data from ARSF Specim AISA Eagle at Dornier Do228-101 D-CALM for the NCAVEO - Network for Calibration and Validation of EO data Campaign", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: ARSF Specim AISA Eagle; PLATFORMS: Dornier Do228-101 D-CALM; " }, "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": 7827, "uuid": "97acc31e1530599d27c36d1e62afacab", "short_code": "proj", "title": "NCAVEO - Network for Calibration and Validation of EO data", "abstract": "The 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. The network currently comprises over 20 groups active in Earth observation in the UK, drawn from universities, government and the commercial sector." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 64847 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 7824, "uuid": "3013f5fdcb544848bb028cb1a31178e9", "short_code": "coll", "title": "NCAVEO: Calibration and Validation Field Experiment: Aircraft and Ground Spectral Measurements, Atmospheric and Biophysical Data Collection", "abstract": "In June 2006 the NERC-funded Network for Calibration and Validation of EO data (NCAVEO) organised a cal-val field experiment in Chilbolton, north Hampshire involving 48 scientists from 20 organisations (click for list). The aim was to undertake a validation exercise based on the protocols and methods developed by the Validation of Land European Remote Sensing Instruments (VALERI) project, but modified as necessary for UK conditions. The experiment is a scoping exercise for the establishment of one or more VALERI sites in the UK as well as an opportunity to learn and share best practice amongst NCAVEO partners and the wider community.\r\n\r\nThe initial plan was to base the experiment at the Barton Bendish test site in East Anglia, but the absence of on-site instrumentation coupled with uncertainty about access to this site and its distance from the main research groups led to a search for other suitable sites. The one chosen was centred on the Services and Technology Facilities Council Chilbolton Facility for Atmospheric and Radio Research (CFARR), approximately 45 km north of Southampton (Figure 1). CFARR comprises a number of state-of-the-art instruments for measuring atmospheric properties, including the 25 metre diameter Chilbolton dish, a 3 GHz doppler-polarisation radar, 1275 MHz clear air radar and a UV vertical sounding LiDAR In addition, the site has a full suite of continuously operating meteorological instruments.\r\n\r\nDatasets collected include Digi HRG data, remotely sensed data from 2 aircrafts, ground spectral data , atmospheric data, biophysical data, and fluvial geomorphological data.\r\n" }, { "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": [ 48925, 48926, 48931, 48928, 48929, 48930, 48924, 48927 ], "onlineresource_set": [ 6278, 6279, 6302, 6303, 6301, 6305 ] }, { "ob_id": 12811, "uuid": "2630314f738644c9b2a6bc3194d615b7", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): GOSAT CH4 Full Physics Level 2 Data Product (CH4_GOS_SRFP), version 2.3.6, generated with the SRFP (RemoTeC) algorithm", "abstract": "Created as part of The European Space Agency's (ESA) GHG CCI project, the XCH4 GOS Full Physics (FP) data product is a level 2, column-averaged mole fraction (mixing ratio) of methane (CH4). The product is part of Climate Research Data Package Number 2 (CRDP#2) and is based upon data generated for the years 2009-2013. It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). By contrast to the Proxy (PR) versions of the product generated with proxy algorithms, the record pages for which are provided in linked documentation, the FP products have been produced using full physics algorithms, in this case the RemoTeC SRFP baseline algorithm.\r\n\r\nThe data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. The product file contains the key products with and without bias correction. Information relevant for the use of the data is also included in the data file, such as the vertical layering and averaging kernels. Additionally, the parameters retrieved simultaneously with XCH4 are included (e.g. surface albedo), as well as retrieval diagnostics like retrieval errors and the quality of the fit. \r\n\r\nFor further information on the product, including the RemoTeC Full Physics algorithm and the TANSO-FTS instrument please see the Product User Guide (PUG) or the Algorithm Theoretical Basis Document in the documentation section. \r\n\r\nThe GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases.\r\nTo register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-06-14T12:11:44.419131", "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI GHG project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "ESA, GHG, GREENHOUSE GASES, CCI, FP, CH4, TANSO-FTS", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "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": 12810, "dataPath": "/neodc/esacci/ghg/data/crdp_2/L2/GOSAT/CH4_GOS_SRFP/v2.3.6", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1644377678, "numberOfFiles": 1663, "fileFormat": "The data are stored in Netcdf format which can be read with standard tools in the common\r\nprogramming languages (IDL, Matlab, Python, Fortran90, C++, etc)." }, "timePeriod": { "ob_id": 3605, "startTime": "2009-01-01T00:00:00", "endTime": "2013-12-31T00:00:00" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2564, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 34, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_ghg_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13295, "uuid": "f0c66ffa30514d2daee821286a014b16", "short_code": "proj", "title": "ESA Greenhouse Gases Climate Change Initiative Project", "abstract": "The European Space Agency Greenhouse Gases Climate Change Initiative (GHG CCI) project is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs)\r\n\r\nCarbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases (GHGs) and a focus of international research activities related to a better understanding of the carbon cycle (see, for example, the Global Carbon Project (GCP)).\r\n \r\nWithin the GHG-CCI project the focus is on satellite data. Satellite observations combined with modelling can add important missing global information on regional CO2 and CH4 (surface) sources and sinks required for better climate prediction. The GHG CCI project started on the 1st September 2010." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 50542, 50543, 55532, 63576, 66434, 66435, 66436, 66439, 66440, 66441, 66443, 66444, 66445, 66446, 66450, 66451, 66452, 66458, 66461, 66464, 66465, 66466, 66467, 66472, 69612, 69613, 69614, 69615, 69616, 69617, 69619, 69620, 86917, 91937, 91938, 91939, 91940 ], "vocabularyKeywords": [ { "ob_id": 10163, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_tansoFts", "resolvedTerm": "TANSO-FTS" }, { "ob_id": 10527, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_gosat_prog", "resolvedTerm": "GOSAT-Programme" }, { "ob_id": 10100, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org44", "resolvedTerm": "Netherlands Institute for Space Research" }, { "ob_id": 10174, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/procLev/proc_level2", "resolvedTerm": "Level 2" }, { "ob_id": 10307, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/dataType/dtype_ch4", "resolvedTerm": "column-averaged dry air mole fraction of CH4" }, { "ob_id": 10529, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/freq/freq_sat_orb", "resolvedTerm": "satellite orbit frequency" }, { "ob_id": 10162, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_gosat", "resolvedTerm": "GOSAT" }, { "ob_id": 10351, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/product/prod_gosat", "resolvedTerm": "GOSAT" }, { "ob_id": 10173, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_ghg", "resolvedTerm": "greenhouse gases" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12808, "uuid": "0508f3dd991144aa80346007a415fb07", "short_code": "coll", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci) dataset collection", "abstract": "The Greenhouse Gases Climate Change Initiative (GHG_cci) data products are near-surface-sensitive dry-air column-averaged mole fractions (mixing ratios) of methane (CH4) and carbon dioxide (CO2), created as part of the European Space Agency's (ESA) Greenhouses Gases Essential Climate Variable (ECV) CCI project. Denoted XCO2 (in ppmv) and XCH4 (in ppbv), the products have been retrieved from the SCIAMACHY instrument on ENVISAT and TANSO-FTS onboard GOSAT, using ECV Core Algorithms (ECAs). Other satellite instruments such as IASI, MIPAS and ACE-FTS have also been used to provide constraints for upper layers, with their corresponding retrieval algorithms referred to as Additional Constraints Algorithms (ACAs). The GHG data products are typically updated annually, the corresponding datasets being called Climate Research Data Packages (CRDP). \r\n\r\nThe products have each been generated from individual sensors, a single merged product not having yet been created \"combining\" the products from different sensors to cover the