Observation List
Get a list of Observation objects.
GET /api/v3/observations/?format=api&offset=2100
{ "count": 10256, "next": "https://api.catalogue.ceda.ac.uk/api/v3/observations/?format=api&limit=100&offset=2200", "previous": "https://api.catalogue.ceda.ac.uk/api/v3/observations/?format=api&limit=100&offset=2000", "results": [ { "ob_id": 13733, "uuid": "234be8bf50ec46478f2720c2eaf14936", "title": "Eyjafjallajokull Volcanic Ash Cloud: Leosphere and Halo Doppler Lidar images from the Chilbolton Observatory, Hampshire", "abstract": "The Icelandic Volcano, Eyjafjallajokull, started erupting on 14th April 2010. The volcanic ash cloud produced covered much of Northern Europe for several weeks causing extensive disruption to air travel. The UK and European atmospheric communities had many instruments - both airborne and ground-based, remote sensing and in-situ - taking measurements of the ash cloud throughout this period. This dataset contains Leosphere and Halo Doppler Lidar images from the Chilbolton Observatory, Hampshire.\r\n", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2010-06-16T15:41:05", "updateFrequency": "notPlanned", "dataLineage": "Data collected from the Chilbolton Facility for Atmospheric and Radio Research (CFARR). A copy of these data were made available to the British Atmospheric Data Centre (BADC) to assist the academic community during this volcanic ash event.", "removedDataReason": "", "keywords": "Eyjafjallajokull, Lidar, Chilbolton", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2014-09-19T13:24:43", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 92, "bboxName": "Chilbolton", "eastBoundLongitude": -1.427, "westBoundLongitude": -1.427, "southBoundLatitude": 51.145, "northBoundLatitude": 51.145 }, "verticalExtent": null, "result_field": { "ob_id": 13734, "dataPath": "/badc/eyjafjallajokull/data/chilbolton", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 14184866, "numberOfFiles": 55, "fileFormat": "Images are PNG formatted" }, "timePeriod": { "ob_id": 513, "startTime": "2010-04-09T23:00:00", "endTime": "2010-08-29T23:00:00" }, "resultQuality": { "ob_id": 437, "explanation": "This is quick look unvetted data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-09-19" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 13735, "uuid": "49d5f639de10440d95c141fb868e961d", "short_code": "acq", "title": "Eyjafjallajokull Volcanic Ash Cloud Leosphere and Halo Doppler Lidar images from Chilbolton Facility", "abstract": " Eyjafjallajokull Volcanic Ash Cloud Leosphere and Halo Doppler Lidar images from Chilbolton Facility" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 50 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2522, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13984, "uuid": "27f35145eb7b45b8829602a7e2cf544a", "short_code": "proj", "title": "Eyjafjallajokull Volcanic Ash Cloud Measurements and Imagery", "abstract": "The Icelandic Volcano, Eyjafjallajokull, started erupting on 14th April 2010. The volcanic ash cloud produced covered much of Northern Europe for several weeks causing extensive disruption to air travel. The UK and European atmospheric communities had many instruments - both airborne and ground-based, remote sensing and in-situ - taking measurements of the ash cloud throughout this period" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 25404, 54654, 54655, 54656, 54657, 54658, 54659, 54660, 54661, 54662, 54664, 54665, 54666, 54667, 55839, 55840, 55841, 55842, 55843, 55844, 89372 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 1917, "uuid": "e6f5502c687f25a6c7009d4704b124b4", "short_code": "coll", "title": "Eyjafjallajokull Volcanic Ash Cloud Measurements and Imagery", "abstract": "The Icelandic Volcano, Eyjafjallajokull, started erupting on 14th April 2010. The volcanic ash cloud produced covered much of Northern Europe for several weeks causing extensive disruption to air travel. The UK and European atmospheric communities had many instruments - both airborne and ground-based, remote sensing and in-situ - taking measurements of the ash cloud throughout this period. The dataset comprises of measurements of aerosol and particle layers (upper and lower boundary, height, horizontal extent) and infra-red and visible imagery of the ash cloud." } ], "responsiblepartyinfo_set": [ 52554, 52559, 52560, 52561, 52562, 52555, 52558, 54257 ], "onlineresource_set": [] }, { "ob_id": 13736, "uuid": "416f7d9132d64010ae4115a579e33a5a", "title": "Eyjafjallajokull Volcanic Ash Cloud: Northern hemisphere satellite imagery", "abstract": "The Icelandic Volcano, Eyjafjallajokull, started erupting on 14th April 2010. The volcanic ash cloud produced covered much of Northern Europe for several weeks causing extensive disruption to air travel. The UK and European atmospheric communities had many instruments - both airborne and ground-based, remote sensing and in-situ - taking measurements of the ash cloud throughout this period. This dataset contains a variety of satellite products including dust and sulphur dioxide (SO2) retrievals.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2010-06-29T12:43:57", "updateFrequency": "notPlanned", "dataLineage": "Data collected by the Met Office's satellite network. A copy of these data were made available to the British Atmospheric Data Centre (BADC) to assist the academic community during this volcanic ash event.", "removedDataReason": "", "keywords": "Eyjafjallajokull, Satellite, SO2, Dust", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2014-09-19T13:24:43", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 826, "bboxName": "met office satellite", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": 0.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13737, "dataPath": "/badc/eyjafjallajokull/data/met_office/data/1_Satellite", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 30774088, "numberOfFiles": 71, "fileFormat": "Images are JPG formatted" }, "timePeriod": { "ob_id": 513, "startTime": "2010-04-09T23:00:00", "endTime": "2010-08-29T23:00:00" }, "resultQuality": { "ob_id": 437, "explanation": "This is quick look unvetted data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-09-19" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 13738, "uuid": "389fe9bfef944558a4a9e6265416e019", "short_code": "acq", "title": "Eyjafjallajokull Volcanic Ash Cloud Met Office Satellite images", "abstract": "Eyjafjallajokull Volcanic Ash Cloud Met Office Satellite images" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 69 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2545, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "msg", "label": "restricted: msg group", "licence": { "ob_id": 22, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/msg.pdf", "licenceClassifications": [ { "ob_id": 4, "classification": "academic" } ] } } ], "projects": [ { "ob_id": 13984, "uuid": "27f35145eb7b45b8829602a7e2cf544a", "short_code": "proj", "title": "Eyjafjallajokull Volcanic Ash Cloud Measurements and Imagery", "abstract": "The Icelandic Volcano, Eyjafjallajokull, started erupting on 14th April 2010. The volcanic ash cloud produced covered much of Northern Europe for several weeks causing extensive disruption to air travel. The UK and European atmospheric communities had many instruments - both airborne and ground-based, remote sensing and in-situ - taking measurements of the ash cloud throughout this period" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 1917, "uuid": "e6f5502c687f25a6c7009d4704b124b4", "short_code": "coll", "title": "Eyjafjallajokull Volcanic Ash Cloud Measurements and Imagery", "abstract": "The Icelandic Volcano, Eyjafjallajokull, started erupting on 14th April 2010. The volcanic ash cloud produced covered much of Northern Europe for several weeks causing extensive disruption to air travel. The UK and European atmospheric communities had many instruments - both airborne and ground-based, remote sensing and in-situ - taking measurements of the ash cloud throughout this period. The dataset comprises of measurements of aerosol and particle layers (upper and lower boundary, height, horizontal extent) and infra-red and visible imagery of the ash cloud." } ], "responsiblepartyinfo_set": [ 52563, 52564, 52565, 52568, 52569, 52570, 52571, 52566 ], "onlineresource_set": [] }, { "ob_id": 13739, "uuid": "0b38c9753f7e413d84b70e46f50a1fa0", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes: Abisko Hemispherical Photography Images", "abstract": "Vegetation and meteorological observations (snow and radiation) were collected by various ground instruments in an area of forest near Abisko (Sweden) and Sodankylä (Finland) during measurement campaigns in March 2011 and March 2012. This dataset contains the hemispherical photography data collected at Abisko site in March 2011. Upward-looking hemispherical photographs were taken at every radiometer position using a Nikon Coolpix 4300 digital camera with a Nikon FC-E8 fisheye lens. The camera was mounted on a small tripod with the lens approximately 20 cm above the snow surface. In each case, the camera was levelled and rotated such that magnetic north is at the top of the photograph. This was a NERC funded project.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-12-08T12:52:49", "updateFrequency": "notPlanned", "dataLineage": "Campaign research data.", "removedDataReason": "", "keywords": "NERC, snow, photography, abisko", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2015-12-14T20:01:28", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 765, "bboxName": "Abisko site", "eastBoundLongitude": 18.5, "westBoundLongitude": 17.5, "southBoundLatitude": 67.5, "northBoundLatitude": 68.5 }, "verticalExtent": null, "result_field": { "ob_id": 13740, "dataPath": "/badc/nerc-rm2010/data/snow-vegetation-atmosphere/abisko/hemispherical_photography", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 47489884, "numberOfFiles": 71, "fileFormat": "JPG images" }, "timePeriod": { "ob_id": 3683, "startTime": "2011-03-08T00:00:00", "endTime": "2011-03-29T23:00:00" }, "resultQuality": { "ob_id": 2101, "explanation": "Campaign Research data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-09-22" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 14279, "uuid": "2dbbf87a71bd425c8af378ac13e9e858", "short_code": "acq", "title": "RM2010 - Abisko Hemispherical Photography data", "abstract": "RM2010 - Abisko Hemispherical Photography data" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 12273, "uuid": "5fcda0aef03b4f0eaa2a665c69b5e029", "short_code": "proj", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes Project", "abstract": "By modifying the amount of solar radiation absorbed at the land surface, bright snow and dark forests have strong influences on weather and climate; either a decrease in snow cover or an increase in forest cover, which shades underlying snow, increases the absorption of radiation and warms the overlying air. \r\n\r\nComputer models for weather forecasting and climate prediction thus have to take these effects into account by calculating the changing mass of snow on the ground and interactions of radiation with forest canopies. Such models generally have coarse resolutions ranging from kilometres to hundreds of kilometres. Forest cover cannot be expected to be continuous over such large distances; instead, northern landscapes are mosaics of evergreen and deciduous forests, clearings, bogs and lakes. Snow can be removed from open areas by wind, shaded by surrounding vegetation or sublimated from forest canopies without ever reaching the ground, and these processes which influence patterns of snow cover depend on the size of the openings, the structure of the vegetation and weather conditions. Snow itself influences patterns of vegetation cover by supplying water, insulating plants and soil from cold winter temperatures and storing nutrients.\r\n\r\nThe aim of this project was to develop better methods for representing interactions between snow, vegetation and the atmosphere in models that, for practical applications, cannot resolve important scales in the patterns of these interactions.\r\n\r\nInformation was gathered on distributions of snow, vegetation and radiation during two field experiments at sites in the arctic: one in Sweden and the other in Finland. These sites were chosen because they have long records of weather and snow conditions, easy access, good maps of vegetation cover from satellites and aircraft and landscapes ranging from sparse deciduous forests to dense coniferous forests that are typical of much larger areas. \r\n\r\nUsing 28 radiometers, and moving them several times during the course of each experiment, allowed us to measure the highly variable patterns of radiation at the snow surface in forests.\r\n\r\nInformation from the field experiments have been used in developing and testing a range of models. To reach the scales of interest, we began with a model that explicitly resolves individual trees and work up through models with progressively coarser resolutions, testing the models at each stage against each other and in comparison with observations. The ultimate objective was a model that will be better able to make use of landscape information in predicting the absorption of radiation at the surface and the accumulation and melt of snow. \r\n\r\nThis project was funded by the Natural Environment Research Council (NERC) for three and a half years from November 2010 to February 2014 (NERC Reference: NE/H008187/1).