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Along with the scanned manuscripts these data cover the period 1760 to 1975.\r\n\r\nVariables available include: atmospheric pressure, temperature, wind speed and rainfall.\r\n\r\nThe scanned manuscripts are from 6 Scottish sites, the Leeds Philosophical Society and the Devon and Exeter Institute."}],"responsiblepartyinfo_set":[219118,219119,219120,219121,219122,219123,219124,219125,219117,219126],"onlineresource_set":[95538]},{"ob_id":45847,"uuid":"88dc78a226634c1c929ce93ba8eb0074","title":"ESA Water Vapour Climate Change Initiative (Water_Vapour_cci): Total Column Water Vapour monthly gridded data over land at 0.5 degree resolution, version 4.2","abstract":"This dataset consists of monthly total column water vapour (TCWV) over land, at a 0.5 degree resolution, observed by various satellite instruments. \r\nIt has been produced by the European Space Agency Water Vapour Climate Change Initiative (Water_Vapour_cci), and forms part of their TCVW over land Climate Data Record 1 (TCWV-land (CDR-1)).\r\n\r\nThis version of the data is v4.2. 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This is an updated dataset from the v3.2 product, in summary providing the following improvements:\r\n- Time series has been extended, now covering years 2000-2023.\r\n- L1b input data has been extended by using the full time range of Terra MODIS measurements, and by ingesting Aqua MODIS and Sentinel-3 OLCI-B as additional sensors.\r\n- Number of L2 observations contributing to a L3 grid cell is now provided per single sensor.\r\n- Flags have been revised and extended.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"","dataLineage":"Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"water vapour, CCI, TCWV","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":true,"language":"English","resolution":"0.05 degrees","status":"completed","dataPublishedTime":"2026-07-01T13:51:09","doiPublishedTime":"2026-07-01T14:01:11","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":45901,"dataPath":"/neodc/esacci/water_vapour/data/TCWV-land/L3/v4.2/0.05deg/monthly/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":31194627100,"numberOfFiles":287,"fileFormat":"Files are provided in NetCDF format."},"timePeriod":{"ob_id":13143,"startTime":"2000-03-01T00:00:00","endTime":"2023-12-31T23:59:59"},"resultQuality":{"ob_id":3785,"explanation":"For inormation on the data quality see the documentation at https://climate.esa.int/projects/water-vapour/","passesTest":true,"resultTitle":"water vapour cci","date":"2021-11-01"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":{"ob_id":45858,"uuid":"747e1b46801f405a915ca8d9475ed065","short_code":"cmppr","title":"ESA Water Vapour Climate Change Initiative: Total Column Water Vapour over land, v4.2","abstract":"The ESA Water Vapour Climate Change Initiative Total Column Water Vapour dataset has been derived from the following satellite instruments:  MERIS on ENVISAT, MODIS on TERRA and OLCI on Sentinel-3.   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The project aims to generate new global high-quality climate data records of both total column and vertically resolved water vapour."}],"inspireTheme":[],"topicCategory":[],"phenomena":[60315,59109,82827,50415,60311,50417,60310,93431,60312,60313,93435,60316,60317,60318,60319],"vocabularyKeywords":[],"identifier_set":[13919],"observationcollection_set":[{"ob_id":45846,"uuid":"a41bd9968f684eebb978af872a4f1c6e","short_code":"coll","title":"ESA Water Vapour Climate Change Initiative (Water_Vapour_cci):   Total Column Water Vapour over land (CDR1), v4.2","abstract":"This collection of data comprises an updated version of the European Space Agency (ESA) Water Vapour Climate Change Initiative (Water Vapour_cci) Total Column Water Vapour over land, Climate Data Record 1 (TCWV-land (CDR1)).   It comprises four datasets providing daily and monthly averages at 0.5 and 0.05 degree resolution respectively.\r\n\r\nThis is an updated version of the previous v3.2 version."}],"responsiblepartyinfo_set":[219160,219161,219162,219159,219163,219164,219165,219166,219168,219167,219232,219233,219169,219170,219171,219172],"onlineresource_set":[95557,95544,95545,95546]},{"ob_id":45849,"uuid":"04d7581f7c024e669bea5624993f8a95","title":"Whole Atmosphere Community Climate Model (WACCM) and WACCM-RR simulations for 2010","abstract":"The dataset was produced from two numerical simulations for the year 2010 using the Whole Atmosphere Community Climate Model with Regional Refinement (WACCM-RR). The standard configuration (Non-RR) uses a global horizontal resolution of approximately 1° (~111 km), while the refined configuration (RR) employs a nested grid of ~1/8° (~14 km) over the contiguous United States (CONUS) with 1° resolution elsewhere. 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The individual IW images cover approximately 200 km in azimuth and 250 km in the range direction with a pixel spacing of 10 m. This product provides along-track primary significant wave height measurements and secondary sea state parameters, calibrated with CMEMS (Copernicus Marine Service) model data and reference in situ measurements at 5 km resolution over each image, processed with the SAR-SeaStaR (SAR Sea State Retrieval) algorithm used developed at the DLR (German Aerospace Center),  separated per satellite and image, including all measurements with flags and uncertainty estimates. These are expert products with rich content and no data loss. The SAR IW data used in the Sea State CCI SAR IW onboard Sentinel-1 Level 2P (L2P) ISSP v4 dataset come from the Sentinel-1 satellite missions spanning from 2014 to 2024 (Sentinel-1 A, Sentinel-1 B).\r\n\r\nReference: Pleskachevsky, A., Tings, B., S. Wiehle, S., Imber, J., Jacobsen, S., 2022. Multiparametric sea state fields from synthetic aperture radar for maritime situational awareness. Remote Sens. Environ., vol. 280, Oct. 2022, Art. no. 113200.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data was produced by the ESA Sea State CCI team at Ifremer and was transferred to CEDA as part of the ESA CCI Open Data Portal project.","removedDataReason":"","keywords":"CCI, Sea State, Integrated Sea State Parameters, ISSP, SAR","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":true,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-07-08T14:56:33","doiPublishedTime":"2026-07-08T15:27:37","removedDataTime":null,"geographicExtent":{"ob_id":2576,"bboxName":"","eastBoundLongitude":180.0,"westBoundLongitude":-180.0,"southBoundLatitude":-80.0,"northBoundLatitude":80.0},"verticalExtent":null,"result_field":{"ob_id":46071,"dataPath":"/neodc/esacci/sea_state/data/v4_release/sar/l2p/sentinel1/dlr-iw/v1.0/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":425389127230,"numberOfFiles":1329829,"fileFormat":"Data are in NetCDF format"},"timePeriod":{"ob_id":13239,"startTime":"2014-10-04T00:00:00","endTime":"2024-12-31T23:59:59"},"resultQuality":{"ob_id":3367,"explanation":"The data were quality checked and compared to in situ reference data. 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The CCI programme was launched by ESA in 2010, to produce long term datasets of Essential Climate Variables (ECV's) derived from global satellite data.   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The EW mode acquires data over 400 km swath width with a coarser pixel spacing of 40 m (GRDM products) and 25 m (GRDH). This product provides along-track primary significant wave height measurements and secondary sea state parameters, calibrated with CMEMS model data and reference in situ measurements at 17.5 km resolution over each image, processed with the SAR-SeaStaR (SAR Sea State Retrieval) algorithm used developed at the DLR (German Aerospace Centre),  separated per satellite and image, including all measurements with flags and uncertainty estimates. These are expert products with rich content and no data loss. The SAR EW data used in the Sea State CCI SAR EW onboard Sentinel-1 Level 2P (L2P) ISSP v4 dataset come from the Sentinel-1 satellite missions spanning from 2014 to 2024 (Sentinel-1 A, Sentinel-1 B).\r\n\r\nReference: Pleskachevsky, A., Tings, B., S. Wiehle, S., Imber, J., Jacobsen, S., 2022. Multiparametric sea state fields from synthetic aperture radar for maritime situational awareness. Remote Sens. 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The CCI programme was launched by ESA in 2010, to produce long term datasets of Essential Climate Variables (ECV's) derived from global satellite data.   In this context, the Sea State CCI+ project was kicked off in 2018 in order to produce a CDR for the new ECV \"Sea State\"."}],"inspireTheme":[],"topicCategory":[],"phenomena":[50561,93842,93843,93844,93845,93846,93847,93848,12182,66527,66528,66530,66536,66537,66541,66542,66543,66544,66545,66546,50559],"vocabularyKeywords":[],"identifier_set":[13932],"observationcollection_set":[],"responsiblepartyinfo_set":[219216,219217,219218,219219,219220,219221,219222,219223,219224,219225],"onlineresource_set":[95551,95553,95554,95715]},{"ob_id":45861,"uuid":"6fac470b997844bb9bf2f4933e031466","title":"BAQS: FIDAS PM data.","abstract":"Data collected using a Palas Fidas 200.\r\nData submitted is hourly PM1.0, PM2.5 and PM10.","creationDate":"2026-05-07T08:45:39.709801","lastUpdatedDate":"2026-05-07T09:32:17.243783","latestDataUpdateTime":"2026-05-07T08:45:39.709806","updateFrequency":"notPlanned","dataLineage":"1. 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Hourly data was compared to Lady Wood AURN and flagged according to whether the data was \r\n0b not_used\r\n1b good\r\n2b bad\r\n3b suspect_data\r\n4b local_unusual_activity","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-05-07"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":45862,"uuid":"22d1c557890848c093c426f2e0335f48","short_code":"acq","title":"Acquisition for: FIDAS PM data.","abstract":""},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[],"projects":[{"ob_id":45718,"uuid":"fc10dbeed0df48d6aff7ab27892e7609","short_code":"proj","title":"Birmingham Air Quality Supersite (BAQS)","abstract":""}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[219242,219243,219244,219245,219246,219247,219248,219249],"onlineresource_set":[]},{"ob_id":45866,"uuid":"3e1a04ac64404455b0baa1591e5ee0a8","title":"BAQS: Aerodyne ACSM data","abstract":"ACSM: Aerosol Chemical Speciation Monitor, providing mass concentrations of organics, sulfate, nitrate, chloride and ammonium.","creationDate":"2026-05-07T09:00:19.502508","lastUpdatedDate":"2026-05-07T09:25:26.032613","latestDataUpdateTime":"2026-05-07T09:00:19.502512","updateFrequency":"notPlanned","dataLineage":"Data collected at the Birmingham Air Quality Site in 20 minute intervals.","removedDataReason":"","keywords":"AMM; NIT; SUL; ORG","publicationState":"working","nonGeographicFlag":true,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":null,"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":13151,"startTime":"2019-03-01T00:00:00","endTime":null},"resultQuality":{"ob_id":4900,"explanation":"2. Raw data collected outside of the operating parameters of the instrument were removed.\r\n3. All ACSM data collected for years before 2026 were scaled until mass closure and flagged according to whether the data was:\r\n\r\n0b not_used\r\n1b good\r\n2b bad\r\n3b suspect_data\r\n4b local_unusual_activity\r\n\r\nMass closure used PM2.5 measured with a Palas FIDAS 200 E with BC measured using an Magee AE33 Aethelometer.  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Hourly 880nm and 370nm data was compared to Lady Wood AURN and flagged according to whether the data was:\r\n\r\n0b not_used\r\n1b good\r\n2b bad\r\n3b suspect_data\r\n4b local_unusual_activity","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-05-07"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":45870,"uuid":"59bc9c38af2b4b2dbe11fce6d4a3d8f0","short_code":"acq","title":"Acquisition for: BAQS: Magee AE33 Aethelometer","abstract":""},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[],"projects":[{"ob_id":45718,"uuid":"fc10dbeed0df48d6aff7ab27892e7609","short_code":"proj","title":"Birmingham Air Quality Supersite (BAQS)","abstract":""}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[219271,219272,219273,219274,219275,219276,219277,219278],"onlineresource_set":[]},{"ob_id":45873,"uuid":"b561993597ad46f58c26cf58693b909d","title":"Processed Autonomous Underwater Vehicle (AUV) multibeam bathymetry and backscatter data collected during RRS James Cook cruise JC257 in the UK-1 exploration area, Clarion-Clipperton Zone, Pacific Ocean, 2024","abstract":"Multibeam Echosounder (MBES) bathymetry and backscatter data were acquired in the UK-1 exploration area of the Clarion-Clipperton Zone (CCZ), Pacific Ocean, using the Autonomous Underwater Vehicle (AUV) Autosub5-mounted Norbit WBMS-bathy MBES during RRS James Cook Cruise JC257 between 16/02/2024 and 09/03/2024. These datasets were collected to investigate local-scale seafloor morphology and to improve understanding of biodiversity patterns and benthic habitat distribution within the CCZ, by scientists from the National Oceanography Centre, Southampton, UK as part of the NERC-funded Seabed Mining And Resilience To EXperimental impact (SMARTEX). The AUV was used to map in high resolution the 0, 1, 16, 30 and 100 km sites. Bathymetric data were processed using Quality Positioning Services (QPS) Qimera 2.7.6, while backscatter data were subsequently processed using QPS FMGT 7.11.2. Tidal corrections were derived at the Long Mooring 1 site using the TMD toolbox, based on the TPXO global tidal inversion model developed at Oregon State University (OSU), and applied to the dataset. CTD-derived sound velocity profiles (SVPs) were then used to further refine the acoustic corrections. Semi-automatic and manual cleaning procedures were carried out to remove erroneous soundings, particularly along the outer swath edges. The 0–1 km site was surveyed during missions AS5M084 and AS5M085; the latter was spatially adjusted through the identification of common seafloor features. Sites at 16 and 30 km were surveyed during mission AS5M089. The 100 km site was mapped during missions AS5M093, AS5M094, and AS5M096, with AS5M093 used as a spatial reference to align the subsequent surveys based on shared geomorphological features. For each site, bathymetric grids were generated at 1, 2, and 5 m resolution, in WGS84 UTM Zone 11N projection, with interpolation applied where necessary to fill gaps between survey lines. Processed .gsf files were then exported to QPS FMGT to produce backscatter mosaics at 0.20 m resolution. Both backscatter and bathymetry data are supplied in .xyz format. Additionally, bathymetry are supplied in ESRI ASCII Raster format, and backscatter as GeoTIFF files.","creationDate":"2026-05-07T14:12:45.936051","lastUpdatedDate":"2026-05-06T15:46:06","latestDataUpdateTime":"2026-05-06T15:46:06","updateFrequency":"","dataLineage":"The data are archived on the British Oceanographic Data Centre (BODC)'s archive at the Centre for Environmental Data Analysis (CEDA) and assigned a DOI. 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Hourly data was compared to Lady Wood AURN and flagged according to whether the data was \r\n0b not_used\r\n1b good\r\n2b bad\r\n3b suspect_data\r\n4b local_unusual_activity","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-05-08"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":45876,"uuid":"6e686ce733964a0eb74499c50297be74","short_code":"acq","title":"Acquisition for: BAQS: FIDAS PN data.","abstract":""},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[],"projects":[{"ob_id":45718,"uuid":"fc10dbeed0df48d6aff7ab27892e7609","short_code":"proj","title":"Birmingham Air Quality Supersite (BAQS)","abstract":""}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[219315,219316,219317,219318,219319,219320,219321,219322],"onlineresource_set":[]},{"ob_id":45881,"uuid":"96388e7a347b4a5fa287f012eb5d6920","title":"EOCIS: CHUK Aerosol Optical Depth, Monthly L3C Product, v1.14","abstract":"This dataset contains Climate High resolution UK (CHUK) Aerosol Optical Depth data produced within the Earth Observation Climate Information Service (EOCIS) project.\r\n\r\nThese data are derived from Swansea University Global Aerosol retrievals (v1.14) for the Sea and Land Surface Temperature Radiometers (SLSTR) on the Sentinel-3A and Sentinel-3B satellites (https://catalogue.ceda.ac.uk/uuid/17d83baf50a644d89a4fb78ca6cccec1/). Original level 2 retrievals in the UK region have been re-projected from the instrument swath onto the Climate High-resolution grid for the UK at 100m resolution and composited on a monthly timescale. They contain the aerosol optical depth and the fine-mode aerosol optical depth at 550nm. Two versions of each variable are included: with and without the post-processing filtering that is used in the global dataset.","creationDate":"2025-02-10T14:53:22.745005","lastUpdatedDate":"2026-05-12T15:53:12","latestDataUpdateTime":"2026-05-12T15:53:16","updateFrequency":"notPlanned","dataLineage":"This dataset was produced by Swansea University in the context of the Earth Observation Climate Information Service project.","removedDataReason":"","keywords":"Aerosol,Optical,depth,UK,SLSTR,Sea,Surface,Temperature,Radiometer,High-resolution,EOCIS","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-06-15T09:37:49","doiPublishedTime":"2026-07-02T13:57:21.203907","removedDataTime":null,"geographicExtent":{"ob_id":4693,"bboxName":"","eastBoundLongitude":4.75,"westBoundLongitude":-15.37,"southBoundLatitude":47.09,"northBoundLatitude":61.14},"verticalExtent":null,"result_field":{"ob_id":45889,"dataPath":"/neodc/eocis/data/CHUK/aerosol_optical_depth/SLSTR/L3C/monthly/v1.14","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":34308490091,"numberOfFiles":190,"fileFormat":"The data are in NetCDF format."},"timePeriod":{"ob_id":12069,"startTime":"2016-05-01T00:00:00","endTime":"2025-03-31T00:00:00"},"resultQuality":{"ob_id":4918,"explanation":"For information on the data quality see the related documentation and links therein.","passesTest":true,"resultTitle":"EOCIS CHUK - see docs.","date":"2026-06-15"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":43477,"uuid":"b485aa86fd1f42188e80bcf2f64de0a5","short_code":"acq","title":"Acquisition for: EOCIS: CHUK Aerosol Optical Depth, V1.0","abstract":""},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[233],"discoveryKeywords":[],"permissions":[{"ob_id":2528,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":8,"licenceURL":"http://creativecommons.org/licenses/by/4.0/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":43216,"uuid":"8bffaba46c4a4b8c82e4be2c91c637b9","short_code":"proj","title":"Earth Observation Climate Information Service (EOCIS)","abstract":"The UK Earth Observation Climate Information Service exploits the observations available from environmental sensors orbiting in space to create climate data records and climate information. EOCIS was announced by the government in November 2022, and formally launched in March 2023. It is funded currently until March 2025. \r\n\r\nEOCIS is a collaboration led by the National Centre for Earth Observation, and involving over a dozen research organisations. EOCIS addresses 12 categories of global and regional essential climate variables, which are the following:\r\n- Sea surface temperature\r\n- Ocean reflectance\r\n- Fire occurrence and emissions\r\n- Aerosol and particulate\r\n- Cloud-aerosol-radiation\r\n- Methane\r\n- Land surface temperature\r\n- Water vapour, ozone\r\n- Arctic: ice sheet mass and sea ice\r\n- Eurasia: surface methane\r\n- Africa: soil water balance\r\n- Antarctic: ice sheet mass and ice velocity\r\n\r\nEOCIS is also creating new climate data at high resolution for the UK specifically. This includes both rapid-response information for climate-linked events (fire early warning and urban flood mapping) and longer term climate data linked to human and ecosystem health and landscape greenhouse gas emissions."}],"inspireTheme":[],"topicCategory":[],"phenomena":[93314,93315,74919,74920,74921,74922],"vocabularyKeywords":[],"identifier_set":[13923],"observationcollection_set":[{"ob_id":45880,"uuid":"061fc86521c24c32b2b29aea08080195","short_code":"coll","title":"EOCIS: CHUK Aerosol Optical Depth","abstract":"This dataset collection contains Climate High resolution UK (CHUK) Aerosol Optical Depth data produced within the Earth Observation Climate Information Service (EOCIS) project.\r\n\r\nThese data are derived from Swansea University Global Aerosol retrievals (v1.14) for the Sea and Land Surface Temperature Radiometers (SLSTR) on the Sentinel-3A and Sentinel-3B satellites (https://catalogue.ceda.ac.uk/uuid/17d83baf50a644d89a4fb78ca6cccec1/). Original level 2 retrievals in the UK region have been re-projected from the instrument swath onto the Climate High-resolution grid for the UK at 100m resolution and composited over daily and monthly timescales. They contain the aerosol optical depth and the fine-mode aerosol optical depth at 550nm. Two versions of each variable are included: with and without the post-processing filtering that is used in the global dataset."}],"responsiblepartyinfo_set":[219346,219347,219348,219349,219350,219351,219353,220060,219352],"onlineresource_set":[95706]},{"ob_id":45882,"uuid":"809e67dc32ac4679a5d6a18a35551213","title":"EOCIS: CHUK Particulate Matter (PM2.5, PM10), Monthly L3C Product, v1.14","abstract":"This dataset contains Particulate Matter (PM2.5, PM10) data produced within the Earth Observation Climate Information Service (EOCIS) project. These data are produced by a machine learning algorithm that combines inputs from satellite, in-situ and analysis data sources. The algorithm generates measurements of the particulate matter (PM) at sizes smaller than 2.5 µm (PM2.5) and 10 µm (PM10). Original level 2 retrievals in the UK region have been reprojected from the instrument swath onto the Climate High-resolution grid for the UK (CHUK) at 100m resolution and composited over daily and monthly timescales. Two versions of each variable are included: with and without the post-processing filtering that is used in the global AOD dataset that is used as an input.","creationDate":"2025-03-27T12:09:23.383695","lastUpdatedDate":"2026-05-12T15:53:46","latestDataUpdateTime":"2026-05-12T15:53:49","updateFrequency":"notPlanned","dataLineage":"This dataset was produced by Swansea University in the context of the Earth Observation Climate Information Service project.","removedDataReason":"","keywords":"Particulate,Matter,PM2.5,PM10,Aerosol,Surface,Temperature,Land,Radiometer,SLSTR,Sea,EOCIS","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-06-15T09:39:59","doiPublishedTime":"2026-07-02T13:58:08.626208","removedDataTime":null,"geographicExtent":{"ob_id":4727,"bboxName":"","eastBoundLongitude":4.75,"westBoundLongitude":-15.37,"southBoundLatitude":47.09,"northBoundLatitude":61.14},"verticalExtent":null,"result_field":{"ob_id":45891,"dataPath":"/neodc/eocis/data/CHUK/particulate_matter/SLSTR/L3C/monthly/v1.14","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":21382335261,"numberOfFiles":136,"fileFormat":"The data are in NetCDF format."},"timePeriod":{"ob_id":12213,"startTime":"2016-05-01T00:00:00","endTime":"2023-12-31T00:00:00"},"resultQuality":{"ob_id":4918,"explanation":"For information on the data quality see the related documentation and links therein.","passesTest":true,"resultTitle":"EOCIS CHUK - see docs.","date":"2026-06-15"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":43743,"uuid":"70b7aa53b799499aba3cc9ea03bdc122","short_code":"acq","title":"Acquisition for: EOCIS: CHUK Particulate Matter (PM2.5, PM10), V1.00","abstract":""},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[233],"discoveryKeywords":[],"permissions":[{"ob_id":2528,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":8,"licenceURL":"http://creativecommons.org/licenses/by/4.0/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":43216,"uuid":"8bffaba46c4a4b8c82e4be2c91c637b9","short_code":"proj","title":"Earth Observation Climate Information Service (EOCIS)","abstract":"The UK Earth Observation Climate Information Service exploits the observations available from environmental sensors orbiting in space to create climate data records and climate information. EOCIS was announced by the government in November 2022, and formally launched in March 2023. It is funded currently until March 2025. \r\n\r\nEOCIS is a collaboration led by the National Centre for Earth Observation, and involving over a dozen research organisations. EOCIS addresses 12 categories of global and regional essential climate variables, which are the following:\r\n- Sea surface temperature\r\n- Ocean reflectance\r\n- Fire occurrence and emissions\r\n- Aerosol and particulate\r\n- Cloud-aerosol-radiation\r\n- Methane\r\n- Land surface temperature\r\n- Water vapour, ozone\r\n- Arctic: ice sheet mass and sea ice\r\n- Eurasia: surface methane\r\n- Africa: soil water balance\r\n- Antarctic: ice sheet mass and ice velocity\r\n\r\nEOCIS is also creating new climate data at high resolution for the UK specifically. This includes both rapid-response information for climate-linked events (fire early warning and urban flood mapping) and longer term climate data linked to human and ecosystem health and landscape greenhouse gas emissions."}],"inspireTheme":[],"topicCategory":[],"phenomena":[74919,74920,74921,74922,93324,93325,93326,93327],"vocabularyKeywords":[],"identifier_set":[13925],"observationcollection_set":[{"ob_id":45879,"uuid":"a01f32f71c4f424d940aaa4a63fbbec4","short_code":"coll","title":"EOCIS: CHUK Particulate Matter (PM2.5, PM10)","abstract":"This dataset collection contains Climate High resolution UK (CHUK) Particulate Matter (PM2.5, PM10) data produced within the Earth Observation Climate Information Service (EOCIS) project. \r\n\r\nThese data are produced by a machine learning algorithm that combines inputs from satellite, in-situ and analysis data sources. The algorithm generates measurements of the particulate matter (PM) at sizes smaller than 2.5 µm (PM2.5) and 10 µm (PM10). Original level 2 retrievals in the UK region have been reprojected from the instrument swath onto the Climate High-resolution grid for the UK at 100m resolution and composited over daily and monthly timescales. Two versions of each variable are included: with and without the post-processing filtering that is used in the global AOD dataset that is used as an input."}],"responsiblepartyinfo_set":[219354,219355,219356,219357,219358,219359,219360,220062,219361],"onlineresource_set":[95704]},{"ob_id":45903,"uuid":"b11a935c076243c1bf5c0c590e62af66","title":"Images of airborne particles including microplastics captured using Burkard spore traps at Hull, UK and Gqeberha, South Africa (March, July, and August 2023)","abstract":"This dataset contains images of airborne particles captured by Burkard spore traps, a method commonly used for global pollen monitoring. The images can be used for the identification, characterisation, and quantification of outdoor airborne particles, including microplastics.\r\n\r\nBurkard spore traps continuously sampled air for seven days at the following times and locations:\r\n- The University of Hull, UK (53° 46’ 16.87” N; 0° 22’ 2.64” W) starting at 10:00 on 10/03/2023\r\n- The University of Hull, UK (53° 46’ 16.87” N; 0° 22’ 2.64” W) starting at 11:00 on 18/07/2023\r\n- Nelson Mandela University, Gqeberha, South Africa (34° 0'4.66\"S; 25°40'2.40\"E) starting at 13:00 on 03/08/2023\r\n\r\nTraps were on flat roofs with the sampling orifice at least 1 m above the surface and at least 2 m away from the building edge. Tape adhesive was glycine jelly and an oxidative digest using 30% hydrogen peroxide was performed to remove organic mater.\r\n\r\nThis dataset consists of screenshot images of airborne particles during downstream analysis with Fourier Transform Infrared (FTIR) spectroscopy, used to identify materials, in OMNIC Picta software. Low-resolution screenshots are provided because the original images are no longer available.\r\n\r\nFiles are named using the convention Burkard_City_Country_Month_DataCollectionDay_ParticleNumber.jpg, e.g.:\r\n- Burkard_Gqeberha_SA_August_1B_3.jpg\r\n- Burkard_Hull_UK_March_C4_48.jpg\r\n\r\nThis dataset was produced under Natural Environment Research Council (NERC) project 'Development of the first global standard for airborne microplastic monitoring' (grant reference: NE/X010201/1).","creationDate":"2026-05-13T14:55:05.581380","lastUpdatedDate":"2026-05-13T14:55:05","latestDataUpdateTime":"2026-05-13T14:55:05","updateFrequency":"notPlanned","dataLineage":"Data were produced by the project team. At the time of archiving the original data were no longer available, so low-resolution JPEG screenshots from the OMNIC Picta software were supplied for archiving at the Centre for Environmental Data Analysis (CEDA) in place of the original data.","removedDataReason":"","keywords":"Airborne, Particles, Microplastics, Pollution, Pollen, Monitoring, Public Health, Air Quality","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":"2026-08-10T14:53:14","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5186,"bboxName":"Hull to Gqeberha","eastBoundLongitude":25.667333,"westBoundLongitude":-0.3674,"southBoundLatitude":-34.001294,"northBoundLatitude":53.77135},"verticalExtent":null,"result_field":{"ob_id":46155,"dataPath":"/badc/deposited2026/Airborne_particles_spore_traps/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":50430499,"numberOfFiles":1538,"fileFormat":"JPEG"},"timePeriod":{"ob_id":13316,"startTime":"2023-03-10T10:00:00","endTime":"2023-08-10T13:00:00"},"resultQuality":{"ob_id":4905,"explanation":"This dataset contains low-resolution JPEG screenshots as the original high-resolution images were not available at the time of archiving.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-05-13"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":45904,"uuid":"45c5d217e851496e83a98b8458e652e6","short_code":"acq","title":"Acquisition for: Airborne particles including microplastics from Burkard Spore Traps","abstract":""},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[236],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":45744,"uuid":"c55be4caa3ac4f99bfb72606058d24ac","short_code":"proj","title":"Development of the first global standard for airborne microplastic monitoring","abstract":"This project aimed to address the growing concern of airborne microplastics (MPs), which are widespread in the environment and increasingly linked to potential human and ecological health impacts. It developed a robust, accessible method for monitoring MPs in air by adapting existing pollen sampling techniques, enabling wider and lower-cost deployment. The project also created automated technologies for identifying and counting MPs using image analysis and calibration reference strips. Through international trials and comparison with established monitoring methods, the research sought to deliver reliable, reproducible global standards for airborne MP measurement, supporting future air quality and public health monitoring."}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[219384,219385,219386,219387,219388,219389,219399,220439,219401,219413],"onlineresource_set":[95896,95897]},{"ob_id":45905,"uuid":"a7c36b1be037423cbcd920a968801b27","title":"Atmospheric tidal coefficients from an SD-WACCM-D simulation at two longitudinal slices: the equator and 69 degrees north (2005–2013)","abstract":"This dataset was extracted from two numerical simulations of the Earth's atmosphere calculated using the Specified Dynamics version of the Whole Atmosphere Community Climate Model (WACCM) with D-region ionic chemistry.\r\n\r\nIncluded with both simulations are the fourier coefficients required to calculate the atmospheric tides at two longitudinal slices, one over the equator and one at 69 degrees north. The latter location covers a highly instrumented site, allowing for the inclusion of radar observations of atmospheric tides. The daily mean state of the atmosphere at these two locations is also included. In the first run, both the geomagnetic activity and F10.7 flux provided to the model represented daily means. In the second run, the data have a three-hour temporal resolution.\r\n\r\nThese data were produced by University of Leeds and British Antarctic Survey (BAS) scientists under Natural Environment Research Council (NERC) project MesoS2D (grant reference: NE/V018426/1).","creationDate":"2026-05-14T09:09:40.043975","lastUpdatedDate":"2026-05-14T09:20:20","latestDataUpdateTime":"2026-05-14T09:09:40","updateFrequency":"notPlanned","dataLineage":"Data were generated using CESM version 2.1.3 using the Archer2 HPC system with time awarded to the MESOS2D project. The fourier coefficients required to calculate the atmospheric tides were accumulated over the course of a data for the diurnal, semidiurnal, and terdiurnal tides. Data were extracted for two longitudinal slices, one over the equator and one at 69 degrees north, the latter of which allows for the calculation of tides over Tromso, a highly instrumented site. These extracted data were supplied by the project team for archiving at CEDA.","removedDataReason":"","keywords":"atmospheric tides, CESM, WACCM, NE/V018426/1","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-05-19T11:00:00","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5157,"bboxName":"Long: -180 to 180; Lat: 69 to 0","eastBoundLongitude":180.0,"westBoundLongitude":-180.0,"southBoundLatitude":0.0,"northBoundLatitude":69.0},"verticalExtent":null,"result_field":{"ob_id":45943,"dataPath":"/badc/deposited2026/MESOS2D_Tidal_Coeff/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":32227174511,"numberOfFiles":5,"fileFormat":"NetCDF"},"timePeriod":{"ob_id":13169,"startTime":"2005-07-02T00:00:00","endTime":"2013-03-26T00:00:00"},"resultQuality":{"ob_id":4907,"explanation":"Outputs were reviewed for physical plausibility by the project researchers.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-05-14"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":45907,"uuid":"36a063c6ce094ac3a603982fc47b1129","short_code":"comp","title":"SD-WACCM-D","abstract":"This dataset was generated using version 2.3.1 of the Community Earth System Model (CESM), developed by the NSF National Center for Atmospheric Science (NCAR). The atmospheric component of the atmosphere was the Whole Atmosphere Community Climate Model (WACCM) with Specified Dynamics (SD) and D-Region ionic chemistry."},"procedureCompositeProcess":null,"imageDetails":[236],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":45906,"uuid":"ae711fc1b34b4474af73ed6776324f93","short_code":"proj","title":"MesoS2D: Mesospheric sub-seasonal to decadal predictability","abstract":"This project combined newly-available middle atmosphere observations from the EISCAT 3D ionospheric radar with the Specified Dynamics version of the Whole Atmosphere Community Climate Model (WACCM) with D-region ionic chemistry to quantify the drivers and variability of the mesosphere. \r\n\r\nThis work provided a first step towards improving predictability of the mesosphere at sub-seasonal to decadal timescales. The mesosphere influences, and is influenced by, in-situ and external effects such as atmospheric waves and tides (upward) and space weather effects (downward); and is strongly coupled to the lower edge of the ionosphere and the other atmospheric regions. A sound scientific understanding of the drivers of variability in the mesosphere is therefore needed in order to advance modelling of the whole atmosphere as a coupled system.\r\n\r\nThis project was led by British Antarctic Survey (BAS) scientists under Natural Environment Research Council (NERC) project MesoS2D (grant reference: NE/V018426/1)."}],"inspireTheme":[],"topicCategory":[],"phenomena":[55053,55056,55057,55058,55059,55070,55071,55072,55073,63011,55077,63014,63015,63016,63017,63018,63019,63020,55084,55086,55085,55080,55087,63013,55078,54920,54921,54924,54925,54926,54927,54930,54931,54932,54933,54934,54935,54936,54937,54938,54939,54940,54941,54943,54944,54946,54947,54948,54949,54952,55037,54954,54955,54956,55038,54963,54964,54965,52192,52193,93417,93418,93419,93420,93421,93422,93423,93424,55036,28669,28670,55039],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[219420,219421,219415,219416,219417,219418,219419,219946,219422,219423,219424,219425],"onlineresource_set":[]},{"ob_id":45914,"uuid":"ef40ee0e4d4c4a208cc81b4a24902631","title":"TEAMx: Multi-scale transport and exchange processes in the atmosphere over mountains – programme and experiment: birdbath and vol scans from the NCAS X-Band Mobile Radar unit 2 deployed at Mount Plose, South Tyrol, Italy, v1.0.0 (20250618-20250915)","abstract":"Vertical calibration (birdbath) and volume scan measurements from the NCAS X-Band Mobile Radar unit 2 deployed at Mount Plose, South Tyrol, Italy. These observations were taken as part of TEAMx: Multi-scale transport and exchange processes in the atmosphere over mountains – programme and experiment between 20250618 and 20250915.\r\n\r\nData products from this deployment include: birdbath scans (90 degree elevation scans used for calibration) and volume scans (vol).\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata and also the linked scan document.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used.","creationDate":"2026-05-18T14:22:24.743625","lastUpdatedDate":"2026-05-18T14:22:24","latestDataUpdateTime":"2026-05-18T14:22:24","updateFrequency":"notPlanned","dataLineage":"Data were processed and prepared by the project team before delivery to the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"NCAS, observation measurements","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-08-10T13:57:52","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5019,"bboxName":"Mount Plose, South Tyrol, Italy","eastBoundLongitude":13.7,"westBoundLongitude":9.77,"southBoundLatitude":45.35,"northBoundLatitude":48.05},"verticalExtent":null,"result_field":{"ob_id":45915,"dataPath":"/badc/ncas-mobile/data/ncas-radar-x-band-2/20250603_teamx/v1.0.0","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":6585178430446,"numberOfFiles":45741,"fileFormat":"Data are netCDF formatted."},"timePeriod":{"ob_id":13175,"startTime":"2025-06-18T14:59:48","endTime":"2025-09-15T12:49:25"},"resultQuality":{"ob_id":4568,"explanation":"These data have been produced in accordance to standard NCAS observational practices. This includes instrument calibration and compliance checking of data against the NCAS Data Standards.","passesTest":true,"resultTitle":"NCAS Standard Data Quality Statement","date":"2024-06-07"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":45916,"uuid":"6dd9fe2570da40a4bddf832aced94cd2","short_code":"acq","title":"TEAMx: Multi-scale transport and exchange processes in the atmosphere over mountains – programme and experiment: NCAS X-Band Mobile Radar unit 2 instrument instrument deployed at Mount Plose, South Tyrol, Italy","abstract":"TEAMx: Multi-scale transport and exchange processes in the atmosphere over mountains – programme and experiment: NCAS X-Band Mobile Radar unit 2 instrument instrument deployed at Mount Plose, South Tyrol, Italy."},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[223],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":44846,"uuid":"f47bf45168294b3caa91a8ca16e49938","short_code":"proj","title":"TEAMxUK","abstract":"Multi-scale Transport and Exchange processes in the Atmosphere over Mountains – programme and eXperiment (TEAMx) is an international research programme that aims at improving our understanding of exchange processes in the atmosphere over mountains and at evaluating how well these are represented in NWP and climate models.  TEAMxUK is the UK component of the TEAMx programme, led by NCAS.\r\nTEAMx is a bottom-up initiative by a number of research institutions and operational centres , supported by a coordination office at the University of Innsbruck and based on national, bi-national and multi-national research projects.  It is motivated by recent scientific and technological progresses in observing and modeling small-scale processes in the atmospheric boundary layer.\r\nThe project includes the TEAMx Observational Campaign (TOC) with ground-based in situ, remote sensing and aircraft measurements across various sites in the European Alps, with target areas in the Inn Valley (Austria), the Adige Valley (Italy), the Alpine Crest between these two, and the Alpine Foreland in Germany.  This took place from September 2024 to September 2025 with two Extensive Observation Periods (EOPs), one in winter (20 January – 28 February 2025 ) and one in summer (16 June – 25 July 2025)"}],"inspireTheme":[],"topicCategory":[],"phenomena":[60930,60931,60932,60933,60934,60938,93343,93344,93345,93346,93347,93348,93349,93350,93351,93352,93353,93354,69325,69327,69330,69331,69332,69333,69334,69335,69336,69337,59111,59112,59113,59115,59127,59128,59129,59130,59131,59132,59133,59134,59135,59136,59137,59138,59139,59140,59141,59143,59144,59145,59146,59147,59148,59149,59150,59151,59152,59153,59154,59155,59156,59157,59160,59161,59162,59163,59164,59165,59168,59169,59172,59174,59175,59181,59182,59183,59184,59185,59188,59191,59192,59193,59194,59197,59198,59199,59200,59202,59212,10621,74661,74662,74663,74664,74665,74666,74667,74668,74669,74670,74671,74672,74673,74674,74675,74676,74677,74678,74679,74680,74681,74682,74683,74684,74685,74686,74687,74688,74689,74690,74691,74692,74693,74694,74695,74696,74697,74698,74699,74700,74701,74702,74703,74704,74705,74706,74707,74708,74709,74710,74711,74712,74713,74714,74715,69608],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[{"ob_id":45397,"uuid":"566eb16a01a04767b6156b90cf140b9e","short_code":"coll","title":"TEAMxUK: ground-based, remote-sensing and in-situ airborne observations from the European Alps area","abstract":"Collection of UK ground-based, in situ, remote sensing and aircraft measurements across various sites in the European Alps during the TEAMx (Multi-scale Transport and Exchange processes in the Atmosphere over Mountains – programme and eXperiment) Observational Campaign (TOC) 2004-2005.