entire available satellite time series. One merged product has however been generated using the EMMA algorithm, covering a limited time period. This EMMA product is mainly used as a comparison tool for products generated using individual algorithms, making up the collection of products used by EMMA. \r\n\r\nTypically the same product (e.g. XCO2 from GOSAT) has been generated using different retrieval algorithms. A baseline algorithm has been used to generate one recommended baseline product, for users unsure which product to choose. Other products are called alternative products. However an alternative product's quality may equal that of the corresponding baseline product. It typically depends upon the application for which a product is required, which product is best to use as methods involved in producing them typically have varying strength and weaknesses. \r\n\r\nFor further information on the products, such as details on the SCIAMACHY and TANSO instruments, the algorithms used to generate the data and the data's format, please see the Product Specification Document (PSD) in the documentation section." } ], "responsiblepartyinfo_set": [ 50869, 48959, 48960, 48957, 140716, 140717, 140719, 140718 ], "onlineresource_set": [ 6344, 6345, 6346, 6347, 6348, 6378, 6380, 6349, 6379, 42063 ] }, { "ob_id": 12813, "uuid": "0b1f65b7aee1462eb01c7c2c416c3454", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): GOSAT CH4 Proxy Level 2 Data Product, version 5.2 (CH4_GOS_OCPR) generated with the OCPR (UoL-PR) algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 2 (CRDP#2), the XCH4 GOS PR (Proxy) product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). \r\n\r\nThis version of the proxy product has been generated using version 5.2 of the OCPR University of Leicester Full-Physics Retrieval Algorithm, based on the original Orbiting Carbon Observatory (OCO) Full Physics Retrieval Algorithm and modified for use on GOSAT spectra baseline algorithm. This algorithm has been designated the baseline algorithm for the GHG CCI proxy methane retrievals. A second product has also been generated from the TANSO-FTS data using an alternative algorithm, the RemoTeC Proxy algorithm, and the link to this product's record page is provided in the documentation section. It is advised that users who aren't sure whether to use the baseline or alternative product use this product generated with the OCPR baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage.\r\n\r\nThe product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further details on the product, including the UoL-PR algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-06-14T12:12:52.074924", "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI GHG project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "ESA, GHG, GREENHOUSE GASES, CCI, CH4, Proxy, UoL, TANSO-FTS", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "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": 12812, "dataPath": "/neodc/esacci/ghg/data/crdp_2/L2/GOSAT/CH4_GOS_OCPR/v5.2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1969028808, "numberOfFiles": 1676, "fileFormat": "The data are stored in Netcdf format which can be read with standard tools in the common\r\nprogramming languages (IDL, Matlab, Python, Fortran90, C++, etc)." }, "timePeriod": { "ob_id": 3605, "startTime": "2009-01-01T00:00:00", "endTime": "2013-12-31T00:00:00" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2564, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 34, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_ghg_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13295, "uuid": "f0c66ffa30514d2daee821286a014b16", "short_code": "proj", "title": "ESA Greenhouse Gases Climate Change Initiative Project", "abstract": "The European Space Agency Greenhouse Gases Climate Change Initiative (GHG CCI) project is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs)\r\n\r\nCarbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases (GHGs) and a focus of international research activities related to a better understanding of the carbon cycle (see, for example, the Global Carbon Project (GCP)).\r\n \r\nWithin the GHG-CCI project the focus is on satellite data. Satellite observations combined with modelling can add important missing global information on regional CO2 and CH4 (surface) sources and sinks required for better climate prediction. 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Denoted XCO2 (in ppmv) and XCH4 (in ppbv), the products have been retrieved from the SCIAMACHY instrument on ENVISAT and TANSO-FTS onboard GOSAT, using ECV Core Algorithms (ECAs). Other satellite instruments such as IASI, MIPAS and ACE-FTS have also been used to provide constraints for upper layers, with their corresponding retrieval algorithms referred to as Additional Constraints Algorithms (ACAs). The GHG data products are typically updated annually, the corresponding datasets being called Climate Research Data Packages (CRDP). \r\n\r\nThe products have each been generated from individual sensors, a single merged product not having yet been created \"combining\" the products from different sensors to cover the entire available satellite time series. One merged product has however been generated using the EMMA algorithm, covering a limited time period. 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The project approach was to develop methodologies for generating Fundamental Climate Data Records (FCDRs) and Climate Data Records (CDRs) that are widely applicable and metrologically rigorous. \r\n\r\nThe “BACI” project translates satellite data streams into novel “essential biodiversity variables” by integrating ground-based observations. The trans-disciplinary project offers new insights into the functioning and state of ecosystems and biodiversity. BACI enables the user community to detect abrupt and transient changes of ecosystems and quantify the implications for regional biodiversity.\r\n\r\nThe UK Natural Environment Research Council has established a knowledge transfer network called NCAVEO (Network for Calibration and Validation of EO data - NCAVEO) which has as its aim the promotion and support of methodologies based upon quantitative, traceable measurements in Earth observation. \r\n\r\nThe Geostationary Earth Radiation Budget 1 & 2 instruments (GERB-1 and GERB-2) make accurate measurements of the Earth Radiation Budget. They are specifically designed to be mounted on a geostationary satellite and are carried onboard the Meteosat Second Generation satellites operated by EUMETSAT. They were produced by a European consortium led by the UK (NERC) together with Belgium, Italy, and EUMETSAT, with funding from national agencies.\r\n\r\nGloboLakes analysed 20 years of data from more than 1000 large lakes across the globe to determine 'what controls the differential sensitivity of lakes to environmental perturbation'. This was an ambitious project that was only possible by bringing together a consortium of scientists with complementary skills. These include expertise in remote sensing of freshwaters and processing large volumes of satellite images, collation and analysis of large-scale environmental data, environmental statistics and the assessment of data uncertainty, freshwater ecology and mechanisms of environmental change and the ability to produce lake models to forecast future lake conditions.\r\n\r\nThis SPEI collaboration consists of high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset over the whole of Africa at different time scales from 1 month to 48 months. It is calculated based on precipitation estimates from the satellite-based Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and potential evaporation estimates by the Global Land Evaporation Amsterdam Model (GLEAM)." } ], "responsiblepartyinfo_set": [ 49126, 49127, 49128, 50864, 140696, 140697, 140699, 140698 ], "onlineresource_set": [ 6355, 6383, 6385, 6386, 6387, 6388, 6546, 6382, 6384, 42062 ] }, { "ob_id": 12837, "uuid": "623e56750f394a37aafafce42217e032", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): GOSAT CH4 Proxy Level 2 Data Product (CH4_GOS_SRPR), version 2.3.6, generated with the SRPR (RemoTeC) algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 2 (CRDP#2), the XCH4 GOS SRPR (Proxy) product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). \r\n\r\nThis proxy version of the product has been generated using the RemoTeC SRPR algorithm, which is being jointly developed at SRON and KIT. This has been designated as an 'alternative' GHG CCI algorithm, and a separate product has also been generated by applying the baseline GHG CCI proxy algorithm (the University of Leicester OCPR algorithm). The link to this product's record page is provided in the documentation section. However, it is advised that users who aren't sure whether to use the baseline or alternative product use the OCPR product generated with the baseline algorithm. 