\r\n" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [ 8678 ], "observationcollection_set": [ { "ob_id": 7768, "uuid": "6947880b98d32e249a8638ebe768efd2", "short_code": "coll", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes Project: Vegetation and Meteorological Observations at the Abisko Site", "abstract": "Vegetation and meteorological observations (snow and radiation) were collected by various ground instruments in an area of forest near Abisko (Sweden) during measurement campaigns in March and April 2011. This data is made available through the BADC. This is a NERC funded project." } ], "responsiblepartyinfo_set": [ 52574, 52575, 52580, 52573, 52577, 52578, 52579, 52576, 54839 ], "onlineresource_set": [] }, { "ob_id": 13741, "uuid": "5850b3fd981a417084b9e02acf7e6fcc", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes: Abisko Laser Scanning data", "abstract": "Vegetation and meteorological observations (snow and radiation) were collected by various ground instruments in an area of forest near Abisko (Sweden) and Sodankylä (Finland) during measurement campaigns in March 2011 and March 2012. This dataset contains the laser scanning data collected at Abisko site in March 2011. \r\n\r\nA Leica C10 terrestrial laser scanner was used to acquire three-dimensional point clouds of the canopies in every study plot. Four scans from the corners of a plot and up to four additional scans from other points were made to ensure that every side of every tree within the plot was visible from at least one scan position. The scanner records x, y and z coordinates and intensity of the first return. Horizontal coordinates were converted to UTM (zones 34W for Abisko).\r\nThis was a NERC funded project.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-11-05T20:45:21.870331", "updateFrequency": "notPlanned", "dataLineage": "Campaign research data.", "removedDataReason": "", "keywords": "NERC, snow, laser, abisko", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2015-12-14T20:07:39", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 765, "bboxName": "Abisko site", "eastBoundLongitude": 18.5, "westBoundLongitude": 17.5, "southBoundLatitude": 67.5, "northBoundLatitude": 68.5 }, "verticalExtent": null, "result_field": { "ob_id": 13742, "dataPath": "/badc/nerc-rm2010/data/snow-vegetation-atmosphere/abisko/laser_scanning", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2997363545, "numberOfFiles": 32, "fileFormat": "compressed files (gz)" }, "timePeriod": { "ob_id": 3683, "startTime": "2011-03-08T00:00:00", "endTime": "2011-03-29T23:00:00" }, "resultQuality": { "ob_id": 2101, "explanation": "Campaign Research data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-09-22" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 14277, "uuid": "32ebccaa873b47e78fa730c2309fbb30", "short_code": "acq", "title": "RM2010 - Abisko Laser Scanning data", "abstract": "RM2010 - Abisko Laser Scanning data" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 12273, "uuid": "5fcda0aef03b4f0eaa2a665c69b5e029", "short_code": "proj", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes Project", "abstract": "By modifying the amount of solar radiation absorbed at the land surface, bright snow and dark forests have strong influences on weather and climate; either a decrease in snow cover or an increase in forest cover, which shades underlying snow, increases the absorption of radiation and warms the overlying air. \r\n\r\nComputer models for weather forecasting and climate prediction thus have to take these effects into account by calculating the changing mass of snow on the ground and interactions of radiation with forest canopies. Such models generally have coarse resolutions ranging from kilometres to hundreds of kilometres. Forest cover cannot be expected to be continuous over such large distances; instead, northern landscapes are mosaics of evergreen and deciduous forests, clearings, bogs and lakes. Snow can be removed from open areas by wind, shaded by surrounding vegetation or sublimated from forest canopies without ever reaching the ground, and these processes which influence patterns of snow cover depend on the size of the openings, the structure of the vegetation and weather conditions. Snow itself influences patterns of vegetation cover by supplying water, insulating plants and soil from cold winter temperatures and storing nutrients.\r\n\r\nThe aim of this project was to develop better methods for representing interactions between snow, vegetation and the atmosphere in models that, for practical applications, cannot resolve important scales in the patterns of these interactions.\r\n\r\nInformation was gathered on distributions of snow, vegetation and radiation during two field experiments at sites in the arctic: one in Sweden and the other in Finland. These sites were chosen because they have long records of weather and snow conditions, easy access, good maps of vegetation cover from satellites and aircraft and landscapes ranging from sparse deciduous forests to dense coniferous forests that are typical of much larger areas. \r\n\r\nUsing 28 radiometers, and moving them several times during the course of each experiment, allowed us to measure the highly variable patterns of radiation at the snow surface in forests.\r\n\r\nInformation from the field experiments have been used in developing and testing a range of models. To reach the scales of interest, we began with a model that explicitly resolves individual trees and work up through models with progressively coarser resolutions, testing the models at each stage against each other and in comparison with observations. The ultimate objective was a model that will be better able to make use of landscape information in predicting the absorption of radiation at the surface and the accumulation and melt of snow. \r\n\r\nThis project was funded by the Natural Environment Research Council (NERC) for three and a half years from November 2010 to February 2014 (NERC Reference: NE/H008187/1).\r\n" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [ 8679 ], "observationcollection_set": [ { "ob_id": 7768, "uuid": "6947880b98d32e249a8638ebe768efd2", "short_code": "coll", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes Project: Vegetation and Meteorological Observations at the Abisko Site", "abstract": "Vegetation and meteorological observations (snow and radiation) were collected by various ground instruments in an area of forest near Abisko (Sweden) during measurement campaigns in March and April 2011. This data is made available through the BADC. This is a NERC funded project." } ], "responsiblepartyinfo_set": [ 52588, 52585, 52586, 52587, 52582, 52583, 52581, 52584, 54865 ], "onlineresource_set": [] }, { "ob_id": 13743, "uuid": "48fb4122e4474cfb88054dfa6a33f75d", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes: Abisko Snow Depth data", "abstract": "Vegetation and meteorological observations (snow and radiation) were collected by various ground instruments in an area of forest near Abisko (Sweden) and Sodankylä (Finland) during measurement campaigns in March 2011 and March 2012. This dataset contains the snow depth data collected at Abisko site in March 2011. \r\nSnow depths were measured by pushing a graduated probe down to the ground surface at points with 2 m spacing in each 20 m × 20 m plot, giving grids of 121 points. \r\nThis was a NERC funded project.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-12-08T13:25:38", "updateFrequency": "notPlanned", "dataLineage": "Campaign research data.", "removedDataReason": "", "keywords": "NERC, snow, abisko", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2015-12-14T20:11:36", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 765, "bboxName": "Abisko site", "eastBoundLongitude": 18.5, "westBoundLongitude": 17.5, "southBoundLatitude": 67.5, "northBoundLatitude": 68.5 }, "verticalExtent": null, "result_field": { "ob_id": 13744, "dataPath": "/badc/nerc-rm2010/data/snow-vegetation-atmosphere/abisko/snowdepth", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 12564, "numberOfFiles": 6, "fileFormat": "BADC CSV format" }, "timePeriod": { "ob_id": 3683, "startTime": "2011-03-08T00:00:00", "endTime": "2011-03-29T23:00:00" }, "resultQuality": { "ob_id": 2101, "explanation": "Campaign Research data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-09-22" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 14274, "uuid": "974584a064e34cc0a40188c043e07489", "short_code": "acq", "title": "RM2010 - Abisko Snow Depth data", "abstract": "RM2010 - Abisko Snow Depth data" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 12273, "uuid": "5fcda0aef03b4f0eaa2a665c69b5e029", "short_code": "proj", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes Project", "abstract": "By modifying the amount of solar radiation absorbed at the land surface, bright snow and dark forests have strong influences on weather and climate; either a decrease in snow cover or an increase in forest cover, which shades underlying snow, increases the absorption of radiation and warms the overlying air. \r\n\r\nComputer models for weather forecasting and climate prediction thus have to take these effects into account by calculating the changing mass of snow on the ground and interactions of radiation with forest canopies. Such models generally have coarse resolutions ranging from kilometres to hundreds of kilometres. Forest cover cannot be expected to be continuous over such large distances; instead, northern landscapes are mosaics of evergreen and deciduous forests, clearings, bogs and lakes. Snow can be removed from open areas by wind, shaded by surrounding vegetation or sublimated from forest canopies without ever reaching the ground, and these processes which influence patterns of snow cover depend on the size of the openings, the structure of the vegetation and weather conditions. Snow itself influences patterns of vegetation cover by supplying water, insulating plants and soil from cold winter temperatures and storing nutrients.\r\n\r\nThe aim of this project was to develop better methods for representing interactions between snow, vegetation and the atmosphere in models that, for practical applications, cannot resolve important scales in the patterns of these interactions.\r\n\r\nInformation was gathered on distributions of snow, vegetation and radiation during two field experiments at sites in the arctic: one in Sweden and the other in Finland. These sites were chosen because they have long records of weather and snow conditions, easy access, good maps of vegetation cover from satellites and aircraft and landscapes ranging from sparse deciduous forests to dense coniferous forests that are typical of much larger areas. \r\n\r\nUsing 28 radiometers, and moving them several times during the course of each experiment, allowed us to measure the highly variable patterns of radiation at the snow surface in forests.\r\n\r\nInformation from the field experiments have been used in developing and testing a range of models. To reach the scales of interest, we began with a model that explicitly resolves individual trees and work up through models with progressively coarser resolutions, testing the models at each stage against each other and in comparison with observations. The ultimate objective was a model that will be better able to make use of landscape information in predicting the absorption of radiation at the surface and the accumulation and melt of snow. \r\n\r\nThis project was funded by the Natural Environment Research Council (NERC) for three and a half years from November 2010 to February 2014 (NERC Reference: NE/H008187/1).\r\n" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 25870, 55555, 55556, 55557 ], "vocabularyKeywords": [], "identifier_set": [ 8680 ], "observationcollection_set": [ { "ob_id": 7768, "uuid": "6947880b98d32e249a8638ebe768efd2", "short_code": "coll", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes Project: Vegetation and Meteorological Observations at the Abisko Site", "abstract": "Vegetation and meteorological observations (snow and radiation) were collected by various ground instruments in an area of forest near Abisko (Sweden) during measurement campaigns in March and April 2011. This data is made available through the BADC. This is a NERC funded project." } ], "responsiblepartyinfo_set": [ 52590, 52591, 52596, 52589, 52594, 52595, 52593, 52592, 52597, 54885 ], "onlineresource_set": [] }, { "ob_id": 13745, "uuid": "d7f7556c58404b86bed2883c066593a9", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes: Abisko Trunk Temperature data", "abstract": "Vegetation and meteorological observations (snow and radiation) were collected by various ground instruments in an area of forest near Abisko (Sweden) and Sodankylä (Finland) during measurement campaigns in March 2011 and March 2012. This dataset contains the trunk temperature data collected at Abisko site in March 2011. Trunk temperatures for selected trees in the continuity plots were measured by inserting thermocouples beneath the bark. This was a NERC funded project.