\r\n\r\nThe data include measurements from target areas in the Inn Valley (Austria), the Adige Valley (Italy), the Alpine Crest between these two, and the Alpine Foreland in Germany. This took place from September 2024 to September 2025 with two Extensive Observation Periods (EOPs), one in winter (20 January – 28 February 2025 ) and one in summer (16 June – 25 July 2025)\r\n\r\nThis collections includes data from :\r\n - In-situ airborne observations by the FAAM BAE-146 aircraft for TEAMxUK.\r\n - remote sensing from NCAS X-band radar\r\n - suite of NCAS surface instrumentation \r\n\r\nTEAMx (TEAMx) was an international research programme that aimed at improving our understanding of exchange processes in the atmosphere over mountains and at evaluating how well these are represented in NWP and climate models."}],"responsiblepartyinfo_set":[219445,219446,219447,219448,219449,219450,219451,219452],"onlineresource_set":[95914]},{"ob_id":45917,"uuid":"a0653e4fcee04492bf7a79bea6a1a638","title":"NCAS Long Term Observations: surface meteorology from the NCAS air pressure sensor unit 1 deployed at the NCAS Chilbolton Atmospheric Observatory (CAO), v1.0","abstract":"Surface meteorology measurements from the NCAS air pressure sensor unit 1 deployed at the NCAS Chilbolton Atmospheric Observatory (CAO). These observations were taken as part of the National Centre for Atmospheric Science (NCAS) long term observations.\n\nData products from this deployment include: surface-met\n\nFor further details of this deployment and the associated dataset please see the internal file metadata.\n\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used.\n        ","creationDate":"2026-05-18T14:27:35.497582","lastUpdatedDate":"2026-05-18T14:27:35.497588","latestDataUpdateTime":"2026-05-18T14:27:35.497591","updateFrequency":"daily","dataLineage":"Data were processed and prepared by the project team before delivery to the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"NCAS, observation measurements","publicationState":"preview","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"ongoing","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":4548,"bboxName":"Chilbolton Hampshire Uk","eastBoundLongitude":-1.437,"westBoundLongitude":-1.437,"southBoundLatitude":51.1445,"northBoundLatitude":51.1445},"verticalExtent":null,"result_field":{"ob_id":45918,"dataPath":"/badc/ncas-cao/data/ncas-pressure-1/20010101_longterm/v1.0","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":379320,"numberOfFiles":2,"fileFormat":"Data are netCDF formatted."},"timePeriod":{"ob_id":13176,"startTime":"2023-06-26T00:00:10","endTime":"2023-06-27T00:00:00"},"resultQuality":{"ob_id":4568,"explanation":"These data have been produced in accordance to standard NCAS observational practices. 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The data is from a variety  of instruments (temperature, humidity, wind, surface temperature, radiation and position), it is stored in NetCDF format using CF conventions.\r\n\r\nThis collection also contains surface turbulence, sea-ice fraction and sea-ice melt pond fraction data derived from the core aircraft measurements.\r\n\r\nThe UK component of the Arctic Summertime-cyclones project field experiment are funded by the Natural Environment Research Council (NERC) NE/T006773/1, NE/T006811/1 and NE/T00682X/1. They will joined by teams from the USA and France, funded by the Office of Naval Research (USA)."}],"responsiblepartyinfo_set":[219537,219538,219539,219540,219541,219542,219543,219544,219545,219546],"onlineresource_set":[]},{"ob_id":45948,"uuid":"16d77f6aa75c46b8b1e60f713a4aca78","title":"Sea ice and melt pond fraction from video analysis for the Arctic Summertime Cyclones Project","abstract":"Data from analysis of six MASIN flights from the Arctic Summertime Cyclones field campaign in Summer 2022. Each data point corresponds to a flux-run of a duration of ~1 minute.  Bulk variables are averaged (mean) along each flux-run, unless otherwise stated in variable description. The sea-ice fraction and melt-pond fraction are from subjectively analysed video footage, where the fraction of sea ice and melt ponds are recorded every minute. Fractions are recorded to the nearest 5% and benchmarked by objective image color analysis of still images. The data set was compiled by Miriam Bennett, with help from Ian Renfrew and Chris Barrell (all University of East Anglia).","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"These data were produced by the project team and the output data were then supplied to CEDA for archiving.","removedDataReason":"","keywords":"MASIN, sea ice, melt pond, NE/T006773/1","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-05-20T09:41:20","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5153,"bboxName":"ASC-masin","eastBoundLongitude":29.0,"westBoundLongitude":-20.57,"southBoundLatitude":75.26,"northBoundLatitude":83.54},"verticalExtent":null,"result_field":{"ob_id":45949,"dataPath":"/badc/arcticcyclones/data/ASC_sea_ice_and_melt_pond_fraction","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":82132,"numberOfFiles":3,"fileFormat":"ASCII text"},"timePeriod":{"ob_id":13191,"startTime":"2022-07-29T11:18:00","endTime":"2022-08-20T13:42:00"},"resultQuality":{"ob_id":3959,"explanation":"No quality information available. Data are as provided by the project team","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2022-06-06"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":45950,"uuid":"c629c1c4e3b04fe985734c350ec0dbf3","short_code":"acq","title":"Arctic Summer-time Cyclones: BAS-MASIN aircraft sea ice and pond melt measurements","abstract":"ASC: BAS-MASIN aircraftsea ice and pond melt measurements"},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[2],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":41265,"uuid":"b84b5f1e0dc14301965f297d277c0135","short_code":"proj","title":"Arctic Summer-time Cyclones: Dynamics and Sea-ice Interaction","abstract":"Arctic cyclones are the dominant type of hazardous weather system affecting the Arctic environment in summer. They can also have critical impacts on sea-ice movement, sometimes resulting in ‘Very Rapid Ice Loss Events’ which present a major challenge to coupled forecasts of the Arctic environment from days out to a season ahead. As a result of global warming, sea ice is becoming thinner across large areas of the Arctic Ocean in summer. This means that winds can move it more easily and in turn the dynamic sea ice distribution is expected to feedback on the developing weather systems.\r\n\r\nThis project will fly two research aircraft into Arctic cyclones developing over the marginal ice zone at the edge of the Arctic Ocean basin. It will measure the turbulent exchange fluxes, flying low above the interface between atmosphere and ice, at the same time as measuring the wind and cloud structure of the cyclones above and the properties of the ice below. Combining the observations with numerical modelling experiments using the latest weather prediction models, the project aims to deduce the dominant physical processes acting and test theoretical mechanisms for two-way interaction between the Arctic cyclones and sea ice.\r\n\r\nThis project and the UK component of the field experiment are funded by the Natural Environment Research Council (NERC) NE/T006773/1, NE/T006811/1 and NE/T00682X/1. They will joined by teams from the USA and France, funded by the Office of Naval Research (USA)."}],"inspireTheme":[],"topicCategory":[],"phenomena":[92544,4385,93410,93411,93412,18405,93413,50340,18408,93414,93415,93416],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[{"ob_id":41339,"uuid":"eb195463b93c47a0aa52a59885908b75","short_code":"coll","title":"Arctic Summer-time Cyclones- Airborne meteorological measurements and derived surface turbulence and sea ice fractions","abstract":"Airborne in-situ observations of core meteorological data collected by the Meteorological Airborne Science INstrumentation (MASIN) instruments on board the British Antarctic Survey instrumented Twin Otter aircraft for the Arctic Summer-time Cyclones: Dynamics and Sea-ice Interaction project. The core data were collected in the Svalbard, Norway and Iceland Sea region between 29th July 2022 and 20th August 2022.  The data is from a variety  of instruments (temperature, humidity, wind, surface temperature, radiation and position), it is stored in NetCDF format using CF conventions.\r\n\r\nThis collection also contains surface turbulence, sea-ice fraction and sea-ice melt pond fraction data derived from the core aircraft measurements.\r\n\r\nThe UK component of the Arctic Summertime-cyclones project field experiment are funded by the Natural Environment Research Council (NERC) NE/T006773/1, NE/T006811/1 and NE/T00682X/1. They will joined by teams from the USA and France, funded by the Office of Naval Research (USA)."}],"responsiblepartyinfo_set":[219551,219552,219553,219554,219555,219556,219557,219560,219559,219550,219558],"onlineresource_set":[]},{"ob_id":45951,"uuid":"ad93d6625d4e4124bb136dbb91b78091","title":"Cyclones, fronts, thunderstorms, and their concurrence: Seven categories of European storm type identified in ECMWF ERA5 over the North Atlantic region","abstract":"A dataset of storm types over Europe developed for the purpose of understanding the importance of these storm types for precipitation in the region.\r\n\r\nThe files are gridded NetCDF format containing one month of data each. They are the storm types identified from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset (ERA5) identified over the North Atlantic/European region.\r\n  \r\nThe storm types are numbered from 1-7 as follows:  \r\n1 - cyclone only  \r\n2 - front only  \r\n3 - thunderstorm only  \r\n4 - cyclone + front  \r\n5 - cyclone + thunderstorm  \r\n6 - front + thunderstorm  \r\n7 - cyclone + front + thunderstorm  \r\n  \r\nThe cyclones and fronts are identified using updated versions of the algorithms described in Catto and Dowdy (2021), specifically the front identification of Sansom and Catto (2023). The thunderstorm data is calculated using a proxy described in Dowdy (2022). See links to publications below.\r\n\r\nThe storm type data are on a 0.25 degree longitude-latitude grid between 20.75 and 69.25 degrees N and 45 degrees W to 45 degrees E, every 6 hours.\r\n\r\nThis dataset was produced under Natural Environment Research Council (NERC) project 'STORMY-WEATHER: Plausible storm hazards in a future climate' (grant reference: NE/V004166/1).","creationDate":"2026-05-19T13:39:21.343898","lastUpdatedDate":"2026-05-19T13:40:09","latestDataUpdateTime":"2026-05-19T13:39:21","updateFrequency":"notPlanned","dataLineage":"The cyclones and fronts are identified using updated versions of the algorithms described in Catto and Dowdy (2021), specifically the front identification of Sansom and Catto (2023). The thunderstorm data is calculated using a proxy described in Dowdy (2022).","removedDataReason":"","keywords":"Storm types,Cyclone,Front,Thunderstorm,Europe","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-09-11T15:30:07","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5155,"bboxName":"","eastBoundLongitude":45.0,"westBoundLongitude":45.0,"southBoundLatitude":20.75,"northBoundLatitude":69.25},"verticalExtent":null,"result_field":{"ob_id":46273,"dataPath":"/badc/deposited2026/European_Storm_Types/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":226169690,"numberOfFiles":470,"fileFormat":"Contact support@ceda.ac.uk for file format information."},"timePeriod":{"ob_id":13194,"startTime":"1980-01-01T00:00:00","endTime":"2018-12-31T00:00:00"},"resultQuality":{"ob_id":4944,"explanation":"The data suppliers have not indicated if any quality control has been undertaken on these data.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-09-11"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":46274,"uuid":"98e771dc9cec45de951a47438b3299b0","short_code":"comp","title":"STORMY-WEATHER storm type methodology","abstract":"The seven STORMY-WEATHER storm types were identified using updated versions of the algorithms described in Catto and Dowdy (2021), specifically the front identification of Sansom and Catto (2023). The thunderstorm data is calculated using a proxy described in Dowdy (2022). See links to publications below."},"procedureCompositeProcess":null,"imageDetails":[236],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":45952,"uuid":"a714d7b7128941c9a989cd7f53936f82","short_code":"proj","title":"STORMY-WEATHER: Plausible storm hazards in a future climate","abstract":"The STORMY-WEATHER project addressed a critical challenge in climate adaptation: improving understanding of how extreme storm hazards may change under a warming climate. While extreme rainfall is becoming more intense and short-duration downpours are increasing, major uncertainties remain regarding how atmospheric circulation, storm tracks, convection, and other physical processes will affect storm intensity, duration, frequency, and persistence. Existing studies have largely focused on changes in peak rainfall intensity over fixed timescales and on likely future outcomes, rather than plausible worst-case scenarios that often drive the greatest risks to infrastructure and communities.\r\n\r\nThe project develops a novel storm-type methodology to identify the physical drivers of change and generate physically plausible high-impact storm hazard storylines. Using the latest climate projections, including advanced convection-permitting climate models that better simulate short-duration extreme rainfall, STORMY-WEATHER examines both precipitation and wind hazards and their response to rising temperatures. The project investigates changes in storm characteristics, rainfall mechanisms, and large-scale circulation patterns, producing practical metrics and tools to support climate risk assessment and adaptation planning for flooding, infrastructure resilience, transport, and energy systems."}],"inspireTheme":[],"topicCategory":[],"phenomena":[103266,53939,53940,75246],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[219563,219564,219565,219566,219567,219568,219571,220478,219572],"onlineresource_set":[95898,95899,95900]},{"ob_id":45955,"uuid":"e8c0d44bcc1f47ff888f3aa5d02b4597","title":"Sea ice fraction estimates from low-level aircraft compiled from ACCACIA, Iceland Greenland Seas Project and Arctic Summertime Cyclones project flights","abstract":"This dataset contains sea-ice fraction estimates, based on albedo from shortwave radiation during low-level aircraft legs, as well as a few other aircraft measurements compiled from several field campaigns: Aerosol Cloud Coupling and Climate Interactions in the Arctic (ACCACIA), Iceland Greenland Seas  (IGP) Project and Arctic Summertime Cyclones (ASC) project flights. The data are derived from the BAE-146 measurements on the FAAM and Meteorological Airborne Science Instrumentation (MASIN) instrumentation measurements onboard the British Antarctic Survey (BAS) Twin Otter aircraft. All field campaigns were funded by NERC under the ACCACIA (NE/I028297/1), IGP (NE/N009754/1) and Arctic Summertime Cyclones (NE/T00682X/1) grants. \r\n\r\nThis compilation is a subset of data taken from ‘surface turbulence data sets’ for each individual campaign (also on CEDA).","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"These data were produced by the project team and the output data were then supplied to CEDA for archiving.","removedDataReason":"","keywords":"ACCACIA, IGP, Arctic Summertime Cyclones, FAAM, MASIN, turbulence","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"ongoing","dataPublishedTime":"2026-05-20T09:46:11","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5156,"bboxName":"IGP, ACCACIA and ASC","eastBoundLongitude":29.0,"westBoundLongitude":-30.0,"southBoundLatitude":60.0,"northBoundLatitude":83.5},"verticalExtent":null,"result_field":{"ob_id":45956,"dataPath":"/badc/accacia/data/ACCACIA_IGP_ASC_sea_ice_fraction_estimates","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":158618,"numberOfFiles":3,"fileFormat":"ASCII text"},"timePeriod":{"ob_id":13195,"startTime":"2013-03-23T00:00:00","endTime":"2022-08-20T13:42:00"},"resultQuality":{"ob_id":3959,"explanation":"No quality information available. Data are as provided by the project team","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2022-06-06"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":45957,"uuid":"3430f8ae8f2645828e0a3adcad8eec95","short_code":"acq","title":"Acquisition for Sea ice fraction estimates from low-level aircraft compiled from ACCACIA, Iceland Greenland Seas Project and Arctic Summertime Cyclones project flights","abstract":"This data set is a compilation of a small number of variables, in particular, sea ice fraction and radiation components, over several field campaigns"},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[2],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":12286,"uuid":"e0e2261d155848fab84b1169aeb2be80","short_code":"proj","title":"Aerosol Cloud Coupling and Climate Interactions in the Arctic (ACCACIA)","abstract":"ACCACIA was a £3M NERC-funded consortium project in collaboration with the Universities of Manchester, York, and East Anglia, and the British Antarctic Survey, along with the Met Office and project partners in the US and Europe. ACCACIA aimed to improve our understanding of aerosol-cloud interactions in the Arctic, and the potential changes and feedbacks that may result from decreasing Arctic sea ice cover in the future. In situ measurements have been made during two field campaigns utilising ship-based measurements of surface aerosol sources and airborne measurements of aerosol and cloud microphysical properties, boundary layer dynamics, and radiative forcing. The observations have been complemented by modelling studies on a range of scales: from explicit aerosol and cloud microphysics process modelling, through large eddy simulation and mesoscale models, up to global climate models."},{"ob_id":24899,"uuid":"2780d047461c42f0a12534ccf42f487a","short_code":"proj","title":"Iceland Greenland seas Project (IGP) including the Atmospheric Forcing of the Iceland Sea (AFIS)","abstract":"The Iceland Greenland seas Project (IGP) is an international project involving the UK, US a Norwegian research communities. The UK component was funded by NERC, under the Atmospheric Forcing of the Iceland Sea (AFIS) project (NE/N009754/1)\r\n\r\nThe Iceland Sea - to the north and east of Iceland - is arguably the least studied of the North Atlantic's subpolar seas. However new discoveries are forcing a redesign of our conceptual model of the North Atlantic's ocean circulation which places the Iceland Sea at the heart of this system and suggests that it requires urgent scientific focus. The recently discovered North Icelandic Jet is thought to be one of two pathways for dense water to pass through the Denmark Strait - the stretch of ocean between Iceland and Greenland - which is the main route for dense waters from the north to enter the Atlantic. Its discovery suggests a new paradigm for where dense water entering the North Atlantic originates. However at present the source of the North Icelandic Jet remains unknown. It is hypothesized that relatively warm Atlantic-origin water is modified into denser water in the Iceland Sea, although it is unclear precisely where, when or how this happens. \r\n\r\nThis project examined the wintertime atmosphere-ocean processes in the Iceland Sea by characterising its atmospheric forcing, i.e. observing the spatial structure and variability of surface heat, moisture and momentum fluxes in the region and the weather systems that dictate these fluxes. In situ observations of air-sea interaction processes from several platforms (an aircraft; and via project partners an unmanned airborne vehicle, a meteorological buoy and a research vessel)  were made and used to evaluate meteorological analyses and reanalyses from operational weather forecasting centres. \r\n\r\nNumerical modelling experiments investigated the dynamics of selected weather systems which strongly influenced the region, but appear not to be well represented; for example, the boundary layers that develop over transitions between sea ice and the open ocean during cold-air outbreaks; or the jets and wakes that occur downstream of Iceland. The unique observations were used to improve model representation of these systems.\r\n\r\nThe project also carried out new high-resolution climate simulations. A series of experiments covered recent past and likely future situations; as well as some idealised situations such as no wintertime sea ice in the Iceland Sea region. This was done using a state-of-the-art atmospheric model with high resolution over the Iceland Sea to investigate changes in the atmospheric circulation and surface fluxes.   \r\n\r\nFinally, in collaboration with the international partners, the project analysed new ocean observations and establish which weather systems are important for changing ocean properties in this region. The project used a range of ocean and atmospheric models to establish how current and future ocean circulation pathways function.  In short, the project determined the role that atmosphere-ocean processes in the Iceland Sea play in creating the dense waters that flow through Denmark Strait and feed into the lower limb of the AMOC.\r\n\r\nThe subpolar region of the North Atlantic is crucial for the global climate system. It is where coupled atmosphere-ocean processes, on a variety of spatial scales, require an integrated approach for their improved understanding and prediction. This region has enhanced 'communication' between the atmosphere and ocean. Here large surface fluxes of heat and moisture make the surface waters colder, saltier and denser resulting in a convective overturning that contributes to the lower limb of the Atlantic Meridional Overturning Circulation (AMOC). The AMOC is an ocean circulation that carries warm water from the tropics northward with a return flow of cold water southwards at depth; it is instrumental in keeping Europe's climate relatively mild."},{"ob_id":41265,"uuid":"b84b5f1e0dc14301965f297d277c0135","short_code":"proj","title":"Arctic Summer-time Cyclones: Dynamics and Sea-ice Interaction","abstract":"Arctic cyclones are the dominant type of hazardous weather system affecting the Arctic environment in summer. They can also have critical impacts on sea-ice movement, sometimes resulting in ‘Very Rapid Ice Loss Events’ which present a major challenge to coupled forecasts of the Arctic environment from days out to a season ahead. As a result of global warming, sea ice is becoming thinner across large areas of the Arctic Ocean in summer. This means that winds can move it more easily and in turn the dynamic sea ice distribution is expected to feedback on the developing weather systems.\r\n\r\nThis project will fly two research aircraft into Arctic cyclones developing over the marginal ice zone at the edge of the Arctic Ocean basin. It will measure the turbulent exchange fluxes, flying low above the interface between atmosphere and ice, at the same time as measuring the wind and cloud structure of the cyclones above and the properties of the ice below. Combining the observations with numerical modelling experiments using the latest weather prediction models, the project aims to deduce the dominant physical processes acting and test theoretical mechanisms for two-way interaction between the Arctic cyclones and sea ice.\r\n\r\nThis project and the UK component of the field experiment are funded by the Natural Environment Research Council (NERC) NE/T006773/1, NE/T006811/1 and NE/T00682X/1. They will joined by teams from the USA and France, funded by the Office of Naval Research (USA)."}],"inspireTheme":[],"topicCategory":[],"phenomena":[92544,20490,4385,93410,93411,50340,93412,93413,18405,93414,18408,93415,93416,93425,93426,93427,93428,93429,93430],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[{"ob_id":41339,"uuid":"eb195463b93c47a0aa52a59885908b75","short_code":"coll","title":"Arctic Summer-time Cyclones- Airborne meteorological measurements and derived surface turbulence and sea ice fractions","abstract":"Airborne in-situ observations of core meteorological data collected by the Meteorological Airborne Science INstrumentation (MASIN) instruments on board the British Antarctic Survey instrumented Twin Otter aircraft for the Arctic Summer-time Cyclones: Dynamics and Sea-ice Interaction project. The core data were collected in the Svalbard, Norway and Iceland Sea region between 29th July 2022 and 20th August 2022.  The data is from a variety  of instruments (temperature, humidity, wind, surface temperature, radiation and position), it is stored in NetCDF format using CF conventions.\r\n\r\nThis collection also contains surface turbulence, sea-ice fraction and sea-ice melt pond fraction data derived from the core aircraft measurements.\r\n\r\nThe UK component of the Arctic Summertime-cyclones project field experiment are funded by the Natural Environment Research Council (NERC) NE/T006773/1, NE/T006811/1 and NE/T00682X/1. They will joined by teams from the USA and France, funded by the Office of Naval Research (USA)."}],"responsiblepartyinfo_set":[219578,219579,219584,219580,219581,219582,219583,219585,219586,219587,219589,219590],"onlineresource_set":[]},{"ob_id":45958,"uuid":"9d86d7af20d9476b95071e7dc2d59ba2","title":"UAV-mounted lidar measurements of peat surface elevation from the Cuvette Centrale peatlands, Congo Basin (February 2019)","abstract":"This dataset contains peat surface elevation measurements acquired between 17–27 February 2019 from Epena and Ekolongouma, two locations in the Cuvette Centrale peatlands region of the central Congo Basin.\r\n\r\nThe data consist of two airborne laser scanning (ALS, or lidar) tracks acquired using a Delair DT26x unmanned aerial vehicle (UAV, or drone) equipped with a Riegl VUX-1UAV scanner, with a ground point density up to 35 per square metre used with a local DGPS (Differential Global Positioning System) ground station. The profiles extend from the peat edge to 2 km and 5 km into the peat region.\r\n\r\nCoordinate system: WGS84, EPSG:4326\r\nFile format: .laz, the industry-standard compressed ALS data format (linked in documentation section)\r\nRelated publication: Davenport, I.J.; McNicol, I.; Mitchard, E.T.A.; Dargie, G.; Suspense, I.; Milongo, B.; Bocko, Y.E.; Hawthorne, D.; Lawson, I.; Baird, A.J.; et al. First Evidence of Peat Domes in the Congo Basin using LiDAR from a Fixed-Wing Drone. Remote Sens. 2020, 12, 2196. https://doi.org/10.3390/rs12142196 (linked in documentation section)\r\n\r\nThis dataset was produced as part of the Natural Environment Research Council (NERC) project CongoPeat: Past, Present and Future of the Peatlands of the Central Congo Basin (grant reference: NE/R016860/1).","creationDate":"2026-05-20T11:59:58.314023","lastUpdatedDate":"2026-05-20T11:59:58","latestDataUpdateTime":"2026-05-20T11:59:58","updateFrequency":"notPlanned","dataLineage":"Acquired using a Delair DT26x unmanned aerial vehicle (UAV, or drone) equipped with a Riegl VUX-1UAV scanner, with a ground point density up to 35 per square metre used with a local DGPS ground station. Delivered by the project team to CEDA for archiving.","removedDataReason":"","keywords":"ALS,LiDAR,UAV,Drone","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-08-13T14:29:45","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5160,"bboxName":"","eastBoundLongitude":17.905,"westBoundLongitude":17.423,"southBoundLatitude":1.188,"northBoundLatitude":1.404},"verticalExtent":null,"result_field":{"ob_id":46148,"dataPath":"/badc/congopeat/data/congo_peat_elevation_lidar","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":2454603091,"numberOfFiles":4,"fileFormat":"LAZ"},"timePeriod":{"ob_id":13198,"startTime":"2019-02-17T00:00:00","endTime":"2019-02-27T00:00:00"},"resultQuality":{"ob_id":4921,"explanation":"Data are archived as supplied by the project team.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-06-24"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":45959,"uuid":"975f5cfb7af048a89f0051819bd22242","short_code":"acq","title":"Acquisition for: UAV ALS data acquired for CongoPeat","abstract":""},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[236],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":46093,"uuid":"740c9234c6cf48bfb825b393568b11fb","short_code":"proj","title":"CongoPeat: Past, Present and Future of the Peatlands of the Central Congo Basin","abstract":"CongoPeat was a five-year research programme led by Professor Simon Lewis of the University of Leeds and funded by Natural Environment Research Council (NERC) grant NE/R016860/1. It investigated the newly discovered peatlands of the central Congo Basin, the largest known tropical peatland complex in the world. Spanning 145,500 km² and storing an estimated 30 billion tonnes of carbon, these peatlands play a globally significant role in climate regulation and biodiversity conservation.\r\n\r\nThe project brought together researchers from six UK universities and five Congolese organisations to improve understanding of the peatlands’ past development, current condition, and future vulnerability to environmental change and human activities. Data outputs from the programme support research on the past, present, and future of the Congo Basin peatlands and provide an evidence base for conservation, sustainable management, and policy-making in the Republic of Congo and the Democratic Republic of the Congo.\r\n\r\nData are archived with the Centre for Environmental Data analysis and the Environmental Information Data Centre."}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[219593,219594,219595,219596,219597,219598,219599,220178,219600],"onlineresource_set":[95720,95606,95607,95730,95944]},{"ob_id":45963,"uuid":"169c4a825c1c4c6e834e24e382deea01","title":"UK Earth System Model 1.1 simulations for the Geoengineering Model Intercomparison Project V0","abstract":"UK Earth System Model 1.1 simulations for the Geoengineering Model Intercomparison Project V0\r\nThe dataset contains commonly-used variables for SSP2-4.5 (2 versions), and G6-1.5K-SAI, G6-1.5K-MCB, and G6-1.5K-HiLLA.\r\nThe G6-1.5K simulations use SSP2-4.5 as the background greenhouse gas emission scenario and maintain global mean temperature at ~1.5K, defined as the mean temperature in 2020-39 via different cooling methods.\r\nG6-1.5K-SAI (Stratospheric Aerosol Injection) emits sulphur dioxide at 30 degrees North and South at 22km.\r\nG6-1.5K-MCB (Marine Cloud Brightening) emits sea salt aerosols at the lowest atmospheric layer in five midlatitude regions.\r\nG6-1.5K-HiLLA (High Latitude Low Altitude) emits sulphur dioxide at 60 degrees North and South at 15km in the spring of each hemisphere.\r\nSAI and HiLLA use the SSP2-4.5 version with heterogeneous chemistry on injected stratospheric aerosols, and MCB uses the SSP2-4.5 version without.","creationDate":"2026-05-21T15:15:59.303873","lastUpdatedDate":"2026-05-21T15:27:53.871767","latestDataUpdateTime":"2026-05-21T15:15:59.303878","updateFrequency":"notPlanned","dataLineage":"This is the CMIP6 generation version of the Geoengineering Model Intercomparison Tier 1 experiments as described in 'The Geoengineering Model Intercomparison Project (GeoMIP) contribution to CMIP7 – description of new experimental protocols and preliminary results' by Visioni et al. (2026) https://doi.org/10.5194/egusphere-2026-2417.\r\nThe simulations were run on the Met Office HPC, CMORised using CDDS, and uploaded to CEDA.","removedDataReason":"","keywords":"CMIP6,UKESM,GeoMIP","publicationState":"preview","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5162,"bboxName":"","eastBoundLongitude":-180.0,"westBoundLongitude":180.0,"southBoundLatitude":-90.0,"northBoundLatitude":90.0},"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":13202,"startTime":"2015-01-01T00:00:00","endTime":"2100-01-01T00:00:00"},"resultQuality":{"ob_id":4911,"explanation":"Model output has only been checked for CF convention compliance, otherwise supplied as-is.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-05-21"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[],"projects":[],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[219645,219646,219647,219648,219649,219650,219652,219653],"onlineresource_set":[95596]},{"ob_id":45964,"uuid":"8c6b162587e34320be276a8503819583","title":"BAQS: SMPS PN data","abstract":"Data collected using a TSI3938. Data submitted is hourly Total Particle concentration and particle size distribution from 10_nm to 800_nm. Data collected at the Birmingham Air Quality Site.","creationDate":"2026-05-22T14:31:01.959861","lastUpdatedDate":"2026-05-22T14:31:01.959864","latestDataUpdateTime":"2026-05-22T14:31:01.959865","updateFrequency":"notPlanned","dataLineage":"1. Data collected at the Birmingham Air Quality Site in minute intervals.","removedDataReason":"","keywords":"","publicationState":"working","nonGeographicFlag":true,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":null,"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":13204,"startTime":"2022-08-01T00:00:00","endTime":null},"resultQuality":{"ob_id":4912,"explanation":"2. Raw data collected outside of the operating parameters of the instrument were removed.\r\n              3. Data (with 75% coverage per hour) was averaged up into 1 hourly steps.\r\n              0b not_used;              1b good;              2b bad;              3b suspect_data;              4b local_unusual_activity; 5b strong_nucleation_event.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-05-22"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":45965,"uuid":"70fe6dbc4c0b4e20a5fd75970efaaa6d","short_code":"acq","title":"Acquisition for: BAQS: SMPS PN data","abstract":""},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[],"projects":[{"ob_id":45718,"uuid":"fc10dbeed0df48d6aff7ab27892e7609","short_code":"proj","title":"Birmingham Air Quality Supersite (BAQS)","abstract":""}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[219658,219659,219660,219661,219662,219663,219664,219665],"onlineresource_set":[]},{"ob_id":45967,"uuid":"0cb6bfc5936041a9a06487359b562454","title":"test for record access","abstract":"test for record access","creationDate":"2026-05-22T14:55:24.879403","lastUpdatedDate":"2026-05-22T14:55:24.879406","latestDataUpdateTime":"2026-05-22T14:55:24.879408","updateFrequency":"notPlanned","dataLineage":"test","removedDataReason":"","keywords":"","publicationState":"working","nonGeographicFlag":true,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":null,"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":13205,"startTime":"2026-05-22T00:00:00","endTime":null},"resultQuality":{"ob_id":4913,"explanation":"test","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-05-22"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[],"projects":[],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[219668,219669,219670,219671,219672,219673,219674],"onlineresource_set":[]},{"ob_id":45968,"uuid":"e020b3328b064b76898bb6e25b7b78d5","title":"TOMCAT (VSLS): Sources and Impacts of Short-Lived Anthropogenic Chlorine","abstract":"The TOMCAT 3D offline chemical transport model is designed to represent the complex interactions between atmospheric chemistry, dynamics, and transport. Simulation is performed using external meteorological reanalysis fields (ERA5) for January 1977 to March 2025. The model simulates the evolution of chemical species by integrating time-varying emissions, solar fluxes, and stratospheric aerosol data. By utilizing predefined scenarios, such as the WMO 2022 projections, the TOMCAT model provides a consistent framework for investigating how short-lived substances and ozone-depleting gases influence stratospheric composition and climate feedback mechanisms over decadal timescales.\r\n\r\nThe data are pre-processed (zonal mean monthly mean on pressure and height levels).","creationDate":"2026-05-26T14:57:36.018190","lastUpdatedDate":"2026-05-26T14:57:36","latestDataUpdateTime":"2026-05-26T14:57:36","updateFrequency":"notPlanned","dataLineage":"The TOMCAT simulation data is from the RUN781 experiment, which was performed on the ARCHER/ARCHER2 supercomputing facilities using the TOMCAT three-dimensional chemical transport model to investigate the impact of short-lived anthropogenic chlorine on the stratosphere. Before being archived at the Centre for Environmental Data Analysis (CEDA), the raw model output underwent a systematic post-processing.  Specific tracer was extracted from the model output file, then it was interpolated from native model vertical grid levels onto a common set of pressure (1000 to 0.1 hPa) and geometric height (1 to 60 km) coordinates, and performing zonal averaging over longitude. Finally, the data was converted into NetCDF format.","removedDataReason":"","keywords":"VSLS,CTM,Stratosphere","publicationState":"preview","nonGeographicFlag":true,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":null,"verticalExtent":null,"result_field":{"ob_id":45997,"dataPath":"/badc/deposited2026/TOMCAT_chlorine/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":694967809,"numberOfFiles":131,"fileFormat":"NetCDF"},"timePeriod":{"ob_id":13207,"startTime":"1977-01-01T00:00:00","endTime":"2026-03-31T00:00:00"},"resultQuality":{"ob_id":4914,"explanation":"NO","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-05-26"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":45969,"uuid":"556cd9784c0c4313b3a214244b07d0a3","short_code":"proj","title":"Sources and Impacts of Short-Lived Anthropogenic Chlorine","abstract":"Depletion of stratospheric ozone allows larger doses of harmful solar UV radiation to reach the surface leading to increases in skin cancer and cataracts in humans and other impacts, such as crop damage. Ozone also affects the Earth's radiation balance and, in particular, ozone depletion in the lower stratosphere (LS) exerts an important climate forcing. While most long-lived ozone-depleting substances (e.g. CFCs) are now controlled by the United Nations Montreal Protocol and their abundances are slowly declining, there remains significant uncertainty surrounding the rate of ozone layer recovery. Changes in the LS may cause delayed ozone recovery or even additional depletion, and can also have important effects on climate. One key uncertainty, highlighted in recent WMO/UNEP Assessments of Stratospheric Ozone Depletion (2014, 2018, 2022, is the increasing importance of uncontrolled chlorine-containing very short-lived substances (VSLS) which can reach the LS and cause ozone depletion.\r\n\r\nThe SISLAC project was a collaboration between the universities of Leeds, Lancaster and East Anglia (UEA). The project built on the UEA's heritage in atmospheric halocarbon measurements to obtain novel observations of chlorine compounds in the key E/SE Asia region and in the global mid-upper troposphere. Surface observations targeted in the key winter periods when polluted emissions from China were detected, a likely major emitter of Cl-VSLS globally.\r\n\r\nThe observations were interpreted using simulations of the TOMCAT 3-D chemical transport model at Leeds and Lancaster. Results of a standard simulation are archived here; further specific experiments are referenced from relevant publications.\r\n\r\nThis project was funded by Natural Environment Research Council (NERC) grant reference: NE/R001782/1."}],"inspireTheme":[],"topicCategory":[],"phenomena":[93440,93441,93442,93443,93444,93445,93446,93447,93448,93449,93450,93451,93452,93453,93454,93455,93456,93457,93458,93459,93460,93461,60438,93462,93463,93464,93465,93466,93467,93468,93469,93470,93471,93472,93473,93474,93475,93476,93477,93478,93479,93480,93481,93482,93483,93484,93485,93486,93487,93488,93489,93490,93491,93492,93493,93494,93495,93496,93497,93498,93499,93500,93501,93502,93503,93504,93505,93506,93507,93508,93509,93510,93511,93512,93513,93514,93515,50559],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[219675,219676,219677,219678,219679,219680,219681,219682,219683],"onlineresource_set":[95602,95599,95600,95601]},{"ob_id":45974,"uuid":"d9e614df708c40ee8ae097cdaf8279a0","title":"ESA Sea Level Budget Closure Climate Change Initiative (SLBC_cci): Time series of global mean sea level budget elements (2004-2022, at monthly resolution) from constrained approach","abstract":"The SLBC_cci+ dataset is provided as a single data collection that contains the Sea Level Budget (SLB) components from the constrained approach. This dataset is a compilation of time series and regional grids of the following elements of the mean sea level budget and ocean mass budget:\r\n\r\n(a) relative sea level;  \r\n(b) the thermosteric component of mean sea level, representing the change in ocean density caused by thermal expansion; \r\n(c) sea level changes due to salinity-driven density variations in the ocean; \r\n(d) the mass contribution to mean sea level.\r\n\r\nUncertainties associated with each component were characterized. These uncertainties are provided as variance-covariance matrices, available at a monthly timescale for both global and regional scales. These matrices enable the estimation of uncertainties in trends and acceleration across any timescales.\r\n\r\nIn the second phase of the project, sea-level budget closure was evaluated using two complementary approaches: (a) an unconstrained approach, in which the sum of the individual contributors is directly compared with the observed relative sea-level change, and (b) a constrained approach based on an inverse method that enforces budget closure while weighting each contributor according to its uncertainty.","creationDate":"2026-05-27T13:45:46.385286","lastUpdatedDate":"2026-05-27T13:29:35","latestDataUpdateTime":"2026-05-27T13:29:35","updateFrequency":"notPlanned","dataLineage":"This dataset is the continuity of the first phase of the SLBC_cci project. It provides the latest scientific estimates of sea level budget components. It includes global estimates for each component from 1993-2023 (the altimetry era) and regional estimates from 2002-2023 (the gravimetry era). Time dependent fields are displayed at monthly resolution for every component. Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"sea level budget closure, sea level, CCI, SLBC","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-09-16T09:47:32","doiPublishedTime":"2026-09-16T09:48:29.314165","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":46122,"dataPath":"/neodc/esacci/sea_level_budget_closure/data/timeseries_slb_element_phase_2/constrained/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":1284232,"numberOfFiles":2,"fileFormat":"NetCDF"},"timePeriod":{"ob_id":13340,"startTime":"2004-01-01T00:00:00","endTime":"2022-12-01T23:59:59"},"resultQuality":{"ob_id":4915,"explanation":"For information on the data quality see the associated documentation.","passesTest":true,"resultTitle":"SLBC Data Quality Statement","date":"2026-05-27"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":32244,"uuid":"b712474c4a8e415b9fa6877652acb93a","short_code":"comp","title":"Compilation of the ESA Climate Change Initiative Sea Level Budget Closure","abstract":"The compilation is a result from the Sea-level Budget Closure (SLBC_cci) project conducted in the framework of ESA’s Climate Change Initiative (CCI). \r\nData and methods underlying the time series are as follows:\r\n(a) satellite altimetry analysis by the Sea Level CCI project.\r\n(b) a new analysis of Argo drifter data with incorporation of sea surface temperature data; an alternative time series consists in an ensemble mean over previous global mean steric sea level anomaly time series.\r\n(c) analysis of monthly global gravity field solutions from the Gravity Recovery and Climate Experiment (GRACE) satellite gravimetry mission.\r\n(d) results from a global glacier model.\r\n(e) analysis of satellite radar altimetry over the Greenland Ice Sheet, amended by results from the global glacier model for the Greenland peripheral glaciers; an alternative time series consists of results from GRACE satellite gravimetry.\r\n(f) analysis of satellite radar altimetry over the Antarctic Ice Sheet; an alternative time series consists of results from GRACE satellite gravimetry.\r\n(g) results from the WaterGAP global hydrological model."},"procedureCompositeProcess":null,"imageDetails":[111],"discoveryKeywords":[],"permissions":[{"ob_id":2584,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":47,"licenceURL":"https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_sealevel_terms_and_conditions.pdf","licenceClassifications":[{"ob_id":3,"classification":"any"}]}}],"projects":[{"ob_id":32240,"uuid":"a549c26e68634b12893dab827b392e66","short_code":"proj","title":"ESA Sea-Level Budget Closure Climate Change Initiative project (SLBC_cci)","abstract":"To assess the accuracy and reliability of our knowledge about sea-level change and its causes, assessments of the sea-level budget (SLB) are indispensable. Closure of the sea-level budget implies that the observed changes of GMSL equal the sum of observed (or otherwise assessed) contributions, namely changes in ocean mass and the steric component. Closure of the ocean mass budget (OMB) implies that the observed ocean-mass change (e.g., from the Gravity Recovery and Climate Experiment, GRACE) is equal to assessed changes of water mass (in solid, liquid or gaseous state) outside the ocean, which are dominated by mass changes of land ice (glaciers and ice sheets) and water stored on the continents as liquid water or snow (land water). Misclosure of these budgets indicates errors in the assessment of some of the components (including effects of undersampling) or contributions from unassessed elements in the budget.\r\n\r\nSince 2010, ESA has developed the Climate Change Initiative (CCI) programme in order to produce consistent and continuous space-based records for Essential Climate Variables (ECVs). The first phase of the SLBC_cci project was conducted from 2017 to 2019 as the first cross-ECV project within CCI. The project aimed at taking advantage of the improved quality of sea-level-related earth observation datasets produced within the CCI programme. The project also developed new data products based on existing CCI products and on other data sources. SLBC_cci concentrated on datasets generated within CCI or by the consortium members as they have thorough insights into the genesis and uncertainty characteristics of the datasets. This facilitated progress towards working in a consistent framework of product specification, uncertainty characterization, and sea level budget analysis, and enabled the identification of unresolved inconsistencies as a prerequisite for future improvements.\r\n\r\nThe first phase of this project covered the precise altimetry era (starting in 1993) with a special focus given to the period 2003/2005 to 2015, coinciding with the availability of GRACE space gravimetry data and Argo drifter data.\r\n\r\nThe new project phase (SBLC_cci+) aims to improve the closure of the global mean sea level budget by: 1) lengthening the time series, 2) assessing budget closure at global and regional scales, 3) providing an explanation of temporal and spatial variability at global and local scales. Depending on the availability of the various elements, the global sea level budget will be updated up to 2022/2023. In addition, the project will address the regional variability of sea level and sea surface temperature, and investigate the contributions of natural/internal climate variability and anthropogenic forcing (detection/attribution) to the associated spatial trends. By extending to regional spatial scales, we can pinpoint areas where the sea level budget does not close, resulting in a regional breakdown of the assessment of the items\r\n that accounts for a significant portion of the individual components used.\r\n\r\nFor further informations : https://climate.esa.int/en/projects/sea-level-budget-closure/"}],"inspireTheme":[],"topicCategory":[],"phenomena":[93955,93956,93957,93958,93959,93960,93961],"vocabularyKeywords":[],"identifier_set":[13970],"observationcollection_set":[],"responsiblepartyinfo_set":[219690,219691,219692,219693,219694,219695,219696,219702,219697,219700,219698,219706,219714,219759,219701,219705,220239,219699,219704,219707,219703,219712,219708,219722,219710,219713,219715,219711,219720,219719,219717,219718,219721],"onlineresource_set":[95604,96004,96006,96007]},{"ob_id":45976,"uuid":"8db04f60f2c2442abcf70affa849791d","title":"ESA Sea Level Budget Closure Climate Change Initiative (SLBC_cci): Time series of mean sea level and water mass budgets at global (1993-2022) and regional scale (2004-2022), at monthly resolution from unconstrained approach","abstract":"This SLBC_cci dataset is provided as a single data collection that contains the sea level budget (SLB) components from the unconstrained approach. This dataset is a compilation of time series and regional grids of the following elements of the mean sea level budget and ocean mass budget:\r\n\r\n(a) relative sea level; \r\n(b) the thermosteric component of mean sea level, representing the change in ocean density caused by thermal expansion; \r\n(c) sea level changes due to salinity-driven density variations in the ocean; \r\n(d) the manometric and barystatic sea level (the mass contribution to sea level); \r\n(e) the glaciers contribution (excluding Greenland and Antarctica); \r\n(f) the Greenland Ice Sheet and Greenland peripheral glaciers contribution; \r\n(g) the Antarctic Ice Sheet contribution; \r\n(h) the contribution from changes in land water storage (including snow cover). \r\n\r\nUncertainties associated with each component were characterized.  These uncertainties are provided as variance-covariance matrices, available at a monthly timescale for both global and regional scales. These matrices enable the estimation of uncertainties in trends and acceleration across any timescales.\r\n\r\nIn the second phase of the project, sea-level budget closure was evaluated using two complementary approaches: (a) an unconstrained approach, in which the sum of the individual contributors is directly compared with the observed relative sea-level change, and (b) a constrained approach based on an inverse method that enforces budget closure while weighting each contributor according to its uncertainty.","creationDate":"2026-05-27T13:45:46.385286","lastUpdatedDate":"2026-05-27T13:29:35","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"This dataset is the continuity of the first phase of the SLBC_cci project. It provides the latest scientific estimates of sea level budget components. It includes global estimates for each component from 1993-2023 (the altimetry era) and regional estimates from 2002-2023 (the gravimetry era). Time dependent fields are displayed at monthly resolution for every component. Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"sea level budget closure, sea level, CCI, SLBC","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-09-16T09:47:14","doiPublishedTime":"2026-09-16T09:48:18.999405","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":46121,"dataPath":"/neodc/esacci/sea_level_budget_closure/data/timeseries_slb_element_phase_2/unconstrained/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":1055211129,"numberOfFiles":2,"fileFormat":"NetCDF"},"timePeriod":{"ob_id":13208,"startTime":"1993-01-15T00:00:00","endTime":"2022-12-15T23:59:59"},"resultQuality":{"ob_id":4915,"explanation":"For information on the data quality see the associated documentation.","passesTest":true,"resultTitle":"SLBC Data Quality Statement","date":"2026-05-27"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":32244,"uuid":"b712474c4a8e415b9fa6877652acb93a","short_code":"comp","title":"Compilation of the ESA Climate Change Initiative Sea Level Budget Closure","abstract":"The compilation is a result from the Sea-level Budget Closure (SLBC_cci) project conducted in the framework of ESA’s Climate Change Initiative (CCI). \r\nData and methods underlying the time series are as follows:\r\n(a) satellite altimetry analysis by the Sea Level CCI project.\r\n(b) a new analysis of Argo drifter data with incorporation of sea surface temperature data; an alternative time series consists in an ensemble mean over previous global mean steric sea level anomaly time series.\r\n(c) analysis of monthly global gravity field solutions from the Gravity Recovery and Climate Experiment (GRACE) satellite gravimetry mission.\r\n(d) results from a global glacier model.\r\n(e) analysis of satellite radar altimetry over the Greenland Ice Sheet, amended by results from the global glacier model for the Greenland peripheral glaciers; an alternative time series consists of results from GRACE satellite gravimetry.\r\n(f) analysis of satellite radar altimetry over the Antarctic Ice Sheet; an alternative time series consists of results from GRACE satellite gravimetry.\r\n(g) results from the WaterGAP global hydrological model."},"procedureCompositeProcess":null,"imageDetails":[111],"discoveryKeywords":[],"permissions":[{"ob_id":2584,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":47,"licenceURL":"https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_sealevel_terms_and_conditions.pdf","licenceClassifications":[{"ob_id":3,"classification":"any"}]}}],"projects":[{"ob_id":32240,"uuid":"a549c26e68634b12893dab827b392e66","short_code":"proj","title":"ESA Sea-Level Budget Closure Climate Change Initiative project (SLBC_cci)","abstract":"To assess the accuracy and reliability of our knowledge about sea-level change and its causes, assessments of the sea-level budget (SLB) are indispensable. Closure of the sea-level budget implies that the observed changes of GMSL equal the sum of observed (or otherwise assessed) contributions, namely changes in ocean mass and the steric component. Closure of the ocean mass budget (OMB) implies that the observed ocean-mass change (e.g., from the Gravity Recovery and Climate Experiment, GRACE) is equal to assessed changes of water mass (in solid, liquid or gaseous state) outside the ocean, which are dominated by mass changes of land ice (glaciers and ice sheets) and water stored on the continents as liquid water or snow (land water). Misclosure of these budgets indicates errors in the assessment of some of the components (including effects of undersampling) or contributions from unassessed elements in the budget.\r\n\r\nSince 2010, ESA has developed the Climate Change Initiative (CCI) programme in order to produce consistent and continuous space-based records for Essential Climate Variables (ECVs). The first phase of the SLBC_cci project was conducted from 2017 to 2019 as the first cross-ECV project within CCI. The project aimed at taking advantage of the improved quality of sea-level-related earth observation datasets produced within the CCI programme. The project also developed new data products based on existing CCI products and on other data sources. SLBC_cci concentrated on datasets generated within CCI or by the consortium members as they have thorough insights into the genesis and uncertainty characteristics of the datasets. This facilitated progress towards working in a consistent framework of product specification, uncertainty characterization, and sea level budget analysis, and enabled the identification of unresolved inconsistencies as a prerequisite for future improvements.\r\n\r\nThe first phase of this project covered the precise altimetry era (starting in 1993) with a special focus given to the period 2003/2005 to 2015, coinciding with the availability of GRACE space gravimetry data and Argo drifter data.\r\n\r\nThe new project phase (SBLC_cci+) aims to improve the closure of the global mean sea level budget by: 1) lengthening the time series, 2) assessing budget closure at global and regional scales, 3) providing an explanation of temporal and spatial variability at global and local scales. Depending on the availability of the various elements, the global sea level budget will be updated up to 2022/2023. In addition, the project will address the regional variability of sea level and sea surface temperature, and investigate the contributions of natural/internal climate variability and anthropogenic forcing (detection/attribution) to the associated spatial trends. By extending to regional spatial scales, we can pinpoint areas where the sea level budget does not close, resulting in a regional breakdown of the assessment of the items\r\n that accounts for a significant portion of the individual components used.\r\n\r\nFor further informations : https://climate.esa.int/en/projects/sea-level-budget-closure/"}],"inspireTheme":[],"topicCategory":[],"phenomena":[93956,93958,93959,93960,93962,93963,93964,93965,93966,93967,93968,93969,93970,93971,93972,93973,93974,93975,93976,93977,93978,93979,93980,93981,93982,93983,93984,93985,93986,93987,93988,93989,93990,93991,93992,93993,93994,60438,52192,52193],"vocabularyKeywords":[],"identifier_set":[13969],"observationcollection_set":[],"responsiblepartyinfo_set":[219725,219726,219727,219728,219729,219730,219731,219737,219732,219735,219733,219741,219749,219758,219736,219740,220240,219734,219739,219742,219738,219747,219743,219757,219745,219748,219750,219746,219755,219754,219752,219753,219756],"onlineresource_set":[96008,95605,96005,96009]},{"ob_id":45978,"uuid":"5d2a217fc9f4405e86ddc98d6693e815","title":"6-hourly data produced by the CESM2 model for the Regional Aerosol Model Intercomparison Project (RAMIP)","abstract":"This record contains 6-hourly data for simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using CESM2. It contains NetCDF output from coupled transient simulations. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe simulations are initialised from the CMIP6 historical experiment. Anthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions in native CESM2 format. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request: https://gmd.copernicus.org/articles/16/4451/2023/\r\n\r\nAcronyms\r\n------------\r\nCESM2: the Community Earth System Model 2 hosted at the National Centre for Atmospheric Research (NCAR) in the US. \r\nSSP1-2.6: experiment based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100.\r\nSSP3-7.0: experiment based on Shared Socioeconomic Pathway SSP3 which is characterised by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nScenarioMIP: the Scenario Model Intercomparison Project simulates climate outcomes based on alternative plausible future scenarios.\r\nCMIP6: is the sixth phase of the Coupled Model Intercomparison Project, a global collaboration of climate modellers.","creationDate":"2025-02-04T13:39:07.370800","lastUpdatedDate":"2025-02-04T13:40:51","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"The simulations are initialised from the CESM2 Large Ensemble (LE) historical experiments.  The baseline SSP370 RAMIP experiment comes directly from the CESM2-LE project. In particular, CESM2 RAMIP uses 10 of the macroperturbation runs (i.e., each ensemble member is initialized from a different year in the preindustrial control simulation) that use an 11-year running mean filter to smooth the CMIP6 biomass burning emissions, including members\r\n\r\nAnthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request:  https://gmd.copernicus.org/articles/16/4451/2023/","removedDataReason":"","keywords":"aerosol, extremes, near-term projections, RAMIP","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-07-23T16:34:46","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":4678,"bboxName":"","eastBoundLongitude":180.0,"westBoundLongitude":-180.0,"southBoundLatitude":-90.0,"northBoundLatitude":90.0},"verticalExtent":null,"result_field":{"ob_id":45979,"dataPath":"/badc/deposited2026/RAMIP_CESM2/RAMIP_RAW_SIX_HOUR_DATA/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":2276767705366,"numberOfFiles":38598,"fileFormat":"NetCDF"},"timePeriod":{"ob_id":12043,"startTime":"2015-01-01T00:00:00","endTime":"2079-12-31T00:00:00"},"resultQuality":{"ob_id":4940,"explanation":"This dataset is uncmorised NetCDF model output. No quality checks were performed by CEDA.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-08-27"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":43461,"uuid":"14416e8347a64c31bb0b2fc744a21331","short_code":"comp","title":"CESM2","abstract":"The CESM2 climate model, released in 2018, includes the following components:\r\naerosol: MAM4 (same grid as atmos), atmos: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb), atmosChem: MAM4 (same grid as atmos), land: CLM5 (same grid as atmos), landIce: CISM2.1, ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m), ocnBgchem: MARBL (same grid as ocean), seaIce: CICE5.1 (same grid as ocean). \r\n\r\nFor CESM2-LE, the model was run by the National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA (NCAR) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 5 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km. For RAMIP, the model was run by the University of California Riverside at NCAR using the cheyenne supercomputer using the same native nominal resolutions."},"procedureCompositeProcess":null,"imageDetails":[230],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":43444,"uuid":"4680fd74cf2244ba8476ed2617e3b41f","short_code":"proj","title":"The Regional Aerosol Model Intercomparison Project (RAMIP)","abstract":"The Regional Aerosol Model Intercomparison Project (RAMIP) will deliver experiments designed to quantify the role of regional aerosol emissions changes in near-term projections. This is unlike any prior MIP, where the focus has been on changes in global emissions and/or very idealised aerosol experiments. Perturbing regional emissions makes RAMIP novel from a scientific standpoint and links the intended analyses more directly to mitigation and adaptation policy issues. From a science perspective, there is limited information on how realistic regional aerosol emissions impact local as well as remote climate conditions. Here, RAMIP will enable an evaluation of the full range of potential influences of realistic and regionally varied aerosol emission changes on near-future climate. From the policy perspective, RAMIP addresses the burning question of how local and remote decisions affecting emissions of aerosols influence climate change in any given region. Here, RAMIP will provide the information needed to make direct links between regional climate policies and regional climate change.\r\n\r\nRAMIP experiments are designed to explore sensitivities to aerosol type and location and provide improved constraints on uncertainties driven by aerosol radiative forcing and the dynamical response to aerosol changes. The core experiments will assess the effects of differences in future global and regional (Africa and the Middle East, East Asia, North America and Europe, and South Asia) aerosol emission trajectories through 2051, while optional experiments will test the nonlinear effects of varying emission locations and aerosol types along this future trajectory. All experiments are based on the shared socioeconomic pathways and are intended to be performed with 6th Climate Model Intercomparison Project (CMIP6) generation models, initialised from the CMIP6 historical experiments, to facilitate comparisons with existing projections. Requested outputs will enable the analysis of the role of aerosol in near-future changes in, for example, temperature and precipitation means and extremes, storms, and air quality."}],"inspireTheme":[],"topicCategory":[],"phenomena":[93598,93599,93600,93601,54933,54934,54935,54936,54937,54938,54939,54940,54941,93591,54943,54944,93592,54946,54947,54948,55077,55078,54949,54952,55080,54954,54955,54956,93604,93605,93606,93607,93608,93609,54963,54964,54965,93613,93610,93611,93612,93597,93602,52192,52193,63011,93593,93603,93594,93595,93596,28669,28670],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[{"ob_id":44020,"uuid":"b7c87e4dafcc486ba1eca2abac752abf","short_code":"coll","title":"CESM2 output prepared for the Regional Aerosol Model Intercomparison Project (RAMIP)","abstract":"This collection contains data for Tier 1 simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using CESM2. It contains NetCDF output from coupled transient simulations with global aerosol reductions, and with regional aerosol reductions over Africa and the Middle East, East Asia, North America and Europe, and South Asia. It also contains NetCDF output for a set of partner experiments with anthropogenic emissions for the year 2050 and fixed, pre-industrial, sea surface temperatures, sea ice extent, and land use. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe data are global, gridded data, from 01/01/2015 to 28/02/2051 for the coupled transient simulations. For the simulations with fixed sea surface temperatures, global, gridded data is provided for 30 years.\r\n\r\nCESM2 is the Community Earth System Model 2 hosted at the National Centre for Atmospheric Research (NCAR) in the US."}],"responsiblepartyinfo_set":[219763,219764,219765,219766,219767,219768,219761,219762],"onlineresource_set":[95609,95611,95610]},{"ob_id":45980,"uuid":"a0daee18c6bb48a3902b5837e3051ad7","title":"test","abstract":"dsdgvfgd ghf dfhdsfh dsfh sdghsdg hdsghsd hdfgh dfgdfgj fgdhfgj fdgh","creationDate":"2026-05-28T14:11:02.399843","lastUpdatedDate":"2026-05-28T14:11:02.399845","latestDataUpdateTime":"2026-05-28T14:11:02.399847","updateFrequency":"notPlanned","dataLineage":"from some place","removedDataReason":"","keywords":"","publicationState":"working","nonGeographicFlag":true,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":null,"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":13211,"startTime":"2026-05-20T00:00:00","endTime":"2026-05-30T00:00:00"},"resultQuality":{"ob_id":4916,"explanation":"bad data","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-05-28"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[],"projects":[],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[219769,219770,219771,219772,219773,219774,219775],"onlineresource_set":[]},{"ob_id":45981,"uuid":"386b3c1ee2054ef5ae0d73060963a9f1","title":"HadUK-Grid Climate Observations by Administrative Regions over the UK, v1.3.2.ceda (1836-2025)","abstract":"HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. Those data at 1 km resolution have been averaged across a set of discrete geographies defining UK administrative regions consistent with data from UKCP18 climate projections. The dataset spans the period from 1836 to 2025 but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.2.ceda HadUK-Grid datasets are as follows:\r\n\r\nChanges to the dataset\r\n*Added data for calendar year 2025\r\n*Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\n\r\nChanges to the input data\r\n*Improved the quality control of the most recent three months of rainfall data (Oct-Dec 2025)\r\n*Improved the quality control of daily rainfall data from 1891-1960\r\n\r\n*Net changes to the input station data:\r\n-Total of 132373597 observations\r\n-131251204 (99.15%) unchanged\r\n-19462 (0.015%) modified for this version\r\n-1102931 (0.83%) added in this version\r\n-43971 (0.03%) deleted from this version\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.","removedDataReason":"","keywords":"Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-06-23T12:21:14","doiPublishedTime":"2026-06-23T13:03:52.647765","removedDataTime":null,"geographicExtent":{"ob_id":2307,"bboxName":"","eastBoundLongitude":1.76,"westBoundLongitude":-8.18,"southBoundLatitude":49.86,"northBoundLatitude":60.86},"verticalExtent":null,"result_field":{"ob_id":45995,"dataPath":"/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.2.ceda/region/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":29446774,"numberOfFiles":224,"fileFormat":"Data are NetCDF formatted"},"timePeriod":{"ob_id":13218,"startTime":"1836-01-01T00:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":3946,"explanation":"Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.","passesTest":true,"resultTitle":"HadUK-Grid v1.1 Data Quality Statement","date":"2022-05-13"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":26870,"uuid":"b1b352825f5548a8bf0639afe335f5ae","short_code":"comp","title":"HadUK-Grid gridded climate observations methodology","abstract":"The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography."},"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":13164,"uuid":"ce252c81a7bd4717834055e31716b265","short_code":"proj","title":"Met Office Hadley Centre - Observations and Climate","abstract":"The Met Office Hadley Centre is one of the UK's foremost climate change research centres.\r\n\r\nThe Hadley Centre produces world-class guidance on the science of climate change and provide a focus in the UK for the scientific issues associated with climate science.\r\n\r\nLargely co-funded by Department of Energy and Climate Change (DECC) and Defra (the Department for Environment, Food and Rural Affairs), the centre provides in-depth information to, and advise, the Government on climate science issues.\r\n\r\nAs one of the world's leading centres for climate science research, the Hadley Centre scientists make significant contributions to peer-reviewed literature and to a variety of climate science reports, including the Assessment Report of the IPCC. The Hadley Centre climate projections were the basis for the Stern Review on the Economics of Climate Change."}],"inspireTheme":[],"topicCategory":[],"phenomena":[51200,54991,64067,6023,54992,54990,50511,62352,62353,62354,62355,62356,61135,62358,93719,93718,93720,93721,54994,50516,50517,54997,51195,51196,51193,52667,52668,51197],"vocabularyKeywords":[],"identifier_set":[13901],"observationcollection_set":[{"ob_id":26862,"uuid":"4dc8450d889a491ebb20e724debe2dfb","short_code":"coll","title":"HadUK-Grid gridded and regional average climate observations for the UK","abstract":"This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.2.ceda, released in June 2026 and containing data up to the end of 2025. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.2.ceda (1836-2025) - Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home). The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised."}],"responsiblepartyinfo_set":[219776,219777,219778,219779,219780,219781,219782,219783,219786,219785,219784,219787,219788,219789,219790],"onlineresource_set":[95613,95612,95614,95615,95616,95617]},{"ob_id":45982,"uuid":"ca4c331d666f4395b1346db9070094ab","title":"HadUK-Grid Climate Observations by UK countries, v1.3.2.ceda (1836-2025)","abstract":"HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. Those data at 1 km resolution have been averaged across a set of discrete geographies defining UK countries consistent with data from UKCP18 climate projections. The dataset spans the period from 1836 to 2025, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.2.ceda HadUK-Grid datasets are as follows:\r\n\r\nChanges to the dataset\r\n*Added data for calendar year 2025\r\n*Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\n\r\nChanges to the input data\r\n*Improved the quality control of the most recent three months of rainfall data (Oct-Dec 2025)\r\n*Improved the quality control of daily rainfall data from 1891-1960\r\n\r\n*Net changes to the input station data:\r\n-Total of 132373597 observations\r\n-131251204 (99.15%) unchanged\r\n-19462 (0.015%) modified for this version\r\n-1102931 (0.83%) added in this version\r\n-43971 (0.03%) deleted from this version\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.","removedDataReason":"","keywords":"Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-06-23T12:20:39","doiPublishedTime":"2026-06-23T13:03:30.567076","removedDataTime":null,"geographicExtent":{"ob_id":2309,"bboxName":"","eastBoundLongitude":1.76,"westBoundLongitude":-8.18,"southBoundLatitude":49.16,"northBoundLatitude":60.86},"verticalExtent":null,"result_field":{"ob_id":45996,"dataPath":"/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.2.ceda/country/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":19368168,"numberOfFiles":224,"fileFormat":"Data are NetCDF formatted"},"timePeriod":{"ob_id":13219,"startTime":"1836-01-01T00:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":3946,"explanation":"Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.","passesTest":true,"resultTitle":"HadUK-Grid v1.1 Data Quality Statement","date":"2022-05-13"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":26870,"uuid":"b1b352825f5548a8bf0639afe335f5ae","short_code":"comp","title":"HadUK-Grid gridded climate observations methodology","abstract":"The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography."},"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":13164,"uuid":"ce252c81a7bd4717834055e31716b265","short_code":"proj","title":"Met Office Hadley Centre - Observations and Climate","abstract":"The Met Office Hadley Centre is one of the UK's foremost climate change research centres.\r\n\r\nThe Hadley Centre produces world-class guidance on the science of climate change and provide a focus in the UK for the scientific issues associated with climate science.\r\n\r\nLargely co-funded by Department of Energy and Climate Change (DECC) and Defra (the Department for Environment, Food and Rural Affairs), the centre provides in-depth information to, and advise, the Government on climate science issues.\r\n\r\nAs one of the world's leading centres for climate science research, the Hadley Centre scientists make significant contributions to peer-reviewed literature and to a variety of climate science reports, including the Assessment Report of the IPCC. The Hadley Centre climate projections were the basis for the Stern Review on the Economics of Climate Change."}],"inspireTheme":[],"topicCategory":[],"phenomena":[51200,54991,64067,6023,54992,54990,50511,62352,62353,62354,62355,62356,61135,93718,93719,93720,93721,54994,50516,50517,54997,60895,51195,51196,51193,52667,52668,51197],"vocabularyKeywords":[],"identifier_set":[13900],"observationcollection_set":[{"ob_id":26862,"uuid":"4dc8450d889a491ebb20e724debe2dfb","short_code":"coll","title":"HadUK-Grid gridded and regional average climate observations for the UK","abstract":"This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.2.ceda, released in June 2026 and containing data up to the end of 2025. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.2.ceda (1836-2025) - Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home). The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised."}],"responsiblepartyinfo_set":[219796,219797,219798,219791,219792,219793,219794,219795,219801,219800,219799,219802,219803,219804,219805],"onlineresource_set":[95618,95619,95620,95621,95622]},{"ob_id":45983,"uuid":"890a2f8a3b2542fbb9618eba906f032a","title":"HadUK-Grid Climate Observations by UK river basins, v1.3.2.ceda (1836-2025)","abstract":"HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. Those data at 1 km resolution have been averaged across a set of discrete geographies defining UK river basins consistent with data from UKCP18 climate projections. The dataset spans the period from 1836 to 2025, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.2.ceda HadUK-Grid datasets are as follows:\r\n \r\nChanges to the dataset\r\n*Added data for calendar year 2025\r\n*Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\n\r\nChanges to the input data\r\n*Improved the quality control of the most recent three months of rainfall data (Oct-Dec 2025)\r\n*Improved the quality control of daily rainfall data from 1891-1960\r\n\r\n*Net changes to the input station data:\r\n-Total of 132373597 observations\r\n-131251204 (99.15%) unchanged\r\n-19462 (0.015%) modified for this version\r\n-1102931 (0.83%) added in this version\r\n-43971 (0.03%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.","removedDataReason":"","keywords":"Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-06-23T12:22:01","doiPublishedTime":"2026-06-23T13:04:22.464826","removedDataTime":null,"geographicExtent":{"ob_id":2308,"bboxName":"","eastBoundLongitude":1.76,"westBoundLongitude":-8.84,"southBoundLatitude":49.86,"northBoundLatitude":60.86},"verticalExtent":null,"result_field":{"ob_id":45994,"dataPath":"/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.2.ceda/river/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":38457367,"numberOfFiles":224,"fileFormat":"Data are NetCDF formatted"},"timePeriod":{"ob_id":13217,"startTime":"1836-01-01T00:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":3946,"explanation":"Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.","passesTest":true,"resultTitle":"HadUK-Grid v1.1 Data Quality Statement","date":"2022-05-13"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":26870,"uuid":"b1b352825f5548a8bf0639afe335f5ae","short_code":"comp","title":"HadUK-Grid gridded climate observations methodology","abstract":"The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography."},"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":13164,"uuid":"ce252c81a7bd4717834055e31716b265","short_code":"proj","title":"Met Office Hadley Centre - Observations and Climate","abstract":"The Met Office Hadley Centre is one of the UK's foremost climate change research centres.\r\n\r\nThe Hadley Centre produces world-class guidance on the science of climate change and provide a focus in the UK for the scientific issues associated with climate science.\r\n\r\nLargely co-funded by Department of Energy and Climate Change (DECC) and Defra (the Department for Environment, Food and Rural Affairs), the centre provides in-depth information to, and advise, the Government on climate science issues.\r\n\r\nAs one of the world's leading centres for climate science research, the Hadley Centre scientists make significant contributions to peer-reviewed literature and to a variety of climate science reports, including the Assessment Report of the IPCC. The Hadley Centre climate projections were the basis for the Stern Review on the Economics of Climate Change."}],"inspireTheme":[],"topicCategory":[],"phenomena":[51200,61135,64067,54991,6023,54992,54990,50511,62352,62353,62354,62355,62356,62357,93718,93719,93720,93721,54994,50516,50517,54997,51195,51196,51193,52667,52668,51197],"vocabularyKeywords":[],"identifier_set":[13902],"observationcollection_set":[{"ob_id":26862,"uuid":"4dc8450d889a491ebb20e724debe2dfb","short_code":"coll","title":"HadUK-Grid gridded and regional average climate observations for the UK","abstract":"This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.2.ceda, released in June 2026 and containing data up to the end of 2025. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.2.ceda (1836-2025) - Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home). The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised."}],"responsiblepartyinfo_set":[219813,219806,219807,219808,219809,219810,219811,219812,219816,219815,219814,219817,219818,219819,219820],"onlineresource_set":[95623,95624,95625,95626,95627]},{"ob_id":45984,"uuid":"d6fe2f491e2f45be95c95fbcbd45c4e3","title":"HadUK-Grid Gridded Climate Observations on a 12km grid over the UK, v1.3.2.ceda (1836-2025)","abstract":"HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The dataset at 12 km resolution is derived from the associated 1 km x 1 km resolution to allow for comparison to data from climate projections. The dataset spans the period from 1836 to 2025, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation). \r\n\r\nThe changes for v1.3.2.ceda HadUK-Grid datasets are as follows:\r\n \r\nChanges to the dataset\r\n*Added data for calendar year 2025\r\n*Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\n\r\nChanges to the input data\r\n*Improved the quality control of the most recent three months of rainfall data (Oct-Dec 2025)\r\n*Improved the quality control of daily rainfall data from 1891-1960\r\n\r\n*Net changes to the input station data:\r\n-Total of 132373597 observations\r\n-131251204 (99.15%) unchanged\r\n-19462 (0.015%) modified for this version\r\n-1102931 (0.83%) added in this version\r\n-43971 (0.03%) deleted from this version\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.","removedDataReason":"","keywords":"Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-06-23T12:26:24","doiPublishedTime":"2026-06-23T13:05:32.669905","removedDataTime":null,"geographicExtent":{"ob_id":2305,"bboxName":"HadUK-Grid area","eastBoundLongitude":4.59,"westBoundLongitude":-12.61,"southBoundLatitude":48.83,"northBoundLatitude":60.57},"verticalExtent":null,"result_field":{"ob_id":45993,"dataPath":"/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.2.ceda/12km/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":4434262970,"numberOfFiles":9907,"fileFormat":"Data are NetCDF formatted"},"timePeriod":{"ob_id":13214,"startTime":"1836-01-01T00:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":3946,"explanation":"Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.","passesTest":true,"resultTitle":"HadUK-Grid v1.1 Data Quality Statement","date":"2022-05-13"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":26870,"uuid":"b1b352825f5548a8bf0639afe335f5ae","short_code":"comp","title":"HadUK-Grid gridded climate observations methodology","abstract":"The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography."},"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":13164,"uuid":"ce252c81a7bd4717834055e31716b265","short_code":"proj","title":"Met Office Hadley Centre - Observations and Climate","abstract":"The Met Office Hadley Centre is one of the UK's foremost climate change research centres.\r\n\r\nThe Hadley Centre produces world-class guidance on the science of climate change and provide a focus in the UK for the scientific issues associated with climate science.\r\n\r\nLargely co-funded by Department of Energy and Climate Change (DECC) and Defra (the Department for Environment, Food and Rural Affairs), the centre provides in-depth information to, and advise, the Government on climate science issues.\r\n\r\nAs one of the world's leading centres for climate science research, the Hadley Centre scientists make significant contributions to peer-reviewed literature and to a variety of climate science reports, including the Assessment Report of the IPCC. The Hadley Centre climate projections were the basis for the Stern Review on the Economics of Climate Change."}],"inspireTheme":[],"topicCategory":[],"phenomena":[51200,6023,93834,93835,93836,93837,93838,93839,62352,93840,62354,62355,62356,93841,62353,93722,93723,93724,93725,93726,93727,93728,93729,93730,93731,93732,93733,93734,93735,93736,93737,52667,52668,64067,54990,54991,54992,54994,50516,54997,50517,11484,11485,11486,51186,51187,51188,51189,51193,51195,51196,51197],"vocabularyKeywords":[],"identifier_set":[13905],"observationcollection_set":[{"ob_id":26862,"uuid":"4dc8450d889a491ebb20e724debe2dfb","short_code":"coll","title":"HadUK-Grid gridded and regional average climate observations for the UK","abstract":"This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.2.ceda, released in June 2026 and containing data up to the end of 2025. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.2.ceda (1836-2025) - Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home). The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised."}],"responsiblepartyinfo_set":[219824,219825,219826,219821,219822,219823,219827,219828,219831,219829,219830,219832,219833,219834,219835],"onlineresource_set":[95632,95628,95629,95630,95631]},{"ob_id":45985,"uuid":"789b3065d74a4c948ab05d33556c86d0","title":"HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.2.ceda (1836-2025)","abstract":"HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions  and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2025, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.2.ceda HadUK-Grid datasets are as follows:\r\n \r\nChanges to the dataset\r\n*Added data for calendar year 2025\r\n*Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\n\r\nChanges to the input data\r\n*Improved the quality control of the most recent three months of rainfall data (Oct-Dec 2025)\r\n*Improved the quality control of daily rainfall data from 1891-1960\r\n\r\n*Net changes to the input station data:\r\n-Total of 132373597 observations\r\n-131251204 (99.15%) unchanged\r\n-19462 (0.015%) modified for this version\r\n-1102931 (0.83%) added in this version\r\n-43971 (0.03%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.","removedDataReason":"","keywords":"Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-06-23T12:28:13","doiPublishedTime":"2026-06-23T13:09:15.954940","removedDataTime":null,"geographicExtent":{"ob_id":2305,"bboxName":"HadUK-Grid area","eastBoundLongitude":4.59,"westBoundLongitude":-12.61,"southBoundLatitude":48.83,"northBoundLatitude":60.57},"verticalExtent":null,"result_field":{"ob_id":45991,"dataPath":"/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.2.ceda/1km/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":497388062923,"numberOfFiles":9907,"fileFormat":"Data are NetCDF formatted"},"timePeriod":{"ob_id":13212,"startTime":"1836-01-01T00:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":3946,"explanation":"Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.","passesTest":true,"resultTitle":"HadUK-Grid v1.1 Data Quality Statement","date":"2022-05-13"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":26870,"uuid":"b1b352825f5548a8bf0639afe335f5ae","short_code":"comp","title":"HadUK-Grid gridded climate observations methodology","abstract":"The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography."},"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":13164,"uuid":"ce252c81a7bd4717834055e31716b265","short_code":"proj","title":"Met Office Hadley Centre - Observations and Climate","abstract":"The Met Office Hadley Centre is one of the UK's foremost climate change research centres.\r\n\r\nThe Hadley Centre produces world-class guidance on the science of climate change and provide a focus in the UK for the scientific issues associated with climate science.\r\n\r\nLargely co-funded by Department of Energy and Climate Change (DECC) and Defra (the Department for Environment, Food and Rural Affairs), the centre provides in-depth information to, and advise, the Government on climate science issues.\r\n\r\nAs one of the world's leading centres for climate science research, the Hadley Centre scientists make significant contributions to peer-reviewed literature and to a variety of climate science reports, including the Assessment Report of the IPCC. The Hadley Centre climate projections were the basis for the Stern Review on the Economics of Climate Change."}],"inspireTheme":[],"topicCategory":[],"phenomena":[51200,6023,93834,93835,93836,93837,93838,93839,62352,93840,62354,62355,62356,93841,62353,93722,93723,93724,93725,93726,93727,93728,93729,93730,93731,93732,93733,93734,93735,93736,93737,52667,52668,64067,54990,54991,54992,54994,50516,54997,50517,11484,11485,11486,51186,51187,51188,51189,51193,51195,51196,51197],"vocabularyKeywords":[],"identifier_set":[13907],"observationcollection_set":[{"ob_id":26862,"uuid":"4dc8450d889a491ebb20e724debe2dfb","short_code":"coll","title":"HadUK-Grid gridded and regional average climate observations for the UK","abstract":"This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.2.ceda, released in June 2026 and containing data up to the end of 2025. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.2.ceda (1836-2025) - Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home). The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised."}],"responsiblepartyinfo_set":[219836,219837,219839,219838,219840,219841,219842,219843,219844,219845,219846,219847,219848,219849,219850],"onlineresource_set":[95633,95634,95635,95636,95637]},{"ob_id":45986,"uuid":"8c4008c25dfe4158bd8961d3c0ada80f","title":"HadUK-Grid Gridded Climate Observations on a 25km grid over the UK, v1.3.2.ceda (1836-2025)","abstract":"HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The dataset at 25 km resolution is derived from the associated 1 km x 1 km resolution to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2025, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.2.ceda HadUK-Grid datasets are as follows:\r\n \r\nChanges to the dataset\r\n*Added data for calendar year 2025\r\n*Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\n\r\nChanges to the input data\r\n*Improved the quality control of the most recent three months of rainfall data (Oct-Dec 2025)\r\n*Improved the quality control of daily rainfall data from 1891-1960\r\n\r\n*Net changes to the input station data:\r\n-Total of 132373597 observations\r\n-131251204 (99.15%) unchanged\r\n-19462 (0.015%) modified for this version\r\n-1102931 (0.83%) added in this version\r\n-43971 (0.03%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.","removedDataReason":"","keywords":"Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-06-23T12:25:37","doiPublishedTime":"2026-06-23T13:05:07.513551","removedDataTime":null,"geographicExtent":{"ob_id":2305,"bboxName":"HadUK-Grid area","eastBoundLongitude":4.59,"westBoundLongitude":-12.61,"southBoundLatitude":48.83,"northBoundLatitude":60.57},"verticalExtent":null,"result_field":{"ob_id":45992,"dataPath":"/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.2.ceda/25km/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":1378569773,"numberOfFiles":9907,"fileFormat":"Data are NetCDF formatted"},"timePeriod":{"ob_id":13215,"startTime":"1836-01-01T00:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":3946,"explanation":"Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.","passesTest":true,"resultTitle":"HadUK-Grid v1.1 Data Quality Statement","date":"2022-05-13"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":26870,"uuid":"b1b352825f5548a8bf0639afe335f5ae","short_code":"comp","title":"HadUK-Grid gridded climate observations methodology","abstract":"The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography."},"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":13164,"uuid":"ce252c81a7bd4717834055e31716b265","short_code":"proj","title":"Met Office Hadley Centre - Observations and Climate","abstract":"The Met Office Hadley Centre is one of the UK's foremost climate change research centres.\r\n\r\nThe Hadley Centre produces world-class guidance on the science of climate change and provide a focus in the UK for the scientific issues associated with climate science.\r\n\r\nLargely co-funded by Department of Energy and Climate Change (DECC) and Defra (the Department for Environment, Food and Rural Affairs), the centre provides in-depth information to, and advise, the Government on climate science issues.\r\n\r\nAs one of the world's leading centres for climate science research, the Hadley Centre scientists make significant contributions to peer-reviewed literature and to a variety of climate science reports, including the Assessment Report of the IPCC. The Hadley Centre climate projections were the basis for the Stern Review on the Economics of Climate Change."}],"inspireTheme":[],"topicCategory":[],"phenomena":[51200,6023,93834,93835,93836,93837,93838,93839,62352,93840,62354,62355,62356,93841,62353,93722,93723,93724,93725,93726,93727,93728,93729,93730,93731,93732,93733,93734,93735,93736,93737,52667,52668,64067,54990,54991,54992,54994,50516,54997,50517,11484,11485,11486,51186,51187,51188,51189,51193,51195,51196,51197],"vocabularyKeywords":[],"identifier_set":[13904],"observationcollection_set":[{"ob_id":26862,"uuid":"4dc8450d889a491ebb20e724debe2dfb","short_code":"coll","title":"HadUK-Grid gridded and regional average climate observations for the UK","abstract":"This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.2.ceda, released in June 2026 and containing data up to the end of 2025. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.2.ceda (1836-2025) - Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home). The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised."}],"responsiblepartyinfo_set":[219851,219852,219853,219854,219855,219856,219857,219858,219859,219860,219861,219862,219863,219864,219865],"onlineresource_set":[95638,95639,95642,95640,95641]},{"ob_id":45987,"uuid":"a7947ae607fd4be8994b940eebca8872","title":"HadUK-Grid Gridded Climate Observations on a 5km grid over the UK, v1.3.2.ceda (1836-2025)","abstract":"HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The dataset at 5 km resolution is derived from the associated 1 km x 1 km resolution to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2025, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.2.ceda HadUK-Grid datasets are as follows:\r\n \r\nChanges to the dataset\r\n*Added data for calendar year 2025\r\n*Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\n\r\nChanges to the input data\r\n*Improved the quality control of the most recent three months of rainfall data (Oct-Dec 2025)\r\n*Improved the quality control of daily rainfall data from 1891-1960\r\n\r\n*Net changes to the input station data:\r\n-Total of 132373597 observations\r\n-131251204 (99.15%) unchanged\r\n-19462 (0.015%) modified for this version\r\n-1102931 (0.83%) added in this version\r\n-43971 (0.03%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.","removedDataReason":"","keywords":"Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-06-23T12:27:27","doiPublishedTime":"2026-06-23T13:06:08.449401","removedDataTime":null,"geographicExtent":{"ob_id":2305,"bboxName":"HadUK-Grid area","eastBoundLongitude":4.59,"westBoundLongitude":-12.61,"southBoundLatitude":48.83,"northBoundLatitude":60.57},"verticalExtent":null,"result_field":{"ob_id":45989,"dataPath":"/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.2.ceda/5km/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":22787009086,"numberOfFiles":9907,"fileFormat":"Data are NetCDF formatted"},"timePeriod":{"ob_id":13213,"startTime":"1836-01-01T00:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":3946,"explanation":"Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.","passesTest":true,"resultTitle":"HadUK-Grid v1.1 Data Quality Statement","date":"2022-05-13"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":26870,"uuid":"b1b352825f5548a8bf0639afe335f5ae","short_code":"comp","title":"HadUK-Grid gridded climate observations methodology","abstract":"The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography."},"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":13164,"uuid":"ce252c81a7bd4717834055e31716b265","short_code":"proj","title":"Met Office Hadley Centre - Observations and Climate","abstract":"The Met Office Hadley Centre is one of the UK's foremost climate change research centres.\r\n\r\nThe Hadley Centre produces world-class guidance on the science of climate change and provide a focus in the UK for the scientific issues associated with climate science.\r\n\r\nLargely co-funded by Department of Energy and Climate Change (DECC) and Defra (the Department for Environment, Food and Rural Affairs), the centre provides in-depth information to, and advise, the Government on climate science issues.\r\n\r\nAs one of the world's leading centres for climate science research, the Hadley Centre scientists make significant contributions to peer-reviewed literature and to a variety of climate science reports, including the Assessment Report of the IPCC. The Hadley Centre climate projections were the basis for the Stern Review on the Economics of Climate Change."}],"inspireTheme":[],"topicCategory":[],"phenomena":[51200,6023,93834,93835,93836,93837,93838,93839,62352,93840,62354,62355,62356,93841,62353,93722,93723,93724,93725,93726,93727,93728,93729,93730,93731,93732,93733,93734,93735,93736,93737,52667,52668,64067,54990,54991,54992,54994,50516,54997,50517,11484,11485,11486,51186,51187,51188,51189,51193,51195,51196,51197],"vocabularyKeywords":[],"identifier_set":[13906],"observationcollection_set":[{"ob_id":26862,"uuid":"4dc8450d889a491ebb20e724debe2dfb","short_code":"coll","title":"HadUK-Grid gridded and regional average climate observations for the UK","abstract":"This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.2.ceda, released in June 2026 and containing data up to the end of 2025. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.2.ceda (1836-2025) - Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home). The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised."}],"responsiblepartyinfo_set":[219866,219867,219868,219869,219870,219871,219872,219873,219874,219875,219876,219877,219878,219879,219880],"onlineresource_set":[95643,95644,95645,95646,95647]},{"ob_id":45988,"uuid":"a613225bcdcb4fe495d9f630f8e86622","title":"HadUK-Grid Gridded Climate Observations on a 60km grid over the UK, v1.3.2.ceda (1836-2025)","abstract":"HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The dataset at 60 km resolution is derived from the associated 1 km x 1 km resolution to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2025, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.2.ceda HadUK-Grid datasets are as follows:\r\n \r\nChanges to the dataset\r\n*Added data for calendar year 2025\r\n*Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\n\r\nChanges to the input data\r\n*Improved the quality control of the most recent three months of rainfall data (Oct-Dec 2025)\r\n*Improved the quality control of daily rainfall data from 1891-1960\r\n\r\n*Net changes to the input station data:\r\n-Total of 132373597 observations\r\n-131251204 (99.15%) unchanged\r\n-19462 (0.015%) modified for this version\r\n-1102931 (0.83%) added in this version\r\n-43971 (0.03%) deleted from this version\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data provided by the UK Met Office for archiving in the Centre for Environmental Data Analysis (CEDA) archives.","removedDataReason":"","keywords":"Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-06-23T12:25:04","doiPublishedTime":"2026-06-23T13:04:52.147871","removedDataTime":null,"geographicExtent":{"ob_id":2305,"bboxName":"HadUK-Grid area","eastBoundLongitude":4.59,"westBoundLongitude":-12.61,"southBoundLatitude":48.83,"northBoundLatitude":60.57},"verticalExtent":null,"result_field":{"ob_id":45990,"dataPath":"/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.3.2.ceda/60km/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":516595077,"numberOfFiles":9907,"fileFormat":"Data are NetCDF formatted"},"timePeriod":{"ob_id":13216,"startTime":"1836-01-01T00:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":3946,"explanation":"Data quality control details for the HadUK-Grid version 1.0 datasets is available in section 2.2. of Hollis et al. (2019). See linked documentation for further details.","passesTest":true,"resultTitle":"HadUK-Grid v1.1 Data Quality Statement","date":"2022-05-13"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":26870,"uuid":"b1b352825f5548a8bf0639afe335f5ae","short_code":"comp","title":"HadUK-Grid gridded climate observations methodology","abstract":"The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography."},"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":13164,"uuid":"ce252c81a7bd4717834055e31716b265","short_code":"proj","title":"Met Office Hadley Centre - Observations and Climate","abstract":"The Met Office Hadley Centre is one of the UK's foremost climate change research centres.\r\n\r\nThe Hadley Centre produces world-class guidance on the science of climate change and provide a focus in the UK for the scientific issues associated with climate science.\r\n\r\nLargely co-funded by Department of Energy and Climate Change (DECC) and Defra (the Department for Environment, Food and Rural Affairs), the centre provides in-depth information to, and advise, the Government on climate science issues.\r\n\r\nAs one of the world's leading centres for climate science research, the Hadley Centre scientists make significant contributions to peer-reviewed literature and to a variety of climate science reports, including the Assessment Report of the IPCC. The Hadley Centre climate projections were the basis for the Stern Review on the Economics of Climate Change."}],"inspireTheme":[],"topicCategory":[],"phenomena":[51200,6023,93834,93835,93836,93837,93838,93839,62352,93840,62354,62355,62356,93841,62353,93722,93723,93724,93725,93726,93727,93728,93729,93730,93731,93732,93733,93734,93735,93736,93737,52667,52668,64067,54990,54991,54992,54994,50516,54997,50517,11484,11485,11486,51186,51187,51188,51189,51193,51195,51196,51197],"vocabularyKeywords":[],"identifier_set":[13903],"observationcollection_set":[{"ob_id":26862,"uuid":"4dc8450d889a491ebb20e724debe2dfb","short_code":"coll","title":"HadUK-Grid gridded and regional average climate observations for the UK","abstract":"This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.2.ceda, released in June 2026 and containing data up to the end of 2025. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.2.ceda (1836-2025) - Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home). The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised."}],"responsiblepartyinfo_set":[219881,219882,219883,219884,219885,219886,219887,219888,219889,219890,219891,219892,219893,219894],"onlineresource_set":[95648,95649,95650,95651,95652]},{"ob_id":46000,"uuid":"92114842e8204b76a764c65f4b78f160","title":"Atmospheric trace gas observations from the UK Deriving Emissions linked to Climate Change (DECC) Network and associated data - Version 26.01","abstract":"This version 26.01 dataset collection consists of atmospheric trace gas observations made as part of the UK Deriving Emissions linked to Climate Change (DECC) Network. It includes core DECC Network measurements, funded by the UK Government Department for Energy Security and Net Zero (TRN1028/06/2015,  TRN1537/06/2018, TRN5488/11/2021 and prj_1604) and through the National Measurement System at the National Physical Laboratory, supplemented by observations  funded through other associated projects. The core DECC network consists of five sites in the UK and Ireland measuring greenhouse and ozone-depleting gases.\r\n\r\nThe four UK-based sites (Ridge Hill, Herefordshire; Tacolneston, Norfolk; Bilsdale, North Yorkshire; and Heathfield, East Sussex) sample air from elevated inlets on tall telecommunications towers. Mace Head, situated on the west coast of Ireland, samples from an inlet within 10 metres of ground level and is ideally situated to intercept baseline air from the North Atlantic Ocean. Data from the decommissioned DECC network site at Angus Tall Tower are also included in this dataset collection, as are data from the affiliated (non-core) sites at Invergowrie (Perth and Kinross), Jodrell Bank (Cheshire), Lerwick (Shetland), and Valentia Island (County Kerry, Ireland). The measurement site at Weybourne, Norfolk, funded by the National Centre for Atmospheric Science (NCAS) and operated by the University of East Anglia, is also affiliated with the network. Weybourne data are archived separately - see links in documentation. Data from the UK DECC network are used to assess atmospheric trends and quantify UK emissions, and feed into other international research programs, including the Integrated Carbon Observation System (ICOS) and Advanced Global Atmospheric Gases Experiment (AGAGE) networks.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2024-08-16T13:43:03","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data were collected using in situ trace gas analysers. Data quality assurance and quality control is carried out regularly by each station PI,  and overall DECC Network data reviews are conducted every 2 months. Data are traceable to international calibration scales.  Data were collected by the DECC network team and deposited at the Centre for Environmental Data Analysis (CEDA) for archiving.","removedDataReason":"","keywords":"UK-DECC, trace gases","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-07-03T13:38:39","doiPublishedTime":"2026-07-06T08:30:23.575561","removedDataTime":null,"geographicExtent":{"ob_id":5166,"bboxName":"UK DECC Network v26.01","eastBoundLongitude":1.1387,"westBoundLongitude":-10.4032,"southBoundLatitude":50.97675,"northBoundLatitude":60.1391},"verticalExtent":null,"result_field":{"ob_id":46014,"dataPath":"/badc/uk-decc-network/data/v26.01","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":5062940227,"numberOfFiles":347,"fileFormat":"NetCDF"},"timePeriod":{"ob_id":13227,"startTime":"1987-01-23T00:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":4465,"explanation":"Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data An alysis (CEDA)","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2023-12-01"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":46001,"uuid":"8f0cd991e51c46329e4504933f83da2f","short_code":"acq","title":"UK-DECC trace species measurements at UK-DECC network sites V26.01","abstract":"UK-DECC trace species measurements including radon at UK-DECC network sites - for V26.01"},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":27561,"uuid":"081a5ec3884441398aa2daae53a6189b","short_code":"proj","title":"UK DECC (Deriving Emissions linked to Climate Change) Network","abstract":"The core UK Deriving Emissions linked to Climate Change (DECC) Network consists of five sites in the UK and Ireland measuring greenhouse and ozone-depleting gases. The four UK-based sites (Ridge Hill, Herefordshire; Tacolneston, Norfolk; Bilsdale, North Yorkshire; and Heathfield, East Sussex) sample air from elevated inlets on tall telecommunications towers. Mace Head, situated on the west coast of Ireland, samples from an inlet within 10 metres of ground level and is ideally situated to intercept baseline air from the North Atlantic Ocean. High frequency measurements of all major greenhouse gases are made at the four UK stations, including carbon dioxide, methane, nitrous oxide and sulfur hexafluoride. \r\n\r\nData from the UK DECC network are used to assess atmospheric trends and quantify UK emissions, and feed into other international research programs, including the Integrated Carbon Observation System (ICOS) and Advanced Global Atmospheric Gases Experiment (AGAGE) networks. This work is funded by the UK Government Department for Energy Security and Net Zero (DESNZ)  under contracts TRN1028/06/2015, TRN1537/06/2018, TRN5488/11/2021 and and prj_1604 to the University of Bristol and through the National Measurement System at the National Physical Laboratory."},{"ob_id":43619,"uuid":"56746739572d409f8f828c5b96eb210d","short_code":"proj","title":"Radon measurements colocated with the UK greenhouse gas observation network","abstract":"Radon (222Rn) has been measured at a number of monitoring stations across the UK greenhouse gas observation network. Radon is measured alongside greenhouse gases at the same or similar inlet heights. These measurements help us to better understand and evaluate transport model uncertainties associated with the estimation of regional greenhouse gas emissions."},{"ob_id":46039,"uuid":"347d31fa3f9840aba86440c03c68e0b1","short_code":"proj","title":"Nitrous oxide measurements at Valentia Island, Co Kerry, Ireland","abstract":"Nitrous oxide measurements were made at Valentia Island, County Kerry, Ireland in work funded by Met Éireann."}],"inspireTheme":[],"topicCategory":[],"phenomena":[74752,74753,74754,74755,93696,93697,93698,93699,93700,93701,93702,93703,93704,93705,93706,93707,93708,93709,93710,93711,93712,93713,93714,74727,74732,93662,74735,93664,74736,74737,93666,74739,93668,74740,93669,74741,93670,93671,74744,93673,93674,74747,74748,93677,74749,93678,74750,74751,93680,93681,93687,93688,93689,93690,93691,93692,93693,93694,93695,12182,93614,93615,93616,93617,93618,93619,93620,93621,93622,93623,93624,93625,93626,93627,93628,93629,93630,93631,93632,93633,93634,93635,93636,93637,93638,93639,93640,93641,93642,93643,93644,93645,93646,93647,93648,93649,93650,93651,93652,93653,93654,93655,93656,93657,93658,93659,93660,93661,74716,93663,74717,93665,74718,93667,74719,74720,74721,74722,74723,74724,74725,74726,74728,74729,74730,74734,74731,93672,74738,74733,93675,93676,74742,74743,93679,74745,74746,93682,93683,93684,93685,93686],"vocabularyKeywords":[],"identifier_set":[13928],"observationcollection_set":[{"ob_id":27499,"uuid":"f5b38d1654d84b03ba79060746541e4f","short_code":"coll","title":"UK DECC (Deriving Emissions linked to Climate Change) Network","abstract":"This dataset collection consists of atmospheric trace gas observations made as part of the UK Deriving Emissions linked to Climate Change (DECC) Network. It includes core DECC Network measurements, funded by the UK Government Department for Energy Security and Net Zero (TRN1028/06/2015, TRN1537/06/2018, TRN5488/11/2021 and prj_1604) and through the National Measurement System at the National Physical Laboratory, supplemented by observations funded through other associated projects. \r\n\r\nThe core DECC network consists of five sites in the UK and Ireland measuring greenhouse and ozone-depleting gases. The four UK-based sites (Ridge Hill, Herefordshire; Tacolneston, Norfolk; Bilsdale, North Yorkshire; and Heathfield, East Sussex) sample air from elevated inlets on tall telecommunications towers. Mace Head, situated on the west coast of Ireland, samples from an inlet within 10 metres of ground level and is ideally situated to intercept baseline air from the North Atlantic Ocean. \r\n\r\nData from the decommissioned DECC network site at Angus Tall Tower are also included in this dataset collection, as are data from the affiliated (non-core) sites at Invergowrie (Perth and Kinross), Jodrell Bank (Cheshire), Lerwick (Shetland), and Valentia Island (County Kerry, Ireland). The measurement site at Weybourne, Norfolk, funded by the National Centre for Atmospheric Science (NCAS) and operated by the University of East Anglia, is also affiliated with the network. Weybourne data are archived separately - see links in documentation. \r\n\r\nData from the UK DECC network are used to assess atmospheric trends and quantify UK emissions, and feed into other international research programs, including the Integrated Carbon Observation System (ICOS) and Advanced Global Atmospheric Gases Experiment (AGAGE) networks."}],"responsiblepartyinfo_set":[219900,219901,219902,219903,219904,219905,219906,219907,219926,219908,219909,219927,219910,219911,219928,219912,219913,219914,219915,219916,219917,219918,219919,219920,219921,219929,219922,219923,219924,219925],"onlineresource_set":[95654]},{"ob_id":46016,"uuid":"f497e0a0f70449f0a4b1e9654011ab14","title":"ESA Land Surface Temperature Climate Change Initiative (LST_cci): Geostationary Operational Environmental Satellite (GOES12-13) level 3 (L3U) product (2004-2017), version 2.00","abstract":"This dataset contains land surface temperatures (LST) and their uncertainty estimates from the IMAGER onboard the Geostationary Operational Environmental Satellite (GOES-12 and GOES-13). 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Level 1 satellite observations were provided by the Satellite Applications Facility on Land Surface Analysis (LSA-SAF).\r\nContact: data.lst-cci@acri-st.fr","removedDataReason":"","keywords":"land surface temperature, CCI, HMWR","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"ongoing","dataPublishedTime":"2026-07-01T10:28:02","doiPublishedTime":"2026-07-01T13:36:55","removedDataTime":null,"geographicExtent":{"ob_id":3468,"bboxName":"LST CCI - MTSAT","eastBoundLongitude":-145.0,"westBoundLongitude":75.0,"southBoundLatitude":-70.0,"northBoundLatitude":70.0},"verticalExtent":null,"result_field":{"ob_id":46051,"dataPath":"/neodc/esacci/land_surface_temperature/data/HMWR_AHI/L3C/v2.00/monthly","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":31540062235,"numberOfFiles":2041,"fileFormat":"NetCDF"},"timePeriod":{"ob_id":13231,"startTime":"2015-12-01T00:00:00","endTime":"2023-12-31T23:59:59"},"resultQuality":{"ob_id":3951,"explanation":"For information on the data quality see the associated LST_cci documentation.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2022-05-17"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":{"ob_id":46030,"uuid":"5ed238e2c42f4669bc34e662894e6676","short_code":"cmppr","title":"Composite process for ESA Land Surface Temperature Climate Change Initiative (LST_cci): Himawari (HMWR8-9) level 3 (L3U) product (2015-2024), version 2.00","abstract":"Data has been derived from the Advanced Himawari Imager (AHI) onboard Himiwari-8 and 9.\r\n\r\nFor information on the retrieval algorithm used see the documentation on the LST CCI webpage."},"imageDetails":[111],"discoveryKeywords":[],"permissions":[{"ob_id":2690,"accessConstraints":null,"accessCategory":"noaccess","accessRoles":null,"label":"noaccess: None group","licence":{"ob_id":30,"licenceURL":"https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_lst_terms_and_conditions.pdf","licenceClassifications":[{"ob_id":3,"classification":"any"}]}}],"projects":[{"ob_id":33361,"uuid":"555149fdc3ef4e23a1de8ece93c29f5d","short_code":"proj","title":"ESA Land Surface Temperature Climate Change Initiative (LST_cci)","abstract":"The land surface temperature (LST) CCI project, which is funded by the European Space Agency (ESA) as part of the Agency’s Climate Change Initiative (CCI) Programme, aims to deliver a significant improvement on the capability of current satellite LST data records to meet the challenging Global Climate Observing System (GCOS) requirements for climate applications to realise the full potential of long-term LST data for climate science.\r\n\r\nAccurate knowledge of LST plays a key role in describing the physics of land-surface processes at regional and global scales as they combine information on both the surface-atmosphere interactions and energy fluxes within the Earth Climate System. 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The cabin is set in approximately 2 acres of grassland with established trees to the North and East, ca 10 km south of Edinburgh (55.862281,-3.205782). The cabin was installed in the 1980s for the then Institute of Terrestrial Ecology (now UK Centre for Ecology and Hydrology), with a basic measurements of total global solar radiation, rainfall, air temperature, wind direction and wind speed at ca 4 m. Initially these were not electronically recorded but in 1988 a Campbell Scientfic data logger was added to allow the automatic reading and recording of the data. Various other sensors were added over the years with the logging system being upgraded as the technology developed. In the early 2000's a taller mast was installed with the sensors at ca 8 m to reduce the influence of the mature trees surrounding the field. The site is been part of national monitoring networks, https://uk-air.defra.gov.uk/interactive-map","creationDate":"2022-11-01T14:54:43.813607","lastUpdatedDate":"2022-11-01T14:43:40","latestDataUpdateTime":null,"updateFrequency":"","dataLineage":"Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"Bush Cabin, CEH","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"ongoing","dataPublishedTime":"2026-08-10T14:10:37","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5170,"bboxName":"Bush Cabin - UKCEH","eastBoundLongitude":-3.205782,"westBoundLongitude":-3.205782,"southBoundLatitude":55.862281,"northBoundLatitude":55.862281},"verticalExtent":null,"result_field":{"ob_id":46041,"dataPath":"/badc/auchencorth/data/BushCabin_1988_2024_met/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":87464094,"numberOfFiles":40,"fileFormat":"BADC-CSV"},"timePeriod":{"ob_id":13233,"startTime":"1998-01-01T00:00:00","endTime":null},"resultQuality":{"ob_id":4105,"explanation":"Data are as supplied by the project team.  No quality assurance has been performed by CEDA","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2022-11-01"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":46042,"uuid":"f63a2db39229431aad3cc9ffcd496185","short_code":"acq","title":"Acquisition for Bush Cabin field site Meteorological measurements","abstract":"Acquisition for Bush Cabin  field site Meteorological measurements"},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[132],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":25088,"uuid":"3b93f94481a841f68bc1ce1e975e3ead","short_code":"proj","title":"Auchencorth Moss Atmospheric Observatory (AU) and associated Field sites","abstract":"Auchencorth Moss Atmospheric Observatory (AU) was established as EMEP (European Monitoring and Evaluation Program, Level 2/3) supersite for the UK in 2006. Long-term monitoring is led by NERC CEH (Centre for Ecology and Hydrology) with contributions from other organisations and research institutes including Ricardo AEA, BureauVeritas, NPL, the University of Birmingham and University of Edinburgh. In April 2014, the site was awarded WMO GAW regional station (World Meteorological Orgamisation Global Atmospheric Watch). In 2017 the site joined the ICOS network (Integrated Carbon Observation System).\r\n\r\nMeteorological measurements at AU were initially made to assist with interpretation of the fluxes, and as such weren't installed with the intention of providing WMO standard measurements. Since 2014, AU has been moving towards these standards as well as enhancing instrumentation.\r\n\r\nSimilar measurements are also made at nearby Easter Bush Field site by the same team."}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[{"ob_id":25087,"uuid":"55c74c02ec8e4afea309043d110a93e7","short_code":"coll","title":"Auchencorth Moss Atmospheric Observatory (AU) and associated field sites: Meteorological observations","abstract":"The Auchencorth Moss Atmospheric Observatory was setup in 1995 to measure meteorology, trace gases, aerosols and their fluxes. It is (55ᵒ47’36” N, 3°14’41” W) an ombrotrophic peatland with an extensive fetch at an elevation of 270 m, lying 18 km SSW of Edinburgh, UK, and can be categorised as a transitional lowland raised bog. The site is grazed with < 1 sheep ha^-1.\r\n\r\nDuring 2000s the site activity has increased and was established in 2006 as EMEP (European Monitoring and Evaluation Program, Level 2/3) supersite for the UK. Long term monitoring is led by NERC CEH with contributions from other organisations/research institutes including Ricardo AEA, BureauVeritas, NPL, the University of Birmingham and University of Edinburgh. In April 2014 the site was awarded WMO GAW regional station (World Meteorological Orgamisation Global Atmospheric Watch). In 2017 the site joined the ICOS network (Integrated Carbon Observation System).\r\nSimilar measurements are also made at nearby Easter Bush Field site by the same team.\r\n\r\nThe meteorological measurements were initially made to assist with interpretation of the fluxes and as such weren't installed with the intention of providing WMO standard measurements."}],"responsiblepartyinfo_set":[220074,220075,220076,220077,220078,220079,220080,220081,220082,220083,220084,220085,220086,220087,220088],"onlineresource_set":[]},{"ob_id":46047,"uuid":"30ad58b60d8c4a4dab6d64a40640540a","title":"The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 5.2","abstract":"The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 5.2 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. In 2017, the IBCAO merged its efforts with the Nippon Foundation-GEBCO Seabed 2030 Project, with the goal of mapping the global seafloor by 2030. The IBCAO Version 5.2 Grid was released in June 2026, updated from IBCAO Version 5.1.\r\n\r\nThe bathymetric grid released in IBCAO Version 5.2 is available in data GeoTIFF raster format. Elevation values are provided in metres (negative below the sea surface). The IBCAO Version 5.2 dataset comprises a grid with Greenland ice sheet data at 100 m, 200 m and 400 m grid cell spacing. A Version 5.2 grid without Greenland ice sheet data is also available. IBCAO Version 5.2 imagery is also provided in .tiff format at 100m grid cell spacing. \r\n\r\nAlongside the bathymetric grid, a data Type Identifier Grid (TID) and Source Identifier Grid (SID) are also provided, each at 100 m resolution. The TID indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on, whilst the SID has a unique number for each of the source data sets included in the bathymetric grid. \r\n\r\nThe data are made available in Polar Stereographic projection co-ordinates (meters), EPSG:3996, true scale set at 75°N. The horizontal datum for the data set is WGS 84 and vertical datum can assumed to be Mean Sea Level (however, note there may be datum issues for older data, which can be to chart datum). Elevation values are in meters (floating point).","creationDate":"2025-02-12T14:37:06.815702","lastUpdatedDate":"2026-06-10T10:08:00","latestDataUpdateTime":null,"updateFrequency":"","dataLineage":"This dataset was generated by organisation with the \"originator centre\" role in this metadata record following their in-house data processing and quality control procedures. It represents version 5.1 of the International Bathymetric Chart of the Arctic Ocean (IBCAO) and has been generated by the originator on behalf of this project. The data set is in the form of a grid that has been generated from a number of sources and using different data collection techniques. Information concerning the source data sets included in the grid is given in the documentation that accompanies the data set. After generation, the grid was then provided to the British Oceanographic Data Centre (BODC) for delivery via the General Bathymetric Chart of the Oceans (GEBCO) web site (maintained at BODC).","removedDataReason":"","keywords":"elevation, oceans","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"ongoing","dataPublishedTime":"2026-06-10T10:08:00","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":4696,"bboxName":"World","eastBoundLongitude":180.0,"westBoundLongitude":-180.0,"southBoundLatitude":-90.0,"northBoundLatitude":90.0},"verticalExtent":null,"result_field":{"ob_id":46048,"dataPath":"/bodc/gebco/ibcao/ibcao_v5.2","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":177987491525,"numberOfFiles":86,"fileFormat":".tiff; .zip; .pdf"},"timePeriod":null,"resultQuality":{"ob_id":3897,"explanation":"The data are provided as-is with no quality control undertaken by the British Oceanographic Data Centre (BODC). The data suppliers have not indicated if any quality control has been undertaken on these data.","passesTest":true,"resultTitle":"BODC Data Quality Statement","date":"2022-03-23"},"validTimePeriod":{"ob_id":12100,"startTime":"2024-07-01T00:00:00","endTime":null},"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[231],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220097,220098,220099,220100,220101,220102,220103,220105],"onlineresource_set":[]},{"ob_id":46061,"uuid":"5e879d08e0b34ea5aa5aac2b3fdf2c2f","title":"ESA Sea State Climate Change Initiative (Sea_State_cci): Global remote sensing multi-mission along-track significant wave height (SWH) from SAR WV onboard Sentinel-1A & 1B, L2P product, release version 4.","abstract":"The ESA Sea State Climate Change Initiative (CCI) project has produced global multi-sensor time-series of along-track satellite synthetic aperture radar (SAR) wave mode (WV) significant wave height (SWH) data (referred to as SAR WV onboard Sentinel-1 Level 2P (L2P) SWH data) with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Ifremer Sentinel-1 SAR Wave Mode Remote Sensing Significant Wave Height product, which is part of the ESA Sea State CCI Version 4.0 release. This is a temporal extension to the previous version 3 release. This product provides along-track SWH measurements at 20km resolution every 100km, processed using the Quach et al statistical model , separated per satellite and pass, including all measurements with flags, corrections and extra parameters from other sources. These are expert products with rich content and no data loss.  The SAR Wave Mode data used in the Sea State CCI dataset v3 come from Sentinel-1 satellite missions spanning from 2015 to 2025 (Sentinel-1 A, Sentinel-1 B).","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data was produced by the ESA Sea State CCI team at Ifremer and was transferred to CEDA as part of the ESA CCI Open Data Portal project.","removedDataReason":"","keywords":"CCI, Sea State, Significant Wave Height, SAR","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":true,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-07-08T08:42:25","doiPublishedTime":"2026-07-08T15:24:37","removedDataTime":null,"geographicExtent":{"ob_id":2576,"bboxName":"","eastBoundLongitude":180.0,"westBoundLongitude":-180.0,"southBoundLatitude":-80.0,"northBoundLatitude":80.0},"verticalExtent":null,"result_field":{"ob_id":46062,"dataPath":"/neodc/esacci/sea_state/data/v4_release/sar/l2p/sentinel1/ifremer-wv/v1.0/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":12942782511,"numberOfFiles":179560,"fileFormat":"Data are in NetCDF format"},"timePeriod":{"ob_id":13237,"startTime":"2015-03-19T00:00:00","endTime":"2025-06-11T23:59:59"},"resultQuality":{"ob_id":3367,"explanation":"The data were quality checked and compared to in situ reference data. For more details on the validation process, refer to the product user guide.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2020-01-20"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":{"ob_id":46066,"uuid":"244601214493474d97c4f66af166e4cc","short_code":"cmppr","title":"Composite process for the ESA Sea State Climate Change Initiative (Sea_State_cci): Global remote sensing multi-mission along-track significant wave height (SWH) from SAR WV onboard Sentinel-1A & 1B, L2P product, release version 4","abstract":"The SAR Wave Mode data used in this dataset comes from Sentinel-1 satellite missions spanning from 2015 to 2025 (Sentinel-1 A, Sentinel-1 B).\r\n\r\nFor more information on the dataset see the product user guide."