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Denoted XCO2 (in ppmv) and XCH4 (in ppbv), the products have been retrieved from the SCIAMACHY instrument on ENVISAT and TANSO-FTS onboard GOSAT, using ECV Core Algorithms (ECAs). Other satellite instruments such as IASI, MIPAS and ACE-FTS have also been used to provide constraints for upper layers, with their corresponding retrieval algorithms referred to as Additional Constraints Algorithms (ACAs). The GHG data products are typically updated annually, the corresponding datasets being called Climate Research Data Packages (CRDP). \r\n\r\nThe products have each been generated from individual sensors, a single merged product not having yet been created \"combining\" the products from different sensors to cover the entire available satellite time series. One merged product has however been generated using the EMMA algorithm, covering a limited time period. 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If users wish to find data from other areas of work undertaken by the observatory they should visit the Armagh Observatory website.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2006-11-14T09:51:10", "updateFrequency": "notPlanned", "dataLineage": "Data are collected at the Armagh Observatory and obtained by the BADC for use by the research community.", "removedDataReason": "", "keywords": "Armagh, Air temperature", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "point", "status": "completed", "dataPublishedTime": "2007-03-19T16:46:20", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 36, "bboxName": "", "eastBoundLongitude": -6.64866, "westBoundLongitude": -6.64866, "southBoundLatitude": 54.3523, "northBoundLatitude": 54.3523 }, "verticalExtent": null, "result_field": { "ob_id": 12842, "dataPath": "/badc/armagh/data/air_temperature", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 969295, "numberOfFiles": 7, "fileFormat": "Data are stored in a bespoke ASCII format. See linked documentation for further details.\r\n" }, "timePeriod": { "ob_id": 3473, "startTime": "1844-01-01T00:01:15", "endTime": "2004-12-31T23:59:59" }, "resultQuality": { "ob_id": 547, "explanation": "Some instruments undergo calibration see Armagh Observatory website for further details: http://climate.arm.ac.uk/aws2/aws2.html", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-02-07" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 2321, "uuid": "5b9d5bd5236947d2b784f68839f18aff", "short_code": "acq", "title": "Acquisition Process for: Data from Armagh Automatic Weather Station (AWS) at Armagh Observatory, Northern Ireland, UK for the Armagh Observatory, UK Collection", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Armagh Automatic Weather Station (AWS); PLATFORMS: Armagh Observatory, Northern Ireland, UK; " }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 41 ], "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": 2318, "uuid": "c77c6c21e4729b46edeabb579d8c1fba", "short_code": "proj", "title": "Armagh Observatory, UK", "abstract": "The Armagh Observatory is a modern astronomical research institute with a rich heritage. Founded in 1790 by Archbishop Richard Robinson, the Observatory is one of the UK and Ireland's leading scientific research establishments. Around 25 astronomers are actively studying Stellar Astrophysics, the Sun, Solar System astronomy, and the Earth's climate." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 25388 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 2315, "uuid": "2bca5457886c9352197c0fe9b7122418", "short_code": "coll", "title": "The Armagh Observatory Climate Observation Data (1796-present)", "abstract": "Data from the Armagh Observatory, founded in 1790 by Archbishop Richard Robinson. There are around 25 astronomers who are actively studying Stellar Astrophysics, the Sun, Solar System astronomy, and the Earth's climate. As well as astronomical observations various meteorological parameters have been recorded since 1794. 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" } ], "responsiblepartyinfo_set": [ 49108, 49109, 49111, 49112, 49113, 49114, 49107, 49110 ], "onlineresource_set": [ 6474, 6501 ] }, { "ob_id": 12855, "uuid": "91a09803bd5a42aeb5d3fd530409b15e", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): SCIAMACHY CH4 Level 2 Data Product (CH4_SCI_IMAP), version 7.0, generated with the IMAP-DOAS algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 2 (CRDP#2), the XCH4 SCI product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the SWIR spectra (channel 6) of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. \r\n\r\nThis product has been derived by applying the IMAP-DOAS algorithm developed at the University of Heidelberg and SRON to the SCIAMACHY data. This procedure and the algorithms validity are thoroughly described in Frankenberg et al (2011), a link to which is provided in linked documentation. A second product has also been generated from the SCIAMACHY data using the Weighting Function Modified DOAS (WFM-DOAS) algorithm, and the link to this product's record page is provided in the documentation section. \r\n\r\nThe data product is stored per orbit in a single NetCDF4 file. Retrieval results are provided for the individual SCIAMACHY spatial footprints, no averaging having been applied. The product file contains the key products and information relevant to using the data, such as the vertical layering and averaging kernels. For further details on the product, including the IMAP algorithm and the SCIAMACHY instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Document in the documentation section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-06-14T12:10:23.621053", "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI GHG project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "ESA, GHG, GREENHOUSE GASES, CCI, CH4, SCIAMACHY, IMAP", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "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": 12856, "dataPath": "/neodc/esacci/ghg/data/crdp_2/L2/SCIAMACHY/CH4_SCI_IMAP/v7.0", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2078063821, "numberOfFiles": 3110, "fileFormat": "The data are stored in Netcdf4 format, which can be read with standard tools in the common\r\nprogramming languages (IDL, Matlab, Python etc). Standard readers for HDF5 can also be used as netCDF4 is based on HDF5." }, "timePeriod": { "ob_id": 3602, "startTime": "2002-10-01T00:00:00", "endTime": "2012-04-08T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2564, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 34, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_ghg_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13295, "uuid": "f0c66ffa30514d2daee821286a014b16", "short_code": "proj", "title": "ESA Greenhouse Gases Climate Change Initiative Project", "abstract": "The European Space Agency Greenhouse Gases Climate Change Initiative (GHG CCI) project is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs)\r\n\r\nCarbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases (GHGs) and a focus of international research activities related to a better understanding of the carbon cycle (see, for example, the Global Carbon Project (GCP)).\r\n \r\nWithin the GHG-CCI project the focus is on satellite data. 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Denoted XCO2 (in ppmv) and XCH4 (in ppbv), the products have been retrieved from the SCIAMACHY instrument on ENVISAT and TANSO-FTS onboard GOSAT, using ECV Core Algorithms (ECAs). Other satellite instruments such as IASI, MIPAS and ACE-FTS have also been used to provide constraints for upper layers, with their corresponding retrieval algorithms referred to as Additional Constraints Algorithms (ACAs). The GHG data products are typically updated annually, the corresponding datasets being called Climate Research Data Packages (CRDP). \r\n\r\nThe products have each been generated from individual sensors, a single merged product not having yet been created \"combining\" the products from different sensors to cover the entire available satellite time series. One merged product has however been generated using the EMMA algorithm, covering a limited time period. This EMMA product is mainly used as a comparison tool for products generated using individual algorithms, making up the collection of products used by EMMA. \r\n\r\nTypically the same product (e.g. XCO2 from GOSAT) has been generated using different retrieval algorithms. A baseline algorithm has been used to generate one recommended baseline product, for users unsure which product to choose. Other products are called alternative products. However an alternative product's quality may equal that of the corresponding baseline product. It typically depends upon the application for which a product is required, which product is best to use as methods involved in producing them typically have varying strength and weaknesses. \r\n\r\nFor further information on the products, such as details on the SCIAMACHY and TANSO instruments, the algorithms used to generate the data and the data's format, please see the Product Specification Document (PSD) in the documentation section." } ], "responsiblepartyinfo_set": [ 