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-12-08T13:24:06.570306", "updateFrequency": "notPlanned", "dataLineage": "Campaign research data.", "removedDataReason": "", "keywords": "NERC, trunk, temperature, abisko", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2015-12-14T20:17:11", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 765, "bboxName": "Abisko site", "eastBoundLongitude": 18.5, "westBoundLongitude": 17.5, "southBoundLatitude": 67.5, "northBoundLatitude": 68.5 }, "verticalExtent": null, "result_field": { "ob_id": 13746, "dataPath": "/badc/nerc-rm2010/data/snow-vegetation-atmosphere/abisko/trunk", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 200142, "numberOfFiles": 2, "fileFormat": "BADC CSV" }, "timePeriod": { "ob_id": 3683, "startTime": "2011-03-08T00:00:00", "endTime": "2011-03-29T23:00:00" }, "resultQuality": { "ob_id": 2101, "explanation": "Campaign Research data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-09-22" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 14272, "uuid": "cf2cd4c168174dc491a0a33202cd4e1e", "short_code": "acq", "title": "RM2010 - Abisko Weather Observations data", "abstract": "RM2010 - Abisko Weather Observations data" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 12273, "uuid": "5fcda0aef03b4f0eaa2a665c69b5e029", "short_code": "proj", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes Project", "abstract": "By modifying the amount of solar radiation absorbed at the land surface, bright snow and dark forests have strong influences on weather and climate; either a decrease in snow cover or an increase in forest cover, which shades underlying snow, increases the absorption of radiation and warms the overlying air. \r\n\r\nComputer models for weather forecasting and climate prediction thus have to take these effects into account by calculating the changing mass of snow on the ground and interactions of radiation with forest canopies. Such models generally have coarse resolutions ranging from kilometres to hundreds of kilometres. Forest cover cannot be expected to be continuous over such large distances; instead, northern landscapes are mosaics of evergreen and deciduous forests, clearings, bogs and lakes. Snow can be removed from open areas by wind, shaded by surrounding vegetation or sublimated from forest canopies without ever reaching the ground, and these processes which influence patterns of snow cover depend on the size of the openings, the structure of the vegetation and weather conditions. Snow itself influences patterns of vegetation cover by supplying water, insulating plants and soil from cold winter temperatures and storing nutrients.\r\n\r\nThe aim of this project was to develop better methods for representing interactions between snow, vegetation and the atmosphere in models that, for practical applications, cannot resolve important scales in the patterns of these interactions.\r\n\r\nInformation was gathered on distributions of snow, vegetation and radiation during two field experiments at sites in the arctic: one in Sweden and the other in Finland. These sites were chosen because they have long records of weather and snow conditions, easy access, good maps of vegetation cover from satellites and aircraft and landscapes ranging from sparse deciduous forests to dense coniferous forests that are typical of much larger areas. \r\n\r\nUsing 28 radiometers, and moving them several times during the course of each experiment, allowed us to measure the highly variable patterns of radiation at the snow surface in forests.\r\n\r\nInformation from the field experiments have been used in developing and testing a range of models. To reach the scales of interest, we began with a model that explicitly resolves individual trees and work up through models with progressively coarser resolutions, testing the models at each stage against each other and in comparison with observations. The ultimate objective was a model that will be better able to make use of landscape information in predicting the absorption of radiation at the surface and the accumulation and melt of snow. \r\n\r\nThis project was funded by the Natural Environment Research Council (NERC) for three and a half years from November 2010 to February 2014 (NERC Reference: NE/H008187/1).\r\n" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 21824, 57965, 57968, 57969 ], "vocabularyKeywords": [], "identifier_set": [ 8681 ], "observationcollection_set": [ { "ob_id": 7768, "uuid": "6947880b98d32e249a8638ebe768efd2", "short_code": "coll", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes Project: Vegetation and Meteorological Observations at the Abisko Site", "abstract": "Vegetation and meteorological observations (snow and radiation) were collected by various ground instruments in an area of forest near Abisko (Sweden) during measurement campaigns in March and April 2011. This data is made available through the BADC. This is a NERC funded project." } ], "responsiblepartyinfo_set": [ 52606, 52599, 52600, 52598, 52604, 52605, 52603, 52602, 52601, 54890 ], "onlineresource_set": [] }, { "ob_id": 13747, "uuid": "f044d036605b451da19b902af963cf9c", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes: Abisko Weather Observations data", "abstract": "Vegetation and meteorological observations (snow and radiation) were collected by various ground instruments in an area of forest near Abisko (Sweden) and Sodankylä (Finland) during measurement campaigns in March 2011 and March 2012. This dataset contains the data produced by a Vaisala WXT520 weather transmitter used to measure temperature, relative humidity, wind speed, wind direction and atmsopheric pressure during the radiometer experiments in each plot in March 2011. This was a NERC funded project.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-12-08T13:13:52.720207", "updateFrequency": "notPlanned", "dataLineage": "Campaign research data.", "removedDataReason": "", "keywords": "NERC, weather observations, abisko", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2015-12-14T20:22:24", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 765, "bboxName": "Abisko site", "eastBoundLongitude": 18.5, "westBoundLongitude": 17.5, "southBoundLatitude": 67.5, "northBoundLatitude": 68.5 }, "verticalExtent": null, "result_field": { "ob_id": 13748, "dataPath": "/badc/nerc-rm2010/data/snow-vegetation-atmosphere/abisko/weather", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 531555, "numberOfFiles": 6, "fileFormat": "BADC CSV" }, "timePeriod": { "ob_id": 3683, "startTime": "2011-03-08T00:00:00", "endTime": "2011-03-29T23:00:00" }, "resultQuality": { "ob_id": 2101, "explanation": "Campaign Research data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-09-22" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 14272, "uuid": "cf2cd4c168174dc491a0a33202cd4e1e", "short_code": "acq", "title": "RM2010 - Abisko Weather Observations data", "abstract": "RM2010 - Abisko Weather Observations data" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 12273, "uuid": "5fcda0aef03b4f0eaa2a665c69b5e029", "short_code": "proj", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes Project", "abstract": "By modifying the amount of solar radiation absorbed at the land surface, bright snow and dark forests have strong influences on weather and climate; either a decrease in snow cover or an increase in forest cover, which shades underlying snow, increases the absorption of radiation and warms the overlying air. \r\n\r\nComputer models for weather forecasting and climate prediction thus have to take these effects into account by calculating the changing mass of snow on the ground and interactions of radiation with forest canopies. Such models generally have coarse resolutions ranging from kilometres to hundreds of kilometres. Forest cover cannot be expected to be continuous over such large distances; instead, northern landscapes are mosaics of evergreen and deciduous forests, clearings, bogs and lakes. Snow can be removed from open areas by wind, shaded by surrounding vegetation or sublimated from forest canopies without ever reaching the ground, and these processes which influence patterns of snow cover depend on the size of the openings, the structure of the vegetation and weather conditions. Snow itself influences patterns of vegetation cover by supplying water, insulating plants and soil from cold winter temperatures and storing nutrients.\r\n\r\nThe aim of this project was to develop better methods for representing interactions between snow, vegetation and the atmosphere in models that, for practical applications, cannot resolve important scales in the patterns of these interactions.\r\n\r\nInformation was gathered on distributions of snow, vegetation and radiation during two field experiments at sites in the arctic: one in Sweden and the other in Finland. These sites were chosen because they have long records of weather and snow conditions, easy access, good maps of vegetation cover from satellites and aircraft and landscapes ranging from sparse deciduous forests to dense coniferous forests that are typical of much larger areas. \r\n\r\nUsing 28 radiometers, and moving them several times during the course of each experiment, allowed us to measure the highly variable patterns of radiation at the snow surface in forests.\r\n\r\nInformation from the field experiments have been used in developing and testing a range of models. To reach the scales of interest, we began with a model that explicitly resolves individual trees and work up through models with progressively coarser resolutions, testing the models at each stage against each other and in comparison with observations. The ultimate objective was a model that will be better able to make use of landscape information in predicting the absorption of radiation at the surface and the accumulation and melt of snow. \r\n\r\nThis project was funded by the Natural Environment Research Council (NERC) for three and a half years from November 2010 to February 2014 (NERC Reference: NE/H008187/1).\r\n" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 25880, 56169, 57963, 57964, 57965, 57966, 57967 ], "vocabularyKeywords": [], "identifier_set": [ 8682 ], "observationcollection_set": [ { "ob_id": 7768, "uuid": "6947880b98d32e249a8638ebe768efd2", "short_code": "coll", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes Project: Vegetation and Meteorological Observations at the Abisko Site", "abstract": "Vegetation and meteorological observations (snow and radiation) were collected by various ground instruments in an area of forest near Abisko (Sweden) during measurement campaigns in March and April 2011. This data is made available through the BADC. This is a NERC funded project." } ], "responsiblepartyinfo_set": [ 52608, 52609, 52615, 52607, 52612, 52613, 52614, 52610, 52611, 54893 ], "onlineresource_set": [] }, { "ob_id": 13761, "uuid": "4e39e3f0b8254b0a9dde34419a89a6f1", "title": "Eyjafjallajokull Volcanic Ash Cloud: raw backscatter profiles from the MST Radar Facility's Vaisala LD40 laser ceilometer, Capel Dewi, Wales", "abstract": "Plots of raw backscatter profiles from the MST Radar Facility's Vaisala LD40 laser ceilometer, Capel Dewi, Wales obtained during the Icelandic Volcano, Eyjafjallajokull, erupting from on 14th April 2010.\r\n\r\nThe volcanic ash cloud produced covered much of Northern Europe for several weeks causing extensive disruption to air travel. The UK and European atmospheric communities had many instruments - both airborne and ground-based, remote sensing and in-situ - taking measurements of the ash cloud throughout this period.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T02:17:26", "updateFrequency": "notPlanned", "dataLineage": "Data collected from the MST Radar Facility's. A copy of these data were made available to the British Atmospheric Data Centre (BADC) to assist the academic community during this volcanic ash event.", "removedDataReason": "", "keywords": "Eyjafjallajokull, MST Radar", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2014-09-19T13:24:43", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 515, "bboxName": "MST radar array", "eastBoundLongitude": -4.0054698, "westBoundLongitude": -4.0054698, "southBoundLatitude": 52.424526, "northBoundLatitude": 52.424526 }, "verticalExtent": null, "result_field": { "ob_id": 13762, "dataPath": "/badc/eyjafjallajokull/data/mstrf", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 499020, "numberOfFiles": 11, "fileFormat": "Images are PNG formatted" }, "timePeriod": { "ob_id": 513, "startTime": "2010-04-09T23:00:00", "endTime": "2010-08-29T23:00:00" }, "resultQuality": { "ob_id": 437, "explanation": "This is quick look unvetted data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-09-19" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 13763, "uuid": "1e4d7d01444841959696320c78d2ac49", "short_code": "acq", "title": "Eyjafjallajokull Volcanic Ash Cloud MST Radar measurements", "abstract": "Laser ceilometer from the NERC MST Radar Facility at Aberystwyth " }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 91 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2522, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13984, "uuid": "27f35145eb7b45b8829602a7e2cf544a", "short_code": "proj", "title": "Eyjafjallajokull Volcanic Ash Cloud Measurements and Imagery", "abstract": "The Icelandic Volcano, Eyjafjallajokull, started erupting on 14th April 2010. The volcanic ash cloud produced covered much of Northern Europe for several weeks causing extensive disruption to air travel. The UK and European atmospheric communities had many instruments - both airborne and ground-based, remote sensing and in-situ - taking measurements of the ash cloud throughout this period" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 25388, 25393, 25404 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 1917, "uuid": "e6f5502c687f25a6c7009d4704b124b4", "short_code": "coll", "title": "Eyjafjallajokull Volcanic Ash Cloud Measurements and Imagery", "abstract": "The Icelandic Volcano, Eyjafjallajokull, started erupting on 14th April 2010. The volcanic ash cloud produced covered much of Northern Europe for several weeks causing extensive disruption to air travel. The UK and European atmospheric communities had many instruments - both airborne and ground-based, remote sensing and in-situ - taking measurements of the ash cloud throughout this period. The dataset comprises of measurements of aerosol and particle layers (upper and lower boundary, height, horizontal extent) and infra-red and visible imagery of the ash cloud." } ], "responsiblepartyinfo_set": [ 52675, 52677, 52680, 52681, 52682, 52683, 54238, 52678 ], "onlineresource_set": [] }, { "ob_id": 13764, "uuid": "7de58a079598413481ac3055d71db95f", "title": "Eyjafjallajokull Volcanic Ash Cloud: NCAS FGAM Instruments", "abstract": "The Icelandic Volcano, Eyjafjallajokull, started erupting on 14th April 2010. The volcanic ash cloud produced covered much of Northern Europe for several weeks causing extensive disruption to air travel. The UK and European atmospheric communities had many instruments - both airborne and ground-based, remote sensing and in-situ - taking measurements of the ash cloud throughout this period. This dataset contains images from Aberystwyth elight and water-vapour lidars, FGAM lidar situated at Cardington and Salford Urban Built-Environment Research Base lidar.