},"imageDetails":[111],"discoveryKeywords":[{"ob_id":1140,"name":"ESACCI"}],"permissions":[{"ob_id":2604,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":63,"licenceURL":"https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_sea_state_terms_and_conditions.pdf","licenceClassifications":[{"ob_id":3,"classification":"any"}]}}],"projects":[{"ob_id":30004,"uuid":"7cfcd20428c3454fafa4e1afec2cf923","short_code":"proj","title":"ESA Sea State Climate Change Initiative Project","abstract":"The European Space Agency (ESA) Sea State CCI+ project is part of ESA's Climate Change Initiative (CCI) programme.   The CCI programme was launched by ESA in 2010, to produce long term datasets of Essential Climate Variables (ECV's) derived from global satellite data.   In this context, the Sea State CCI+ project was kicked off in 2018 in order to produce a CDR for the new ECV \"Sea State\"."}],"inspireTheme":[],"topicCategory":[],"phenomena":[50561,67859,67860,67861,67862,67863,67864,67865,67866,67867,67868,67869,67870,67871,67872,67873,67874,66538,66539,50559],"vocabularyKeywords":[],"identifier_set":[13929],"observationcollection_set":[],"responsiblepartyinfo_set":[220107,220108,220109,220110,220111,220112,220113,220114,220115,220116,220117,220118,220119],"onlineresource_set":[95692,95693,95694]},{"ob_id":46067,"uuid":"7e19d1be1cc5486294155ad23534ffa0","title":"ESA Sea State Climate Change Initiative (Sea_State_cci): Global remote sensing multi-mission along-track Integrated Sea State Parameters (ISSP) from SAR WV onboard Sentinel-1A & 1B, L2P product, release version 4","abstract":"The ESA Sea State Climate Change Initiative (CCI) project has produced global multi-sensor time-series of along-track satellite synthetic aperture radar (SAR) wave mode (WV) integrated sea state parameters (ISSP) data from Sentinel-1 (referred to as SAR WV onboard Sentinel-1 Level 2P (L2P) ISSP data) with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Sentinel-1 SAR Wave Mode Remote Sensing Integrated Sea State Parameter product, which forms part of the ESA Sea State CCI version 4.0 release. This is a temporal extension to the previous version 3 release. This product provides along-track primary significant wave height measurements and secondary sea state parameters, calibrated with CMEMS (Copernicus Marine Service) model data and reference in situ measurements at 20km resolution every 100km, processed using the Pleskachevsky et. al., 2021 empirical model, separated per satellite and pass, including all measurements with flags and uncertainty estimates. These are expert products with rich content and no data loss. The SAR Wave Mode data used in the Sea State CCI SAR WV onboard Sentinel-1 Level 2P (L2P) ISSP v4 dataset come from the Sentinel-1 satellite missions spanning from 2014 to 2024 (Sentinel-1 A, Sentinel-1 B).","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data was produced by the ESA Sea State CCI team and was transferred to CEDA as part of the ESA CCI Open Data Portal project.","removedDataReason":"","keywords":"CCI, Sea State, Integrated Sea State Parameters, ISSP, SAR","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":true,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-07-08T15:02:52","doiPublishedTime":"2026-07-08T15:25:56","removedDataTime":null,"geographicExtent":{"ob_id":2576,"bboxName":"","eastBoundLongitude":180.0,"westBoundLongitude":-180.0,"southBoundLatitude":-80.0,"northBoundLatitude":80.0},"verticalExtent":null,"result_field":{"ob_id":46068,"dataPath":"/neodc/esacci/sea_state/data/v4_release/sar/l2p/sentinel1/dlr-wv/v1.0/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":8964720928,"numberOfFiles":176098,"fileFormat":"Data are in NetCDF format"},"timePeriod":{"ob_id":13238,"startTime":"2014-12-01T00:00:00","endTime":"2024-12-30T23:59:59"},"resultQuality":{"ob_id":3367,"explanation":"The data were quality checked and compared to in situ reference data. For more details on the validation process, refer to the product user guide.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2020-01-20"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":{"ob_id":46069,"uuid":"582ce56e698c4f63af888c6afa27c48e","short_code":"cmppr","title":"Composite process for the ESA Sea State Climate Change Initiative (Sea_State_cci): Global remote sensing multi-mission along-track Integrated Sea State Parameters (ISSP) from SAR WV onboard Sentinel-1A & 1B, L2P product, version 4","abstract":"The SAR Wave Mode data used in this dataset comes from Sentinel-1 satellite missions spanning from 2014 to 2024 (Sentinel-1 A, Sentinel-1 B).\r\n\r\nFor more information on the dataset see the product user guide."},"imageDetails":[111],"discoveryKeywords":[{"ob_id":1140,"name":"ESACCI"}],"permissions":[{"ob_id":2604,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":63,"licenceURL":"https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_sea_state_terms_and_conditions.pdf","licenceClassifications":[{"ob_id":3,"classification":"any"}]}}],"projects":[{"ob_id":30004,"uuid":"7cfcd20428c3454fafa4e1afec2cf923","short_code":"proj","title":"ESA Sea State Climate Change Initiative Project","abstract":"The European Space Agency (ESA) Sea State CCI+ project is part of ESA's Climate Change Initiative (CCI) programme.   The CCI programme was launched by ESA in 2010, to produce long term datasets of Essential Climate Variables (ECV's) derived from global satellite data.   In this context, the Sea State CCI+ project was kicked off in 2018 in order to produce a CDR for the new ECV \"Sea State\"."}],"inspireTheme":[],"topicCategory":[],"phenomena":[66528,50561,66530,66536,66537,66541,66542,66543,66544,66545,66546,12182,66527,50559],"vocabularyKeywords":[],"identifier_set":[13930],"observationcollection_set":[],"responsiblepartyinfo_set":[220126,220127,220128,220129,220130,220131,220132,220133,220134,220135],"onlineresource_set":[95698,95699,95700,95701]},{"ob_id":46081,"uuid":"4507b91bf5094c82b43f2f546cc224e0","title":"HadUK-Grid Gridded Climate Observations: latest provisional data","abstract":"HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. Those 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections, released annually as verified versions via the CEDA data archive.\r\n\r\nBetween releases the Met Office make available provisional data, covered by this catalogue entry, for which recent months are available to download via the HadObs website. The latest data will be added shortly after the end of each month.\r\n\r\nThese provisional data can be used to extend the data series available in the latest release on CEDA.\r\n\r\nThe provisional data are produced for routine monitoring activities at the Met Office. These provisional versions therefore will be subject to amendment or revision before they become part of a fully citeable version of the dataset available from CEDA.\r\n\r\nThe provisional grids are generated from station observations available in near-real time. Although basic checks to eliminate any obviously suspect values will have been applied, the observations will not have been through the full quality control process. The provisional grids will also be based on fewer stations than the annual releases as not all stations report in near-real time. This is most significant for rainfall for which a large proportion of the observations are received in slower time.\r\n\r\nThe provisional data files are only provided for a subset of the full HadUK-Grid dataset. The provisional gridded data produced are:\r\n\r\nDaily: max and min temperatures (tasmax, tasmin) and rainfall\r\nMonthly: average, min and max air temperatures (tas, tasmax, tasmin), rainfall, sunshine, ground frost and surface wind\r\n\r\nFour variables are not included because the files are not generated in near-real time - these are relative humidity, mean sea level pressure, vapour pressure and days of snow lying. Seasonal and annual grids and area averages are also excluded. National and regional averages can be found on the Met Office website (see online link on this record).\r\n\r\nTo reduce storage requirements and download times we have applied additional file compression to the provisional datasets compared to the annual release. This will have the effect of a small reduction in the precision of the data.\r\n\r\nNote that the Met Office provisional HadUK-Grid content is not an operational service and the page will be maintained on a best endeavours basis. Data files will be removed from there once superseded by the next annual release via the CEDA archive.\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"monthly","dataLineage":"The provisional data are provided by the UK Met Office to complement the annual release data in the Centre for Environmental Data Analysis (CEDA) archives. Once the annual release is made, provisional data covered by the annual release are removed.","removedDataReason":"","keywords":"Met Office, UKCP18, BEIS, Defra, land surface, climate observations, hadobs","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"ongoing","dataPublishedTime":"2026-06-29T11:12:44","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":2305,"bboxName":"HadUK-Grid area","eastBoundLongitude":4.59,"westBoundLongitude":-12.61,"southBoundLatitude":48.83,"northBoundLatitude":60.57},"verticalExtent":null,"result_field":{"ob_id":46082,"dataPath":"https://www.metoffice.gov.uk/hadobs/hadukgrid/index.html","oldDataPath":[],"storageLocation":"external","storageStatus":"online","volume":0,"numberOfFiles":0,"fileFormat":"Data are NetCDF formatted"},"timePeriod":{"ob_id":13244,"startTime":"2026-01-01T00:00:00","endTime":null},"resultQuality":{"ob_id":4923,"explanation":"Provisional data produced for routine monitoring activities at the Met Office. These provisional versions therefore will be subject to amendment or revision before they become part of a fully citeable version of the dataset available from CEDA Archive.","passesTest":true,"resultTitle":"HadUK-Grid provisional release","date":"2026-06-29"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":26870,"uuid":"b1b352825f5548a8bf0639afe335f5ae","short_code":"comp","title":"HadUK-Grid gridded climate observations methodology","abstract":"The gridded data sets are based on the archive of UK weather observations held at the Met Office. The density of the station network used varies through time, and for different climate variables - for example, for the temperature variables the number of stations rises from about 270 in 1910s to 600 in the mid-1990s, before falling to 450 in 2006. Regression and interpolation are used to generate values on a regular grid from the irregular station network, taking into account factors such as latitude and longitude, altitude and terrain shape, coastal influence, and urban land use. This alleviates the impact of station openings and closures on homogeneity, but the impacts of a changing station network cannot be removed entirely, especially in areas of complex topography or sparse station coverage.\r\n\r\nThe methods used to generate the grids are described in more detail in a paper published by Hollis et al. (2019) https://doi.org/10.1002/gdj3.78 (see linked documentation on this record).\r\n\r\nTo help users combine the observational data sets with the UKCP18 climate projections, the 1km x 1km grid is averaged to grids at resolutions to match those of the climate projections. Each 5 x 5 km, 12 x 12 km, 25 x 25 km or 60 x 60 km grid box value is an average of the all the 1 × 1 km grid cell values that fall within it. A set of regional values for UK administrative regions, river basins and countries are calculated as the average of all 1 × 1 km grid cell values that fall within the defined geography."},"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"permissions":[],"projects":[{"ob_id":13164,"uuid":"ce252c81a7bd4717834055e31716b265","short_code":"proj","title":"Met Office Hadley Centre - Observations and Climate","abstract":"The Met Office Hadley Centre is one of the UK's foremost climate change research centres.\r\n\r\nThe Hadley Centre produces world-class guidance on the science of climate change and provide a focus in the UK for the scientific issues associated with climate science.\r\n\r\nLargely co-funded by Department of Energy and Climate Change (DECC) and Defra (the Department for Environment, Food and Rural Affairs), the centre provides in-depth information to, and advise, the Government on climate science issues.\r\n\r\nAs one of the world's leading centres for climate science research, the Hadley Centre scientists make significant contributions to peer-reviewed literature and to a variety of climate science reports, including the Assessment Report of the IPCC. The Hadley Centre climate projections were the basis for the Stern Review on the Economics of Climate Change."}],"inspireTheme":[],"topicCategory":[],"phenomena":[93849,93850,93851,93852,93853,93854,93855,93856,93857,93858,93859,93860,93861,93862,93863,93864,93865,93866,93867,93868,93869,93870,93871,93872,93873,93874,93875,93876,93877,93878,93879,93880,93881,93882,93883,93884,93885,93886,93887,93888,93889,93890,93891,93892,93893,93894,93895,93342],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[{"ob_id":26862,"uuid":"4dc8450d889a491ebb20e724debe2dfb","short_code":"coll","title":"HadUK-Grid gridded and regional average climate observations for the UK","abstract":"This Dataset Collection contains a number of different versions of the HadUK-Grid dataset, each of which present a set of gridded climate variables extending from the present back to the 19th Century. The primary purpose of these data are to facilitate monitoring of the UK climate and research into climate variability, climate change, impacts and adaptation. The Met Office uses these data for operational monitoring of the UK's climate.\r\n\r\nThe data have been interpolated from meteorological station data onto a uniform grid at 1km by 1km resolution to provide complete and consistent coverage across the UK. The 1km data set has been regridded to different resolutions and regional averages to create a collection allowing for comparison to data from UKCP18 climate projections.\r\n\r\nA new version of HadUK-Grid is released each year. The latest version is v1.3.2.ceda, released in June 2026 and containing data up to the end of 2025. A summary of previous releases can be found below. Provisional data for more recent months can be found on the Met Office web site https://www.metoffice.gov.uk/hadobs/hadukgrid/.\r\n\r\nEach version comprises eight Datasets - gridded data at 1, 5, 12, 25 and 60 km resolution, plus three sets of area averages (UK countries, admin regions and river basins).\r\n\r\nThe earliest year of data varies by variable and has changed as more data are digitised. Currently the start years are:\r\n1836 (monthly rainfall)\r\n1884 (monthly max/mean/min air temperature)\r\n1891 (daily rainfall)\r\n1910 (monthly sunshine)\r\n1931 (daily max/min air temperature)\r\n1961 (monthly days of ground frost, relative humidity, mean sea level pressure and vapour pressure)\r\n1969 (monthly mean wind speed)\r\n1971 (monthly days of lying snow)\r\n\r\nThe grids are provided at daily (max/min air temperature and rainfall only), monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods.\r\n\r\nThe latest release has been created by the Met Office funded by the UK Department for Science, Innovation and Technology (DSIT).\r\n\r\nPrevious versions were created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project.\r\n\r\nFor all versions, the data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\".\r\n\r\nThe data are provided under Open Government Licence v3 (see each dataset for links to licence and associated citations to use).\r\n\r\nList of dataset versions (latest first) and key differences (each release also extends the dataset by one year):\r\n\r\nv1.3.2.ceda (1836-2025) - Addition of new variables: daily mean temperature, days of air frost, days of rain >1mm, days of rain >10mm, summer days (daily tmax > 25)\r\nv1.3.1.ceda (1836-2024) - Daily temperature extended back to 1931 (from 1960). Historical data recovery has improved daily rainfall over Scotland for 1922-1945.\r\nv1.3.0.ceda (1836-2023) - Historical data recovery has improved daily rainfall over Scotland for 1945-1960.\r\nv1.2.0.ceda (1836-2022) - Monthly sunshine extended back to 1910 (from 1919). Incorporation of Rainfall Rescue v2.\r\nv1.1.0.0 (1836-2021) - Addition of climate averages for 1991-2020. Rainfall Rescue v1 dataset incorporated into the monthly rainfall grids which are extended back to 1836 (from 1862).\r\nv1.0.3.0 (1862-2020)\r\nv1.0.2.1 (1862-2019) - Monthly sunshine extended back to 1919 (from 1929). Historical data recovery has also improved monthly rainfall 1862-1910, daily rainfall 1891-1910 and monthly temperature 1900-1909. Correction to the grid definition for 12 km grid product to match the UKCP18 climate model products.\r\nv1.0.1.0 (1862-2018) - Addition of 5km data.\r\nv1.0.0.0 (1862-2017) - Initial release.\r\n\r\nSee the change log file for each version for further details.\r\n\r\nNote: The introduction of the '.ceda' suffix was done to highlight that CEDA is the source of these data files compared to other potential sources (e.g. the UKCP User Interface https://ukclimateprojections-ui.metoffice.gov.uk/ui/home). The data values are the same - it is the way the data are packaged that may differ between sources.\r\n\r\nEach version following the initial release is accompanied by change log files. These list new files in the version compared with the previous version plus summary totals of the number of files that remained the same, modified and removed. Links to these change logs are available in the 'Details/Docs' section of each dataset. Additionally, a summary change log file is provided which gives an overview of all changes to the data sources and processing methods since the initial release. This summary can be found in the 'Details/Docs' section below or via the individual datasets.\r\n\r\nThis collection supersedes the UKCP09 Dataset Collection and contains all datasets within the major version 1 release (i.e. v1.#.#.#). See Hollis et al. (2019; linked documentation) for details on the version numbering utilised."}],"responsiblepartyinfo_set":[220149,220154,220158,220150,220151,220153,220156,220155,220159,220157,220160,220161,220162,220163],"onlineresource_set":[95719,95713,95714,95710,95711,95712]},{"ob_id":46083,"uuid":"6415e9e095e249ab9509f9c7878d1f11","title":"Antarctic Ice Sheet Surface Elevation Change (SEC) for the ESA Antarctic CCI+ Phase-2 project ","abstract":"Gridded Antarctic Ice Sheet Surface Elevation Change (SEC) products derived from cross-calibrated radar and laser satellite altimetry missions since 1991. Products are processed by the Centre for Polar Observation and Modelling (CPOM) as part of the Antarctic CCI+ Phase-2 project for the European Space Agency (ESA). The dataset includes multi-mission 5-year rates of surface elevation change (dH/dt), cumulative annual dH grids, single radar altimetry mission SEC products (ERS-1, ERS-2, ENVISAT, CryoSat-2, Sentinel-3A, Sentinel-3B), and an ICESat-2 laser altimetry SEC product. All gridded products are provided on a 5 km south polar stereographic grid (EPSG:3031).","creationDate":"2026-06-19T14:34:28.933220","lastUpdatedDate":"2026-06-19T14:38:03.725423","latestDataUpdateTime":"2026-06-19T14:34:28.933225","updateFrequency":"notPlanned","dataLineage":"Surface elevation change products are derived from radar altimetry data acquired by ERS-1 (1991–1996), ERS-2 (1995–2003), ENVISAT (2002–2012), CryoSat-2 (2010–present), Sentinel-3A (2016–present), and Sentinel-3B (2018–present), and from laser altimetry data acquired by ICESat-2 (2018–present). Cross-calibration of radar altimetry missions was performed to produce consistent multi-mission records. Processing was carried out by CPOM. Products are provided on a 5 km south polar stereographic grid (EPSG:3031). Single-mission SEC products represent the full operational period of each mission. Multi-mission products combine all available radar altimetry missions.","removedDataReason":"","keywords":"Antarctica,Altimetry,Surface Elevation Change,CryoSat-2,ICESat-2,Sentinel-3,ERS,ENVISAT,SEC,ESA CCI","publicationState":"preview","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5172,"bboxName":"","eastBoundLongitude":-180.0,"westBoundLongitude":180.0,"southBoundLatitude":-90.0,"northBoundLatitude":-60.0},"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":13248,"startTime":"1991-12-09T00:00:00","endTime":"2025-09-30T00:00:00"},"resultQuality":{"ob_id":4919,"explanation":"Products include gridded uncertainty estimates alongside surface elevation change rates. Multi-mission products are derived from cross-calibrated radar altimetry data to ensure consistency across the record. Data are released as version 2 (v2) under the Antarctic CCI+ Phase-2 project.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-06-19"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":46085,"uuid":"fd7062df62004998a4e1476834e6d2e9","short_code":"acq","title":"Acquisition for: Antarctic Ice Sheet Surface Elevation Change (SEC) for the ESA Antarctic CCI+ Phase-2 project ","abstract":""},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[],"projects":[{"ob_id":46084,"uuid":"23d7c16042ba46ba97691b7b5dc3df76","short_code":"proj","title":"Antarctic CCI+ Phase-2","abstract":"ESA Climate Change Initiative project to generate and validate Antarctic Ice Sheet climate data records from satellite observations."}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220164,220165,220166,220167,220168,220169,220170],"onlineresource_set":[95717]},{"ob_id":46092,"uuid":"d61136bca15d4e3f8547c4b539fb5656","title":"JULES-Peat model outputs simulating the formation and development of the Cuvette Centrale peatlands, Congo Basin (20,000 BP to 60 BP / 18,000 BCE to 1940 CE)","abstract":"This dataset contains model outputs which simulate the formation and development of the Central Congo Basin peatlands. The model used was JULES-Peat, a new version of the Joint UK Land Environment Simulator (JULES), the land surface component of the UK Earth System Model.\r\n\r\nTen simulations were run under conditions representing those in the Central Congo Basin peatlands over the past 20,000 years, introducing new changes to the model in each new simulation. Details of the ten model runs, files used, and code changes can be found in the document Congo_Peat_JULES_runs_details. The files used to run JULES can be found in the Run_JULES_u-an231 directory.\r\n\r\nThe temporal range of the data is reported in years before present (BP), where present is the year 2000 CE. 20,000 BP to 60 BP is equivalent to 18,000 BCE to 1940 CE.\r\n\r\nThis dataset has one related publication: \"Improving the representation of tropical peatland processes in the JULES land surface model using data from the Central Congo Basin\", Cook et al. 2026 (linked in the documentation section).\r\n\r\nThis dataset was produced as part of the Natural Environment Research Council (NERC) project CongoPeat: Past, Present and Future of the Peatlands of the Central Congo Basin (grant reference: NE/R016860/1). The modelling study was carried out by Peter Anthony Cook at the Global Systems Institute, University of Exeter, Exeter, UK.","creationDate":"2026-06-26T14:31:23.158068","lastUpdatedDate":"2026-06-26T15:44:20","latestDataUpdateTime":"2026-06-26T14:31:23","updateFrequency":"notPlanned","dataLineage":"Data were generated using JULES-Peat, a new version of the Joint UK Land Environment Simulator (JULES), the land surface component of the UK Earth System Model, to simulate the formation and development of the peatlands.","removedDataReason":"","keywords":"CongoPeat, Tropical Peatlands, Carbon Store, JULES-Peat Model, Paleo Climate Simulations, Vulnerability of Peatlands, Central Congo Basin, NE/R016860/1","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-08-20T12:55:24","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5194,"bboxName":"Centre of Congo Basin","eastBoundLongitude":18.0,"westBoundLongitude":18.0,"southBoundLatitude":0.0,"northBoundLatitude":0.0},"verticalExtent":null,"result_field":{"ob_id":46149,"dataPath":"/badc/congopeat/data/Congo_Peat_JULES_Runs","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":29143537667,"numberOfFiles":186,"fileFormat":"NetCDF"},"timePeriod":{"ob_id":13319,"startTime":"0001-01-01T00:00:00","endTime":"1940-01-01T00:00:00"},"resultQuality":{"ob_id":4922,"explanation":"Model output rather that measured values.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-06-26"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":46189,"uuid":"b3498a1d22c24787abf59b7684f8b6d6","short_code":"comp","title":"JULES-Peat","abstract":"JULES-Peat modifies the peatland scheme in the Joint UK Land Environment Simulator (JULES), the land surface component of the UK Earth System Model. In particular, JULES-Peat changes the vegetation litter composition and the dependence of peat decay on soil moisture. \r\n\r\nThe modifications are informed by field measurements and comparing the simulated peat accumulation and loss over 20,000 years with peat core records, including the “Ghost Interval” period when reduced precipitation starting ~5,000 years before present resulted in significant peat loss. JULES-Peat is driven with a reconstruction of precipitation from peat core proxy data and other meteorological data from a global palaeoclimate model. \r\n\r\nThe original JULES peatland scheme was unable to accumulate the observed quantities of peat or simulate the losses of peat suggested by palaeo records. This updated version of JULES simulates peat increases until 3,000 BP, when reduced precipitation results in substantial loss until 1,000 BP.\r\n\r\nThe JULES-Peat code is available on the Met Office Science Repository Service (requires registration for an account): https://code.metoffice.gov.uk/trac/jules/browser/main/branches/dev/eleanorburke/vn6.2_accumulate_soil"},"procedureCompositeProcess":null,"imageDetails":[236],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":46093,"uuid":"740c9234c6cf48bfb825b393568b11fb","short_code":"proj","title":"CongoPeat: Past, Present and Future of the Peatlands of the Central Congo Basin","abstract":"CongoPeat was a five-year research programme led by Professor Simon Lewis of the University of Leeds and funded by Natural Environment Research Council (NERC) grant NE/R016860/1. It investigated the newly discovered peatlands of the central Congo Basin, the largest known tropical peatland complex in the world. Spanning 145,500 km² and storing an estimated 30 billion tonnes of carbon, these peatlands play a globally significant role in climate regulation and biodiversity conservation.\r\n\r\nThe project brought together researchers from six UK universities and five Congolese organisations to improve understanding of the peatlands’ past development, current condition, and future vulnerability to environmental change and human activities. Data outputs from the programme support research on the past, present, and future of the Congo Basin peatlands and provide an evidence base for conservation, sustainable management, and policy-making in the Republic of Congo and the Democratic Republic of the Congo.\r\n\r\nData are archived with the Centre for Environmental Data analysis and the Environmental Information Data Centre."}],"inspireTheme":[],"topicCategory":[],"phenomena":[93738,93739,93740,93741,93742,93744,93745,93746,93747,93748,93750,93751,93752,93753,93754,93755,93756,93757,93758,93759,93760,93761,93762,93763,93764,93765,93766,93767,93768,93769,93770,93771,93772,93773,93774,93778,93780,93781,93782,93784,93785,84123,84126,94004,94005,94006,94007,94008,94009,94010,94011,94012,94013,94014,94015,94016,94017,94018,94019,94020,94021,94022,94023,94024,94025,94026,94027,94028,94029,94030,94031,94032,94033,94034,94035,94036,94037,94038,94039,94040,94041,94042,94043,94044,94045,94046,94047,94048,94049,94050,94051,94052,94053,94054,94055,94056,94057,94058,94059,94060,94061,94062,94063,94064,94065,94066,94067,94068,94069,94070,94071,94072,94073,94074,94075,94076,94077,94078,94079,94080,94081,94082,94083,94084,94085,94086,94087,94088,8142],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220188,220190,220183,220184,220185,220186,220187,220560],"onlineresource_set":[95731,95732,95918]},{"ob_id":46098,"uuid":"8cd69bd991a942a3828bd7b24d039ad7","title":"EOCIS: Daily land surface temperature from Landsat 8/9, level 2 merged (L2) UK product, version 1.00","abstract":"This dataset contains land surface temperatures (LSTs) and their uncertainty estimates from the Thermal Infrared Sensor (TIRS) on Landsat 8/9. Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.\r\n\r\nDaytime temperature estimates are provided at approximately 10:30 local solar time. Temperatures are reported in Kelvin and represent the skin temperature of the Earth's surface.\r\n\r\n\r\nThe dataset was produced by the University of Leicester (UoL) and LSTs were retrieved using the (UoL) LST retrieval algorithm and data were processed in the UoL processing chain.\r\n\r\nThe dataset was produced as part of the UK Earth Observation Climate Information Service (EOCIS) and is based on development funded under ESA CCI with additional funding from NCEO.  The EOCIS dataset includes and continues the CCI v4 CDR (currently under development).","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"The data record has been produced by the University of Leicester as part of the UK Earth Observation Climate Information Service (EOCIS) project and is based on development funded under ESA CCI with additional funding from NCEO.","removedDataReason":"","keywords":"land surface temperature, EOCIS, Landsat","publicationState":"preview","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"0.01 degree","status":"ongoing","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":2609,"bboxName":"UK","eastBoundLongitude":2.02,"westBoundLongitude":-10.85,"southBoundLatitude":49.82,"northBoundLatitude":59.48},"verticalExtent":null,"result_field":{"ob_id":46150,"dataPath":"/neodc/eocis/data/CHUK/land_surface_temperature/LANDSAT8_TIRS/L2/v1.0","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":7366618967,"numberOfFiles":1827,"fileFormat":"These data are in netCDF format."},"timePeriod":{"ob_id":13264,"startTime":"2018-01-01T00:00:00","endTime":"2022-12-31T23:59:59"},"resultQuality":{"ob_id":4634,"explanation":"Data are as provided by the data producer.   For further information on the data quality see the associated documentation.","passesTest":true,"resultTitle":"LST EOCIS","date":"2024-12-19"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":{"ob_id":46105,"uuid":"a9ad50230c5a41c688e2cc33bc0ad015","short_code":"cmppr","title":"Composite process for EOCIS LST: Daily land surface temperature from Landsat 8/9, level 2 merged (L2) UK product, version 1.00","abstract":"Data has been derived from the Thermal Infrared Sensor (TIRS) on Landsat8/9."},"imageDetails":[],"discoveryKeywords":[],"permissions":[{"ob_id":2528,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":8,"licenceURL":"http://creativecommons.org/licenses/by/4.0/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":43216,"uuid":"8bffaba46c4a4b8c82e4be2c91c637b9","short_code":"proj","title":"Earth Observation Climate Information Service (EOCIS)","abstract":"The UK Earth Observation Climate Information Service exploits the observations available from environmental sensors orbiting in space to create climate data records and climate information. EOCIS was announced by the government in November 2022, and formally launched in March 2023. It is funded currently until March 2025. \r\n\r\nEOCIS is a collaboration led by the National Centre for Earth Observation, and involving over a dozen research organisations. EOCIS addresses 12 categories of global and regional essential climate variables, which are the following:\r\n- Sea surface temperature\r\n- Ocean reflectance\r\n- Fire occurrence and emissions\r\n- Aerosol and particulate\r\n- Cloud-aerosol-radiation\r\n- Methane\r\n- Land surface temperature\r\n- Water vapour, ozone\r\n- Arctic: ice sheet mass and sea ice\r\n- Eurasia: surface methane\r\n- Africa: soil water balance\r\n- Antarctic: ice sheet mass and ice velocity\r\n\r\nEOCIS is also creating new climate data at high resolution for the UK specifically. This includes both rapid-response information for climate-linked events (fire early warning and urban flood mapping) and longer term climate data linked to human and ecosystem health and landscape greenhouse gas emissions."}],"inspireTheme":[],"topicCategory":[],"phenomena":[46768,102917,74919,74920,74921,74922],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220197,220198,220199,220200,220201,220202,220203,220204,220205,220265,220207,220206,220208],"onlineresource_set":[95734,95735]},{"ob_id":46099,"uuid":"4c7e812010a441e8afe5f91cfc4e8b7d","title":"Secondary Organic Aerosol Prediction in Realistic Atmospheres (SOAPRA) laboratory data set (2024)","abstract":"Funded by the UK's Natural Environment Research Council (NERC) under grant NE/V012665/1, the Secondary Organic Aerosol Prediction in Realistic Atmospheres (SOAPRA) project aimed to advance the predictive capability for secondary organic aerosol in the atmosphere.\r\n\r\nA key component of the work was development of a method to constrain the rate coefficients of gas-phase reaction rates relevant to secondary organic aerosol, as published in https://doi.org/10.5194/ar-3-417-2025. The method and it's associated software were called autoCONSTRAINT, and its dataset is contained in this record.\r\n\r\nAs part of this paper, the PyCHAM (CHemistry with Aerosol Microphysics in Python) computational model was used, with the relevant outputs contained in PyCHAM_simulation_outputs_for_autoCONSTRAINT_comparison.nc. Specifically, identifiers and concentrations of individual components output from PyCHAM are provided.\r\n\r\nThe outputs from autoCONSTRAINT, relevant to this paper, are contained in autoCONSTRAINT_outputs.nc. Specifically, chemical reactions, rate coefficients and radical names are provided.\r\n\r\nConcentrations, rate coefficients, chemical reactions and component names have been recorded, in the form of netcdf files, with separate variables for each of these recordings. Results are for simulated laboratory experiments in aerosol chambers, with simulated experiments typically last for approximately 7 hours. The description of the PyCHAM and autoCONSTRAINT methods are provided in https://doi.org/10.5194/ar-3-417-2025. This work was carried out because previously a repeatable and standardisable method for quantifying rate coefficients from aerosol chamber experiments was unavailable. The work was primarily completed by Lukas Pichelstorfer, with support from Simon O'Meara, and the principal investigator was Gordon McFiggans. All data relevant to the project's 2025 paper (https://doi.org/10.5194/ar-3-417-2025) are provided.","creationDate":"2026-06-29T13:09:13.247702","lastUpdatedDate":"2026-06-29T13:05:09","latestDataUpdateTime":"2026-06-29T13:05:09","updateFrequency":"","dataLineage":"The data was created by the authors during the stated temporal range using the tools described in the Description section of this record. Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"Secondary organic aerosol, Computational simulation, Chemical kinetics, Organic chemistry, Photochemistry, Atmospheric Science, Atmospheric Chemistry","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"planned","dataPublishedTime":"2026-07-07T09:00:06","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":529,"bboxName":"Global (-180 to 180)","eastBoundLongitude":180.0,"westBoundLongitude":-180.0,"southBoundLatitude":-90.0,"northBoundLatitude":90.0},"verticalExtent":null,"result_field":{"ob_id":46102,"dataPath":"/badc/deposited2026/SOAPRA","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":79087,"numberOfFiles":3,"fileFormat":"netcdf"},"timePeriod":{"ob_id":13253,"startTime":"2024-07-17T00:00:00","endTime":"2024-07-17T23:59:59"},"resultQuality":{"ob_id":4924,"explanation":"Data are simulation outputs for hypothetical experiments and are not from measurements.","passesTest":true,"resultTitle":"NE/V012665/1 - CEDA Data Quality Statement","date":"2026-06-29"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":46100,"uuid":"a6e3334374c747c6a24ff922d0a4f6f6","short_code":"comp","title":"CHemistry with Aerosol Microphysics in Python (PyCHAM) and semi-automated constraint of chemical rate coefficients (autoCONSTRAINT).","abstract":"PyCHAM solves gas-phase photochemistry and phase partitioning to simalate the time-series of a chemical system with a zero-dimensional spatial approach. AutoCONSTRAINT analytically solves the rate coefficients of gas-phase reactions using observed/simulated gas-phase concentrations and chemical theory."},"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":46101,"uuid":"a5fd12288d9b4f4fb66f1b1ed56292ad","short_code":"proj","title":"Secondary Organic Aerosol Prediction in Realistic Atmospheres (SOAPRA) (NE/V012665/1)","abstract":"Aerosol particles are key drivers of reduced air quality and provide significant offsetting of warming by greenhouse gases. The organic fraction is frequently observed to dominate mass of fine particulate matter (PM) and secondary organic aerosol (SOA) is the major contributor. With air pollution responsible for 11 % of global deaths annually and air temperature rise within 0.5 degree C of the target pursued by Paris Agreement signatories, accurate forecasts of organic aerosol particle mass loadings are required to inform policy decisions. Experimental results presented in  recent landmark study to investigate the mechanisms determining SOA formation in atmospheric mixtures will be interrogated. \r\n\r\nNew mechanistic chemical understanding developed from this work will be included into a coupled model of gaseous photochemistry and aerosol formation. Detailed comparison of the model with measured gaseous and aerosol composition will enable unprecedented confidence in our understanding of the interactions that can occur in the real atmosphere. The model will demonstrate the magnitude of interactions to be expected in airmasses containing natural and manmade pollutants that promises to enable reasonable mechanistic interpretation of SOA formation in the real atmosphere for the first time.\r\n\r\nThis project will develop a mechanistic quantitative representation of oxidative chemistry leading to SOA formation in realistic atmospheric mixtures including interactions between biogenic and anthropogenic precursors. The project will demonstrate its predictive capability by comparison with existing and emerging experimental data and use it to evaluate the potential for SOA formation and uncertainty ranges across VOC mixtures at VOC:NOx regimes applicable to the real atmosphere. \r\n\r\nThe recent study (McFiggans et al., 2019) was transformative in that it showed that the formation of particulate mass in mixtures of gaseous precursors cannot be assumed to be the sum of that formed independently from the components of the mixture. The study demonstrated that this resulted from two effects: i) oxidant scavenging; competition of the precursor molecules for the available oxidant and ii) product scavenging; vapour phase interactions between oxidation products that would have otherwise reacted to form condensed particulate mass. These two effects lead to the requirement for a realistic treatment of SOA formation in mixtures in order to predict atmospheric PM loading and its effect on human health and climate. \r\n\r\nData from a large number of published and (as yet) unpublished laboratory and chamber experiments, investigating SOA formation from the oxidation of individual VOC and their mixtures. In each, the project quantifies the formation of highly-oxygenated organic molecules (HOM) found to be major contributors to the condensed SOA mass. The VOC include key species from the major biogenic and anthropogenic classes of SOA precursors. The project will extend the benchmark mechanism for atmospheric VOC oxidation to incorporate the most recent mechanistic understanding of HOM into our chamber model of coupled photochemistry and aerosol microphysics. The project will optimise simulations using this model by comparison with the experimental data and conduct further simulations to establish the critical dependencies of SOA formation in the atmosphere. Large scale air quality and climate models will need to capture these relationships to enable confidence to be placed in their predictions. The project will include a simplified mechanism based on the same framework as our more detailed scheme into the EMEP regional pollution model to demonstrate the impact of interactions in atmospheric mixtures of VOC on regional PM."}],"inspireTheme":[],"topicCategory":[],"phenomena":[93896,93897,93898,93899,93900,93901,93902],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220209,220210,220211,220212,220213,220214,220215,220232,220216,220217],"onlineresource_set":[95736]},{"ob_id":46107,"uuid":"77f24586752943b99719c66075a434fe","title":"Monthly climatologies of marine iodide and iodate generated using the I-CYCLE model","abstract":"Ocean iodide and iodate concentration fields for present day (2000-2019), historical (1880-1899) and future (2080-2099 under SSP585 scenario) generated using the I-CYCLE global ocean model of iodine cycling. Data is a monthly climatology for these three periods. It is on tri-polar grid.","creationDate":"2026-07-01T15:23:13.379291","lastUpdatedDate":"2026-07-01T15:24:43.133936","latestDataUpdateTime":"2026-07-01T15:23:13.379295","updateFrequency":"notPlanned","dataLineage":"Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"ocean,iodine","publicationState":"working","nonGeographicFlag":true,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":null,"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":13263,"startTime":"2000-01-01T00:00:00","endTime":"2019-12-01T00:00:00"},"resultQuality":{"ob_id":4926,"explanation":"na","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-07-01"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":46112,"uuid":"630fbdc720034a99b8835bc4e41e2f2f","short_code":"comp","title":"I-CYCLE","abstract":"Global ocean iodine cycling model"},"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[],"projects":[{"ob_id":46108,"uuid":"3918ad29976d4075b6ff208b3a8781f0","short_code":"proj","title":"Iodine sea-air emissions and atmospheric impacts in a changing world (I-SEA)","abstract":"na"}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220241,220242,220243,220244,220245,220246,220247,220248,220249,220250,220251,220252],"onlineresource_set":[95740]},{"ob_id":46118,"uuid":"eae8d3c9c5d64d4f901c5221dad18a86","title":"ESA River Discharge Climate Change Initiative (RD_cci):  Nadir radar altimeters Water Level product, v2.1","abstract":"This dataset contains water level (WL) data from the ESA Climate Change Initiative River Discharge project (RD_cci).   