49130, 49131, 49133, 50854, 140700, 140701, 140703, 140702 ], "onlineresource_set": [ 6484, 6483, 6485, 6486, 6487, 6488, 6489, 6490, 6491, 6545, 42061 ] }, { "ob_id": 12857, "uuid": "5518ef811d4c45da9474056986c78cfd", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): SCIAMACHY CH4 Level 2 Data Product (CH4_SCI_WFMD), version 3.7, generated with the WFMD algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 2 (CRDP#2), the XCH4 SCI product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. \r\n\r\nThis product has been derived by applying the Weighting Function Modified DOAS (WFMD) algorithm to the SCIAMACHY data, a least-squares method based on scaling pre-selected atmospheric vertical profiles. A second product has also been generated from the SCIAMACHY data using the IMAP algorithm, and the link to this product's record page is provided in the documentation section. \r\n\r\nThe data product is stored per day in separate NetCDF-files (NetCDF-4 classic model). The product files contain the key products and other information relevant for the use of the data e.g. the averaging kernels. Note that the results since November 2005 are considered to be of reduced quality in comparison to the earlier results because the extended-wavelength part (1590-1770 nm) of SCIAMACHY's channel 6, covering the methane 2v3 absorption band used for the methane retrieval, is subject to irreversible displacement damage induced by high energy solar protons, which occurs from time to time at individual detector pixels. Therefore several affected detector pixels had to be excluded for the time period since November 2005. \r\n\r\nFor further information on the product, including details of the WFMD algorithm and the SCIAMACHY instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-06-14T12:06:53.513480", "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI GHG project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "ESA, GHG, GREENHOUSE GASES, CCI, CH4, SCIAMACHY, WFMD", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "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": 12859, "dataPath": "/neodc/esacci/ghg/data/crdp_2/L2/SCIAMACHY/CH4_SCI_WFMD/v3.7", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2754177044, "numberOfFiles": 3211, "fileFormat": "The data are stored in NetCDF format (NetCDF-4 classic model) which can be read with standard tools in the common programming languages (IDL, Matlab, Python etc).\r\n" }, "timePeriod": { "ob_id": 3601, "startTime": "2002-08-14T23:00:00", "endTime": "2012-03-24T00:00:00" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [], "discoveryKeywords": [], "permissions": [ { "ob_id": 2564, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 34, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_ghg_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13295, "uuid": "f0c66ffa30514d2daee821286a014b16", "short_code": "proj", "title": "ESA Greenhouse Gases Climate Change Initiative Project", "abstract": "The European Space Agency Greenhouse Gases Climate Change Initiative (GHG CCI) project is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs)\r\n\r\nCarbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases (GHGs) and a focus of international research activities related to a better understanding of the carbon cycle (see, for example, the Global Carbon Project (GCP)).\r\n \r\nWithin the GHG-CCI project the focus is on satellite data. Satellite observations combined with modelling can add important missing global information on regional CO2 and CH4 (surface) sources and sinks required for better climate prediction. 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This EMMA product is mainly used as a comparison tool for products generated using individual algorithms, making up the collection of products used by EMMA. \r\n\r\nTypically the same product (e.g. XCO2 from GOSAT) has been generated using different retrieval algorithms. A baseline algorithm has been used to generate one recommended baseline product, for users unsure which product to choose. Other products are called alternative products. However an alternative product's quality may equal that of the corresponding baseline product. It typically depends upon the application for which a product is required, which product is best to use as methods involved in producing them typically have varying strength and weaknesses. \r\n\r\nFor further information on the products, such as details on the SCIAMACHY and TANSO instruments, the algorithms used to generate the data and the data's format, please see the Product Specification Document (PSD) in the documentation section." } ], "responsiblepartyinfo_set": [ 49136, 49134, 50853, 49137, 140704, 140705, 140707, 140706 ], "onlineresource_set": [ 6498, 6499, 6502, 6503, 6504, 6506, 6544, 6500, 6505, 42060 ] }, { "ob_id": 12860, "uuid": "999f83c401fe4e47a0d3393b4c25c53f", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Merged CO2 Level 2 Data Product (CO2_EMMA), version 2.0, generated with the EMMA algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG), the XCO2 EMMA product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). 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Denoted XCO2 (in ppmv) and XCH4 (in ppbv), the products have been retrieved from the SCIAMACHY instrument on ENVISAT and TANSO-FTS onboard GOSAT, using ECV Core Algorithms (ECAs). Other satellite instruments such as IASI, MIPAS and ACE-FTS have also been used to provide constraints for upper layers, with their corresponding retrieval algorithms referred to as Additional Constraints Algorithms (ACAs). The GHG data products are typically updated annually, the corresponding datasets being called Climate Research Data Packages (CRDP). \r\n\r\nThe products have each been generated from individual sensors, a single merged product not having yet been created \"combining\" the products from different sensors to cover the entire available satellite time series. One merged product has however been generated using the EMMA algorithm, covering a limited time period. This EMMA product is mainly used as a comparison tool for products generated using individual algorithms, making up the collection of products used by EMMA. \r\n\r\nTypically the same product (e.g. XCO2 from GOSAT) has been generated using different retrieval algorithms. A baseline algorithm has been used to generate one recommended baseline product, for users unsure which product to choose. Other products are called alternative products. However an alternative product's quality may equal that of the corresponding baseline product. It typically depends upon the application for which a product is required, which product is best to use as methods involved in producing them typically have varying strength and weaknesses. \r\n\r\nFor further information on the products, such as details on the SCIAMACHY and TANSO instruments, the algorithms used to generate the data and the data's format, please see the Product Specification Document (PSD) in the documentation section." } ], "responsiblepartyinfo_set": [ 49138, 49139, 49141, 50852, 140712, 140713, 140715, 140714 ], "onlineresource_set": [ 6526, 6527, 6513, 6512, 6525, 16175, 42059 ] }, { "ob_id": 12862, "uuid": "130450cdf1034235aa2a5107dc513d81", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): GOSAT CO2 Level 2 Data Product (CO2_GOS_OCFP) version 5.2, generated with the OCFP (UoL-FP) algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project, the XCO2 GOSAT product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). The University of Leicester Full-Physics Retrieval Algorithm has been applied to the TANSO-FTS data, based on the original Orbiting Carbon Observatory (OCO) Full Physics Retrieval Algorithm and modified for use on GOSAT spectra. A second product has also been generated from the data using the SRFP algorithm, and the link to this product's record page is provided in the documentation section. \r\n\r\nThe XCO2 product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further information, including details of the OCFP algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) in the documentation section or the Algorithm Theoretical Basis Document for version 5.1 of the product (no ATBD is yet available for version 5.2).", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-06-14T12:01:02.156451", "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI GHG project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "ESA, GHG, CCI, CO2, OCFP", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "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": 12863, "dataPath": "/neodc/esacci/ghg/data/crdp_2/L2/GOSAT/CO2_GOS_OCFP/v5.2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1519903371, "numberOfFiles": 1680, "fileFormat": "The data is stored in NetCDF format which can be read with standard tools in the common\r\nprogramming languages (IDL, Matlab, Python etc)." }, "timePeriod": { "ob_id": 3604, "startTime": "2009-04-22T23:00:00", "endTime": "2012-12-31T00:00:00" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2564, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 34, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_ghg_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13295, "uuid": "f0c66ffa30514d2daee821286a014b16", "short_code": "proj", "title": "ESA Greenhouse Gases Climate Change Initiative Project", "abstract": "The European Space Agency Greenhouse Gases Climate Change Initiative (GHG CCI) project is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs)\r\n\r\nCarbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases (GHGs) and a focus of international research activities related to a better understanding of the carbon cycle (see, for example, the Global Carbon Project (GCP)).