\r\n\r\nAsh was seen frequently over Capel Dewi and Cardington during the periods 13th - 23rd April 2010 and 11th - 17th May. The ash tended to occur in single, narrow, uniform layers during the first period but in multiple, thicker, patchy layers during the second period. Work has begun on trying to determine the properties of the ash from the lidar observations. A comparison of the Raman lidar returns at 355 and 387 nm gives the lidar (optical extinction to backscatter) ratio. The unexpectedly (and controversially) large mean values for the April period (182) suggest that the ash particles were much larger and darker than those associated with eruptions of Mount Etna (mean lidar ratio values of 55). DK confirmed that similarly large values were found for observations made by an airborne lidar system.\r\n\r\nThe ultimate aim of this type of work is to be able to define the ash source function, which is required to initiate the dispersion model. For example, how much mass was ejected and to what heights? Moreover, how did the ash particles behave one they are airborne? For example, how quickly, did they start to sediment? DK clarified that high pressure over the British Isles appeared to be the driving force which caused the ash to enter the BL - not sedimentation. In order to improve the interpretation of remote sensing data, more will need to be known about the properties of the ash particles, e.g. their complex refractive index. It may be necessary to improve the lidar scattering models for this type of particle, e.g. to encompass Mie scattering.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2010-05-11T09:03:00", "updateFrequency": "notPlanned", "dataLineage": "A copy of these data were made available to the British Atmospheric Data Centre (BADC) to assist the academic community during this volcanic ash event.", "removedDataReason": "", "keywords": "Eyjafjallajokull, FGAM Instruments", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2014-09-19T13:24:43", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 31, "bboxName": "", "eastBoundLongitude": 10.0, "westBoundLongitude": -20.0, "southBoundLatitude": 40.0, "northBoundLatitude": 70.0 }, "verticalExtent": null, "result_field": { "ob_id": 13765, "dataPath": "/badc/eyjafjallajokull/data/ncas-fgam-instruments/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 12575825, "numberOfFiles": 89, "fileFormat": "Images are PNG formatted" }, "timePeriod": { "ob_id": 513, "startTime": "2010-04-09T23:00:00", "endTime": "2010-08-29T23:00:00" }, "resultQuality": { "ob_id": 437, "explanation": "This is quick look unvetted data.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-09-19" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 13767, "uuid": "7cc04c3259f1481bbd2136ff984459e4", "short_code": "acq", "title": "Eyjafjallajokull Volcanic Ash Cloud NCAS FGAM Instruments", "abstract": "NCAS FGAM Instruments includes Aberystwyth elight and water-vapour lidars, FGAM lidar situated at Cardington and Salford Urban Built-Environment Research Base lidar \r\n\r\n" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 38 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2522, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 13984, "uuid": "27f35145eb7b45b8829602a7e2cf544a", "short_code": "proj", "title": "Eyjafjallajokull Volcanic Ash Cloud Measurements and Imagery", "abstract": "The Icelandic Volcano, Eyjafjallajokull, started erupting on 14th April 2010. 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The UK and European atmospheric communities had many instruments - both airborne and ground-based, remote sensing and in-situ - taking measurements of the ash cloud throughout this period. The dataset comprises of measurements of aerosol and particle layers (upper and lower boundary, height, horizontal extent) and infra-red and visible imagery of the ash cloud." } ], "responsiblepartyinfo_set": [ 52684, 52689, 52690, 52691, 52692, 52686, 52685, 52688 ], "onlineresource_set": [] }, { "ob_id": 13772, "uuid": "e8a3561149c0448fa34bd64f072d69f1", "title": "Relative humidity data from 23 stations on Kilimanjaro (East Africa) over three years", "abstract": "Data were collected under the NERC funded project - The role of land-use change on influencing mountain climate on Kilimanjaro, East Africa (NE/J013366/1) - lead by Dr Nicholas Pepin (University of Portsmouth) which investigated the influence of land-use on surface climate (temperature and moisture availability) on Mount Kilimanjaro in Africa. \r\n\r\nRelative humidity measurements were taken at hourly intervals at 23 stations on Mount Kilimanjaro between September 2012 and September 2015. 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These CDs contain the total ozone and UV radiance data." } ], "responsiblepartyinfo_set": [ 52845, 52846, 52844, 52849, 52850, 52851, 52852, 52847, 52848 ], "onlineresource_set": [ 8323, 8322 ] }, { "ob_id": 13801, "uuid": "672e6e5d9aae4eac805175a80e40b535", "title": "Interrogating Trees as Archives of Environmental Sulphur Variability Project: Historical Sulphur Concentrations and Isotopic Values in tree rings (1840-2012)", "abstract": "This dataset contains sulphur concentrations and isotopic values found in tree rings.\r\n\r\nSamples were collected from several sites in Italy and in the UK.\r\n\r\nIn Italy, samples were collected within a 4km radius of the Ernesto Cave (NE Italian Alps) using 5 and 12 mm diameter increment borers. Standard dendroecological procedures were used to produce absolutely dated records and mean ring-width chronologies. Thirty individual trees were used to build a master chronology for sample cores collected from Abies alba (type of fir tree)). Of the collected cores, two trees (Abies 1, cambial age 160; and Abies 2, cambial age 90) underwent preliminary investigation for sulphur concentration and intra-cellular speciation as a background to developing a method for extracting sulphur isotopes from the same samples. In sampling the trees, no oils, polish wax or lubricant was used to reduce potential contamination from sulphurcontaining compounds.\r\n\r\nWood powders were extracted by carefully drilling 5-year blocks of dated rings to yield a well-mixed, representative sample of approximately 40 mg for sulphur isotope analysis. On a sub-section of the conifer samples, a cold resin extraction was conducted using a 9:1 high purity (Aristar grade) acetone:water mixture for 48 h, followed by multiple washes with hot and cold deionised water to remove the potentially mobile resinous component and any surface bound mobile (soluble) sulphur.\r\n\r\nSamples were also collected in the UK from Beech, Oak, Sycamore and Ash trees at sites near Lancaster, Manchester and Grizedale. Then all samples were analysed by continuous-flow-isotope-ratio mass spectrometry using an Isoprime 100 mass spectrometer linked to an Elementar Pyrocube analyser at the University of Lancaster, Lancaster Environment Centre. \r\n\r\nThe results are presented in this dataset.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-12-16T18:32:04.039660", "updateFrequency": "notPlanned", "dataLineage": "Data provided by P. Wynn in December 2015.", "removedDataReason": "", "keywords": "NERC, sulphur, tree rings, dendrochemistry", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2015-12-16T19:34:28", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 772, "bboxName": "UK and Northern Italy tree rings sites", "eastBoundLongitude": 11.5, "westBoundLongitude": -3.0, "southBoundLatitude": 45.0, "northBoundLatitude": 54.5 }, "verticalExtent": null, "result_field": { "ob_id": 13802, "dataPath": "/badc/nerc-rm2010/data/tree-sulphur-var", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1205950, "numberOfFiles": 4, "fileFormat": "Data are BADC CSV formatted" }, "timePeriod": { "ob_id": 3686, "startTime": "1840-01-01T00:01:15", "endTime": "2012-12-31T00:00:00" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 14269, "uuid": "d8a80d153136474ebc9d288f5a5da06f", "short_code": "acq", "title": "RM2010 - Historical Sulphur Concentrations and Isotopic Values in tree rings (1840-2012)", "abstract": "RM2010 - Historical Sulphur Concentrations and Isotopic Values in tree rings (1840-2012)" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 12274, "uuid": "22bd6d14c5d74b84bd5a0835b9f9fb7a", "short_code": "proj", "title": "Interrogating Trees as Archives of Environmental Sulphur Variability Project", "abstract": "'Give me a tree and I'll read climate history' is the basic premise of dendrochronology, and to a large extent is perfectly true. Each ring within a tree represents one year of growth and contains within it a record of the prevailing environmental conditions. Trees can thus be age dated, and used as a record of climate change through ring-width analysis and chemical composition. \r\n\r\nHowever, chemical interpretations of the nutrient chemistry within each ring have often been subject to much criticism. The basic premise that nutrients which are taken up by the tree are encapsulated to represent environmental conditions for that particular year, is true only for elements which are immobilised from further biological transport accross the width of the tree.\r\n\r\nWe now think we have found such an element which is fixed within the woody tissues during growth and can be used with certainty for environmental reconstruction - this element is sulphur. \r\n\r\nThat sulphur should be the element which is fixed within the annual growth rings is fortuitous given its key role in modulating climate and fantastic potential as an environmental diagnostic tool. The injection of sulphur aerosol into the atmosphere is a key determinant of climate through backscattering and absorption of radiation, and has long been a concern for terrestrial ecology, causing widespread acidification of catchments upon deposition. \r\n\r\nTwo of the key sources of sulphur aerosol injected into the atmosphere are from volcanic and industrial emissions. Both sources can be readily distinguished from background inputs using concentrations and stable isotopes, rendering the sulphur isotopic content of palaeoarchives to be perhaps one of the most important diagnostic elemental signatures available.\r\n \r\nWhilst the sulphur isotopic content of ice cores has been extensively exploited, the more localised archives such as speleothems and tree rings have largely remained beyond the reach of climate change scientists and we have yet to discover many of the secrets they harbour. \r\n\r\nWhilst we have initiated and had excellent success with extracting the sulphur record from speleothems, we believe trees will behave as a much more sensitive, readily available record of local atmospheric change over the past millenium. We believe we are now in a position to conduct an intensive research programme to extract the sulphur isotopic composition of trees and forge ahead with the development of such an important local indicator of sulphur forcing and atmospheric change.\r\n\r\nThis project is funded by the Natural Environment Research Council (NERC) for one and a half year from September 2010 to May 2012 (NERC Reference: NE/H012257/1).\r\n" } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 25966, 89411, 89412, 89413, 89414 ], "vocabularyKeywords": [], "identifier_set": [ 8691 ], "observationcollection_set": [ { "ob_id": 13790, "uuid": "327e87e5123f4d20a1766dca366364b8", "short_code": "coll", "title": "Interrogating Trees as Archives of Environmental Sulphur Variability Project: Sulphur Dendrochemistry measurement collection from trees in Italy and in the UK", "abstract": "Sulphur is an element which is fixed within the woody tissues during growth and can be used with certainty for environmental reconstruction.\r\n\r\nThat sulphur should be the element which is fixed within the annual growth rings is fortuitous given its key role in modulating climate and fantastic potential as an environmental diagnostic tool. The injection of sulphur aerosol into the atmosphere is a key determinant of climate through backscattering and absorption of radiation, and has long been a concern for terrestrial ecology, causing widespread acidification of catchments upon deposition. \r\n\r\nHistorical sulphur concentration and isotopic values obtained from tree cores in Italy and in the UK are presented, spanning the period 1840-2012.\r\n\r\nThis work was funded by NERC (grant NE/H012257/1).\r\n" } ], "responsiblepartyinfo_set": [ 55339, 52853, 52854, 52855, 52860, 52861, 52862, 52863, 54911 ], "onlineresource_set": [ 8325 ] }, { "ob_id": 13804, "uuid": "510b22c6d12e4635b604c172b583167e", "title": "STFC RAL methane retrievals from IASI on board MetOp-A, version 1.0", "abstract": "The Infrared Atmospheric Sounding Interferometer (IASI) methane dataset contains height-resolved and column-averaged volume mixing ratios of atmospheric methane (CH4). It also includes column-averaged water vapour (H2O), a scale factor for the HDO volume mixing ratio profile, surface temperature, effective cloud fraction, effective cloud-top pressure and scale factors for two systematic residual spectra which are jointly retrieved from the spectral range 1232.25-1290.00 cm-1 by the Rutherford Appleton Laboratory (RAL) IASI optimal estimation methane retrieval scheme. The dataset additionally contains selected a priori values and uncertainties adopted in the optimal estimation scheme and retrieval output diagnostics such as the retrieval cost and the averaging kernels.