Water level in this context corresponds to the distance between river surface water and a reference surface (the WGS84 ellipsoid). This physical variable might also be referred to as Water Surface Elevation (WSE) in other dataset or publications.\r\n\r\nThis version of the dataset is v2.1\r\n\r\nThese river water level time series have been computed in at 54 locations (within 18 river basins). The data has been derived from nadir viewing satellite radar altimeter missions (ERS-2, Envisat, Saral, Topex-Poseidon, Jason-1, Jason-2, Jason-3, Sentinel-3A/B and Sentinel 6A). At each location, time series are provided for each available single nadir radar altimetry mission. Based on these single mission time series, merged multi-missions WL time series (with two different methodologies for some basins) have also been produced.","creationDate":"2023-12-06T08:01:27.903402","lastUpdatedDate":"2023-12-06T08:00:25","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"CCI, Water Level, River Discharge","publicationState":"preview","nonGeographicFlag":false,"dontHarvestFromProjects":true,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":529,"bboxName":"Global (-180 to 180)","eastBoundLongitude":180.0,"westBoundLongitude":-180.0,"southBoundLatitude":-90.0,"northBoundLatitude":90.0},"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":11558,"startTime":"1992-12-22T00:00:00","endTime":"2023-09-18T23:59:59"},"resultQuality":{"ob_id":4524,"explanation":"For information on the data quality see the related documentation","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2024-02-09"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":{"ob_id":45148,"uuid":"79e4f3bf7eff49f0bca0e2ed787d191a","short_code":"cmppr","title":"Composite process for ESA River Discharge Climate Change Initiative (RD_cci):  Water Level product, v2.0","abstract":"The data has been derived from nadir viewing satellite radar altimeter missions  (ERS-2, Envisat, Saral, Topex-Poseidon, Jason-1, Jason-2, Jason-3, Sentinel-3A/B and Sentinel 6)."},"imageDetails":[111],"discoveryKeywords":[],"permissions":[],"projects":[{"ob_id":41537,"uuid":"dbba9cfe8d104648b19e39f4c2da1a27","short_code":"proj","title":"ESA River Discharge Climate Change Initiative (RD_cci)","abstract":"The ESA river discharge Climate Change Initiative project aims to derive long term climate data records (at least over 20-years) of river discharge for some selected river basins (and some locations in the river network) using satellite remote sensing observations (altimetry and multispectral images) and ancillary data."}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220266,220267,220268,220269,220270,220271,220272,220273,220274,220275,220276,220277,220278,220279,220280,220281,220282],"onlineresource_set":[95769,95770,95771,95772,95773]},{"ob_id":46123,"uuid":"94d6572a308e477c86e0ce7c4d771311","title":"University of Leicester GOSAT Proxy XCH4 v10.0","abstract":"The University of Leicester GOSAT Proxy XCH4 v10.0 data set contains column-averaged dry-air mole fraction of methane (XCH4) generated from the Greenhouse Gas Observing Satellite (GOSAT) Level 1B data using the University of Leicester Full-Physics retrieval scheme (UoL-FP) using the Proxy retrieval approach.\r\n\r\nThis data is an NCEO funded update/extension to the European Space Agency Climate Change Initiative (CCI) CH4_GOS_OCPR V7.0. and the Copernicus Climate Change Service (C3S)  CH_4 v7.2 data sets. It's a full reprocessing, based on different underlying L1B radiance data with additional changes.  GOSAT Level 1B files (version 220/221) were acquired directly from the National Institute for Environmental Studies (NIES) GOSAT Data Archive Service (GDAS) Data Server and are processed with the Leicester Retrieval Preparation Toolset to extract the measured radiances along with all required sounding-specific ancillary information such as the measurement time, location and geometry.  The spectral data were then inputted into the UoL-FP retrieval algorithm where the Proxy retrieval approach is used to obtain the column-averaged dry-air mole fraction of methane (XCH4). Post-filtering and bias correction against the Total Carbon Column Observing Network is then performed. See process information and documentation for further details.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":"2026-08-03T13:52:49","updateFrequency":"notPlanned","dataLineage":"Data were produced by the University of Leicester project team and delivered to Centre for Environmental Data Analysis (CEDA) for archival and publication. The data was produced under NCEO.","removedDataReason":"","keywords":"GOSAT, CH4, Methane","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":true,"language":"English","resolution":"","status":"ongoing","dataPublishedTime":"2026-08-10T15:07:47","doiPublishedTime":"2026-08-26T14:21:05.002434","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":46165,"dataPath":"/neodc/gosat/data/ch4/UoL_gosat1_v10/CH4_GOSAT_OCPR/v10.0/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":10600083122,"numberOfFiles":5897,"fileFormat":"Data are in NetCDF format"},"timePeriod":{"ob_id":13297,"startTime":"2009-04-23T00:00:00","endTime":"2025-12-18T23:59:59"},"resultQuality":{"ob_id":3411,"explanation":"The data has been fully validated by the University of Leicester project team","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2020-05-05"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":{"ob_id":46167,"uuid":"b4023a252ee144a4b0aaedf935bcc1bb","short_code":"cmppr","title":"Composite process for University of Leicester GOSAT Proxy XCH4 v10","abstract":"The latest version of the GOSAT Level 1B files (version 210.210) are acquired directly from the NIES GDAS Data Server and are processed with the Leicester Retrieval Preparation Toolset to extract the measured radiances along with all required sounding-specific ancillary information such as the measurement time, location and geometry. These measured radiances have the recommended radiometric calibration and degradation corrections applied as per Yoshida et al., 2013 with an estimate of the spectral noise derived from the standard deviation of the out-of-band signal. The spectral data were then inputted into the UoL-FP retrieval algorithm where the Proxy retrieval approach is used to obtain the column-averaged dry-air mole fraction of methane (XCH4). Post-filtering and bias correction against the Total Carbon Column Observing Network is then performed"},"imageDetails":[130],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":5002,"uuid":"60e718d3f2957f742c89b2b4fc159718","short_code":"proj","title":"National Centre for Earth Observation (NCEO)","abstract":"The National Centre for Earth Observation is a partnership of scientists and institutions, from a range of disciplines, who are using data from Earth observation satellites to monitor global and regional changes in the environment and to improve understanding of the Earth system so that we can predict future environmental conditions.\r\n\r\nNCEO's Vision is to unlock the full potential of Earth observation to monitor, diagnose and predict climate and environmental changes, ensuring that these scientific advances are delivered to the wider community embedded in world class science."}],"inspireTheme":[],"topicCategory":[],"phenomena":[68633,68622,68623,68624,68625,68626,68627,66452,68628,68630,68629,68632,66456,68634,68635,68631,68637,68638,68639,68636,68641,68642,68643,68644,103077,68646,68645,68640,50542,50543,63576],"vocabularyKeywords":[],"identifier_set":[13961],"observationcollection_set":[],"responsiblepartyinfo_set":[220296,220297,220298,220299,220300,220301,220302,220293,220295,220294,220500,220501],"onlineresource_set":[95776,95777,95778,95779,95780,95911]},{"ob_id":46124,"uuid":"8209b9acb92e4ba69188c9c8ff7a3b76","title":"University of Leicester GOSAT-2 Proxy XCH4, v2.0","abstract":"The University of Leicester GOSAT-2 Proxy XCH4, v2.0 data set contains column-averaged dry-air mole fraction of methane (XCH4) generated from the Greenhouse Gas Observing Satellite (GOSAT-2) Level 1B data using the University of Leicester Full-Physics retrieval scheme (UoL-FP) using the Proxy retrieval approach.\r\n\r\nThis data is the University of Leicester GOSAT-2 Proxy XCH4 v2.0 dataset. This dataset is consistent with the GOSAT dataset (https://catalogue.ceda.ac.uk/uuid/94d6572a308e477c86e0ce7c4d771311/). The latest version of the GOSAT-2 Level 1B files were processed with the Leicester Retrieval Preparation Toolset to extract the measured radiances along with all required sounding-specific ancillary information such as the measurement time, location and geometry. The data were processed through the UoL-FP retrieval algorithm where the Proxy retrieval approach is used to obtain the column-averaged dry-air mole fraction of methane (XCH4). \r\n\r\nWe bias-correct this data to be consistent with the GOSAT dataset and evaluate it’s performance against the the Total Carbon Column Observing Network via the same methodology as used for the GOSAT data. See process information and documentation for further details.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":"2026-08-03T13:56:54","updateFrequency":"notPlanned","dataLineage":"Data were produced by the University of Leicester project team and delivered to Centre for Environmental Data Analysis (CEDA) for archival and publication.  The data was produced under the National Centre for Earth Observation (NCEO).","removedDataReason":"","keywords":"GOSAT-2, CH4, Methane, EOCIS","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":true,"language":"English","resolution":"","status":"ongoing","dataPublishedTime":"2026-08-10T15:04:45","doiPublishedTime":"2026-08-26T14:19:27.110628","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":46166,"dataPath":"/neodc/gosat/data/ch4/UoL_gosat2_v2/CH4_GOSAT2_OCPR/v2.0/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":5189138505,"numberOfFiles":2383,"fileFormat":"Data are in NetCDF format"},"timePeriod":{"ob_id":13298,"startTime":"2019-02-05T00:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":3411,"explanation":"The data has been fully validated by the University of Leicester project team","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2020-05-05"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":{"ob_id":46168,"uuid":"586888ecf6334a76a0487311b3a0f288","short_code":"cmppr","title":"Composite process for University of Leicester GOSAT-2 Proxy XCH4 v2.0","abstract":"The latest version of the GOSAT-2 Level 1B files were processed with the Leicester Retrieval Preparation Toolset to extract the measured radiances along with all required sounding-specific ancillary information such as the measurement time, location and geometry. The data were processed through the UoL-FP retrieval algorithm where the Proxy retrieval approach is used to obtain the column-averaged dry-air mole fraction of methane (XCH4). Post-filtering and bias correction against the Total Carbon Column Observing Network is then performed, via the same methodology as used for the GOSAT-1 data."},"imageDetails":[130],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":5002,"uuid":"60e718d3f2957f742c89b2b4fc159718","short_code":"proj","title":"National Centre for Earth Observation (NCEO)","abstract":"The National Centre for Earth Observation is a partnership of scientists and institutions, from a range of disciplines, who are using data from Earth observation satellites to monitor global and regional changes in the environment and to improve understanding of the Earth system so that we can predict future environmental conditions.\r\n\r\nNCEO's Vision is to unlock the full potential of Earth observation to monitor, diagnose and predict climate and environmental changes, ensuring that these scientific advances are delivered to the wider community embedded in world class science."}],"inspireTheme":[],"topicCategory":[],"phenomena":[68633,68622,68623,68624,68625,68626,68627,66452,68628,68630,68629,68632,66456,68634,68635,68631,68637,68638,68639,68636,68641,68642,68643,68644,103077,68646,68645,68640,50542,50543,63576],"vocabularyKeywords":[],"identifier_set":[13960],"observationcollection_set":[],"responsiblepartyinfo_set":[220311,220312,220313,220305,220306,220314,220307,220308,220309,220310,220315,220316,220317],"onlineresource_set":[95814,95815,95816]},{"ob_id":46125,"uuid":"388f913cf6994f67a5ca91a195be22de","title":"GMCP: A Global Multisource Merging-and-Calibration Precipitation Dataset","abstract":"Highly accurate global gridded precipitation datasets for precipitation occurrences and volumes are essential for understanding the water, energy, and carbon cycles on Earth in the context of a changing climate. This study aimed to introduce a new fully global multisource merged precipitation dataset with high quality and resolutions of 1-hourly and 0.1° from 2000 to the present. This dataset integrated the advantages of ground gauge-, satellite-, and model-based precipitation estimates, particularly regarding precipitation occurrence, which can benefit scientific research communities and societal applications worldwide, including hydrological, climatological, meteorological, and water resource management.","creationDate":"2026-07-10T15:59:42.190548","lastUpdatedDate":"2026-07-10T16:03:33.033834","latestDataUpdateTime":"2026-07-10T15:59:42.190553","updateFrequency":"notPlanned","dataLineage":"The Global Multisource Merged and Calibration Precipitation (GMCP) dataset was generated by integrating gauge-, satellite-, and reanalysis/model-based precipitation estimates through a merging-and-calibration framework. The primary input datasets include ERA5-Land, GSMaP-MVK, and GPM IMERG-Late, which provide complementary information on precipitation occurrence and intensity. The framework combines these datasets to exploit their respective strengths while mitigating individual limitations, with a particular emphasis on improving precipitation occurrence detection. Calibration and quality-control procedures were applied during the merging process to produce a consistent global precipitation product at 0.1° spatial resolution and 1-hourly temporal resolution. The resulting dataset covers the global land surface from 2000 to the present and was generated using standardized processing workflows before being archived at the data centre.","removedDataReason":"","keywords":"precipitation,global rainfall,high resolution,satellite remote sensing","publicationState":"preview","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5177,"bboxName":"","eastBoundLongitude":180.0,"westBoundLongitude":-180.0,"southBoundLatitude":-90.0,"northBoundLatitude":90.0},"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":13273,"startTime":"2000-01-01T00:00:00","endTime":null},"resultQuality":{"ob_id":4928,"explanation":"The quality of the GMCP dataset was assessed through comprehensive validation against independent rain gauge observations and by comparison with existing global precipitation products across multiple spatial and temporal scales. Performance was evaluated using standard statistical metrics, including the correlation coefficient (CC), root-mean-square error (RMSE), and Heidke skill score (HSS), with particular emphasis on precipitation occurrence and intensity. Results demonstrate that GMCP generally outperforms the input datasets (ERA5-Land, GSMaP-MVK, and IMERG-Late) as well as widely used multisource precipitation products, including IMERG-Final, MSWEP V2, and CHIRPS, in representing precipitation variability and occurrence. Validation was conducted over diverse regions, including the contiguous United States and mainland China, indicating that the dataset provides reliable high-resolution global precipitation estimates for hydrological, climatological, meteorological, and water resou","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-07-10"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[],"projects":[],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220318,220319,220320,220321,220322,220323,220324,220325,220326,220327,220328],"onlineresource_set":[95817]},{"ob_id":46127,"uuid":"9b9f50a366a64f2099bcbe163054b24b","title":"DigiBog_Congo outputs for the impact of climate and land use","abstract":"This dataset contains the DigiBog_Congo outputs for the simulations in \"Land-use change causes rapid carbon losses in Congo Basin peatlands across climate scenarios, whereas the effects of climate change alone are uncertain\" (https://doi.org/10.1098/rtsb.2024.0486). The model code can also be found at https://doi.org/10.5281/zenodo.15319266.\r\n\r\nThis dataset was produced as part of the Natural Environment Research Council (NERC) project CongoPeat: Past, Present and Future of the Peatlands of the Central Congo Basin (grant reference: NE/R016860/1).","creationDate":"2026-07-15T13:41:03.525554","lastUpdatedDate":"2026-07-15T13:41:03","latestDataUpdateTime":"2026-07-15T13:41:03","updateFrequency":"notPlanned","dataLineage":"These data are the result of simulations using the DigiBog peatland development model. The simulations were developed and parameterised for the CongoPeat project  NERC large grant (NE/R016860/1).","removedDataReason":"","keywords":"Peat,Swamp forest,Simulation,Congo Basin","publicationState":"preview","nonGeographicFlag":true,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":null,"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":13280,"startTime":"1950-01-01T00:00:00","endTime":"2099-12-31T00:00:00"},"resultQuality":null,"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":46128,"uuid":"8d924f6a07ba44b39bd4cac110f9d6d3","short_code":"comp","title":"DigiBog_Congo","abstract":"DigiBog_Congo was developed as a model of interfluvial (rain-fed) peatlands in the Congo Basin\r\nand has successfully simulated long-term trends in peatland net carbon balance over 20,000\r\nyears. The model was structured and primarily parameterised using two years of empirical\r\ndata (litterfall, decomposition, and water-table depth) collected from two sites within an\r\ninterfluvial peatland."},"procedureCompositeProcess":null,"imageDetails":[236],"discoveryKeywords":[],"permissions":[],"projects":[{"ob_id":46093,"uuid":"740c9234c6cf48bfb825b393568b11fb","short_code":"proj","title":"CongoPeat: Past, Present and Future of the Peatlands of the Central Congo Basin","abstract":"CongoPeat was a five-year research programme led by Professor Simon Lewis of the University of Leeds and funded by Natural Environment Research Council (NERC) grant NE/R016860/1. It investigated the newly discovered peatlands of the central Congo Basin, the largest known tropical peatland complex in the world. Spanning 145,500 km² and storing an estimated 30 billion tonnes of carbon, these peatlands play a globally significant role in climate regulation and biodiversity conservation.\r\n\r\nThe project brought together researchers from six UK universities and five Congolese organisations to improve understanding of the peatlands’ past development, current condition, and future vulnerability to environmental change and human activities. Data outputs from the programme support research on the past, present, and future of the Congo Basin peatlands and provide an evidence base for conservation, sustainable management, and policy-making in the Republic of Congo and the Democratic Republic of the Congo.\r\n\r\nData are archived with the Centre for Environmental Data analysis and the Environmental Information Data Centre."}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220338,220339,220340,220341,220342,220343,220344,220345],"onlineresource_set":[95946]},{"ob_id":46129,"uuid":"92f8cee08d884d27a99397ae8a299f73","title":"Climate model simulations of decadal-scale South Pacific Convergence Zone (SPCZ) rainfall using the Intermediate General Circulation Model version 4 (IGCM4)","abstract":"This dataset contains outputs from modelling experiments using the Intermediate Global Circulation Model version 4 (IGCM4). The experiments use plausible scenarios of climate variability to simulate the processes driving South Pacific Convergence Zone (SPCZ) rainfall, and the decadal-scale SPCZ changes likely under different past and future modes of climate variability.\r\n\r\nDirectory names refer to the different experiments, in which perturbations were added onto sea surface temperatures corresponding to the: Atlantic Multidecadal Variability (A); Interdecadal Pacific Oscillation (I); and Southern Ocean (S). The numbers preceding each letter encode the size of the perturbation (see Skinner et al. for full details). For example, the directory 0A0I0S contains variables from the pre-industrial control experiment onto which no perturbations were added, while the directory 0A-3I0S contains variables from the experiment in which a three standard deviation magnitude negative IPO event was added onto the prescribed sea surface temperatures.\r\n\r\nEach experiment's directory contains the following daily data in netCDF format:\r\n- clouds.nc - Low, mid and high levels clouds\r\n- olr.nc - Outgoing longwave radiation\r\n- ppt.nc - Precipitation\r\n- tsfc.nc - Surface temperature\r\n- zg_500.nc - Geopotential height at 500 hPa\r\n- ta_250.nc - Air temperature at 250 hPa\r\n- ta_850.nc - Air temperature at 850 hPa\r\n- uwnd_250.nc - Zonal wind velocity at 250 hPa\r\n- uwnd_850.nc - Zonal wind velocity at 850 hPa\r\n- vwnd_250.nc - Meridional wind velocity at 250 hPa\r\n- vwnd_850.nc - Meridional wind velocity at 850 hPa\r\n\r\nThis dataset has two related publications:\r\n- Peaple et al. \"Ocean variability drives a millennial-scale shift in South Pacific hydroclimate.\" Communications Earth & Environment 6.1 (2025): 679. DOI: https://doi.org/10.1038/s43247-025-02676-5 (linked in the documentation section below)\r\n- Skinner et al. \"Decadal-scale drivers of South Pacific hydroclimate variability.\" Quarterly Journal of the Royal Meteorological Society (2026)\r\n\r\nThis dataset was produced as part of the Natural Environment Research Council (NERC) project Pacific Rainfall over Millennial Scales (PROMS) (grant reference: NE/W005565/1).","creationDate":"2026-07-16T09:32:50.228999","lastUpdatedDate":"2026-07-16T09:32:50","latestDataUpdateTime":"2026-07-16T09:32:50","updateFrequency":"notPlanned","dataLineage":"Data were generated using the Intermediate General Circulation Model version 4 (IGCM4), data were saved in netCDF format and then submitted to CEDA for archiving.","removedDataReason":"","keywords":"IGCM4, Climate Variability, Rainfall, Hydroclimate, Ocean, Sea Surface Temperature","publicationState":"preview","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"ongoing","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":529,"bboxName":"Global (-180 to 180)","eastBoundLongitude":180.0,"westBoundLongitude":-180.0,"southBoundLatitude":-90.0,"northBoundLatitude":90.0},"verticalExtent":null,"result_field":{"ob_id":46130,"dataPath":"/badc/deposited2026/PROMS_IGCMmodel_output","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":122700535865,"numberOfFiles":112,"fileFormat":"NetCDF"},"timePeriod":null,"resultQuality":null,"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":30088,"uuid":"3d2ed346f82d4532a4b792a5d6b61b7d","short_code":"comp","title":"Intermediate General Circulation Model version 4 (IGCM4)","abstract":"The IGCM4 (Intermediate Global Circulation Model version 4) is a global spectral primitive equation climate model whose predecessors have extensively been used in areas such as climate research, process modelling and atmospheric dynamics. The IGCM4's niche and utility lies in its speed and flexibility allied with the complexity of a primitive equation climate model. Moist processes such as clouds, evaporation, atmospheric radiation and soil moisture are simulated in the model, though in a simplified manner compared to state-of-the-art global circulation models (GCMs). IGCM4 is a parallelised model, enabling both very long integrations to be conducted and the effects of higher resolutions to be explored. It has also undergone changes such as alterations to the cloud and surface processes and the addition of gravity wave drag. These changes have resulted in a significant improvement to the IGCM's representation of the mean climate as well as its representation of stratospheric processes such as sudden stratospheric warmings. The IGCM4's physical changes and climatology are described in the paper linked in the documentation section."},"procedureCompositeProcess":null,"imageDetails":[236],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":46232,"uuid":"386d72b8c3334c3faf94528d85b7bd20","short_code":"proj","title":"Pacific Rainfall over Millennial Scales (PROMS)","abstract":"The Tropical South Pacific (TSP) contains over 5,700 islands and a vulnerable population of around 10 million people, 57% of whom live within 1 km of the coast. Freshwater availability and food security depend on rainfall generated by the South Pacific Convergence Zone (SPCZ), the largest convergence zone in the Southern Hemisphere. Variations in SPCZ location and strength drive seasonal to centennial changes in precipitation, influencing droughts, flooding, cyclone pathways, ecosystem resilience, and the ability of Pacific Island nations to meet Sustainable Development Goals. Historical evidence also links prolonged rainfall changes to island abandonment, migration, and shifts in agricultural practices.\r\n\r\nUnderstanding long-term SPCZ variability is limited by the scarcity of high-resolution palaeoclimate records. Existing precipitation proxies are geographically restricted, often discontinuous, and generally shorter than 600 years, while instrumental observations span less than a century. Current evidence suggests SPCZ rainfall responds to remote climate modes including the Interdecadal Pacific Oscillation, Atlantic Multidecadal Variability, and Southern Annular Mode, but available data are insufficient to test mechanisms or validate climate models.\r\n\r\nThis project generated a network of quantitative precipitation reconstructions spanning the SPCZ over the past 3,500 years, combined with with climate model experiments to identify how large-scale climate variability drives SPCZ rainfall. This provides fundamental new understanding of past and future hydroclimate change across the Tropical South Pacific."}],"inspireTheme":[],"topicCategory":[],"phenomena":[70656,28417,70658,70659,70660,70662,1319,1320,93995,93996,93997,93998,93999,94000,94001,94002,6583],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220347,220348,220349,220350,220351,220352,220353],"onlineresource_set":[95818]},{"ob_id":46132,"uuid":"187d44d4dafd4d53917794643765765f","title":"MIDAS Open: UK soil temperature data, v202607","abstract":"The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2025.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2025.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2026-07-17T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data collated by the Met Office and archived in the Met Office's MIDAS database. Data are extracted from a sub-set of available tables and delivered to Centre for Environmental Data Analysis (CEDA) approximately on a yearly basis.","removedDataReason":"","keywords":"Met Office, MIDAS, UK, meteorology, soil temperatures","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-07-23T11:46:04","doiPublishedTime":"2026-07-23T14:18:00.056373","removedDataTime":null,"geographicExtent":{"ob_id":18,"bboxName":"MIDAS UK table s geographic domain","eastBoundLongitude":1.74002,"westBoundLongitude":-5.54236,"southBoundLatitude":50.1172,"northBoundLatitude":60.7592},"verticalExtent":null,"result_field":{"ob_id":46141,"dataPath":"/badc/ukmo-midas-open/data/uk-soil-temperature-obs/dataset-version-202607/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":4455334601,"numberOfFiles":24347,"fileFormat":"Data are BADC-CSV formatted."},"timePeriod":{"ob_id":13288,"startTime":"1900-01-01T09:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":301,"explanation":"Data undergo quality checking by the Met Office. State of the data in the quality control process and level of data quality are indicated using version numbers and quality control flagging with the data. See documentation about how to use the quality control flagging and version numbers.\n\nThere are also some known data from commissioning trials in the data, which are given a src_id of 99999. These should be ignored by the user.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2014-09-11"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":1227,"uuid":"0c787dde18584b3293d4f55daf6ef431","short_code":"acq","title":"Acquisition Process for: UK Soil Temperature Data, Part of the Met Office Integrated Data Archive System (MIDAS)","abstract":"This acquisition is comprised of the following: INSTRUMENTS: Thermometer; PLATFORMS: NCM (National Climate Message) Station Network, HCM (Hourly Climate Messages) Station Network, DLY3208 (Daily observations from Metform 3208) Station Network, AWSHRLY (Automatic Weather Station Hourly values) Station Network;"},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"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"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":1186,"uuid":"245df050d57a500c183b88df509f5f5a","short_code":"proj","title":"Met Office Integrated Data Archive System (MIDAS)","abstract":"Since the early days of this century the Met Office has been responsible for maintaining the public memory of the weather. All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."}],"inspireTheme":[],"topicCategory":[],"phenomena":[76672,76674,76675,76678,76679,76680,76682,76690,76694,76695,76696,76697,76698,76699,76700,76701,76702,76703,76704,76705,76706,76707,76708,76709,76710,76711,76712,76713,76714,76715,76716],"vocabularyKeywords":[],"identifier_set":[13940],"observationcollection_set":[{"ob_id":26184,"uuid":"dbd451271eb04662beade68da43546e1","short_code":"coll","title":"Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)","abstract":"MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."}],"responsiblepartyinfo_set":[220354,220355,220356,220357,220358,220359,220360,220361,220362],"onlineresource_set":[95819,95820,95821,95822,95823,95824,95825,95826,95827]},{"ob_id":46133,"uuid":"c7393fdc2c974071a2efd7f8601b1bab","title":"MIDAS Open: UK mean wind data, v202607","abstract":"The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2025.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2025.\r\n\r\nFor further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK,  section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2026-07-17T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data collated by the Met Office and archived in the Met Office's MIDAS database. Data are extracted from a sub-set of available tables and delivered to Centre for Environmental Data Analysis (CEDA) approximately on a yearly basis.","removedDataReason":"","keywords":"Met Office, MIDAS, UK, meteorology, wind speed, wind direction, gust","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-07-23T11:54:30","doiPublishedTime":"2026-07-23T14:18:20.160088","removedDataTime":null,"geographicExtent":{"ob_id":17,"bboxName":"","eastBoundLongitude":1.74002,"westBoundLongitude":-8.5636,"southBoundLatitude":49.914,"northBoundLatitude":60.8562},"verticalExtent":null,"result_field":{"ob_id":46142,"dataPath":"/badc/ukmo-midas-open/data/uk-mean-wind-obs/dataset-version-202607/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":9523851052,"numberOfFiles":16155,"fileFormat":"Data are BADC-CSV formatted."},"timePeriod":{"ob_id":13287,"startTime":"1949-01-01T00:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":296,"explanation":"Data undergo quality checking by the Met Office. State of the data in the quality control process and level of data quality are indicated using version numbers and quality control flagging with the data. See documentation about how to use the quality control flagging and version numbers.\n\nThere are also some known data from commissioning trials in the data, which are given a src_id of 99999. These should be ignored by the user.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2014-09-11"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":1194,"uuid":"38b9698404d64725bc8a0b9b6b6f15ae","short_code":"acq","title":"Acquisition Process for: UK Mean Wind Data, Part of the Met Office Integrated Data Archive System (MIDAS)","abstract":"This acquisition is comprised of the following: INSTRUMENTS: Anemometer; PLATFORMS: Land SYNOP (surface synoptic observations) Station Network, HCM (Hourly Climate Messages) Station Network, AWSHRLY (Automatic Weather Station Hourly values) Station Network, DLY3208 (Daily observations from Metform 3208) Station Network, HWND6910 (Hourly WIND from Metform 6910) Station Network, HWNDAUTO (Hourly WiND from AUTOmatic recording devices) Station Network; "},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":1186,"uuid":"245df050d57a500c183b88df509f5f5a","short_code":"proj","title":"Met Office Integrated Data Archive System (MIDAS)","abstract":"Since the early days of this century the Met Office has been responsible for maintaining the public memory of the weather. All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."}],"inspireTheme":[],"topicCategory":[],"phenomena":[76672,76674,76675,76678,76679,76680,76682,76683,76686,76690,76694,76695,76696,76697,76838,76839,76840,76841,76842,76843,76844,76845,76846,76847,76848,76849,76850,76851],"vocabularyKeywords":[],"identifier_set":[13941],"observationcollection_set":[{"ob_id":26184,"uuid":"dbd451271eb04662beade68da43546e1","short_code":"coll","title":"Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)","abstract":"MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."}],"responsiblepartyinfo_set":[220363,220364,220365,220366,220367,220368,220369,220370,220371],"onlineresource_set":[95832,95833,95828,95834,95829,95830,95831,95835,95836]},{"ob_id":46134,"uuid":"d04207b551674c07801b7d4e6d883e50","title":"MIDAS Open: UK hourly weather observation data, v202607","abstract":"The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2025.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2025.\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2026-07-17T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data collated by the Met Office and archived in the Met Office's MIDAS database. 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State of the data in the quality control process and level of data quality are indicated using version numbers and quality control flagging with the data. See documentation about how to use the quality control flagging and version numbers.\n\nThere are also some known data from commissioning trials in the data, which are given a src_id of 99999. These should be ignored by the user.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2014-09-11"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":27186,"uuid":"336b071077af4805a8394f1402c5c26b","short_code":"acq","title":"Acquisition Process for: UK Hourly Weather Observation Data, Part of the Met Office Integrated Data Archive System (MIDAS) Open version (excluded METARS)","abstract":"This acquisition is comprised of the following: INSTRUMENTS: Thermometer, Visiometer, Station Observer, Sunshine Recorder, Raingauge, Cloud Recorder, Snow Depth Sensor, Present (and Past) Weather Sensor; PLATFORMS: Land SYNOP (surface synoptic observations) Station Network, METAR (MEteorological Terminal Aviation Routine Weather Report) Station Network, NCM (National Climate Message) Station Network, DLY3208 (Daily observations from Metform 3208) Station Network, AWSHRLY (Automatic Weather Station Hourly values) Station Network, HSUN3445 (Hourly values of SUNshine duration from Metform 3445) Station Network;"},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":1186,"uuid":"245df050d57a500c183b88df509f5f5a","short_code":"proj","title":"Met Office Integrated Data Archive System (MIDAS)","abstract":"Since the early days of this century the Met Office has been responsible for maintaining the public memory of the weather. All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."}],"inspireTheme":[],"topicCategory":[],"phenomena":[76800,76801,76802,76803,76804,76805,76806,76807,76808,76809,76810,76811,76812,76813,76814,76815,76816,76817,76818,76819,76820,76821,76822,76823,76824,76825,76826,76827,76828,76829,76830,76831,76832,76833,76834,76835,76836,76837,76672,76674,76675,76679,76680,76682,76690,76694,76695,76696,76697,76709,76742,76743,76744,76745,76746,76747,76748,76749,76750,76751,76752,76753,76754,76755,76756,76757,76758,76759,76760,76761,76762,76763,76764,76765,76766,76767,76768,76769,76770,76771,76772,76773,76774,76775,76776,76777,76778,76779,76780,76781,76782,76783,76784,76785,76786,76787,76788,76789,76790,76791,76792,76793,76794,76795,76796,76797,76798,76799],"vocabularyKeywords":[],"identifier_set":[13944],"observationcollection_set":[{"ob_id":26184,"uuid":"dbd451271eb04662beade68da43546e1","short_code":"coll","title":"Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)","abstract":"MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."}],"responsiblepartyinfo_set":[220372,220373,220374,220375,220376,220377,220378,220379,220380],"onlineresource_set":[95840,95841,95845,95837,95838,95842,95839,95843,95844]},{"ob_id":46135,"uuid":"bfaf1bbf650a4a48ae33e4424b66c66d","title":"MIDAS Open: UK hourly solar radiation data, v202607","abstract":"The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light. \r\n\r\nFor details about the different measurements made and the limited number of sites making them please see the MIDAS Solar Irradiance table linked to in the online resources section of this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2025.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2025.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2026-07-17T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data collated by the Met Office and archived in the Met Office's MIDAS database. 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All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."}],"inspireTheme":[],"topicCategory":[],"phenomena":[76672,76673,76674,76675,76676,76677,76678,76679,76680,76681,76682,76683,76684,76685,76686,76687,76688,76689,76690,76691,76692,76693,76694,76695,76696,76697],"vocabularyKeywords":[],"identifier_set":[13942],"observationcollection_set":[{"ob_id":26184,"uuid":"dbd451271eb04662beade68da43546e1","short_code":"coll","title":"Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)","abstract":"MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."}],"responsiblepartyinfo_set":[220381,220382,220383,220384,220385,220386,220387,220388,220389],"onlineresource_set":[95846,95847,95848,95850,95851,95852,95853,95855,95849,95854]},{"ob_id":46136,"uuid":"40577fca24d1483eb1fc9d6d6648e465","title":"MIDAS Open: UK hourly rainfall data, v202607","abstract":"The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2025.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2026-07-17T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data collated by the Met Office and archived in the Met Office's MIDAS database. 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State of the data in the quality control process and level of data quality are indicated using version numbers and quality control flagging with the data. See documentation about how to use the quality control flagging and version numbers.\n\nThere are also some known data from commissioning trials in the data, which are given a src_id of 99999. 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All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."}],"inspireTheme":[],"topicCategory":[],"phenomena":[76672,76674,76675,76740,76741,76678,76679,76680,76682,76683,76686,76690,76694,76695,76696,76697,76717,76718,76721],"vocabularyKeywords":[],"identifier_set":[13937],"observationcollection_set":[{"ob_id":26184,"uuid":"dbd451271eb04662beade68da43546e1","short_code":"coll","title":"Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)","abstract":"MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."}],"responsiblepartyinfo_set":[220390,220391,220392,220393,220394,220395,220396,220397,220398],"onlineresource_set":[95860,95861,95862,95856,95857,95858,95859,95863,95864]},{"ob_id":46137,"uuid":"5a99fe8bd1364e2f85f9fde21e494ae1","title":"MIDAS Open: UK daily weather observation data, v202607","abstract":"The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1887 to 2025. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2025.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2026-07-17T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data collated by the Met Office and archived in the Met Office's MIDAS database. Data are extracted from a sub-set of available tables and delivered to Centre for Environmental Data Analysis (CEDA) approximately on a yearly basis.","removedDataReason":"","keywords":"Met Office, MIDAS, UK, meteorology, daily, diurnal, monthly","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-07-23T13:43:46","doiPublishedTime":"2026-07-23T14:18:49.557690","removedDataTime":null,"geographicExtent":{"ob_id":18,"bboxName":"MIDAS UK table s geographic domain","eastBoundLongitude":1.74002,"westBoundLongitude":-5.54236,"southBoundLatitude":50.1172,"northBoundLatitude":60.7592},"verticalExtent":null,"result_field":{"ob_id":46146,"dataPath":"/badc/ukmo-midas-open/data/uk-daily-weather-obs/dataset-version-202607/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":3267549207,"numberOfFiles":52815,"fileFormat":"Data are BADC-CSV formatted."