\r\n \r\nWithin the GHG-CCI project the focus is on satellite data. Satellite observations combined with modelling can add important missing global information on regional CO2 and CH4 (surface) sources and sinks required for better climate prediction. The GHG CCI project started on the 1st September 2010." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 1050, 1635, 1636, 11816, 11852, 11853, 11854, 11855, 11856, 11857, 11858, 11859, 11860, 11863, 11864, 11866, 11867, 11868, 11869, 11870, 11871, 11872, 25159, 25160, 25161 ], "vocabularyKeywords": [ { "ob_id": 10174, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/procLev/proc_level2", "resolvedTerm": "Level 2" }, { "ob_id": 10162, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_gosat", "resolvedTerm": "GOSAT" }, { "ob_id": 10163, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_tansoFts", "resolvedTerm": "TANSO-FTS" }, { "ob_id": 10351, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/product/prod_gosat", "resolvedTerm": "GOSAT" }, { "ob_id": 10173, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_ghg", "resolvedTerm": "greenhouse gases" }, { "ob_id": 10211, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/dataType/dtype_co2", "resolvedTerm": "column-averaged dry air mole fraction of CO2" }, { "ob_id": 10529, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/freq/freq_sat_orb", "resolvedTerm": "satellite orbit frequency" }, { "ob_id": 10527, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_gosat_prog", "resolvedTerm": "GOSAT-Programme" }, { "ob_id": 10094, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org65", "resolvedTerm": "University of Leicester" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12808, "uuid": "0508f3dd991144aa80346007a415fb07", "short_code": "coll", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci) dataset collection", "abstract": "The Greenhouse Gases Climate Change Initiative (GHG_cci) data products are near-surface-sensitive dry-air column-averaged mole fractions (mixing ratios) of methane (CH4) and carbon dioxide (CO2), created as part of the European Space Agency's (ESA) Greenhouses Gases Essential Climate Variable (ECV) CCI project. Denoted XCO2 (in ppmv) and XCH4 (in ppbv), the products have been retrieved from the SCIAMACHY instrument on ENVISAT and TANSO-FTS onboard GOSAT, using ECV Core Algorithms (ECAs). Other satellite instruments such as IASI, MIPAS and ACE-FTS have also been used to provide constraints for upper layers, with their corresponding retrieval algorithms referred to as Additional Constraints Algorithms (ACAs). The GHG data products are typically updated annually, the corresponding datasets being called Climate Research Data Packages (CRDP). \r\n\r\nThe products have each been generated from individual sensors, a single merged product not having yet been created \"combining\" the products from different sensors to cover the entire available satellite time series. One merged product has however been generated using the EMMA algorithm, covering a limited time period. This EMMA product is mainly used as a comparison tool for products generated using individual algorithms, making up the collection of products used by EMMA. \r\n\r\nTypically the same product (e.g. XCO2 from GOSAT) has been generated using different retrieval algorithms. A baseline algorithm has been used to generate one recommended baseline product, for users unsure which product to choose. Other products are called alternative products. However an alternative product's quality may equal that of the corresponding baseline product. It typically depends upon the application for which a product is required, which product is best to use as methods involved in producing them typically have varying strength and weaknesses. \r\n\r\nFor further information on the products, such as details on the SCIAMACHY and TANSO instruments, the algorithms used to generate the data and the data's format, please see the Product Specification Document (PSD) in the documentation section." }, { "ob_id": 30128, "uuid": "7fe9f59731ab47b6a20e792e0cba4641", "short_code": "coll", "title": "National Centre for Earth Observation (NCEO) partnered datasets", "abstract": "The National Centre for Earth Observation (NCEO) has a proud tradition of being involved with some of the most successful international collaborations in the Earth observation. This Collection contains dataset generated and/or archived with the support of NCEO resource or scientific expertise. Some notable collaboration which generated data within this collection are as follows:\r\n\r\nThe European Space Agency (ESA)'s Climate Change Initiative (CCI) program. The program goal is to provide stable, long-term, satellite-based Essential Climate Variable (ECV) data products for climate modelers and researchers.\r\n\r\nThe EUSTACE (EU Surface Temperature for All Corners of Earth) project is produced publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques.\r\n\r\nFIDUCEO has created new climate datasets from Earth Observations with a rigorous treatment of uncertainty informed by the discipline of metrology. This response to the need for enhanced credibility for climate data, to support rigorous science, decision-making and climate services. The project approach was to develop methodologies for generating Fundamental Climate Data Records (FCDRs) and Climate Data Records (CDRs) that are widely applicable and metrologically rigorous. \r\n\r\nThe “BACI” project translates satellite data streams into novel “essential biodiversity variables” by integrating ground-based observations. The trans-disciplinary project offers new insights into the functioning and state of ecosystems and biodiversity. BACI enables the user community to detect abrupt and transient changes of ecosystems and quantify the implications for regional biodiversity.\r\n\r\nThe UK Natural Environment Research Council has established a knowledge transfer network called NCAVEO (Network for Calibration and Validation of EO data - NCAVEO) which has as its aim the promotion and support of methodologies based upon quantitative, traceable measurements in Earth observation. \r\n\r\nThe Geostationary Earth Radiation Budget 1 & 2 instruments (GERB-1 and GERB-2) make accurate measurements of the Earth Radiation Budget. They are specifically designed to be mounted on a geostationary satellite and are carried onboard the Meteosat Second Generation satellites operated by EUMETSAT. They were produced by a European consortium led by the UK (NERC) together with Belgium, Italy, and EUMETSAT, with funding from national agencies.\r\n\r\nGloboLakes analysed 20 years of data from more than 1000 large lakes across the globe to determine 'what controls the differential sensitivity of lakes to environmental perturbation'. This was an ambitious project that was only possible by bringing together a consortium of scientists with complementary skills. These include expertise in remote sensing of freshwaters and processing large volumes of satellite images, collation and analysis of large-scale environmental data, environmental statistics and the assessment of data uncertainty, freshwater ecology and mechanisms of environmental change and the ability to produce lake models to forecast future lake conditions.