\r\n\r\nThis work was funded by the National Centre for Earth Observation (NCEO) under the UK Natural Environment Research Council (NERC) with additional funding from EUMETSAT.\r\n\r\nData were produced by the Science and Technology Facilities Council (STFC) Remote Sensing Group (RSG) at the Rutherford Appleton Laboratory (RAL).\r\n\r\nThis is version 1.0 of this dataset and is the first to be released.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2016-03-21T06:52:13.454651", "updateFrequency": "notPlanned", "dataLineage": "Data produced by the Rutherford Appleton Laboratory (RAL) Remote Sensing Group (RSG). The development of the Infrared Atmospheric Sounding Interferometer (IASI) offline thermal-IR methane retrieval was funded by the Natural Environment Research Council (NERC) through its National Centre for Earth Observation (NCEO) with additional funding from EUMETSAT.", "removedDataReason": "", "keywords": "methane, IASI, optimal estimation, retrieval, averaging kernels, assimilation", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2016-03-17T13:04:16", "doiPublishedTime": "2016-03-18T15:28:03", "removedDataTime": null, "geographicExtent": { "ob_id": 1, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 14477, "dataPath": "/neodc/iasi_ch4_ral/data/metop-a/l2/tir/v1.0", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 799843801935, "numberOfFiles": 169774, "fileFormat": "Files are formatted in netCDF4." }, "timePeriod": { "ob_id": 3759, "startTime": "2007-05-31T23:00:00", "endTime": "2016-12-31T23:59:59" }, "resultQuality": { "ob_id": 1, "explanation": "See dataset associated documentation", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2012-08-15" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 14467, "uuid": "cafe6ea7f301424aa81624b98401d33e", "short_code": "cmppr", "title": "STFC RAL IASI methane retrieval", "abstract": "Retrieval of methane from MetOp IASI" }, "imageDetails": [ 130 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2522, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 5002, "uuid": "60e718d3f2957f742c89b2b4fc159718", "short_code": "proj", "title": "National Centre for Earth Observation (NCEO)", "abstract": "The National Centre for Earth Observation is a partnership of scientists and institutions, from a range of disciplines, who are using data from Earth observation satellites to monitor global and regional changes in the environment and to improve understanding of the Earth system so that we can predict future environmental conditions.\r\n\r\nNCEO's Vision is to unlock the full potential of Earth observation to monitor, diagnose and predict climate and environmental changes, ensuring that these scientific advances are delivered to the wider community embedded in world class science." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 26276, 61970, 61971, 61972, 61973, 61974, 61975, 61976, 61977, 61978, 61979, 61980, 61981, 61982, 61983, 61984, 61985, 61986, 61987, 61988, 61989, 61990, 61991, 61992, 61993, 61994, 61995, 61996, 61997, 61998, 61999, 62000, 62001, 62002, 62003, 62004, 82411, 82419, 82422, 89119 ], "vocabularyKeywords": [], "identifier_set": [ 8813 ], "observationcollection_set": [ { "ob_id": 14469, "uuid": "bdea6532df314effb9addc6bca1e9f55", "short_code": "coll", "title": "STFC RAL methane retrievals from MetOp IASI", "abstract": "This dataset collection contains various versions of the STFC RAL Infrared Atmospheric Sounding Interferometer (IASI) methane dataset , which contains height-resolved and column-averaged volume mixing ratios of atmospheric methane (CH4). The dataset also includes column-averaged water vapour (H2O), a scale factor for the HDO (water vapour isotopologue) volume mixing ratio profile, surface temperature, effective cloud fraction, effective cloud-top pressure and scale factors for two systematic residual spectra which are jointly retrieved from the spectral range 1232.25-1290.00 cm-1 by the Rutherford Appleton Laboratory (RAL) IASI optimal estimation methane retrieval scheme. The dataset also contains selected a priori values and uncertainties adopted in the optimal estimation scheme and retrieval output diagnostics such as the retrieval cost and the averaging kernels. \r\n\r\nData were produced by the United Kingdom Research and Innovation (UKRI) Science and Technology Facilities Council (STFC) Remote Sensing Group (RSG) at the Rutherford Appleton Laboratory (RAL).\r\n\r\nThe development of the STFC RAL methane retrieval was funded by the Natural Environment Research Council (NERC) through its National Centre for Earth Observation (NCEO) with additional funding from EUMETSAT." }, { "ob_id": 30127, "uuid": "82b29f96b8c94db28ecc51a479f8c9c6", "short_code": "coll", "title": "National Centre for Earth Observation (NCEO) Core datasets", "abstract": "This NCEO Core data set collection contains data generated by the National Centre for Earth Observation core scientific programmes. NCEO is a National Environment Research Council (NERC) research centre with more than 80 scientists distributed across leading UK universities and research organisations and led by Professor John Remedios at the University of Leicester.\r\n\r\nNCEO provides the UK with core expertise in Earth Observation science, data sets and merging techniques, and model evaluation to underpin Earth System research and the UK’s international contribution to environmental science. NCEO scientists work strategically with space agencies, play significant roles in mission planning, and generate internationally-recognised data products from 20 different satellite instruments." } ], "responsiblepartyinfo_set": [ 57367, 56123, 56124, 56125, 56127, 56128, 56192, 56172, 56126, 56193, 56180, 56194, 56195, 56196, 56197, 56198 ], "onlineresource_set": [ 36930, 16173 ] }, { "ob_id": 13805, "uuid": "b42d475e2a344ef9931f10bf60ae6fa8", "title": "Total Ozone Mapping Spectrometer (TOMS): NIMBUS-7 Daily UV Exposure measurements at the Earth's Surface", "abstract": "Data from the Total Ozone Mapping Spectrometer (TOMS), which used backscattered ultraviolet radiance to infer total column ozone measurements (gridded daily for the entire globe). This CD-ROM contains one file for each day from November 1, 1978 to March 6, 1993 (with a few missing days). Each file contains data representing the relative daily areal exposures of ultraviolet (UV) radiation effective in causing skin irritation, computed at each 1 degree latitude by 1.25 degree longitude pixel, between latitudes 65S and 65N. These data were derived from measurements made by NASA's Total Ozone Mapping Spectrometer (TOMS), which was flown aboard the Nimbus-7 satellite.\r\n", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "1999-03-27T21:16:01", "updateFrequency": "notPlanned", "dataLineage": "Data collected by NASA's Total Ozone Mapping Spectrometer (TOMS) and published on CD-ROM. A copy of the data were obtained by the BADC to assist in data access and to ensure long term preservation.", "removedDataReason": "", "keywords": "ATMOSPHERICRADIATION ATMOSPHERE ATMOSPHERICCHEMISTRY", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "1996-12-10T02:16:33", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13806, "dataPath": "/badc/CDs/toms_CDs/nimbus7_toms_uv_exposure", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 631280342, "numberOfFiles": 5313, "fileFormat": "Data are ASCII formatted and images are GIF formatted" }, "timePeriod": { "ob_id": 125, "startTime": "1978-01-11T00:00:00", "endTime": "1993-05-05T23:00:00" }, "resultQuality": { "ob_id": 111, "explanation": "Data were prepared by NASA. Check documentation for further details", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-01-27" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 462, "uuid": "ee8de65a7a3a49d19d58efe9a5958c4f", "short_code": "cmppr", "title": "Composite Process for: TOMS on NIMBUS-7 (1978-1993)", "abstract": "This process is comprised of multiple procedures: 1. Acquisition: Acquisition Process for: TOMS on NIMBUS-7 (1978-1993); \n2. Computation: DETAILS NEEDED - COMPUTATION CREATED FOR SATELLITE COMPOSITE. deployed on NIMBUS 7 Satellite; \n" }, "imageDetails": [ 64 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2521, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 456, "uuid": "4dc6e00a11f3c86bee4161b14470199f", "short_code": "proj", "title": "NASA - National Aeronautics and Space Administration", "abstract": "The National Aeronautics and Space Administration (NASA)'s mission is to pioneer the future in space exploration, scientific discovery, and aeronautics research." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 21771, 22890, 25394, 26002 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 453, "uuid": "80cbbbead55a6e83e9646ecacf9ffb5e", "short_code": "coll", "title": "Total Ozone Mapping Spectrometer (TOMS) - CD-ROM's (version 7): Global Total Column Ozone Measurements", "abstract": "The Total Ozone Mapping Spectrometer (TOMS) is an instrument built and operated by the National Aeronautics and Space Administration (NASA). The instrument uses backscattered ultraviolet radiance to infer total column ozone measurements. The data consists of daily gridded averages of total ozone covering the entire globe. The original Nimbus-7 TOMS operated from November 1978 until May 1993. Meteor-3 TOMS was launched in August 1991 and operated until December 1994. These CDs contain the total ozone and UV radiance data." } ], "responsiblepartyinfo_set": [ 52865, 52866, 52864, 52869, 52870, 52871, 52872, 52868, 52867 ], "onlineresource_set": [ 8328, 8327 ] }, { "ob_id": 13807, "uuid": "f154e848f42041499d17ab85140d875a", "title": "Coupled Ocean Atmosphere and European Climate (COAPEC): Southampton Oeanographic Centre (SOC) Adjusted Climatology data", "abstract": "The Coupled Ocean Atmosphere and European Climate (COAPEC) is a NERC thematic programme designed to examine the variability of the Earth's climate. The goal of COAPEC is to determine the impact on climate, especially European climate, of the coupling between the Atlantic Ocean and the atmosphere. The British Atmospheric Data Centre (BADC) is the primary distribution data centre for COAPEC. This dataset contains adjusted climatology data from the Southampton Oceanographic Centre (SOC).", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T13:15:39", "updateFrequency": "notPlanned", "dataLineage": "To aid researchers within the Coupled Ocean Atmosphere and European Climate (COAPEC) programme, datasets have been retrieved from a variety of coupled models including: The 1000 year HadCM3 dataset has been extracted from the Met Office and these data have been added to the archive at the BADC; The data from a 500 year HadCM3 control integration performed on a linux Beowulf cluster using UM (Unified Model) version 4.5 at the BADC has recently been included in the archive.", "removedDataReason": "", "keywords": "COAPEC, SOC, Climatology", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2001-12-10T03:02:06", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13808, "dataPath": "/badc/coapec/data/soc_flux/adjusted_clim", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 7077404, "numberOfFiles": 13, "fileFormat": "Data are ASCII and netCDF formatted" }, "timePeriod": { "ob_id": 1575, "startTime": "1980-01-01T00:00:00", "endTime": "1993-01-01T00:00:00" }, "resultQuality": { "ob_id": 1415, "explanation": "not known", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-01-25" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 5451, "uuid": "adb18d57a25c49279009b2205c847925", "short_code": "cmppr", "title": "Composite Process for: Data from SOC at Southampton Oeanographic Centre (SOC) for the Coupled Ocean Atmosphere and European Climate (COAPEC) NERC Research Programme Project", "abstract": "This process is comprised of multiple procedures: 1. Computation: SOC deployed on Southampton Oeanographic Centre (SOC); \n" }, "imageDetails": [ 80 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2566, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "coapec", "label": "restricted: coapec group", "licence": { "ob_id": 12, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement.pdf", "licenceClassifications": [ { "ob_id": 4, "classification": "academic" } ] } } ], "projects": [ { "ob_id": 5441, "uuid": "e22b91c35015d34116078ccc25b5026e", "short_code": "proj", "title": "Coupled Ocean Atmosphere and European Climate (COAPEC) NERC Research Programme", "abstract": "COAPEC is a NERC thematic programme designed to examine the variability of the Earth's climate. The goal of COAPEC is to determine the impact on climate, especially European climate, of the coupling between the Atlantic Ocean and the atmosphere. The BADC is the primary distribution data centre for COAPEC. Data sets available under COAPEC include 100 year (2079 - 2178) full fields and 1000 year (1849-2849) limited fields of the Hadley Centre HadCM3 model." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6868, 13197, 20939, 21824, 21919, 21955, 21962, 22320, 22321, 22346, 22390, 22857, 22858, 22859, 22860, 22861, 22862, 22864, 22865, 22866, 22868, 22869, 22870, 22874, 22875, 22876, 25382, 25388, 25392, 25393, 25857, 25859, 25874, 25900, 25905, 25912, 25951, 25952, 25953, 25954, 25955 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 5438, "uuid": "fce964f2c07f107e3db5fb0a5c09c9b8", "short_code": "coll", "title": "Coupled Ocean Atmosphere and European Climate (COAPEC): Monthly Means of Atmospheric and Oceanic Model Data", "abstract": "The COAPEC (Coupled Ocean-Atmosphere Processes and European Climate) programme was a 5 year NERC thematic programme designed to examine the variability of the Earth's climate. Interactions between the oceans and the atmosphere play a major role in governing this variability. The goal of COAPEC was to determine the impact on climate, especially European climate, of the coupling between the Atlantic Ocean and the atmosphere, including the influence of ENSO on this coupling.