},"timePeriod":{"ob_id":13283,"startTime":"1887-01-01T00:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":306,"explanation":"Data undergo quality checking by the Met Office. 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The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."}],"inspireTheme":[],"topicCategory":[],"phenomena":[76672,76674,76675,76678,76679,76680,76808,76682,76690,76694,76695,76696,76697,76852,76853,76854,76855,76856,76857,76858,76859,76860,76861,76862,76863,76864,76865,76866,76867,76868,76869,76870,76871,76872,76873,76874,76875,76876],"vocabularyKeywords":[],"identifier_set":[13943],"observationcollection_set":[{"ob_id":26184,"uuid":"dbd451271eb04662beade68da43546e1","short_code":"coll","title":"Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)","abstract":"MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."}],"responsiblepartyinfo_set":[220399,220400,220401,220402,220403,220404,220405,220406,220407],"onlineresource_set":[95865,95866,95867,95871,95868,95869,95872,95870,95873]},{"ob_id":46138,"uuid":"1854bb17ec454841b04e243a1352f25a","title":"MIDAS Open: UK daily temperature data, v202607","abstract":"The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2025. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2025.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2026-07-17T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data collated by the Met Office and archived in the Met Office's MIDAS database. Data are extracted from a sub-set of available tables and delivered to Centre for Environmental Data Analysis (CEDA) approximately on a yearly basis.","removedDataReason":"","keywords":"Met Office, MIDAS, UK, meteorology, temperature, diurnal, daily, monthly","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-07-23T13:44:58","doiPublishedTime":"2026-07-23T14:17:44.749557","removedDataTime":null,"geographicExtent":{"ob_id":18,"bboxName":"MIDAS UK table s geographic domain","eastBoundLongitude":1.74002,"westBoundLongitude":-5.54236,"southBoundLatitude":50.1172,"northBoundLatitude":60.7592},"verticalExtent":null,"result_field":{"ob_id":46144,"dataPath":"/badc/ukmo-midas-open/data/uk-daily-temperature-obs/dataset-version-202607/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":2283367894,"numberOfFiles":65997,"fileFormat":"Data are BADC-CSV formatted."},"timePeriod":{"ob_id":13282,"startTime":"1853-01-01T00:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":305,"explanation":"Data undergo quality checking by the Met Office. State of the data in the quality control process and level of data quality are indicated using version numbers and quality control flagging with the data. See documentation about how to use the quality control flagging and version numbers.\n\nThere are also some known data from commissioning trials in the data, which are given a src_id of 99999. These should be ignored by the user.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2014-09-11"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":1243,"uuid":"93916103ebf54c5fad1e24fee0255e91","short_code":"acq","title":"Acquisition Process for: UK Daily Temperature Data, Part of the Met Office Integrated Data Archive System (MIDAS)","abstract":"This acquisition is comprised of the following: INSTRUMENTS: Thermometer; PLATFORMS: NCM (National Climate Message) Station Network, DLY3208 (Daily observations from Metform 3208) Station Network, AWSDLY (Automatic Weather Station Daily values) Station Network; "},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":1186,"uuid":"245df050d57a500c183b88df509f5f5a","short_code":"proj","title":"Met Office Integrated Data Archive System (MIDAS)","abstract":"Since the early days of this century the Met Office has been responsible for maintaining the public memory of the weather. All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."}],"inspireTheme":[],"topicCategory":[],"phenomena":[76672,76736,76674,76675,76737,76738,76678,76739,76680,76690,76694,76695,76696,76697,76724,76725,76726,76727,76728,76729,76730,76731,76732,76733,76734,76735],"vocabularyKeywords":[],"identifier_set":[13939],"observationcollection_set":[{"ob_id":26184,"uuid":"dbd451271eb04662beade68da43546e1","short_code":"coll","title":"Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)","abstract":"MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."}],"responsiblepartyinfo_set":[220408,220409,220410,220411,220412,220413,220414,220415,220416],"onlineresource_set":[95874,95875,95877,95876,95878,95879,95880,95881,95882]},{"ob_id":46139,"uuid":"88b5bdf6131e4c1cb7acb8bde984deda","title":"MIDAS Open: UK daily rainfall data, v202607","abstract":"The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2025. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version (202507) of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2025.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2026-07-17T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data collated by the Met Office and archived in the Met Office's MIDAS database. Data are extracted from a sub-set of available tables and delivered to Centre for Environmental Data Analysis (CEDA) approximately on a yearly basis.","removedDataReason":"","keywords":"Met Office, MIDAS, UK, meteorology, rainfall, diurnal, daily, monthly","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-07-23T13:19:06","doiPublishedTime":"2026-07-23T14:17:17.539094","removedDataTime":null,"geographicExtent":{"ob_id":18,"bboxName":"MIDAS UK table s geographic domain","eastBoundLongitude":1.74002,"westBoundLongitude":-5.54236,"southBoundLatitude":50.1172,"northBoundLatitude":60.7592},"verticalExtent":null,"result_field":{"ob_id":46147,"dataPath":"/badc/ukmo-midas-open/data/uk-daily-rain-obs/dataset-version-202607/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":9618307918,"numberOfFiles":477047,"fileFormat":"Data are BADC-CSV formatted"},"timePeriod":{"ob_id":13281,"startTime":"1853-01-02T00:00:00","endTime":"2025-12-31T23:59:59"},"resultQuality":{"ob_id":297,"explanation":"Data undergo quality checking by the Met Office. State of the data in the quality control process and level of data quality are indicated using version numbers and quality control flagging with the data. See documentation about how to use the quality control flagging and version numbers.\n\nThere are also some known data from commissioning trials in the data, which are given a src_id of 99999. These should be ignored by the user.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2014-09-11"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":27187,"uuid":"037f3eff9db941a583b252e800a94979","short_code":"acq","title":"Acquisition Process for: UK Daily Rainfall Data, Part of the Met Office Integrated Data Archive System (MIDAS) Open  - excludes WADRAIN and WAMRAIN","abstract":"This acquisition is comprised of the following: INSTRUMENTS: Raingauge; PLATFORMS: DLY3208 (Daily observations from Metform 3208) Station Network, SSER (Solid State Event Recorder) Station Network, WADRAIN (Water Authorities Daily RAINfall) Station Network, WAMRAIN (Water Authorities Monthly RAINfall value) Station Network, NCM (National Climate Message) Station Network, AWSDLY (Automatic Weather Station Daily values) Station Network;"},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":1186,"uuid":"245df050d57a500c183b88df509f5f5a","short_code":"proj","title":"Met Office Integrated Data Archive System (MIDAS)","abstract":"Since the early days of this century the Met Office has been responsible for maintaining the public memory of the weather. All meteorological observations made in the UK and over neighbouring sea areas have been carefully recorded and placed in an archive where they may be accessed today by those with an interest in the weather and where they will also be available to those in future generations. The current climate database is MIDAS (Met Office Integrated Data Archive System) which has a relational structure. The MIDAS database contains the following general types of meteorological data: surface observations over land areas of the UK as far back as the digital record extends, a selection of global surface observations for the last 20 years, global surface marine observations from national and international sources as far back as the digital record extends, radiosonde observations over the UK, and at overseas stations operated by the Met Office, as far back as the digital record extends, a selection of global radiosonde observations for the last 10 years."}],"inspireTheme":[],"topicCategory":[],"phenomena":[76672,76674,76675,76678,76679,76680,76682,76690,76694,76695,76696,76697,76717,76718,76719,76720,76721,76722,76723],"vocabularyKeywords":[],"identifier_set":[13938],"observationcollection_set":[{"ob_id":26184,"uuid":"dbd451271eb04662beade68da43546e1","short_code":"coll","title":"Met Office MIDAS Open: UK Land Surface Stations Data (1853-current)","abstract":"MIDAS Open is the open data version of the Met Office Integrated Data Archive System (MIDAS) containing land surface station data starting from 1853 and ending at the of the previous complete year. This collection comprises of hourly and daily weather measurements and observations of parameters relating to temperature, rainfall, sunshine, radiation, wind and weather observations such as present weather codes, cloud cover, snow etc.\r\n\r\nThe collection contains land surface observations data from those stations where the data have been designated as public sector information. Prior to version v202407 this consisted of stations operated by the Met Office only, but from version v202407, daily and hourly rainfall observations from stations with gauges owned by the Environment Agency (EA), Scottish Environment Protection Agency (SEPA) and Natural Resources Wales (NRW) have also been included in the collection. Since then, stations owned by other third-party organisations where approval for inclusion has been reached have also been added to the product.\r\n\r\nAll of these data are provided under an Open Government Licence. \r\n\r\nThe current collection contains the following proportions of the fuller MIDAS dataset collection:\r\n\r\n96% of daily temperature observations\r\n96% of daily weather observations\r\n92% of hourly weather observations\r\n94% of daily rainfall observations\r\n96% of hourly rainfall observations\r\n98% of soil temperature observations\r\n96% of solar radiation observations\r\n93% of mean wind observations\r\n\r\nDaily rainfall: Versions up until MIDAS Open v202407 only have about 13% coverage of observations. In version v202407, the coverage was increased to 58% with the inclusion of the third-party hydrological agency stations. In version v202507, the coverage was increased further to 94% with the inclusion of historic closed stations.\r\n\r\nThe fuller \"Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations Data (1853-current)\" collection is made available for academic use via the Centre for Environmental Data Analysis.\r\n\r\nThe MIDAS Open collection is updated annually in a delayed mode to ensure that data acquisition and quality control procedures have all been completed. Quality controlled (qc-version-1) and non-quality controlled (qc-version-0) data are available from 1853 where available, although this will vary by station depending on the operation period of the station. The collection includes stations which are currently operational as well as stations which were operational in the past and have since closed.\r\n\r\nEach version of the dataset will include data up until the end of the previous complete year relative to the year in the version number of the dataset (e.g. v202407 included data up until the end of 2023).\r\n\r\nNote: This collection does not supersede the full MIDAS collection which is also archived at CEDA."}],"responsiblepartyinfo_set":[220417,220418,220419,220420,220421,220422,220423,220424,220425],"onlineresource_set":[95883,95884,95885,95886,95887,95888,95889,95890,95891]},{"ob_id":46151,"uuid":"43238f63ed684fe489b7763200cb584d","title":"Bias-corrected 1 km hourly UKCP18 Local precipitation and air temperature, Great Britain, 1980-2080","abstract":"Bias-corrected hourly precipitation and mean air temperature derived from the 5km British National Grid version of the UK Climate Projections 2018 Local simulations under Representative Concentration Pathway 8.5 (RCP8.5). The source simulations were originally run at 2.2km resolution. The dataset includes all 16 ensemble members.\r\nThe data cover Great Britain at 1km resolution on the British National Grid and are limited to grid cells where the model and relevant observational reference data overlap. Temporal coverage is December 1980 to November 2080 at hourly resolution. The cumulative distribution function transform (CDFt) method was trained over December 1990 to November 2010 using CEH-GEAR1hr v2 for precipitation and HadUK-Grid version 1.3.1 for temperature. Data are supplied as monthly NetCDF-4 files. The dataset is intended for hydroclimatic impact assessments and related climate-risk studies.","creationDate":"2026-07-17T17:24:48.602706","lastUpdatedDate":"2026-07-17T17:27:33.515039","latestDataUpdateTime":"2026-07-17T17:24:48.602712","updateFrequency":"notPlanned","dataLineage":"The source data are the UKCP18 Local (2.2 km) projections produced by the Met Office Hadley Centre under RCP8.5 and regridded by the Met Office to a 5 km British National Grid. The 5 km fields were remapped to the 1 km grids of the reference datasets: CEH-GEAR1hr (hourly precipitation; Newcastle University and UKCEH) and HadUK-Grid v1.3.1 (air temperature; Met Office; hourly values derived from daily maximum and minimum temperature). Four bias correction methods (quantile mapping, ISIMIP3BASD, scaled distribution mapping, CDFt) were screened using ensemble member 01 over two 10 x 10 grid-cell blocks in the Scottish Highlands and East Anglia. CDFt performed most consistently and was applied to hourly precipitation and temperature for all 16 members over the full domain, trained over December 1990 to November 2010. Processing used the ibicus Python package on the JASMIN facility. Full details are given in Zha, He and Lowe (Journal of Hydrology, submitted).","removedDataReason":"","keywords":"bias correction,UKCP18 Local,convection-permitting model,hourly precipitation,air temperature,climate projections,RCP8.5,Great Britain,CDFt","publicationState":"preview","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5185,"bboxName":"","eastBoundLongitude":2.66,"westBoundLongitude":-9.12,"southBoundLatitude":49.81,"northBoundLatitude":60.54},"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":13291,"startTime":"1980-12-01T00:00:00","endTime":"2080-11-30T00:00:00"},"resultQuality":null,"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[],"projects":[{"ob_id":46152,"uuid":"70b177eab95f4355aa1895ddc7e51acd","short_code":"proj","title":"Open Evaluation of Climate-resilient Interventions for Land Management, Soil Health and Net Zero","abstract":"OpenLAND (Open Evaluation of Climate-Resilient Interventions for Land Management, Soil Health and Net Zero) is a three-year UKRI-BBSRC project led by the University of East Anglia under the Transforming Land Use for Net Zero, Nature and People (LUNZ) programme. It builds a UK-wide, spatially explicit modelling framework to evaluate net zero pathways for land management, soil health and biodiversity. This dataset provides bias-corrected climate inputs for hydroclimatic modelling in the project."}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220426,220427,220428,220429,220430,220431,220432,220433,220434],"onlineresource_set":[]},{"ob_id":46158,"uuid":"57640822f34e43908acbe97d6bbc4c33","title":"High speed camera images for tracking microplastic fibre transport in a boundary layer wind tunnel (2024)","abstract":"The following files contain images extracted from recorded videos of particle tracking velocimetry in wind tunnel experiments examining the interaction between sand and airflow. These experiments are part of the NERC funded project 'Microplastic Entrainment, Transport and Fragmentation, in Atmospheric Boundary-layer Flows'. \r\n\r\nThe directory contains files with .tif images corresponding to the experiments with sand particles, under air velocities of 6  and 10 metres per second. The videos were recorded with a Dimax HD high speed camera and lasted 4.1 seconds.  Frames were captured with a 200 micro seconds exposure rate of 1550 per second, through a Nikon Micro Nikkor 200 mm F4 objective lens in 12 bit grayscale with a pixel resolution of 1920 by 1080.  The rectangular viewing area of each image spanned a physical distance of 62 mm in width, parallel to the mean wind flow, and 35 mm in height. The experiments were run from Jun 24 to July 5th, 2024, in the Trent Environmental Wind Tunnel (TEWT) Facilities, at Trent University, Ontario, Canada.\r\n\r\nThis dataset was generated as part of NERC grant: NE/X00015X/1:Microplastic entrainment, transport and fragmentation in atmospheric boundary-layer flows\r\n\r\n\r\nThe folder names correspond to the following structure: Test number _ test repetition (R1, R2, R3) _ experimental tunnel air velocity _ particle release distance from the camera (Upwind_Fibre_Position_ …). \r\n\r\nThe image names within each folder correspond to the following structure: Test number _ particle release distance from the camera (L0cm, L25cm, L60cm, L110cm, L200cm) _ test repetition (R1, R2, R3) _ consecutive image number (0001, …, 6155).","creationDate":"2026-07-28T12:59:46.967045","lastUpdatedDate":"2026-07-28T13:03:31","latestDataUpdateTime":"2026-07-28T12:59:46","updateFrequency":"notPlanned","dataLineage":"Videos were recorded with a Dimax HD high speed camera and lasted 4.1 seconds. Frames were captured with a 200 micro seconds exposure rate of 1550 per second, through a Nikon Micro Nikkor 200 mm F4 objective lens in 12 bit grayscale with a pixel resolution of 1920 by 1080. Data provided by the project team to CEDA for archival.","removedDataReason":"","keywords":"Wind tunnel,Particle tracking velocimetry,Sand","publicationState":"preview","nonGeographicFlag":true,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":null,"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":13317,"startTime":"2024-06-24T00:00:00","endTime":"2024-07-05T23:59:59"},"resultQuality":{"ob_id":4933,"explanation":"N/A","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-07-28"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":46188,"uuid":"236d8423f72e46c7b8cb96fdc69ab025","short_code":"acq","title":"Acquisition for wind tunnel images of sand transport experiments","abstract":"Acquisition for wind tunnel images of sand transport experiments"},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[236],"discoveryKeywords":[],"permissions":[],"projects":[{"ob_id":43609,"uuid":"f3eba22d26bd4a5aad91503a96d9478c","short_code":"proj","title":"NE/X00015X/1:Microplastic entrainment, transport and fragmentation in atmospheric boundary-layer flows","abstract":"The overall aim of this research is to understand the processes of microplastic entrainment and transport by wind and how these processes affect the material properties of microplastics. The knowledge gained will inform models for predicting land-atmosphere microplastic flux and distribution.\r\n\r\nNERC grant: NE/X00015X/1:Microplastic entrainment, transport and fragmentation in atmospheric boundary-layer flows"}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220458,220459,220460,220461,220462,220463,220464,220465,220466,220467,220468,220469,220470,220471,220472],"onlineresource_set":[]},{"ob_id":46160,"uuid":"2de684c1211e4d89a5deba150eeb3689","title":"Model output data to support Evaluation of a simplified double-moment aerosol scheme (SOL/INSOL) using satellite, airborne and ground based observations over the UK.","abstract":"This dataset contains the [expand the acronym here]UM-RAL3.3 model output needed to reproduce figures and tables in \"Evaluation of a simplified double-moment aerosol scheme (SOL/INSOL) using satellite, airborne and ground based observations over the UK\" by Angela Mynard, Anthony C Jones, Joseph Carton-Kelly, Paul Field, Steven J Able and Florent Fabien Malavelle, submitted to Geoscientific Model Development, July 2026. This data supports reproduction of the model aspect of the figures and tables only. See paper for observational data sources.\r\n\r\nThe data consist of the main case study, sensitivity experiments and forecast lead time experiments.","creationDate":"2026-07-29T15:11:22.634209","lastUpdatedDate":"2026-07-29T14:57:13","latestDataUpdateTime":"2026-07-29T14:57:13","updateFrequency":"","dataLineage":"Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"ongoing","dataPublishedTime":"2026-07-30T11:28:53","doiPublishedTime":"2026-07-30T11:29:12.939151","removedDataTime":null,"geographicExtent":{"ob_id":5187,"bboxName":"","eastBoundLongitude":3.9840284160293815,"westBoundLongitude":-10.125157090145867,"southBoundLatitude":48.47571743418529,"northBoundLatitude":59.48854782900217},"verticalExtent":null,"result_field":{"ob_id":46161,"dataPath":"/badc/deposited2026/aerosol_solinsol_paper_data","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":94081745,"numberOfFiles":14,"fileFormat":"NetCDF"},"timePeriod":{"ob_id":13296,"startTime":"2020-11-26T13:00:00","endTime":"2022-03-24T13:00:00"},"resultQuality":{"ob_id":4934,"explanation":"No data quality conformance information was supplied","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-07-29"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":46162,"uuid":"2f5ac3714bb94039bef59e69403bd952","short_code":"comp","title":"Computation for UM-RAL3.3 double-moment aerosol scheme (SOL/INSOL)","abstract":"Figures in the paper were produced using Python (3.10) and Iris scientific analysis software (3.11)."},"procedureCompositeProcess":null,"imageDetails":[69],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[],"inspireTheme":[],"topicCategory":[],"phenomena":[102401,102920,102921,102922,102923,102924,102925,102926,102927,102928,102929,102930,102931,102932,102933,102934,102935,102936,102937,102938,102939,102940,102941,102942,102943,102944,102945,102946,102947,102948,102949,102950,102951,102952,102953,102954,102955,102956,102957,102958,102959,102960,102961,102962,102963,102964,102965,102966,102967,102968,102969,102970,102971,102972,102973,102974,102975,102976,102977,102978,62531,102979,102980,102981,102982,102983,102984,102985,102986,102987,102988,102989,102990,102991,102992,102993,102994,102995,102996,102997,102998,102999,54873,54874,103000,103001,103002,103003,103004,103005,103006,103007,103008,103009,103010,103011,103012,103013,103014,103015,103016,103017,103018,103019,103020,103021,103022,103023,103024,103025,103026,103027,103028,103029,103030,103031,103032,103033,103034,103035,103036,103037,103038,103040,103041,103042,103043,103044,103045,103046,103047,103048,103049,103050,103051,103052,103053,103054,103055,103056,103057,103058,103059,103060,103061,54875,103062,103063,103064,103065,59037,59038,103066,103067,103068,103069,103070,103071,103072,103073,103074,103075,103076,21677,21678,67761,103039,11573,55648,62353,21990,51186,51187,22005],"vocabularyKeywords":[],"identifier_set":[13946],"observationcollection_set":[],"responsiblepartyinfo_set":[220479,220480,220481,220482,220483,220484,220485,220486],"onlineresource_set":[]},{"ob_id":46171,"uuid":"eb6fd71dbfce413c94d68821df341e0d","title":"Hydroacoustic monitoring of bedload and suspended sediment sampling of the West Rapti river, Nepal","abstract":"This dataset contains amplitude and frequency metrics calculated from 30s hydrophone recordings in the West Rapti river in the monsoon season of 2024, alongside water level data supplied by the department of Hydrology and Meteorology. Recordings are made at various amplification gains, which are specified within datasets. There are also suspended sediment concentration data, which was measured daily during the 2024 monsoon.","creationDate":"2026-08-04T13:28:00.699938","lastUpdatedDate":"2026-08-04T13:46:14.834199","latestDataUpdateTime":"2026-08-04T13:28:00.699943","updateFrequency":"notPlanned","dataLineage":"Hydrophones recorded 30s wav files every 15-20 minutes at various gain amplifications, specified in dataset files. Sample rate is 48 kHz. Data was processed in Python using scikit-maad to calculate RMS amplitude and spectral centroid of the recordings. Suspended sediment was measured manually by filtering techniques at 12:00 each day.","removedDataReason":"","keywords":"Hydrophone,Spectral Centroid,RMS Amplitude,Suspended sediment concentration","publicationState":"preview","nonGeographicFlag":true,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":null,"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":13305,"startTime":"2024-04-22T00:00:00","endTime":"2024-11-04T00:00:00"},"resultQuality":{"ob_id":4936,"explanation":"Amplitude and spectral centroid calculated using conventional relationships from frequency-filtered data to exclude frequencies below 2 kHz, otherwise supplied as-is. Where possible, the datasets contain % of clipped files, determined from clipdetect package. Suspended sediment was dried thoroughly in a lab oven prior to weighing with a mass balance of 0.0001 g precision.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-08-04"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":46173,"uuid":"e1d75f0d02524f76bbd8bdc5c146660b","short_code":"acq","title":"Acquisition for: West_Rapti_2024_Hydrophone","abstract":""},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[],"projects":[{"ob_id":46172,"uuid":"417bfd527140407e8960d40fc3bf670c","short_code":"proj","title":"Hydroacoustic monitoring of bedload and suspended sediment sampling of the West Rapti river, Nepal","abstract":"Here we present an acoustic dataset from the Bagasoti gauging station at West Rapti river in Nepal over the duration of the 2024 summer monsoon season. Two Aquarian hydrophones were deployed in the river bank to document the onset, evolution and decline of bedload transport, and to compare this to daily suspended sediment concentration measurements through the season."}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220506,220507,220508,220509,220510,220511,220512,220513],"onlineresource_set":[95903,95904]},{"ob_id":46178,"uuid":"cf49a96f67374c69b23702e0cc4c7c0d","title":"ESA Lakes Climate Change Initiative (Lakes_cci): harmonised gap-filled LSWT-LIC, Version 3.0","abstract":"This dataset contains the harmonised, gap-filled version of European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) version 3.0 dataset for two of the Lakes Essential Climate Variable (ECV) Products: Lake Surface Water temperature (LSWT) and Lake Ice Cover (LIC).\r\nThe dataset covers the period 2000–2023 and includes more than 2,000 inland water bodies and \r\nBecause the gap-filled LSWT and LIC products are harmonised, they are fully consistent. Therefore, no water temperature is reported for grid cells classified as ice-covered. \r\nThe list of lakes for which the products are available is provided as a CSV file in the catalogue. The lake mask for each lake is provided in every data file the corresponding data file.\r\nThis dataset was produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project. For more information about the Lakes_cci please visit the project website.","creationDate":"2026-08-06T11:27:01.870966","lastUpdatedDate":"2026-08-06T19:53:32.314161","latestDataUpdateTime":"2026-08-06T11:27:01.870974","updateFrequency":"notPlanned","dataLineage":"Data were produced by the LIC and LSWT ESA CCI (Lakes_cci) project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"ESA,CCI,Lakes,consistent ECV,gap-filling,temperature,ice","publicationState":"working","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5188,"bboxName":"","eastBoundLongitude":180.0,"westBoundLongitude":-180.0,"southBoundLatitude":-90.0,"northBoundLatitude":90.0},"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":13315,"startTime":"2000-01-01T00:00:00","endTime":"2023-12-31T00:00:00"},"resultQuality":null,"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[],"projects":[{"ob_id":46179,"uuid":"c848582b942d4a8ba493733e9d002241","short_code":"proj","title":"ESA Lakes Climate Change Initiative (Lakes_cci)","abstract":""}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220522,220523,220524,220525,220526,220527,220534,220535,220536,220537,220538,220539],"onlineresource_set":[]},{"ob_id":46180,"uuid":"cb437b7efe664348b8aab3b6a86e035c","title":"SPLICE project: Spectral information for oak and hazel, Alice Holt Forest, Hampshire, UK, July 2023","abstract":"This dataset contains spectral information collected within the Alice Holt Forest. This work was conducted as part of a wider field campaign examining photosynthesis and forest structure across the Alice Holt site.\r\n\r\nData were collected between from 18th-20th July 2023. Measurements were taken from each leaf only during the day.\r\n\r\nFiles are provided following the naming convention H#_B#_C#_S.000X.sig. In this, T’ or ‘H’ shows the tree or understory (Hazel) measurement, and the platform, branch, and leaf-cluster are given (#). The final number denotes measurement, with 5 (X) measurements taken from each cluster, each from a different leaf in the middle avoiding the midvein and any damaged areas. Measurements were not taken for all branches or leaf-clusters, as some branches were taken down by wind between labelling and the measurement period.\r\n\r\nRaw data are provided in 128 .sig files. Raw data were processed in python using Specdal and FieldSpecUtils packages. First, regions of spectrometer overlap (1000 and 1800 nm) were averaged and spliced. Next, spectra were linearly interpolated to correspond to wavelengths of 1nm spacing. Then, the relative reflectance spectra were multiplied by the white reference panel’s known laboratory calibrated reflectance profile to yield absolute reflectance. The processed data are provided in Alice_Holt_Hyperspectral.csv.","creationDate":"2026-08-06T16:35:23.087749","lastUpdatedDate":"2026-08-06T13:09:31","latestDataUpdateTime":"2026-08-06T13:09:31","updateFrequency":"","dataLineage":"Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"SPLICE, Spectra, Trees, Oak, Hazel, Hampshire","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-08-13T10:11:13","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5189,"bboxName":"Alice Holt Forrest Hampshire","eastBoundLongitude":-0.86056,"westBoundLongitude":-0.86056,"southBoundLatitude":51.15412,"northBoundLatitude":51.15412},"verticalExtent":null,"result_field":{"ob_id":46181,"dataPath":"/neodc/splice/data/SPLICE_Field_Data_Spectrometer","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":11028550,"numberOfFiles":133,"fileFormat":"This dataset contains 128 .sig files and one .csv file, with a total size of 10 MB.\r\nFile Structure: The Alice_Holt_Hyperspectral.csv is organized by wavelength (nm), and sample (as given in the\r\nfilename"},"timePeriod":{"ob_id":13314,"startTime":"2023-07-18T00:00:00","endTime":"2023-07-20T00:00:00"},"resultQuality":{"ob_id":4937,"explanation":"The data was validated by the NCEO project team at the University of Reading","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-08-06"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":{"ob_id":46185,"uuid":"767060ede1084e4986e4a96151d94fe6","short_code":"cmppr","title":"SPLICE: Spectral information for oak and hazel, Alice Holt Forest, Hampshire, UK, July 2023","abstract":"Samples were taken from a tower set up within the forest with six platforms (P), at two-meter\r\nintervals (number corresponding to platform number, not height above ground level). The tower\r\nwas set up such that it was between two oak trees (T), with several branches (B) overhanging the\r\nplatforms. Each branch was split into leaf clusters (C) where leaves were sampled. The hazel\r\nunderstory was also sampled in the same manner.\r\n\r\n\r\nThese data were collected with a HR-1024i field spectrometer with leaf clip attachment and\r\nactive light source (Spectra Vista Corp, USA). The HR-1024i spectrometer is comprised of three\r\ndispersion grating spectrometers with overlapping wavelength ranges: Very Near Infrared (VNIR),\r\n1.5 nm sampling interval, 350–1000 nm range; Short Wavelength Infrared 1 (SWIR1), 3.8 nm\r\nsampling interval, 1000–1890 nm range; SWIR2, 2.5 nm sampling interval, 1890–2500 nm range.\r\nThe leaf clip includes an inbuilt Spectralon white reference standard which was used to take a\r\nwhite reference between each leaf cluster. A dark reference is taken automatically by the\r\ninstrument with every measurement.\r\n\r\nRaw data is provided in 128 .sig files. Raw data was processed in python using Specdal and\r\nFieldSpecUtils packages. First, regions of spectrometer overlap (1000 and 1800 nm) were\r\naveraged and spliced. Next, spectra were linearly interpolated to correspond to wavelengths of\r\n1nm spacing. Then, the relative reflectance spectra were multiplied by the white reference\r\npanel’s known laboratory calibrated reflectance profile to yield absolute reflectance. The\r\nprocessed data are provided in Alice_Holt_Hyperspectral.csv."},"imageDetails":[2],"discoveryKeywords":[{"ob_id":1138,"name":"NDGO0003"}],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":45716,"uuid":"dd612cd174eb42af8045037c5a07ab3d","short_code":"proj","title":"Structure, Photosynthesis and Light In Canopy Environments (SPLICE)","abstract":"The SPLICE project (Structure, Photosynthesis and Light In Canopy Environments) sought to improve our understanding of global photosynthesis and hence our ability to model climate change, by considering the way in which the three-dimensional structure of plants interacts with light and how this in turn impacts on the uptake of carbon. It employed state-of-the-art techniques to measure the three dimensional structure and photosynthesis of forests and construct detailed computer simulations to create a virtual laboratory that we can use to improve simulations from climate models."}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220541,220542,220543,220544,220545,220546,220551,220552,220553,220554],"onlineresource_set":[]},{"ob_id":46190,"uuid":"8f21a917f4954787874c039a55cd310a","title":"GEMINI-UK EM27-SUN greenhouse gas column concentration data","abstract":"The Greenhouse gas Emissions Monitoring network to Inform Net-zero Initiatives for the UK (GEMINI-UK) is a network of ten sun-tracking Fourier transform spectrometers hosted at sites around the UK. They provide column-averaged concentrations of the greenhouse gases carbon dioxide and methane (as well as carbon monoxide and water vapour) on days where there is a clear, cloud-free line of sight to the Sun for at least part of the day.\r\n\r\nThe first site, at the Weybourne Atmospheric Observatory, began operation in September 2024, and a number of other sites have been added to the network since. Each site comprises a Bruker EM27/SUN Fourier transform spectrometer and solar tracker, housed in an automated weatherproof enclosure based on a design developed at the University of Edinburgh. The data are contributing towards the GEMMA project (Greenhouse gas Measurement and Modelling Advancement) which aims to provide timely, frequent, data-driven estimates of the UK's carbon emissions.","creationDate":"2026-08-14T15:35:14.020804","lastUpdatedDate":"2026-08-14T15:35:34.847945","latestDataUpdateTime":"2026-08-14T15:35:14.020808","updateFrequency":"notPlanned","dataLineage":"Individual interferograms measured using the EM27/SUN instrument were processed using the PROFFASTv2.0 retrieval code, then collated into a single netCDF file for each day of measurements.","removedDataReason":"","keywords":"Greenhouse gases,Carbon dioxide,Methane,Carbon monoxide,Remote sensing,Atmospheric composition","publicationState":"working","nonGeographicFlag":true,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"pending","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":null,"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":13321,"startTime":"2024-09-24T00:00:00","endTime":null},"resultQuality":null,"validTimePeriod":null,"procedureAcquisition":{"ob_id":46191,"uuid":"d93fd81f37994399a9edeab2bb01fbf6","short_code":"acq","title":"Acquisition for: GEMINI-UK EM27-SUN greenhouse gas column concentration data","abstract":""},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[],"projects":[],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220564,220561,220562,220563,220565,220566,220567,220568,220569],"onlineresource_set":[]},{"ob_id":46194,"uuid":"c24e2ac59c094346a45535fe4e51752a","title":"Longterm observations of volatile organic compounds from the NCAS Dual Column Gas Chromatograph- Flame Ionization Detector unit 4 deployed at the Cabo Verde Atmospheric Observatory, v1.0 (20190515-onwards)","abstract":"Observations of volatile organic compound concentrations from the National Centre for Atmospheric Science Atmospheric Measurement and Observation Facility's Dual Column Gas Chromatograph- Flame Ionization Detector unit 4 (ncas-dc-gc-fid-4) deployed at the Cabo Verde Atmospheric Observatory from May 2019.  These observations were taken as part of longterm observations at the site.\r\n\r\nData products from this deployment include: dimethyl sulfide concentrations.\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2026-08-18T16:17:15","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Data were collected, quality controlled and prepared for archiving by the instrument scientists before upload to the Centre for Environmental Data Analysis (CEDA) for long term archiving.","removedDataReason":"","keywords":"NCAS, AMOF, CVAO, Volatile organic compound, Cape Verde, dms, c2h6s, dimethyl sulphide, dimethyl sulfide","publicationState":"preview","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":12,"bboxName":"Cape Verde Atmospheric Observatory Site","eastBoundLongitude":-24.871,"westBoundLongitude":-24.871,"southBoundLatitude":16.848,"northBoundLatitude":16.848},"verticalExtent":null,"result_field":{"ob_id":46195,"dataPath":"/badc/ncas-cvao/data/ncas-dc-gc-fid-4/20190515_longterm/v1.0/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":1889909,"numberOfFiles":2,"fileFormat":"NetCDF"},"timePeriod":{"ob_id":13322,"startTime":"2019-05-15T00:00:00","endTime":null},"resultQuality":{"ob_id":3233,"explanation":"Data are as given by the data provider, no quality control has been performed by the Centre for Environmental Data Analysis (CEDA)","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2019-01-30"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":46196,"uuid":"6ae64023b89d4a5a80f681a5fc176901","short_code":"acq","title":"Acquisition for Longterm observations of volatile organic compounds from the NCAS dc-gc-fid unit 4 deployed at Cabo Verde Atmospheric Observatory, v1.0 (20190515-onwards)","abstract":"Acquisition for Longterm observations of volatile organic compounds from the NCAS Dual Column Gas Chromatograph- Flame Ionization Detector unit 4 deployed at from Cabo Verde Atmospheric Observatory, v1.0 (20190515-onwards)"},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[223],"discoveryKeywords":[],"permissions":[{"ob_id":2522,"accessConstraints":null,"accessCategory":"registered","accessRoles":null,"label":"registered: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":43720,"uuid":"d3685300168848f290dd3a9ec14cc8ac","short_code":"proj","title":"Wessex Convection experiment - Observing the Evolving Structures of Turbulence (WOEST)","abstract":"This project, WesCon - Observing the Evolving Structures of Turbulence (WOEST), complements the Met Office's Wessex Convection Experiment (WesCon) project by enabling frequent observations of the same turbulent structures at high resolution. In terms of moist convective turbulence, WOEST will radically advance observations of cloud dynamics by tracking precipitating cores of convective clouds and the turbulent regions embedded within them in real-time using four dual-polarisation Doppler radars. The radar scans will also be coordinated with the FAAM aircraft location to enable coincident observations. In terms of boundary-layer turbulence and variability, their evolution will be captured uniquely by multiple UAS, which will be coordinated to capture hourly profiles of temperature, humidity, and winds to study the small-scale variability in the lowest 2km of the atmosphere. Additionally, an array of cloud cameras will be used to reconstruct the 3D motion and evolution of boundary-layer clouds, to be related to the turbulent and dynamic evolution of the boundary layer as measured by remote sensing instruments such as lidar (to measure cloud bases and humidity profiles) and wind profilers.\r\n\r\nThe observations gathered in WOEST will capture turbulent processes in the atmosphere at a range of fine spatial and temporal scales. Our multi-instrument approach will enable us to evaluate simulations of turbulence and dynamics in convective clouds and how the structure and evolution of the boundary layer influence moist convective turbulence at a range of scales, including at the process-level relating turbulence to the strength and size of updrafts. This will lead to a new understanding of the variability and evolution of the boundary layer in the context of the surrounding cloud field and the variability of turbulence and cloud dynamics. Such insights should lead to significant improvements within the sub-grid turbulence parametrisations that allow both km-scale global weather and climate simulations and sub-km-scale regional weather forecasts to more accurately predict the evolution and intensity of hazardous convective storms."