\r\n\r\nThis SPEI collaboration consists of high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset over the whole of Africa at different time scales from 1 month to 48 months. It is calculated based on precipitation estimates from the satellite-based Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and potential evaporation estimates by the Global Land Evaporation Amsterdam Model (GLEAM)." } ], "responsiblepartyinfo_set": [ 49145, 49142, 49143, 50851, 140671, 140672, 140674, 140673 ], "onlineresource_set": [ 6540, 6541, 6542, 6543, 6534, 6571, 6533, 6539, 42058 ] }, { "ob_id": 12864, "uuid": "61424ae2a8364db2bb9cb077d644872e", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): GOSAT CO2 Level 2 Data Product (CO2_GOS_SRFP) version 2.3.6, generated with the SRFP (RemoTeC) algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and Climate Research Data Package Number 2 (CRDP#2), the XCO2 GOSAT product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). In this case, the RemoTeC Full Physics (SRFP) algorithm, jointly developed at SRON and KIT, has been applied to the TANSO-FTS data. A second product has also been generated from the data using the OCFP (University of Leicester Full Physics) algorithm, and the link to this product's record page can be found in the documentation section. \r\n\r\nThe data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. The product file contains the key standard products, i.e. the retrieved column averaged dry air mixing ratio XCO2 with bias correction, averaging kernels and quality flags, as well as secondary products specific for the RemoTeC algorithm. For further information, including details of the SRFP algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Document in the documentation section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-06-14T12:02:53.937463", "updateFrequency": "", "dataLineage": "Data were processed by the ESA CCI GHG project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "ESA, GHG, GREENHOUSE GASES, CCI, CO2, GOSAT, SRFP", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "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": 12865, "dataPath": "/neodc/esacci/ghg/data/crdp_2/L2/GOSAT/CO2_GOS_SRFP/v2.3.6", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1644571693, "numberOfFiles": 1663, "fileFormat": "The data are stored in Netcdf format which can be read with standard tools in the common\r\nprogramming languages (IDL, Matlab, Python etc)." }, "timePeriod": { "ob_id": 3603, "startTime": "2009-05-31T23:00:00", "endTime": "2013-12-30T00:00:00" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2564, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 34, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_ghg_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13295, "uuid": "f0c66ffa30514d2daee821286a014b16", "short_code": "proj", "title": "ESA Greenhouse Gases Climate Change Initiative Project", "abstract": "The European Space Agency Greenhouse Gases Climate Change Initiative (GHG CCI) project is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs)\r\n\r\nCarbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases (GHGs) and a focus of international research activities related to a better understanding of the carbon cycle (see, for example, the Global Carbon Project (GCP)).\r\n \r\nWithin the GHG-CCI project the focus is on satellite data. Satellite observations combined with modelling can add important missing global information on regional CO2 and CH4 (surface) sources and sinks required for better climate prediction. The GHG CCI project started on the 1st September 2010." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 1050, 1635, 1636, 11791, 11792, 11793, 11794, 11795, 11796, 11797, 11798, 11800, 11801, 11802, 11803, 11804, 11805, 11807, 11808, 11809, 11810, 11813, 11814, 11815, 11816, 11817, 11818, 11820, 11821, 11822, 11830, 11831, 11832, 11841, 13269, 13271, 13277 ], "vocabularyKeywords": [ { "ob_id": 10174, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/procLev/proc_level2", "resolvedTerm": "Level 2" }, { "ob_id": 10162, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_gosat", "resolvedTerm": "GOSAT" }, { "ob_id": 10163, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_tansoFts", "resolvedTerm": "TANSO-FTS" }, { "ob_id": 10351, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/product/prod_gosat", "resolvedTerm": "GOSAT" }, { "ob_id": 10173, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_ghg", "resolvedTerm": "greenhouse gases" }, { "ob_id": 10211, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/dataType/dtype_co2", "resolvedTerm": "column-averaged dry air mole fraction of CO2" }, { "ob_id": 10529, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/freq/freq_sat_orb", "resolvedTerm": "satellite orbit frequency" }, { "ob_id": 10527, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_gosat_prog", "resolvedTerm": "GOSAT-Programme" }, { "ob_id": 10100, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org44", "resolvedTerm": "Netherlands Institute for Space Research" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12808, "uuid": "0508f3dd991144aa80346007a415fb07", "short_code": "coll", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci) dataset collection", "abstract": "The Greenhouse Gases Climate Change Initiative (GHG_cci) data products are near-surface-sensitive dry-air column-averaged mole fractions (mixing ratios) of methane (CH4) and carbon dioxide (CO2), created as part of the European Space Agency's (ESA) Greenhouses Gases Essential Climate Variable (ECV) CCI project. Denoted XCO2 (in ppmv) and XCH4 (in ppbv), the products have been retrieved from the SCIAMACHY instrument on ENVISAT and TANSO-FTS onboard GOSAT, using ECV Core Algorithms (ECAs). Other satellite instruments such as IASI, MIPAS and ACE-FTS have also been used to provide constraints for upper layers, with their corresponding retrieval algorithms referred to as Additional Constraints Algorithms (ACAs). The GHG data products are typically updated annually, the corresponding datasets being called Climate Research Data Packages (CRDP). \r\n\r\nThe products have each been generated from individual sensors, a single merged product not having yet been created \"combining\" the products from different sensors to cover the entire available satellite time series. One merged product has however been generated using the EMMA algorithm, covering a limited time period. This EMMA product is mainly used as a comparison tool for products generated using individual algorithms, making up the collection of products used by EMMA. \r\n\r\nTypically the same product (e.g. XCO2 from GOSAT) has been generated using different retrieval algorithms. A baseline algorithm has been used to generate one recommended baseline product, for users unsure which product to choose. Other products are called alternative products. However an alternative product's quality may equal that of the corresponding baseline product. It typically depends upon the application for which a product is required, which product is best to use as methods involved in producing them typically have varying strength and weaknesses. \r\n\r\nFor further information on the products, such as details on the SCIAMACHY and TANSO instruments, the algorithms used to generate the data and the data's format, please see the Product Specification Document (PSD) in the documentation section." } ], "responsiblepartyinfo_set": [ 49159, 49162, 49161, 140675, 140676, 140678, 140679, 140677 ], "onlineresource_set": [ 6556, 6564, 6565, 6566, 6567, 6568, 6569, 6557, 42068 ] }, { "ob_id": 12868, "uuid": "ce524139de81430e840d9a33daab3385", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): SCIAMACHY CO2 Level 2 Data Product (CO2_SCI_WFMD), version 3.8, generated with the WFMD algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 2 (CRDP#2), the WFMD XCO2 SCIAMACHY product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced using data acquired from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. \r\n\r\nThis product has been derived using the Weighting Function Modified DOAS (WFM-DOAS) algorithm, a least-squares method based on scaling pre-selected atmospheric vertical profiles. Note that this has been designated as an 'alternative' algorithm for the GHG CCI, and another XCO2 product has also been generated from the SCIAMACHY data using the baseline algorithm (the Bremen Optimal Estimation DOAS (BESD) algorithm). The link to this product's record page is provided in the documentation section. It is advised that users who aren't sure whether to use the baseline or alternative product use the product generated with the BESD baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage provided in the documentation section. \r\n\r\nThe data product is stored per day in seperate NetCDF-files (NetCDF-4 classic model). The product files contain the key products, i.e. the retrieved column-averaged dry air mole fractions for XCO2, several other useful parameters and additional information relevant to using the data e.g. the averaging kernels. For further information on the product, including details of the WFMD algorithm, the SCIAMACHY instrument and issues associated with the data please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-06-14T11:59:07.046799", "updateFrequency": "unknown", "dataLineage": "Data were processed by the ESA CCI GHG project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project", "removedDataReason": "", "keywords": "ESA, GREENHOUSE GASES, GHG, CCI, CO2, SCIAMACHY, WFMD, L2", "publicationState": "working", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "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": 12869, "dataPath": "/neodc/esacci/ghg/data/crdp_2/L2/SCIAMACHY/CO2_SCI_WFMD/v3.8", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1523735640, "numberOfFiles": 3332, "fileFormat": "The data are stored in NetCDF format (NetCDF-4 classic model) which can be read with standard tools in the common programming languages (IDL, Matlab, Python etc)" }, "timePeriod": { "ob_id": 3602, "startTime": "2002-10-01T00:00:00", "endTime": "2012-04-08T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [], "permissions": [ { "ob_id": 2564, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 34, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_ghg_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13295, "uuid": "f0c66ffa30514d2daee821286a014b16", "short_code": "proj", "title": "ESA Greenhouse Gases Climate Change Initiative Project", "abstract": "The European Space Agency Greenhouse Gases Climate Change Initiative (GHG CCI) project is one of several projects of ESA's Climate Change Initiative (CCI), which will deliver various Essential Climate Variables (ECVs)\r\n\r\nCarbon dioxide (CO2) and methane (CH4) are the two most important anthropogenic greenhouse gases (GHGs) and a focus of international research activities related to a better understanding of the carbon cycle (see, for example, the Global Carbon Project (GCP)).