\r\n\r\nTo aid researchers within the COAPEC programme, datasets have been retrieved from a variety of coupled models.\r\n\r\n* 100 years (2079 - 2178) monthly means of all atmospheric and oceanic fields derived from the control run of the Hadley Centre HadCM3 model.\r\n* 1000 years (1849-2849) of monthly means of selected parameters from the HadCM3 control run.\r\n* 50 years (1950-2000) of MOM (GFDL Modular Ocean Model) data.\r\n* Output from the 100 year HadCM3 control integration produced using UM4.5 on the BADC Beowulf Cluster.\r\n* Surface flux climatology data from SOC\r\n\r\nIf using the 100 year dataset from the Hadley Centre, please be aware that the run was restarted part of the way through. 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Res., 116, D20206, doi:10.1029/2011JD016074] over different climate periods.\r\n\r\nfrequency is daily and monthly. \r\n\r\nDaily Atmospheric variables are:\r\nclt pr psl rlut rsds tas tasmax tasmin tdps uas vas\r\n\r\nMonthly atmos variables:\r\nal clt hfls hfss mrso pr psl rls rlut rsds rsdt rss rsut snld ta tas tasmax tasmin tdps uas vas zg\r\n\r\n", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-11-20T14:23:17", "updateFrequency": "notPlanned", "dataLineage": "Data were supplied by SPECS participants to CEDA for archiving in 2015.", "removedDataReason": "", "keywords": "specs, ifs, ecmwf, climate, model", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2015-12-17T19:03:45", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 528, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13816, "dataPath": "/badc/specs/data/SPECS/output/ECMWF/IFS4/aerosols/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 480712083649, "numberOfFiles": 30295, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 3687, "startTime": "1992-04-30T23:00:00", "endTime": "2012-05-30T23:00:00" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 153 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2528, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 8, "licenceURL": "http://creativecommons.org/licenses/by/4.0/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 12970, "uuid": "c9b4b1fcab734987bcbfb36437734ca7", "short_code": "proj", "title": "Seasonal-to-decadal climate Prediction for the improvement of European Climate Services (SPECS)", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nThe improved understanding and seamless predictions will offer better estimates of the future frequency of high-impact, extreme climatic events and of the prediction uncertainty. New services to convey climate information and its quality will be used.\r\n\r\nSPECS will be, among other things, the glue to coalesce the outcome of previous research efforts that hardly took climate prediction into account. It will ensure interoperability so as to easily incorporate their application in an operational context, provide the basis for improving the capacity of European policy making, industry and society to adapt to near-future climate variations and a coordinated response to some of the GFCS components.\r\n\r\nThis project is funded by the Seventh Framework Programme (FP7) of the European Commission (GA 308378)." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6023, 11044, 11045, 50418, 50426, 50427, 50475, 50496, 50498, 50554, 50555, 50566, 50579, 50591, 50596, 50598, 50603, 50608, 52741, 52747, 52748, 52755, 53094, 53095, 53105, 53128, 53129, 53130, 53131, 53132, 53134, 53135, 53136, 54797 ], "vocabularyKeywords": [], "identifier_set": [ 8694 ], "observationcollection_set": [ { "ob_id": 6086, "uuid": "2d9c5f2cc621fb9bc0062356851b31b9", "short_code": "coll", "title": "SPECS: Seasonal-to-decadal climate prediction model outputs", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nA core set of common experiments has been defined, to which most forecast systems will contribute. Another set of coordinated experiments, tier 1, includes the experiments that one or more forecast systems are planning to run. \r\n\r\nA standard seasonal experimental set up will consist of ten-member ensembles, with two start dates per year (first of May and November) over the 1981-2012 period and seven-month forecast length. \r\n\r\nThe standard decadal experimental set up consists in five-member ensembles, starting on the first of November (or some time close to that date) of the years 1960, 1963, 1965, 1968, 1970, 1973, 1975, 1978, 1980, 1983, 1985, 1988, 1990, 1993, 1995, 1998, 2000, 2003, 2005, 2008, 2010, 2013, with a five-year forecast length. \r\n\r\nA description of the main experiments, with the minimum contribution in terms of start dates, forecast length and ensemble size follows: \r\n1 - Assessment of the impact of soil-moisture initial conditions (seasonal): contributing EC-Earth, IFS/NEMO (ECMWF), CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG);\r\n2 - Assessment of the impact of sea-ice initialization (interannual); contributing EC-Earth (IC3), IPSL-CM5, CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG)\r\n3 - Assessment of impact of increased horizontal resolution (seasonal and decadal); contributing CNRM-CM5 (CERFACS, decadal; MeteoF, seasonal), EC-Earth (IC3, seasonal; KNMI and SMHI, decadal), MPI-ESM (MPG, seasonal and decadal), IPSL-CM5 (decadal), UM (seasonal and decadal); \r\n4 - Assessment of impact of an improved stratosphere (seasonal and decadal) including interannually-varying ozone; contributing EC-Earth (KNMI seasonal with ozone; SMHI decadal), IFS/NEMO (ECMWF, seasonal), CNRM-CM5 (MeteoF, seasonal), UM (seasonal, decadal);\r\n5 - Assessment of impact of additional start dates (decadal); contributing EC-Earth (KNMI, SMHI), MPI-ESM (MPG), IPSL-CM5.\r\n\r\nSPECS research has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under SPECS project (grant agreement n° 308378)." } ], "responsiblepartyinfo_set": [ 52910, 52916, 52909, 52914, 52915, 52918, 52913, 52912, 52911, 54819, 52917 ], "onlineresource_set": [ 8339, 8341 ] }, { "ob_id": 13817, "uuid": "e2fa7ab1d5b34e2b928b23488329ddef", "title": "SPECS - ECMWF-IFS4 Model data prepared for SPECS SnowInit (2004-2014)", "abstract": "This dataset includes the ECMWF-IFS4 model output prepared for SPECS SnowInit (2004-2014). These data were prepared by the European Centre for Medium-range Weather Forecasting (ECMWF), as part of the SPECS project. \r\n\r\nModel id is IFS4 (atmosphere: IFS4(201505212,CY42R1,N128TL255L91); ocean:NEMO3.4.1(L34E5,ORCA1_Z42,1°L42); seaice:N/A; MACC:N/A; land:CHTESSEL,ERA-Interim forcing, lakes, fixed glaciers (CY41R1, internal exp.id gd80, climate.v012); wave:WAM(CY41R1,1°); ozone:Cariolle(v2.9); climversion:climate.v012), no external forcing.\r\n\r\nfrequency is daily and monthly. \r\n\r\nDaily Atmospheric variables are:\r\nclt pr psl rlut rsds tas tasmax tasmin tdps uas vas\r\n\r\nMonthly atmos variables:\r\nal clt hfls hfss mrso pr psl rls rlut rsds rsdt rss rsut snld ta tas tasmax tasmin tdps uas vas zg\r\n\r\n", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-12-11T02:49:07", "updateFrequency": "notPlanned", "dataLineage": "Data were supplied by SPECS participants to CEDA for archiving in 2015.", "removedDataReason": "", "keywords": "specs, ifs, ecmwf, climate, model", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2015-12-17T19:19:25", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 528, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13818, "dataPath": "/badc/specs/data/SPECS/output/ECMWF/IFS4/snowInit/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 2343168101397, "numberOfFiles": 149843, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 3688, "startTime": "2004-11-01T00:00:00", "endTime": "2014-03-31T23:00:00" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 153 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2528, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 8, "licenceURL": "http://creativecommons.org/licenses/by/4.0/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 12970, "uuid": "c9b4b1fcab734987bcbfb36437734ca7", "short_code": "proj", "title": "Seasonal-to-decadal climate Prediction for the improvement of European Climate Services (SPECS)", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nThe improved understanding and seamless predictions will offer better estimates of the future frequency of high-impact, extreme climatic events and of the prediction uncertainty. New services to convey climate information and its quality will be used.\r\n\r\nSPECS will be, among other things, the glue to coalesce the outcome of previous research efforts that hardly took climate prediction into account. It will ensure interoperability so as to easily incorporate their application in an operational context, provide the basis for improving the capacity of European policy making, industry and society to adapt to near-future climate variations and a coordinated response to some of the GFCS components.\r\n\r\nThis project is funded by the Seventh Framework Programme (FP7) of the European Commission (GA 308378)." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6023, 11044, 11045, 50418, 50426, 50475, 50496, 50498, 50554, 50555, 50566, 50579, 50591, 50596, 50598, 50603, 50608, 52741, 52747, 52748, 52755, 53094, 53095, 53105, 53128, 53129, 53130, 53131, 53132, 53133, 53134, 53135, 53136, 54797 ], "vocabularyKeywords": [], "identifier_set": [ 8695 ], "observationcollection_set": [ { "ob_id": 6086, "uuid": "2d9c5f2cc621fb9bc0062356851b31b9", "short_code": "coll", "title": "SPECS: Seasonal-to-decadal climate prediction model outputs", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nA core set of common experiments has been defined, to which most forecast systems will contribute. Another set of coordinated experiments, tier 1, includes the experiments that one or more forecast systems are planning to run. \r\n\r\nA standard seasonal experimental set up will consist of ten-member ensembles, with two start dates per year (first of May and November) over the 1981-2012 period and seven-month forecast length. \r\n\r\nThe standard decadal experimental set up consists in five-member ensembles, starting on the first of November (or some time close to that date) of the years 1960, 1963, 1965, 1968, 1970, 1973, 1975, 1978, 1980, 1983, 1985, 1988, 1990, 1993, 1995, 1998, 2000, 2003, 2005, 2008, 2010, 2013, with a five-year forecast length. \r\n\r\nA description of the main experiments, with the minimum contribution in terms of start dates, forecast length and ensemble size follows: \r\n1 - Assessment of the impact of soil-moisture initial conditions (seasonal): contributing EC-Earth, IFS/NEMO (ECMWF), CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG);\r\n2 - Assessment of the impact of sea-ice initialization (interannual); contributing EC-Earth (IC3), IPSL-CM5, CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG)\r\n3 - Assessment of impact of increased horizontal resolution (seasonal and decadal); contributing CNRM-CM5 (CERFACS, decadal; MeteoF, seasonal), EC-Earth (IC3, seasonal; KNMI and SMHI, decadal), MPI-ESM (MPG, seasonal and decadal), IPSL-CM5 (decadal), UM (seasonal and decadal); \r\n4 - Assessment of impact of an improved stratosphere (seasonal and decadal) including interannually-varying ozone; contributing EC-Earth (KNMI seasonal with ozone; SMHI decadal), IFS/NEMO (ECMWF, seasonal), CNRM-CM5 (MeteoF, seasonal), UM (seasonal, decadal);\r\n5 - Assessment of impact of additional start dates (decadal); contributing EC-Earth (KNMI, SMHI), MPI-ESM (MPG), IPSL-CM5.\r\n\r\nSPECS research has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under SPECS project (grant agreement n° 308378)." } ], "responsiblepartyinfo_set": [ 52928, 52921, 52919, 52923, 52924, 52926, 52927, 52922, 52925, 54823 ], "onlineresource_set": [ 8342, 8343 ] }, { "ob_id": 13819, "uuid": "c206cf8a07164b80ac6d6af5a03f45a3", "title": "SPECS - ECMWF-IFS4 Model data prepared for SPECS SoilMoistureInit (1981-2013)", "abstract": "This dataset includes the ECMWF-IFS4 model output prepared for SPECS SoilMoistureInit (1981-2013). These data were prepared by the European Centre for Medium-range Weather Forecasting (ECMWF), as part of the SPECS project. \r\n\r\nModel id is IFS4 (atmosphere: IFS4(201505212,CY41R1,N128TL255L91); ocean:NEMO3.4.1(L34E5,ORCA1_Z42,1°L42); seaice:N/A; MACC:N/A; land:CHTESSEL,ERA-Interim forcing, active lakes, GPCP correction, carbon fixes (CY40R1, internal exp.id g2ze, climate.v009); wave:WAM(CY41R1,1°); ozone:Cariolle(v2.9); climversion:climate.v010), no external forcing.\r\n\r\nfrequency is daily and monthly. \r\n\r\nDaily Atmospheric variables are:\r\nclt pr psl rlut rsds tas tasmax tasmin tdps uas vas\r\n\r\nMonthly atmos variables:\r\nal clt hfls hfss mrso pr psl rls rlut rsds rsdt rss rsut snld ta tas tasmax tasmin tdps uas vas zg\r\n\r\n", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T03:06:16", "updateFrequency": "notPlanned", "dataLineage": "Data were supplied by SPECS participants to CEDA for archiving in 2015.", "removedDataReason": "", "keywords": "specs, ifs, ecmwf, climate, model", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2015-12-17T19:29:40", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 528, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13820, "dataPath": "/badc/specs/data/SPECS/output/ECMWF/IFS4/soilMoistureInit/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 939955274514, "numberOfFiles": 52801, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 3689, "startTime": "1981-04-30T23:00:00", "endTime": "2013-04-30T23:00:00" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 153 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2528, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 8, "licenceURL": "http://creativecommons.org/licenses/by/4.0/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 12970, "uuid": "c9b4b1fcab734987bcbfb36437734ca7", "short_code": "proj", "title": "Seasonal-to-decadal climate Prediction for the improvement of European Climate Services (SPECS)", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nThe improved understanding and seamless predictions will offer better estimates of the future frequency of high-impact, extreme climatic events and of the prediction uncertainty. New services to convey climate information and its quality will be used.