}],"inspireTheme":[],"topicCategory":[],"phenomena":[103082,53936,53937,53938,53939,53940,53941,53942,53943,53944,74110,58079],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220583,220584,220586,220587,220588,220589,220590,220592,220593],"onlineresource_set":[]},{"ob_id":46201,"uuid":"cd8c8121bda14e5c81440eef14d7d464","title":"Microbiology-Ocean-Cloud-Coupling in the High Arctic (MOCCHA): aerosol backscatter and radial winds from the NCAS Doppler Aerosol Lidar unit 1 deployed onboard Swedish Maritime Administration Icebreaker Oden, v1.0 (20180809-20180920)","abstract":"Aerosol backscatter and radial winds measurements from the NCAS Doppler Aerosol Lidar unit 1 deployed onboard Swedish Maritime Administration Icebreaker Oden. These observations were taken as part of Microbiology-Ocean-Cloud-Coupling in the High Arctic (MOCCHA) between 20180809 and 20180920.\n\nData products from this deployment include: aerosol-backscatter-radial-winds\n\nFor further details of this deployment and the associated dataset please see the internal file metadata.\n\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used.\n        ","creationDate":"2026-08-20T12:06:07.266050","lastUpdatedDate":"2026-08-20T12:06:07.266056","latestDataUpdateTime":"2026-08-20T12:06:07.266058","updateFrequency":"notPlanned","dataLineage":"Data were processed and prepared by the project team before delivery to the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"NCAS, observation measurements","publicationState":"preview","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5195,"bboxName":"Arctic, Sweden, Norway","eastBoundLongitude":47.6706,"westBoundLongitude":44.2457,"southBoundLatitude":88.5675,"northBoundLatitude":87.5947},"verticalExtent":null,"result_field":{"ob_id":46202,"dataPath":"/badc/ncas-mobile/data/ncas-lidar-dop-1/20180801_moccha/v1.0","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":76805529898,"numberOfFiles":103,"fileFormat":"Data are netCDF formatted."},"timePeriod":{"ob_id":13325,"startTime":"2018-08-09T00:00:39","endTime":"2018-09-20T09:32:21"},"resultQuality":{"ob_id":4568,"explanation":"These data have been produced in accordance to standard NCAS observational practices. 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In terms of moist convective turbulence, WOEST will radically advance observations of cloud dynamics by tracking precipitating cores of convective clouds and the turbulent regions embedded within them in real-time using four dual-polarisation Doppler radars. The radar scans will also be coordinated with the FAAM aircraft location to enable coincident observations. In terms of boundary-layer turbulence and variability, their evolution will be captured uniquely by multiple UAS, which will be coordinated to capture hourly profiles of temperature, humidity, and winds to study the small-scale variability in the lowest 2km of the atmosphere. Additionally, an array of cloud cameras will be used to reconstruct the 3D motion and evolution of boundary-layer clouds, to be related to the turbulent and dynamic evolution of the boundary layer as measured by remote sensing instruments such as lidar (to measure cloud bases and humidity profiles) and wind profilers.\r\n\r\nThe observations gathered in WOEST will capture turbulent processes in the atmosphere at a range of fine spatial and temporal scales. Our multi-instrument approach will enable us to evaluate simulations of turbulence and dynamics in convective clouds and how the structure and evolution of the boundary layer influence moist convective turbulence at a range of scales, including at the process-level relating turbulence to the strength and size of updrafts. This will lead to a new understanding of the variability and evolution of the boundary layer in the context of the surrounding cloud field and the variability of turbulence and cloud dynamics. Such insights should lead to significant improvements within the sub-grid turbulence parametrisations that allow both km-scale global weather and climate simulations and sub-km-scale regional weather forecasts to more accurately predict the evolution and intensity of hazardous convective storms."}],"inspireTheme":[],"topicCategory":[],"phenomena":[60930,60931,60932,60933,60934,60938,69325,69327,69330,69331,69332,69333,69334,69335,69336,69337,59111,59112,59113,59115,59127,59128,59129,59130,59131,59132,59133,59134,59135,59136,59137,59138,59139,59140,59141,59143,59144,59145,59146,59147,59148,59149,59150,59151,59152,59153,59154,59155,59156,59157,59160,59161,59162,59163,59164,59165,59168,59169,59172,59174,59175,59181,59182,59183,59184,59185,59188,59191,59192,59193,59194,59197,59198,59199,59200,59202,59212,10621,74661,74662,74663,74664,74665,74666,74667,74668,74669,74670,74671,74672,74673,74674,74675,74676,74677,74678,74679,74680,74681,74682,74683,74684,74685,74686,74687,74688,74689,74690,74691,74692,74693,74694,74695,74696,74697,74698,74699,74700,74701,74702,74703,74704,74705,74706,74707,74708,74709,74710,74711,74712,74713,74714,74715],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[{"ob_id":43875,"uuid":"36756ff1928f4a1684902b470cda774e","short_code":"coll","title":"Wessex convection experiment - Observing the Evolving Structures of Turbulence (WOEST)","abstract":"A collection of groundbased and airborne datasets gathered to capture turbulent processes in the atmosphere at a range of fine spatial and temporal scales for the Wessex convection experiment - Observing the Evolving Structures of Turbulence (WOEST) project during summer 2023. This multi-instrument collection is used to evaluate simulations of turbulence and dynamics in convective clouds and how the structure and evolution of the boundary layer influences moist convective turbulence at a range of scales."}],"responsiblepartyinfo_set":[220638,220639,220640,220641,220642,220643,220644,220645],"onlineresource_set":[]},{"ob_id":46211,"uuid":"c7365ad6d24e4d1f8c28c2ec07fea16e","title":"AQUABLE: rain liquid water content velocity reflectivity from the NCAS Micro Rain Radar unit 1 deployed at Manchester Air Quality Supersite (MAQS), v1.0 (20210603-20210803)","abstract":"Rain liquid water content (lwc), velocity and reflectivity measurements from the NCAS Micro Rain Radar unit 1 deployed at Manchester Air Quality Supersite (MAQS). 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Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used.\n        ","creationDate":"2026-08-20T12:06:35.062785","lastUpdatedDate":"2026-08-20T12:06:35.062791","latestDataUpdateTime":"2026-08-20T12:06:35.062795","updateFrequency":"notPlanned","dataLineage":"Data were processed and prepared by the project team before delivery to the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"NCAS, observation measurements","publicationState":"preview","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5197,"bboxName":"Manchester, University Of Manchester, U","eastBoundLongitude":-2.2145,"westBoundLongitude":-2.2145,"southBoundLatitude":53.4442,"northBoundLatitude":53.4442},"verticalExtent":null,"result_field":{"ob_id":46212,"dataPath":"/badc/ncas-mobile/data/ncas-mrr-1/20210525_aquable/v1.0","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":14437840267,"numberOfFiles":133,"fileFormat":"Data are netCDF formatted."},"timePeriod":{"ob_id":13328,"startTime":"2021-06-03T00:00:02","endTime":"2021-08-03T23:59:54"},"resultQuality":{"ob_id":4568,"explanation":"These data have been produced in accordance to standard NCAS observational practices. 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These observations were taken as part of NCAS Long Term Observations at Chilbolton Observatory between 20231001 and 20250306.\r\n\r\nData products from this deployment include: birdbath, vol\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used.","creationDate":"2026-08-20T12:29:15.752647","lastUpdatedDate":"2026-08-20T12:29:15","latestDataUpdateTime":"2026-08-20T12:29:15","updateFrequency":"notPlanned","dataLineage":"Data were processed and prepared by the project team before delivery to the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"NCAS, observation measurements","publicationState":"preview","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5198,"bboxName":"X-band-radar-2 at CAO","eastBoundLongitude":-0.01,"westBoundLongitude":-2.87,"southBoundLatitude":52.04,"northBoundLatitude":50.25},"verticalExtent":null,"result_field":{"ob_id":46216,"dataPath":"/badc/ncas-mobile/data/ncas-radar-x-band-2/20231001_cao/v1.0.0","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":11604781227513,"numberOfFiles":179485,"fileFormat":"Data are netCDF formatted."},"timePeriod":{"ob_id":13333,"startTime":"2023-10-01T01:49:02","endTime":"2025-03-06T09:19:58"},"resultQuality":{"ob_id":4568,"explanation":"These data have been produced in accordance to standard NCAS observational practices. 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This work was conducted as part of a wider field campaign examining photosynthesis and forest structure across the Alice Holt site.\r\n\r\nData were collected in the daytime on the 18th July 2023. Flights were conducted at two sites within the Alice Holt forest, the first at approximately 51.155396° N, –0.864384° W (‘Site One’), and the second at approximately 51.155453° N, –0.865355° W (‘Site Two’). These locations are shown visually in ‘Sample_Locations.pdf’. The positions within each flight are recorded in the relevant Trigger_Log directories.\r\n\r\nThe data have been processed to radiances using a python conversion tool which is given within the dataset (Piccolo_Radiometric_Conversion_Tool.py). The dataset is comprised of 434 files, that are a total of 305 MB. Data are provided as both .nc and .csv files. The XXX_irradiance.csv files contain irradiances (W cm-2 nm-1) are organized by wavelength (nm) and acquisition time, with five samples at each wavelength. The XXX_radiance.csv files contain a radiance (W sr-1 cm-2 nm-1) for each wavelength.\r\n\r\nData from both site locations are within the ‘Site_One_51_155396_-0_864384’ and ‘Site_Two_51_155453_-0_865355’ directories, with the flights for each given in subsequent directories, e.g., ‘First Flight_51_155373_-0_864409’. Data for each flight is then found in e.g., ‘splice_20230718_d2_s1_40a’. Calibration files and processing code are also included.","creationDate":"2026-08-26T10:23:01.246826","lastUpdatedDate":"2026-08-26T10:16:35","latestDataUpdateTime":"2026-08-26T10:16:35","updateFrequency":"","dataLineage":"Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"Alice Holt, Forest, drone, Trees, Splice, biomass","publicationState":"preview","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5199,"bboxName":"AliceHolt Drone 2023","eastBoundLongitude":-0.8535,"westBoundLongitude":-0.864384,"southBoundLatitude":51.155453,"northBoundLatitude":51.155396},"verticalExtent":null,"result_field":{"ob_id":46221,"dataPath":"/neodc/splice/data/SPLICE_Field_Data_Drone","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":217516755,"numberOfFiles":437,"fileFormat":"The dataset is comprised of 434 files, that are a total of 305 MB. Files are in NetCDF, CSV and PDF formats. Files with .pico extension are JSON files wrapped in a custom extension.\r\n\r\nArchive structure: Data from both site locations are within the ‘Site_One_51_155396_-0_864384’ and ‘Site_Two_51_155453_-0_865355’ directories, with the flights for each given in subsequent directories, e.g., ‘First Flight_51_155373_-0_864409’. Data for each flight is then found in e.g.,\r\n‘splice_20230718_d2_s1_40a’. Calibration files and processing code are also included. For full details of the structure please see the documentation_drone_flights.pdf file archived with the data."},"timePeriod":{"ob_id":13334,"startTime":"2023-07-18T00:00:00","endTime":"2023-07-18T00:00:00"},"resultQuality":null,"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":{"ob_id":46225,"uuid":"d2442b4759ea49caac53b47ab0a5a579","short_code":"cmppr","title":"Alice Holt  Forest Drone Data composite process 2023","abstract":"Flights were conducted at two sites within the Alice Holt forest, the first at approximately\r\n51.155396° N, –0.864384° W (‘Site One’), and the second at approximately 51.155453° N, –\r\n0.865355° W (‘Site Two’). These locations are shown visually in ‘Sample_Locations.pdf’. The\r\npositions within each flight are recorded in the relevant Trigger_Log directories.\r\n\r\nThe data have been processed to radiances using a python conversion tool which is given within\r\nthe dataset (Piccolo_Radiometric_Conversion_Tool.py). Data are provided as both .nc and .csv\r\nfiles. The XXX_irradiance.csv files contain irradiances (W cm-2 nm-1) are organized by wavelength\r\n(nm) and acquisition time, with five samples at each wavelength. The XXX_radiance.csv files\r\ncontain a radiance (W sr-1 cm-2 nm-1) for each wavelength."},"imageDetails":[2],"discoveryKeywords":[{"ob_id":1142,"name":"NDGO0005"}],"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"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":45716,"uuid":"dd612cd174eb42af8045037c5a07ab3d","short_code":"proj","title":"Structure, Photosynthesis and Light In Canopy Environments (SPLICE)","abstract":"The SPLICE project (Structure, Photosynthesis and Light In Canopy Environments) sought to improve our understanding of global photosynthesis and hence our ability to model climate change, by considering the way in which the three-dimensional structure of plants interacts with light and how this in turn impacts on the uptake of carbon. It employed state-of-the-art techniques to measure the three dimensional structure and photosynthesis of forests and construct detailed computer simulations to create a virtual laboratory that we can use to improve simulations from climate models."}],"inspireTheme":[],"topicCategory":[],"phenomena":[103204,103205,103206,103207,103208,103209,103210,103211,103212,103213,103214,103215,103216,103217],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220689,220690,220691,220692,220693,220694,220695,220696,220697,220698,220699,220700],"onlineresource_set":[95957]},{"ob_id":46227,"uuid":"8f932c8964904e1ab07c1a5e2817fe12","title":"SPLICE: Terrestrial Laser Scanning (TLS) for UK Alice Holt plot AH2, July 2023","abstract":"Terrestrial laser scanning was collected on the 18th July 2023 by Mat Disney and Meg Stretton using a Riegl VZ-400i for the SPLICE project. The data was collected at the Alice Holt Forest, which is an ancient mixed woodland spanning approximately 850 hectares on Gault Clay and Upper Greensand soils at the north-western edge of the Weald in southeast England.\r\n\r\nScans were acquired using chain sampling at 34 locations along a 12.5 m Cartesian grid to ensure sufficient data overlap to produce a high-quality point cloud of this forest plot. Capturing a complete sample of the scene at each location requires two scans (an upright scan and a tilt scan), owing to a 100° field of view. Upright scans are odd-numbered while tilt scans are even-numbered. The angular resolution between sequentially fired pulses is 0.04°, resulting in approximately 22.4 million emitted pulses per scan (i.e., 5.42 billion per ha). Up to four targets can be resolved per pulse, with a nominal ranging accuracy of 5 mm. The laser itself is characterized by a beam divergence of 0.35 mrad, and the diameter of the beam at emission is 7 mm (e.g., the diameter of the beam at a range of 50 m, would be 21 mm). The pulse repetition rate is 300 kHz, therefore, each scan takes approximately 3 minutes to complete.\r\n\r\nTo generate a plot-level point cloud, scans were coarse registered using GNSS enabled Auto-Registration 2 (AR2) with coarse registration fine-tuned using Multi Station Adjustment 2 (MSA2). The Sensor's Orientation and Position (SOP) matrix for all scans was saved into the \"matrix\" project directory and the GNSS coordinates (geographical coordinate system: WGS84 Cartesian) for all scans saved as a .kmz file.\r\n\r\nFor more information please see the Site_and_data_collection_and_processing_details-2.pdf and SPLICE_example_TLS_data_directory_structure-1.pdf documents archived with the data.","creationDate":"2026-08-26T14:50:39.461242","lastUpdatedDate":"2026-08-26T14:27:17","latestDataUpdateTime":"2026-08-26T14:27:17","updateFrequency":"","dataLineage":"Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).","removedDataReason":"","keywords":"Alice Holt, Forest, TLS, Trees, Splice, biomass","publicationState":"preview","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":5200,"bboxName":"Splice TLS scans for alice holt forest","eastBoundLongitude":-0.86388,"westBoundLongitude":-0.864835,"southBoundLatitude":51.155065,"northBoundLatitude":51.155565},"verticalExtent":null,"result_field":{"ob_id":46226,"dataPath":"/neodc/tls/data/raw/uk/AH2/2023-07-18-AHL2.PROJ","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":206231501239,"numberOfFiles":52271,"fileFormat":"The following terrestrial LiDAR-derived products are available the Alice Holt plot:\r\n1. Raw terrestrial LiDAR data from each scan (no filtering was applied in RiSCAN PRO), stored in\r\nthe RXP data stream format developed by RIEGL.\r\n2. Transformation matrices necessary for rotating and translating the coordinate system of each\r\nscan, into the coordinate system of the first scan. Stored in DAT format.\r\n3. Pre-processed terrestrial LiDAR data:\r\na. full-resolution 10m tiled plot point clouds including attributes such as XYZ, scan position\r\nindex, reflectance, deviation, etc. stored in polygon PLY format.\r\nb. downsampled 10m tiled plot point clouds including attributes such as XYZ, scan position\r\nindex, reflectance, deviation, etc. stored in polygon PLY format.\r\nc. A tile_index file (maps the spatial location of the tiled point clouds) stored in DAT format.\r\nd. Bounding geometry files setting plot boundaries with and without a buffer surrounding the\r\nplot. Stored in shapefile SHP, DBF, SHX and CPG formats.\r\n4. Downsampled 10m tiled plot point clouds segmented into leaf, wood, ground points or coarse\r\nwoody debris. Stored in polygon file format PLY format.\r\n5. Wood-leaf separated tree-level point clouds including segmentation results and classification\r\nprobabilities for each point are stored in polygon PLY format.\r\n6. QSM files:\r\na. in_plot CSV (for plots processed with TLS2trees) lists all trees to be modelled with QSMs\r\nas they are located inside the plot boundary.\r\nb. out_plot CSV (for plots processed with TLS2trees) lists all trees NOT to be modelled as\r\nthey are located outside the plot boundary.\r\nc. plot_boundary CSV (for plots processed with TLS2trees) shows the location of all\r\nin_plot trees within each plot boundary.\r\nd. QSM processing files (.MAT Matlab).\r\ne. QSMs derived from each woody tree-level point cloud, (.MAT Matlab)\r\n7. We provide pre-processed and segmented terrestrial LiDAR data in PLY format as it supports\r\nfull 3D object representation, including polygons and geometric primitives, in addition to point\r\ndata. This is essential for storing quantitative structure models (QSMs), which go beyond point\r\nclouds to describe tree geometry. The PLY format is open, widely supported in Python and R,\r\nand can be converted to LAS/LAZ when only point data are required.\r\n8. Tree-attributes file (.CSV) containing biophysical parameters derived from both the point clouds\r\nand QSMs: DBH, tree height, tree-level volume and AGB with uncertainty, plot-level AGB and\r\nassociated uncertainty.\r\n9. Figures of all individually segmented trees arranged by tree DBH size (largest to smallest DBH)\r\nfor each FBRMS plot(PNG image format).\r\n10. GNSS coordinates (geographical coordinate system: WGS84 Cartesian) for all scan positions\r\nstored in KMZ zip-compressed format. These files are available for the seven French Guiana\r\nand Gabon FBRMS plots.\r\n\r\nMore detail can be found in the Site_and_data_collection_and_processing_details.pdf document archived with the data"},"timePeriod":{"ob_id":13335,"startTime":"2023-07-17T00:00:00","endTime":"2023-07-18T00:00:00"},"resultQuality":null,"validTimePeriod":null,"procedureAcquisition":{"ob_id":46252,"uuid":"064cf2e7ccd0446999ce9351b3e434a5","short_code":"acq","title":"SPLICE: Terrestrial Laser Scanning (TLS) for UK Alice Holt plot AH2, July 2023","abstract":"Scans were acquired using chain sampling at 34 locations along a 12.5 m Cartesian grid to ensure\r\nsufficient data overlap to produce a high-quality point cloud of this forest plot. Capturing a complete\r\nsample of the scene at each location requires two scans (an upright scan and a tilt scan), owing to a\r\n100° field of view. Upright scans will be odd-numbered while tilt scans will be even-numbered. The\r\ncharacteristics of the REIGL VZ-400i used to collected TLS data at Alice Holt can be seen on the\r\ntable below. To generate a plot-level point cloud, scans were coarse registered using GNSS enabled\r\nAuto-Registration 2 (AR2) with coarse registration fine-tuned using Multi Station Adjustment 2\r\n(MSA2) The Sensor's Orientation and Position (SOP) matrix for all scans was saved into the\r\n\\\"matrix\\\" project directory and the GNSS coordinates (geographical coordinate system: WGS84\r\nCartesian) for all scans saved as a .kmz file. Full details of the data acquisitive can be found in the Site_and_data_collection_and_processing_details.pdf  archived with the data."},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[2],"discoveryKeywords":[{"ob_id":1138,"name":"NDGO0003"}],"permissions":[{"ob_id":2528,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":8,"licenceURL":"http://creativecommons.org/licenses/by/4.0/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":45716,"uuid":"dd612cd174eb42af8045037c5a07ab3d","short_code":"proj","title":"Structure, Photosynthesis and Light In Canopy Environments (SPLICE)","abstract":"The SPLICE project (Structure, Photosynthesis and Light In Canopy Environments) sought to improve our understanding of global photosynthesis and hence our ability to model climate change, by considering the way in which the three-dimensional structure of plants interacts with light and how this in turn impacts on the uptake of carbon. It employed state-of-the-art techniques to measure the three dimensional structure and photosynthesis of forests and construct detailed computer simulations to create a virtual laboratory that we can use to improve simulations from climate models."}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220705,220706,220707,220708,220709,220710,220711,220718,220712,220713,220714,220715,220716,220717],"onlineresource_set":[]},{"ob_id":46228,"uuid":"139744a1b5764ca5a0306f37ad14105a","title":"DMS concentrations in the Antarctic Peninsula (v2)","abstract":"This dataset contains the time series of dimethyl sulfate (DMS) concentrations measured at East Beach Hut near the British Antarctic Survey (BAS) Rothera station off the coast of the Antarctic peninsula since late Feb 2022, as part of the Southern Ocean Clouds (SOC) project.\r\n\r\nThe data was collected using an iDirac gas chromatograph. DMS is naturally emitted from the oceans into the atmosphere, and has a direct effect on climate through cloud formation.\r\n\r\nThis data is openly accessible for research purposes. Please do contact the authors if you plan to use this data for publications.","creationDate":"2025-01-18T18:05:15.917284","lastUpdatedDate":"2025-02-01T15:11:58","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"Raw chromatogram from the iDirac were converted into concentrations as described in Bolas et al., AMT, 2020. Data underwent QA/QC procedures as described in Bolas et al.","removedDataReason":"","keywords":"DMS,dimethyl sulfide,iDirac,VOCs,Antarctica","publicationState":"citable","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"ongoing","dataPublishedTime":"2026-09-10T14:40:51","doiPublishedTime":"2026-09-10T14:41:13.502234","removedDataTime":null,"geographicExtent":{"ob_id":4677,"bboxName":"","eastBoundLongitude":-68.113369,"westBoundLongitude":-68.113396,"southBoundLatitude":-67.568469,"northBoundLatitude":-67.568469},"verticalExtent":null,"result_field":{"ob_id":46229,"dataPath":"/badc/deposited2025/Southern_Ocean_Clouds/dms_rothera_v2","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":787807,"numberOfFiles":2,"fileFormat":"CSV"},"timePeriod":{"ob_id":13337,"startTime":"2022-02-26T00:00:00","endTime":"2025-02-21T00:00:00"},"resultQuality":{"ob_id":4643,"explanation":"Gas standards for DMS were prepared gravimetrically by diluting a higher concentration parent mixture (106 ± 5.3 nmol mol−1 in nitrogen, BOC) to ~12 nmol mol−1 respectively, with high-purity nitrogen (BIP+, Air Products), inside Silconert2000-treated stainless steel cylinders (RE24133-PI 500 mL sample cylinder, Thames Restek).","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2025-01-18"},"validTimePeriod":null,"procedureAcquisition":{"ob_id":43403,"uuid":"48e432113e764cf58c8020ef53f063ec","short_code":"acq","title":"Acquisition for: DMS concentration measurements in the Antarctic Peninsula","abstract":""},"procedureComputation":null,"procedureCompositeProcess":null,"imageDetails":[],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":43402,"uuid":"2a8f43443fa9432c88cc84d9a34a75ae","short_code":"proj","title":"Southern Ocean Clouds","abstract":"See details at https://www.cranfield.ac.uk/research-projects/understanding-cloud-formation-in-antarctica"}],"inspireTheme":[],"topicCategory":[],"phenomena":[80066,80068],"vocabularyKeywords":[],"identifier_set":[13968],"observationcollection_set":[],"responsiblepartyinfo_set":[220719,220720,220721,220722,220723,220724,220725,220726,220727,220728,220729,220730,220731],"onlineresource_set":[95959]},{"ob_id":46230,"uuid":"acb6ff397e014ade82f131e8eeb2850d","title":"Ice fraction data produced by the CESM2 model for the Regional Aerosol Model Intercomparison Project (RAMIP)","abstract":"This record contains ice fraction data for simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using CESM2. It contains NetCDF output from coupled transient simulations. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe simulations are initialised from the CMIP6 historical experiment. Anthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions in native CESM2 format. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request: https://gmd.copernicus.org/articles/16/4451/2023/\r\n\r\nAcronyms\r\n------------\r\nCESM2: the Community Earth System Model 2 hosted at the National Centre for Atmospheric Research (NCAR) in the US. \r\nSSP1-2.6: experiment based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges and RCP2.6, a future pathway with a radiative forcing of 2.6 W/m2 in the year 2100.\r\nSSP3-7.0: experiment based on Shared Socioeconomic Pathway SSP3 which is characterised by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nScenarioMIP: the Scenario Model Intercomparison Project simulates climate outcomes based on alternative plausible future scenarios.\r\nCMIP6: is the sixth phase of the Coupled Model Intercomparison Project, a global collaboration of climate modellers.","creationDate":"2025-02-04T13:39:07.370800","lastUpdatedDate":"2025-02-04T13:40:51","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"The simulations are initialised from the CESM2 Large Ensemble (LE) historical experiments.  The baseline SSP370 RAMIP experiment comes directly from the CESM2-LE project. In particular, CESM2 RAMIP uses 10 of the macroperturbation runs (i.e., each ensemble member is initialized from a different year in the preindustrial control simulation) that use an 11-year running mean filter to smooth the CMIP6 biomass burning emissions, including members\r\n\r\nAnthropogenic emissions designed for the ScenarioMIP experiments SSP3-7.0 and SSP1-2.6 are used. All experiments follow SSP3-7.0, with perturbations to regional aerosol and precursor emissions using SSP1-2.6 emissions, following the RAMIP protocol. Data are provided for a subset of CMIP6 variables, following their CMIP6 definitions. Some 3D variables are produced at reduced vertical resolution compared to CMIP6. These are identified with new variable names, as set out in the RAMIP data request:  https://gmd.copernicus.org/articles/16/4451/2023/","removedDataReason":"","keywords":"aerosol, extremes, near-term projections, RAMIP","publicationState":"published","nonGeographicFlag":false,"dontHarvestFromProjects":false,"language":"English","resolution":"","status":"completed","dataPublishedTime":"2026-08-27T14:01:17","doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":4678,"bboxName":"","eastBoundLongitude":180.0,"westBoundLongitude":-180.0,"southBoundLatitude":-90.0,"northBoundLatitude":90.0},"verticalExtent":null,"result_field":{"ob_id":46231,"dataPath":"/badc/deposited2026/RAMIP_CESM2/ICEFRAC/","oldDataPath":[],"storageLocation":"internal","storageStatus":"online","volume":8679436996,"numberOfFiles":61,"fileFormat":"NetCDF"},"timePeriod":{"ob_id":12043,"startTime":"2015-01-01T00:00:00","endTime":"2079-12-31T00:00:00"},"resultQuality":{"ob_id":4941,"explanation":"This dataset is uncmorised NetCDF model output. No quality checks were performed by CEDA.","passesTest":true,"resultTitle":"CEDA Data Quality Statement","date":"2026-08-27"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":{"ob_id":43461,"uuid":"14416e8347a64c31bb0b2fc744a21331","short_code":"comp","title":"CESM2","abstract":"The CESM2 climate model, released in 2018, includes the following components:\r\naerosol: MAM4 (same grid as atmos), atmos: CAM6 (0.9x1.25 finite volume grid; 288 x 192 longitude/latitude; 32 levels; top level 2.25 mb), atmosChem: MAM4 (same grid as atmos), land: CLM5 (same grid as atmos), landIce: CISM2.1, ocean: POP2 (320x384 longitude/latitude; 60 levels; top grid cell 0-10 m), ocnBgchem: MARBL (same grid as ocean), seaIce: CICE5.1 (same grid as ocean). \r\n\r\nFor CESM2-LE, the model was run by the National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA (NCAR) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, atmosChem: 100 km, land: 100 km, landIce: 5 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km. For RAMIP, the model was run by the University of California Riverside at NCAR using the cheyenne supercomputer using the same native nominal resolutions."},"procedureCompositeProcess":null,"imageDetails":[230],"discoveryKeywords":[],"permissions":[{"ob_id":2526,"accessConstraints":null,"accessCategory":"public","accessRoles":null,"label":"public: None group","licence":{"ob_id":3,"licenceURL":"http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/","licenceClassifications":[{"ob_id":3,"classification":"any"},{"ob_id":11,"classification":"attribution required"}]}}],"projects":[{"ob_id":43444,"uuid":"4680fd74cf2244ba8476ed2617e3b41f","short_code":"proj","title":"The Regional Aerosol Model Intercomparison Project (RAMIP)","abstract":"The Regional Aerosol Model Intercomparison Project (RAMIP) will deliver experiments designed to quantify the role of regional aerosol emissions changes in near-term projections. This is unlike any prior MIP, where the focus has been on changes in global emissions and/or very idealised aerosol experiments. Perturbing regional emissions makes RAMIP novel from a scientific standpoint and links the intended analyses more directly to mitigation and adaptation policy issues. From a science perspective, there is limited information on how realistic regional aerosol emissions impact local as well as remote climate conditions. Here, RAMIP will enable an evaluation of the full range of potential influences of realistic and regionally varied aerosol emission changes on near-future climate. From the policy perspective, RAMIP addresses the burning question of how local and remote decisions affecting emissions of aerosols influence climate change in any given region. Here, RAMIP will provide the information needed to make direct links between regional climate policies and regional climate change.\r\n\r\nRAMIP experiments are designed to explore sensitivities to aerosol type and location and provide improved constraints on uncertainties driven by aerosol radiative forcing and the dynamical response to aerosol changes. The core experiments will assess the effects of differences in future global and regional (Africa and the Middle East, East Asia, North America and Europe, and South Asia) aerosol emission trajectories through 2051, while optional experiments will test the nonlinear effects of varying emission locations and aerosol types along this future trajectory. All experiments are based on the shared socioeconomic pathways and are intended to be performed with 6th Climate Model Intercomparison Project (CMIP6) generation models, initialised from the CMIP6 historical experiments, to facilitate comparisons with existing projections. Requested outputs will enable the analysis of the role of aerosol in near-future changes in, for example, temperature and precipitation means and extremes, storms, and air quality."}],"inspireTheme":[],"topicCategory":[],"phenomena":[54956,54933,54934,54935,54936,93593,93594,54939,93595,93596,93597,93599,93600,93598,54943,54947,93601,93602,84646,93603,54952,55080,54954,54955,93604,93605,93606,93607,93608,93610,103218,54963,103219,54964,54937,54938,54965,54940,93611,54941,93612,93613,54944,52192,54946,63011,54948,54949,55077,55078,28669,28670],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[{"ob_id":44020,"uuid":"b7c87e4dafcc486ba1eca2abac752abf","short_code":"coll","title":"CESM2 output prepared for the Regional Aerosol Model Intercomparison Project (RAMIP)","abstract":"This collection contains data for Tier 1 simulations from the Regional Aerosol Model Intercomparison Project (RAMIP), produced using CESM2. It contains NetCDF output from coupled transient simulations with global aerosol reductions, and with regional aerosol reductions over Africa and the Middle East, East Asia, North America and Europe, and South Asia. It also contains NetCDF output for a set of partner experiments with anthropogenic emissions for the year 2050 and fixed, pre-industrial, sea surface temperatures, sea ice extent, and land use. For a full description of the experiments, see: https://gmd.copernicus.org/articles/16/4451/2023/.\r\n\r\nThe data are global, gridded data, from 01/01/2015 to 28/02/2051 for the coupled transient simulations. For the simulations with fixed sea surface temperatures, global, gridded data is provided for 30 years.\r\n\r\nCESM2 is the Community Earth System Model 2 hosted at the National Centre for Atmospheric Research (NCAR) in the US."}],"responsiblepartyinfo_set":[220733,220734,220735,220737,220736,220738,220739,220740],"onlineresource_set":[95960,95961,95962]},{"ob_id":46233,"uuid":"15d625bbb4084dee976c8560103814eb","title":"ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Weekly sea surface salinity product on a 0.25 degree global grid, v6.3, for 2010 to 2023","abstract":"This dataset contains Sea Surface Salinity (SSS) v6.3 data at a spatial resolution of 50km and a time resolution of 1 week. It is spatially sampled on a 0.25 degree grid and 1 day of time sampling. This product is also available separately on polar 25km EASE (Equal Area Scalable Earth) grids. A monthly product is also available. 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It has been spatially sampled on a regular 0.25° grid and 1 day of time sampling. This product is also available on polar 25 km EASE-2 (Equal Area Scalable Earth) grid.\r\n\r\nA monthly product is also available, at a spatial resolution of 50 km and a time resolution of 1 month. It is spatially sampled on a 0.25° grid and 15 days of time sampling. This product is also available on polar 25km EASE-2 grid.\r\n\r\n\r\nIn addition to salinity, information on uncertainties are provided. For more information, see the user guide and product documentation available on the Sea Surface Salinity CCI web page (linked below)."}],"responsiblepartyinfo_set":[220910,220911,220912,220913,220914,220915,220916,220917,220918,220919,220920,220921,220922,220923,220924,220925,220926,220927,220928,220929,220930,220931,220932,220933,220934,220935,220936,220937,220938,220939,220940,220941,220942],"onlineresource_set":[95988,95986,95987,95989]},{"ob_id":46239,"uuid":"e348292c77e5477891bf835367a4eae4","title":"ESA Land Surface Temperature Climate Change Initiative (LST_cci): All-weather MicroWave Land Surface Temperature (MW-LST) global data record (1996-2020), v6.04","abstract":"MW-LST is a data record of land surface temperature (LST) derived from the microwave instruments Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager / Sounder (SSMIS). Observations available at frequencies close to 18, 22, 26, and 85 GHz are used as an input to a retrieval algorithm that produces LST over all continental surfaces, twice per day (6 am/pm), at a spatial resolution of ~25 km, and over 25 years (1996-2020). \r\n\r\nThe data record has been produced by the company Estellus working within the ESA Land Surface Temperature Climate Change Initiative (LST_cci).   Compared with the remaining infrared LST data records of the LST_cci, the spatial resolution of the MW-LST is coarser, and the associated retrieval errors are larger. However, it offers LST estimates for clear-sky and cloudy conditions, therefore complementing the IR LST data records, which can only provide LST for clear skies. The data record is temporally and spatially complete, although in rare occasions some data can be missing due to missing observations, e.g., due to satellite maintenance operations or anomalous behavior. The data record is provided on a regular grid of 0.25x0.25 degrees, saved as daily, monthly, and yearly netcdf files. The reader is referred to the LST_cci website for more information about how the data record was derived, and how to use the data and associated quality flags and estimated uncertainty.\r\n\r\nThis version of the data is v2.33.   It fixes an issue that was found with the variable 'lst_unc_time_correction' in the previous v2.23, but is otherwise identical.","creationDate":"2022-07-22T09:15:57.183554","lastUpdatedDate":"2022-07-22T09:15:57","latestDataUpdateTime":null,"updateFrequency":"notPlanned","dataLineage":"The data record has been produced by the company Estellus working within the ESA Land Surface Temperature Climate Change Initiative (LST_cci),  and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).  ). The source of satellite Level 1 observations is the Fundamental Climate Data Record of Microwave Imager Radiances (https://doi.org/10.5676/EUM_SAF_CM/FCDR_MWI/V003), kindly provided by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF).\r\nContact: data.lst-cci@acri-st.fr","removedDataReason":"","keywords":"land surface temperature, CCI","publicationState":"working","nonGeographicFlag":false,"dontHarvestFromProjects":true,"language":"English","resolution":"","status":"completed","dataPublishedTime":null,"doiPublishedTime":null,"removedDataTime":null,"geographicExtent":{"ob_id":2896,"bboxName":"","eastBoundLongitude":180.0,"westBoundLongitude":-180.0,"southBoundLatitude":-90.0,"northBoundLatitude":90.0},"verticalExtent":null,"result_field":null,"timePeriod":{"ob_id":9163,"startTime":"1996-01-01T00:00:00","endTime":"2020-12-31T23:59:59"},"resultQuality":{"ob_id":3798,"explanation":"For information on the data quality see the associated LST_cci documentation","passesTest":true,"resultTitle":"LST cci","date":"2021-11-30"},"validTimePeriod":null,"procedureAcquisition":null,"procedureComputation":null,"procedureCompositeProcess":{"ob_id":33373,"uuid":"96cc894239c341d182941c9205e62ca6","short_code":"cmppr","title":"Composite process for ESA Land Surface Temperature Climate Change Initiative (LST_cci): All-weather daily MicroWave Land Surface Temperature (MW-LST) global data record (1996-2020)","abstract":"The land surface temperature (LST) data has been derived from the microwave instruments Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager / Sounder (SSMIS). Observations available at frequencies close to 18, 22, 26, and 85 GHz are used as an input to a retrieval algorithm that produces LST over all continental surfaces, twice per day (6 am/pm), at a spatial resolution of ~25 km, and over 25 years (1996-2020)."},"imageDetails":[111],"discoveryKeywords":[],"permissions":[],"projects":[{"ob_id":33361,"uuid":"555149fdc3ef4e23a1de8ece93c29f5d","short_code":"proj","title":"ESA Land Surface Temperature Climate Change Initiative (LST_cci)","abstract":"The land surface temperature (LST) CCI project, which is funded by the European Space Agency (ESA) as part of the Agency’s Climate Change Initiative (CCI) Programme, aims to deliver a significant improvement on the capability of current satellite LST data records to meet the challenging Global Climate Observing System (GCOS) requirements for climate applications to realise the full potential of long-term LST data for climate science.\r\n\r\nAccurate knowledge of LST plays a key role in describing the physics of land-surface processes at regional and global scales as they combine information on both the surface-atmosphere interactions and energy fluxes within the Earth Climate System. LST provides a metric of surface state when combined with vegetation parameters and soil moisture and is one of the drivers of vegetation phenology. Furthermore, LST is an independent temperature data set for quantifying climate change complementary to the near-surface air temperature ECV based on in situ measurements and reanalyses.\r\n\r\nThe team uses data from a variety of satellites to provide an accurate view of temperatures across land surfaces globally over the past +20 years. This involves developing innovative techniques to merge data from different satellites into combined long-term satellite records for climate. These will all be evaluated by scientists working at leading climate centres."}],"inspireTheme":[],"topicCategory":[],"phenomena":[],"vocabularyKeywords":[],"identifier_set":[],"observationcollection_set":[],"responsiblepartyinfo_set":[220946,220947,220948,220949,220950,220943,220944,220945,220951],"onlineresource_set":[95990,95991,95992,95993,95994]}]}