\r\n \r\nWithin the GHG-CCI project the focus is on satellite data. Satellite observations combined with modelling can add important missing global information on regional CO2 and CH4 (surface) sources and sinks required for better climate prediction. The GHG CCI project started on the 1st September 2010." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 1050, 4776, 4777, 11820, 11846, 11847, 11848, 11887, 11888, 11889, 11890, 11891, 11892, 11893, 11894, 11895, 11896, 11897, 11898, 11899, 11900 ], "vocabularyKeywords": [ { "ob_id": 10174, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/procLev/proc_level2", "resolvedTerm": "Level 2" }, { "ob_id": 10329, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/product/prod_sciam", "resolvedTerm": "SCIAMACHY" }, { "ob_id": 10529, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/freq/freq_sat_orb", "resolvedTerm": "satellite orbit frequency" }, { "ob_id": 10139, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org61", "resolvedTerm": "University of Bremen" }, { "ob_id": 10211, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/dataType/dtype_co2", "resolvedTerm": "column-averaged dry air mole fraction of CO2" }, { "ob_id": 10173, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/ecv/cciecv_ghg", "resolvedTerm": "greenhouse gases" }, { "ob_id": 10257, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_sciamachy", "resolvedTerm": "SCIAMACHY" }, { "ob_id": 10184, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_envisat", "resolvedTerm": "Envisat" }, { "ob_id": 10469, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_envisat_prog", "resolvedTerm": "Environmental Satellite" } ], "identifier_set": [], "observationcollection_set": [ { "ob_id": 12808, "uuid": "0508f3dd991144aa80346007a415fb07", "short_code": "coll", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci) dataset collection", "abstract": "The Greenhouse Gases Climate Change Initiative (GHG_cci) data products are near-surface-sensitive dry-air column-averaged mole fractions (mixing ratios) of methane (CH4) and carbon dioxide (CO2), created as part of the European Space Agency's (ESA) Greenhouses Gases Essential Climate Variable (ECV) CCI project. Denoted XCO2 (in ppmv) and XCH4 (in ppbv), the products have been retrieved from the SCIAMACHY instrument on ENVISAT and TANSO-FTS onboard GOSAT, using ECV Core Algorithms (ECAs). Other satellite instruments such as IASI, MIPAS and ACE-FTS have also been used to provide constraints for upper layers, with their corresponding retrieval algorithms referred to as Additional Constraints Algorithms (ACAs). The GHG data products are typically updated annually, the corresponding datasets being called Climate Research Data Packages (CRDP). \r\n\r\nThe products have each been generated from individual sensors, a single merged product not having yet been created \"combining\" the products from different sensors to cover the entire available satellite time series. One merged product has however been generated using the EMMA algorithm, covering a limited time period. This EMMA product is mainly used as a comparison tool for products generated using individual algorithms, making up the collection of products used by EMMA. \r\n\r\nTypically the same product (e.g. XCO2 from GOSAT) has been generated using different retrieval algorithms. A baseline algorithm has been used to generate one recommended baseline product, for users unsure which product to choose. Other products are called alternative products. However an alternative product's quality may equal that of the corresponding baseline product. It typically depends upon the application for which a product is required, which product is best to use as methods involved in producing them typically have varying strength and weaknesses. \r\n\r\nFor further information on the products, such as details on the SCIAMACHY and TANSO instruments, the algorithms used to generate the data and the data's format, please see the Product Specification Document (PSD) in the documentation section." } ], "responsiblepartyinfo_set": [ 49177, 49176, 49175, 49174, 140680, 140681, 140683, 140682 ], "onlineresource_set": [ 6614, 6617, 6618, 6619, 6621, 6622, 6615, 6620, 42066 ] }, { "ob_id": 12878, "uuid": "515df65d974541df82740062974212aa", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 02.1", "abstract": "The Soil Moisture CCI 'Active' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) 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, and AMSR2 satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v02.1 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2013-12-31 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 version 2.0 or the paper by Wagner 2012, both available in the documentation section. An overview of all known errors of the dataset is provided in the Comprehensive Error Characterization Report. 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 following references:\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. 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" }, "timePeriod": { "ob_id": 7067, "startTime": "1991-08-04T23:00:00", "endTime": "2013-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 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, 54640, 54641, 54642, 54643, 54644, 54645, 54646, 54647 ], "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": 10215, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/freq/freq_day", "resolvedTerm": "day" }, { "ob_id": 10379, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_ami_scat", "resolvedTerm": "AMI-SCAT" }, { "ob_id": 10285, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_ers1", "resolvedTerm": "ERS-1" }, { "ob_id": 10281, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_ers2", "resolvedTerm": "ERS-2" }, { "ob_id": 10365, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_ers", "resolvedTerm": "ERS" }, { "ob_id": 10104, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org70", "resolvedTerm": "Vienna University of Technology" }, { "ob_id": 10149, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org71", "resolvedTerm": "VU University Amsterdam" }, { "ob_id": 10175, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/procLev/proc_level3S", "resolvedTerm": "Level 3S" }, { "ob_id": 10185, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_ascat", "resolvedTerm": "ASCAT" }, { "ob_id": 10181, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/procLev/proc_level3", "resolvedTerm": "Level 3" }, { "ob_id": 10302, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/dataType/dtype_ssms", "resolvedTerm": "surface soil moisture degree of saturation absolute" }, { "ob_id": 10205, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_metOpA", "resolvedTerm": "Metop-A" }, { "ob_id": 10339, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/product/prod_active", "resolvedTerm": "ACTIVE" }, { "ob_id": 10493, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_metop", "resolvedTerm": "Metop" } ], "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": 26172, "uuid": "f4f77c55fd304ada9bfe2195927a053b", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 02.1 data collection", "abstract": "Soil Moisture data (version 02.1) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside 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 the AMI-WS and ASCAT satellite instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2. 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 2014-12-31 and the Active product covering 1991-08-05 to 2014-12-31. 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) or the paper by Wagner 2012, both available in linked documentation. 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 references as follows:\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" } ], "responsiblepartyinfo_set": [ 49200, 49199, 49197, 109462, 109847, 143311, 143312, 55921, 109848, 109463, 109849, 109850, 109851, 109852, 109853, 109854, 109855, 109856, 109857, 109858, 109859, 109860, 109861, 109862 ], "onlineresource_set": [ 6636, 6637, 6638, 6710, 6711, 6640, 24771, 6639, 42133 ] }, { "ob_id": 12881, "uuid": "a1ff285fb94c4c359269b1a12df957ec", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Passive' Product, Version 02.1", "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 scatterometer and radiometer soil moisture products, merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. 