\r\n\r\nSPECS will be, among other things, the glue to coalesce the outcome of previous research efforts that hardly took climate prediction into account. It will ensure interoperability so as to easily incorporate their application in an operational context, provide the basis for improving the capacity of European policy making, industry and society to adapt to near-future climate variations and a coordinated response to some of the GFCS components.\r\n\r\nThis project is funded by the Seventh Framework Programme (FP7) of the European Commission (GA 308378)." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6023, 11044, 11045, 50418, 50475, 50496, 50498, 50554, 50555, 50566, 50579, 50591, 50596, 50598, 50603, 50608, 52741, 52747, 52748, 52755, 53094, 53095, 53105, 53128, 53129, 53130, 53131, 53132, 53133, 53134, 53135, 53136, 54797 ], "vocabularyKeywords": [], "identifier_set": [ 8696 ], "observationcollection_set": [ { "ob_id": 6086, "uuid": "2d9c5f2cc621fb9bc0062356851b31b9", "short_code": "coll", "title": "SPECS: Seasonal-to-decadal climate prediction model outputs", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nA core set of common experiments has been defined, to which most forecast systems will contribute. Another set of coordinated experiments, tier 1, includes the experiments that one or more forecast systems are planning to run. \r\n\r\nA standard seasonal experimental set up will consist of ten-member ensembles, with two start dates per year (first of May and November) over the 1981-2012 period and seven-month forecast length. \r\n\r\nThe standard decadal experimental set up consists in five-member ensembles, starting on the first of November (or some time close to that date) of the years 1960, 1963, 1965, 1968, 1970, 1973, 1975, 1978, 1980, 1983, 1985, 1988, 1990, 1993, 1995, 1998, 2000, 2003, 2005, 2008, 2010, 2013, with a five-year forecast length. \r\n\r\nA description of the main experiments, with the minimum contribution in terms of start dates, forecast length and ensemble size follows: \r\n1 - Assessment of the impact of soil-moisture initial conditions (seasonal): contributing EC-Earth, IFS/NEMO (ECMWF), CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG);\r\n2 - Assessment of the impact of sea-ice initialization (interannual); contributing EC-Earth (IC3), IPSL-CM5, CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG)\r\n3 - Assessment of impact of increased horizontal resolution (seasonal and decadal); contributing CNRM-CM5 (CERFACS, decadal; MeteoF, seasonal), EC-Earth (IC3, seasonal; KNMI and SMHI, decadal), MPI-ESM (MPG, seasonal and decadal), IPSL-CM5 (decadal), UM (seasonal and decadal); \r\n4 - Assessment of impact of an improved stratosphere (seasonal and decadal) including interannually-varying ozone; contributing EC-Earth (KNMI seasonal with ozone; SMHI decadal), IFS/NEMO (ECMWF, seasonal), CNRM-CM5 (MeteoF, seasonal), UM (seasonal, decadal);\r\n5 - Assessment of impact of additional start dates (decadal); contributing EC-Earth (KNMI, SMHI), MPI-ESM (MPG), IPSL-CM5.\r\n\r\nSPECS research has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under SPECS project (grant agreement n° 308378)." } ], "responsiblepartyinfo_set": [ 52937, 52930, 52931, 52929, 52935, 52936, 52934, 52933, 54828 ], "onlineresource_set": [ 8345, 8346 ] }, { "ob_id": 13821, "uuid": "0d549f8edc9442b29e3a6b92c517df0f", "title": "SPECS - MOHC-GloSea5 model output prepared for SPECS aerosols (1992-2012)", "abstract": "This dataset includes the Met Office GloSea5 model output prepared for SPECS aerosols (1992-2012). These data were prepared by the Met Office Hadley Centre, as part of the SPECS project. \r\n \r\nModel id is GloSea5 (GloSea5: HadGEM3 v3.0 (2014); atmosphere: UM (GA3.0) ; ocean: NEMO (v2, ORCA0.25) ; coupler: OASIS3 (v3.3); sea ice: CICE), frequency is daily and monthly. \r\n\r\nDaily Atmospheric variables are:\r\npr psl rls rlut tas tasmax tasmin\r\n\r\nMonthly atmos variables:\r\npr psl ta tas zg\r\n\r\nMonthly seaIce variables:\r\nsic sit snd\r\n\r\nOcean variables:\r\nso thetao tos uo vo\r\n", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T01:49:30", "updateFrequency": "notPlanned", "dataLineage": "Data were supplied by SPECS participants to CEDA for archiving in 2015. Data was checked for compliance with CF standards and SPECS requirements.", "removedDataReason": "", "keywords": "specs, MOHC, GloSea5, climate, model", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2015-12-17T19:40:41", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 528, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13822, "dataPath": "/badc/specs/data/SPECS/output/MOHC/GloSea5/aerosols", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 116928203184, "numberOfFiles": 8449, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 3690, "startTime": "1992-04-30T23:00:00", "endTime": "2012-04-30T23:00:00" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 153 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2528, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 8, "licenceURL": "http://creativecommons.org/licenses/by/4.0/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 12970, "uuid": "c9b4b1fcab734987bcbfb36437734ca7", "short_code": "proj", "title": "Seasonal-to-decadal climate Prediction for the improvement of European Climate Services (SPECS)", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nThe improved understanding and seamless predictions will offer better estimates of the future frequency of high-impact, extreme climatic events and of the prediction uncertainty. New services to convey climate information and its quality will be used.\r\n\r\nSPECS will be, among other things, the glue to coalesce the outcome of previous research efforts that hardly took climate prediction into account. It will ensure interoperability so as to easily incorporate their application in an operational context, provide the basis for improving the capacity of European policy making, industry and society to adapt to near-future climate variations and a coordinated response to some of the GFCS components.\r\n\r\nThis project is funded by the Seventh Framework Programme (FP7) of the European Commission (GA 308378)." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 12334, 12335, 12336, 50426, 50427, 50475, 50496, 50498, 50566, 50569, 50603, 50608, 50623, 50624, 51186, 51187, 52741, 53094, 53095, 53096, 53097, 53098, 53099, 53100, 53101, 53102, 53103, 53104, 53105, 53106, 53107, 53108, 53109, 53110, 53111, 53112, 53113 ], "vocabularyKeywords": [], "identifier_set": [ 8697 ], "observationcollection_set": [ { "ob_id": 6086, "uuid": "2d9c5f2cc621fb9bc0062356851b31b9", "short_code": "coll", "title": "SPECS: Seasonal-to-decadal climate prediction model outputs", "abstract": "SPECS will undertake research and dissemination activities to deliver a new generation of European climate forecast systems, with improved forecast quality and efficient regionalisation tools to produce reliable, local climate information over land at seasonal-to-decadal time scales, and provide an enhanced communication protocol and services to satisfy the climate information needs of a wide range of public and private stakeholders.\r\n\r\nA core set of common experiments has been defined, to which most forecast systems will contribute. Another set of coordinated experiments, tier 1, includes the experiments that one or more forecast systems are planning to run. \r\n\r\nA standard seasonal experimental set up will consist of ten-member ensembles, with two start dates per year (first of May and November) over the 1981-2012 period and seven-month forecast length. \r\n\r\nThe standard decadal experimental set up consists in five-member ensembles, starting on the first of November (or some time close to that date) of the years 1960, 1963, 1965, 1968, 1970, 1973, 1975, 1978, 1980, 1983, 1985, 1988, 1990, 1993, 1995, 1998, 2000, 2003, 2005, 2008, 2010, 2013, with a five-year forecast length. \r\n\r\nA description of the main experiments, with the minimum contribution in terms of start dates, forecast length and ensemble size follows: \r\n1 - Assessment of the impact of soil-moisture initial conditions (seasonal): contributing EC-Earth, IFS/NEMO (ECMWF), CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG);\r\n2 - Assessment of the impact of sea-ice initialization (interannual); contributing EC-Earth (IC3), IPSL-CM5, CNRM-CM5 (MeteoF), UM, MPI-ESM (MPG)\r\n3 - Assessment of impact of increased horizontal resolution (seasonal and decadal); contributing CNRM-CM5 (CERFACS, decadal; MeteoF, seasonal), EC-Earth (IC3, seasonal; KNMI and SMHI, decadal), MPI-ESM (MPG, seasonal and decadal), IPSL-CM5 (decadal), UM (seasonal and decadal); \r\n4 - Assessment of impact of an improved stratosphere (seasonal and decadal) including interannually-varying ozone; contributing EC-Earth (KNMI seasonal with ozone; SMHI decadal), IFS/NEMO (ECMWF, seasonal), CNRM-CM5 (MeteoF, seasonal), UM (seasonal, decadal);\r\n5 - Assessment of impact of additional start dates (decadal); contributing EC-Earth (KNMI, SMHI), MPI-ESM (MPG), IPSL-CM5.\r\n\r\nSPECS research has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under SPECS project (grant agreement n° 308378)." } ], "responsiblepartyinfo_set": [ 52939, 52945, 52938, 52940, 52942, 52943, 52944, 52941, 54832 ], "onlineresource_set": [] }, { "ob_id": 13823, "uuid": "d51e1062534b4429a312b5f52b54a2c9", "title": "Data from the 1.5km70lev configuration of the Met Office UKV NWP model - Release 02/2015", "abstract": "Data from the operational NWP (Numerical Weather Prediction) output from the Variable resolution UK (UKV) part of the Met Office Unified Model. 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This new archive is essentially a mirror of a subset of the NWP archive at the Met Office (as extracted from the Met Office Archive Storage System (MASS)).", "removedDataReason": "", "keywords": "NWP, Met Office, UM, unified model, Global atmospheric model", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "25km grid", "status": "completed", "dataPublishedTime": "2015-12-18T13:45:59", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13834, "dataPath": "/badc/ukmo-nwp/data/global/25km70lev/r2014_01", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 6772337838932, "numberOfFiles": 4205, "fileFormat": "Met Office PP format" }, "timePeriod": { "ob_id": 3702, "startTime": "2014-01-21T00:00:00", "endTime": "2014-07-14T23:00:00" }, "resultQuality": { "ob_id": 991, "explanation": "Operational Numerical Weather Prediction (NWP) data from the Met Office.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-08-30" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 1045, "uuid": "1f9b9fa8e13742318a682c87b27e9c63", "short_code": "comp", "title": "Met Office operational unified model (UM) deployed on Met Office supercomputer (Exeter)", "abstract": "This computation involved: Met Office operational unified model (UM) deployed on Met Office supercomputer (Exeter)." }, "procedureCompositeProcess": null, "imageDetails": [ 69 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2667, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 101, "licenceURL": "https://creativecommons.org/licenses/by-nc-sa/4.0/", "licenceClassifications": [ { "ob_id": 6, "classification": "personal" }, { "ob_id": 4, "classification": "academic" }, { "ob_id": 5, "classification": "policy" } ] } } ], "projects": [ { "ob_id": 555, "uuid": "f46cfa4784fb454e105f336981f1a82b", "short_code": "proj", "title": "Met Office Numerical Weather Prediction (NWP) System", "abstract": "All forecasts, of whatever type, are ultimately based on the predictions from the Met Office suite of sophisticated atmospheric and oceanic models, run on their powerful supercomputer. This form of forecasting is known as numerical weather prediction (NWP). Numerical weather prediction (NWP) is the process of obtaining an objective forecast of the future state of the atmosphere by running a computer model. The Met Office Unified Model is run operationally, in a number of configurations, for weather forecasting at the Met Office." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 2730, 2731, 2732, 2733, 2734, 2735, 2736, 2737, 2738, 2743, 2744, 2745, 2746, 2747, 2748, 2749, 2750, 2751, 2752, 2753, 2756, 2757, 2758, 2760, 2761, 2763, 2764, 2765, 2766, 2769, 2770, 2771, 2777, 2787, 2790, 2791, 2796, 2799, 2802, 2803, 2804, 2807, 2817, 2818, 2820, 2823, 2825, 2826, 2827, 2828, 2829, 2830, 2831, 2832, 2833, 2834, 2835, 2836, 2837, 2839, 2840, 2841, 2842, 2843, 2844, 2845, 2847, 2848, 2849, 2850, 2853, 2854, 2855, 2856, 2857, 2858, 2859, 2862, 2868, 2869, 2873, 2874, 2875, 2876, 2877, 2878, 2880, 2881, 2882, 2889, 2890, 2891, 2892, 2893, 2894, 2911, 2912, 2920, 2942, 2950, 2957, 2968, 2980, 3349, 3350, 3351, 3352, 3353, 3354, 3355, 3356, 6643, 6644 ], "vocabularyKeywords": [], "identifier_set": [ 8710 ], "observationcollection_set": [ { "ob_id": 3939, "uuid": "41f061e11217e549a498971725e90520", "short_code": "coll", "title": "Operational Numerical Weather Prediction (NWP) Output from the Global Atmospheric Part of the Met Office Unified Model (UM)", "abstract": "This dataset contains operational NWP (Numerical Weather Prediction) output from the global atmospheric part of the Met Office global atmospheric Unified Model.