'Active' and 'Combined' products have also been created, the 'Active' product being a fusion of AMI-WS and ASCAT derived scatterometer and radiometer soil moisture products and the 'Combined Product' being a blended product based on the former two data sets. \r\n\r\nThe v02.1 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 2013-12-31. 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 version or the paper by Wagner 2012, both available in the documentation section. An overview of all known errors of the dataset is provided in the Comprehensive Error Characterization Report. 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 following references:\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. 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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": 26172, "uuid": "f4f77c55fd304ada9bfe2195927a053b", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 02.1 data collection", "abstract": "Soil Moisture data (version 02.1) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside 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 the AMI-WS and ASCAT satellite instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2. 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 2014-12-31 and the Active product covering 1991-08-05 to 2014-12-31. 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) or the paper by Wagner 2012, both available in linked documentation. 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 references as follows:\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. 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This is to help interpreting the results from OXICOA campaign by showing the seasonal variations." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 3636, "uuid": "c82574d742b6172e7abd7d01524eb22c", "short_code": "coll", "title": "ACSOE OXICOA EASE-96 and EASE-97: Airborne and Ground-based Measurements of Atmospheric Oxidants", "abstract": "The Atmospheric Chemistry Studies in the Oceanic Environment (ACSOE) was a 5-year Natural Environment Research Council (NERC) programme on tropospheric chemistry coordinated by the University of East Anglia and involving research groups from a number of UK universities and research institutes. The project had three consortia of UK institutes and universities, each of which focused on a different scientific topic. OXICOA (OXIdising Capacity of the Ocean Atmosphere) was a study of oxidant, radical and related gas-phase chemistry in the clean and moderately polluted marine atmosphere. The Eastern Atlantic Spring/Summer Experiments (EASE-96 and EASE-97) were carried to collect data. The dataset includes measurements of the OH and HO2 radicals, measurements of halogen oxide radicals at Mace Head in conjunction with a survey of potential organic halogen source gases. 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The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these both being fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. \r\n\r\nThe v02.1 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 2013-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version 2.0 or the paper by Wagner 2012, both available in the documentation section. An overview of all known errors associated with it is provided in the Comprehensive Error Characterization Report. 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 following references:\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. 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"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": 26172, "uuid": "f4f77c55fd304ada9bfe2195927a053b", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 02.1 data collection", "abstract": "Soil Moisture data (version 02.1) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside 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 the AMI-WS and ASCAT satellite instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2. 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 2014-12-31 and the Active product covering 1991-08-05 to 2014-12-31. 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) or the paper by Wagner 2012, both available in linked documentation. 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 references as follows:\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" } ], "responsiblepartyinfo_set": [ 49233, 49236, 49234, 109464, 143315, 143316, 55905, 109465, 109880, 109881, 109882, 109883, 109884, 109885, 109886, 109887, 109888, 109889, 109890, 109891, 109892, 109893, 109894 ], "onlineresource_set": [ 6714, 6719, 6715, 6718, 6720, 6716, 24775, 6717, 42135 ] }, { "ob_id": 12889, "uuid": "3c3345982d4f4d9ab5d0155bee0277d5", "title": "ESA ALPHASAT: preprocessed radio propagation measurements at 40 GHz at Chilbolton, Hampshire v1", "abstract": "Radio propagation measurements at 40 GHz at Chilbolton, Hampshire for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": 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the Aldo Paradoni Payload (TDP5) propagation beacon.\r\n\r\nMeasurements were made at 20 and 40 GHz frequencies.\r\n\r\nThe measurements were made as part of the ESA funded ASALASCA (Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon) project. \r\n\r\nThe collection is additionally supplemented by surface meteorological measurements from the Chilbolton Observatory, Hampshire, UK for use in conjunction with the radio propagation measurements made at Chilbolton.\r\n\r\nMeasurements began in July 2016 and are presently ongoing." } ], "responsiblepartyinfo_set": [ 49314, 49315, 49316, 49317, 103862, 103863, 103864, 103866, 103865, 49318 ], "onlineresource_set": [] }, { "ob_id": 12890, "uuid": "4eec83c4bbec4c8ea873188d90fc243f", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 02.1", "abstract": "Ancillary datasets were used in the 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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 v02.1 Soil Moisture CCI data.\r\n\r\nFor further information on these and the references associated with them please see the Product Specification Document (PSD), a link to which is provided in linked documentation. The \"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, and AMSR2 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 or within the Product Specification Document.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T12:18:51", "updateFrequency": "notPlanned", "dataLineage": "Data were processed by the ESA CCI Soil Moisture project team and transferred to CEDA for the ESA CCI Open Data Portal Project.\r\nThis data forms part of the v02.1 Soil Moisture dataset (doi:10.5285/f4f77c55fd304ada9bfe2195927a053b. http://dx.doi.org/10.5285/f4f77c55fd304ada9bfe2195927a053b )", "removedDataReason": "", "keywords": "ESA, Soil Moisture, CCI, Ancillary", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2018-06-07T15:53:09", "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": 12910, "dataPath": "/neodc/esacci/soil_moisture/data/ancillary/v02.1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1584922, "numberOfFiles": 6, "fileFormat": "NetCDF-4 classic format. " }, "timePeriod": { "ob_id": 7091, "startTime": "2002-06-30T23:00:00", "endTime": "2011-10-04T22:59:59" }, "resultQuality": { "ob_id": 3135, "explanation": "as supplied by the Soil Moisture CCI team", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2018-06-22" }, "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": [ 52664, 52665, 54682, 54683, 54684, 54685, 54686 ], "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": 10149, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org71", "resolvedTerm": "VU University Amsterdam" }, { "ob_id": 10104, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/org/org70", "resolvedTerm": "Vienna University of Technology" } ], "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": 26172, "uuid": "f4f77c55fd304ada9bfe2195927a053b", "short_code": "coll", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Version 02.1 data collection", "abstract": "Soil Moisture data (version 02.1) from the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. This dataset collection contains three surface soil moisture datasets, alongside 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 the AMI-WS and ASCAT satellite instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2. 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 2014-12-31 and the Active product covering 1991-08-05 to 2014-12-31. 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) or the paper by Wagner 2012, both available in linked documentation. 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 references as follows:\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. 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