\r\n\r\nThe Met Office Unified Model is the numerical modelling system developed and used at the Met Office (it is run operationally for weather forecasting). It is 'seamless' in that different configurations of the same model are used across all time and space scales.\r\n\r\nThis model can produce several datasets of which CEDA holds the following:\r\n\r\n Met Office Global Atmospheric Model data\r\n Met Office North Atlantic/European (NAE) Mesoscale Model data \r\n\r\nThe Met Office Global Atmospheric Model has 25 km resolution with 70 vertical levels. It Covers the entire globe and 144 hours in the future twice a day. The Global model provides boundary information for the NAE model, for which additional shorter runs (48 hours) are produced twice a day. The model is kept close to the real atmosphere using hybrid 4D-Var data assimilation of observations. 17km resolution with 70 vertical levels is now also available.\r\n\r\nAnalyses and first forecast steps are stored to give a time resolution of 1 hour up to 6 hours after each analysis timestep.\r\n\r\nThe NWP global output archive starts on 1 January 2012, and is ongoing. " }, { "ob_id": 1042, "uuid": "220f1c04ffe39af29233b78c2cf2699a", "short_code": "coll", "title": "Operational Numerical Weather Prediction (NWP) Output from the North Atlantic European (NAE) Part of the Met Office Unified Model (UM)", "abstract": "Data from the operational NWP (Numerical Weather Prediction) output from the North Atlantic European (NAE) part of the Met Office Unified Model. The NAE model runs on a grid centred around the UK. Analyses and first forecast steps are stored to give an hourly resolution for 6 hours following each analysis time-step. This archive currently holds data from January 2012 onwards but data will be back populated for earlier years." } ], "responsiblepartyinfo_set": [ 52987, 52992, 52993, 52994, 52988, 52989, 52990, 52991, 54829, 168615 ], "onlineresource_set": [ 8368 ] }, { "ob_id": 13832, "uuid": "c0455ab814224a05ac74642d3d44b73e", "title": "Gridded Global Surface Ozone Metrics data (1971-2015) for Atmospheric Chemistry Model Evaluation - version 2.7", "abstract": "This dataset consists of version 2.7 gridded surface ozone metrics for atmospheric chemistry model evaluation. These data have global coverage on both monthly and annual timescales from 1971-2015. Multiple model resolutions were used and can be easily identified within the filename. \r\n\r\nData are stored as NetCDF-4 files, with one file per model resolution at each time resolution. The files hold gridded surface ozone data from multiple databases (WMO GAW, EPA CASTNET, EPA AQS, Canadian CAPMON, Canadian NAPS, European EMEP, European AirBase, East Asian Acid Deposition Monitoring Network EANET), plus metadata. Metrics include the moments of the distribution, percentiles, maximum daily eight-hour average (MDA8), SOMO35, AOT40, and metrics related to air quality regulatory thresholds. In addition, metadata for all contributing sites (e.g. Site name, latitude, longitude) are included in each file.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-12-21T11:18:19.729171", "updateFrequency": "notPlanned", "dataLineage": "Data were processed by the authors and delivered to CEDA for archiving. It appears that the file CCMI_SurfaceOzoneObs_1x1a_Annual_v2.7.nc is a compressed tar archive (usually filename extension given as a .tar.gz), but in this instant it has been incorrectly given the filename extension .nc. Even though the file is only 128MB when compressed, it expands to 21GB of uncompressed data, consisting of all the other netCDF files that are present in the same directory, /badc/proc-earth-model/data/ozone-metrics/v2.7. However, it does not contain a netCDF file called CCMI_SurfaceOzoneObs_1x1a_Annual_v2.7.nc and unfortunately not available for archiving.", "removedDataReason": "", "keywords": "Ozone", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "various grid resolutions", "status": "completed", "dataPublishedTime": "2015-12-21T12:06:24", "doiPublishedTime": "2016-02-02T10:21:30", "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": 13833, "dataPath": "/badc/proc-earth-model/data/ozone-metrics/v2.7", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 14159289740, "numberOfFiles": 18, "fileFormat": "NetCDF" }, "timePeriod": { "ob_id": 3336, "startTime": "1970-12-31T23:00:00", "endTime": "2015-12-31T23:59:59" }, "resultQuality": null, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2522, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 12368, "uuid": "0a5fb98570a0459fb326deb173f50b2f", "short_code": "proj", "title": "Process Based Earth System Model (ESM) Evaluation", "abstract": "This project was funded by the Natural Environment Research Council (NERC) with the grant reference - NE/K016008/1 - led by Professor Mathew Evans (University of York).\r\n\r\nClimate change and air pollution are two of the biggest challenges facing humanity today. Ozone and particulate matter are pollutants that are particularly harmful to human health. Recent studies have suggested that in the UK alone they cause 50,000 extra deaths and result in a financial burden of 8-22 billion pounds per year. Both ozone and particulate matter also play an important role in climate change. Ozone absorbs infra-red radiation resulting in a warming of the climate. Particles scatter and absorb incoming solar radiation and alter the properties of clouds. This results in complex interactions with the Earth's climate, with some types of aerosol pollution warming climate whereas others cool climate. Future air quality depends both on changes to emissions of pollutants and to changes in climate. Furthermore, a warming climate can result in worsened air pollution, which in turn can drive additional warming, meaning that complex feedbacks are possible between air pollution and climate.\r\n\r\nTo help understand these complex interactions and feedbacks scientists have developed Earth System Models that include a description of the important physical and biogeochemical processes. These models are increasingly being used by policy makers to make predictions about future air quality and climate and to guide policy decisions. It is therefore important that the models are rigorously tested. \r\n\r\nThis testing involves using detailed observations of atmospheric composition that have been made over the past few decades at locations around the world. Most model evaluation to date has involved testing whether the models simulate current average concentrations of atmospheric pollutants. Whilst this is a useful and necessary first step in model evaluation it does not test whether the model accurately simulates the change in concentration of a pollutant under changing emissions or changing climate. For example, does the model capture the real-world change in concentrations of a pollutant given a particular change in emission or under a future climate change scenario? This is particularly important as these predictions under-pin policy recommendations for air quality abatement. \r\n\r\nThis project synthesised long-term (multi-decadal) observations of ozone and particulate matter and their atmospheric precursors. They used these observations to explore trends and variability that have been observed over the past few decades. A model-observation framework was developed that can be used to evaluate how well models simulate observed variability and trends. The project tested state-of-the-art Earth System Models using existing model output from model intercomparison exercises. Finally, they explored the model processes that are driving simulated variability and trends.\r\n\r\nThe results inform the scientific community as to the fidelity of Earth System Models. This project helped to improve our models and give us more confidence in our predictions.\r\n\r\nThe overall objective of this project was to develop and implement a framework capable of evaluating the sensitivity of atmospheric composition simulated by ESMs to changing climate and emissions. \r\n\r\nOur scientific objectives were to:\r\n\r\nO1. Develop observationally-based metrics and relationships with which to evaluate variability and trends in atmospheric composition and its drivers in ESMs. \r\n\r\nO2. Understand the sensitivity of observed and simulated atmospheric composition to environmental drivers.\r\n\r\nO3. Quantify the ability of ESMs to capture observed temporal variability and trends in atmospheric composition.\r\n\r\nO4. Improve our understanding of the processes driving observed variability in atmospheric composition." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 25394, 50542, 50543, 63576, 83653, 83654, 83655, 83656, 83657, 83658, 83659, 83660, 83661, 83662, 83663, 83664, 83665, 83666, 83667, 83668, 83669, 83670, 83671, 83672, 83673, 83674, 83675, 83676 ], "vocabularyKeywords": [], "identifier_set": [ 8771 ], "observationcollection_set": [ { "ob_id": 12398, "uuid": "5af3f51efc1d46c88d35be217b20fad3", "short_code": "coll", "title": "Process Based Earth System Model Evaluation: Gridded Global Surface Ozone Metrics and Precursor species data collection for Atmospheric Chemistry Model Evaluation", "abstract": "This dataset collection presents a global surface ozone compilation for long-term trends and ESM (Earth System Model) evaluation.\r\n\r\nThe project (Process Based Earth System Model Evaluation) brought together all publicly available surface ozone observations from online databases from the modern era to build a consistent dataset for the evaluation of chemical transport and chemistry-climate (Earth System) models for projects such as the Chemistry-Climate Model Initiative (CCMI) and Aer-Chem-MIP. \r\n\r\nFrom a total dataset of approximately 6600 sites and 500 million hourly observations from 1971-2015, approximately 2200 sites and 200 million hourly observations pass screening as high-quality sites in regional background locations that are appropriate for use in global model evaluation. There was generally good data volume in the datasets since the start of air quality monitoring networks in 1990 through to 2013. Ozone observations are biased heavily toward North America and Europe with sparse coverage over the rest of the globe. \r\n\r\nThis dataset collection was made available for the purposes of model evaluation as a set of gridded metrics intended to describe the distribution of ozone concentrations on monthly and annual timescales. This collection currently holds version 2.4 data only, but future versions may follow." } ], "responsiblepartyinfo_set": [ 53001, 52999, 52997, 53000, 52998, 52996, 53002, 143585, 52995 ], "onlineresource_set": [ 8357, 8359, 8358, 94660 ] }, { "ob_id": 13835, "uuid": "8e6cf60c24104ffc935479d46ae9b9d2", "title": "Data from the 17km70lev configuration of the Met Office Global NWP model - Release 07/2014", "abstract": "Data from the operational NWP (Numerical Weather Prediction) output from the global atmospheric part of the Met Office Unified Model. Analyses and first forecast steps are stored to give an hourly time resolution for 6 hours following each analysis time-step. 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This form of forecasting is known as numerical weather prediction (NWP). Numerical weather prediction (NWP) is the process of obtaining an objective forecast of the future state of the atmosphere by running a computer model. The Met Office Unified Model is run operationally, in a number of configurations, for weather forecasting at the Met Office." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 2730, 2731, 2732, 2733, 2734, 2736, 2737, 2738, 2743, 2744, 2745, 2746, 2747, 2748, 2749, 2750, 2751, 2752, 2753, 2756, 2757, 2758, 2760, 2761, 2763, 2764, 2765, 2766, 2769, 2770, 2771, 2777, 2790, 2791, 2796, 2799, 2802, 2803, 2807, 2817, 2818, 2820, 2823, 2825, 2826, 2827, 2828, 2829, 2830, 2831, 2832, 2833, 2834, 2835, 2836, 2837, 2839, 2840, 2841, 2842, 2843, 2844, 2845, 2847, 2848, 2849, 2850, 2853, 2854, 2855, 2856, 2857, 2858, 2859, 2862, 2868, 2873, 2874, 2875, 2876, 2877, 2878, 2880, 2881, 2882, 2889, 2890, 2891, 2892, 2911, 2912, 2920, 2942, 2950, 2957, 2968, 2980, 3349, 3350, 3351, 3352, 3353, 3354, 3355, 3356, 6643, 6644 ], "vocabularyKeywords": [], "identifier_set": [ 8714 ], "observationcollection_set": [ { "ob_id": 3939, "uuid": "41f061e11217e549a498971725e90520", "short_code": "coll", "title": "Operational Numerical Weather Prediction (NWP) Output from the Global Atmospheric Part of the Met Office Unified Model (UM)", "abstract": "This dataset contains operational NWP (Numerical Weather Prediction) output from the global atmospheric part of the Met Office global atmospheric Unified Model.\r\n\r\nThe Met Office Unified Model is the numerical modelling system developed and used at the Met Office (it is run operationally for weather forecasting). It is 'seamless' in that different configurations of the same model are used across all time and space scales.\r\n\r\nThis model can produce several datasets of which CEDA holds the following:\r\n\r\n Met Office Global Atmospheric Model data\r\n Met Office North Atlantic/European (NAE) Mesoscale Model data \r\n\r\nThe Met Office Global Atmospheric Model has 25 km resolution with 70 vertical levels. It Covers the entire globe and 144 hours in the future twice a day. The Global model provides boundary information for the NAE model, for which additional shorter runs (48 hours) are produced twice a day. The model is kept close to the real atmosphere using hybrid 4D-Var data assimilation of observations. 17km resolution with 70 vertical levels is now also available.\r\n\r\nAnalyses and first forecast steps are stored to give a time resolution of 1 hour up to 6 hours after each analysis timestep.\r\n\r\nThe NWP global output archive starts on 1 January 2012, and is ongoing. " }, { "ob_id": 1042, "uuid": "220f1c04ffe39af29233b78c2cf2699a", "short_code": "coll", "title": "Operational Numerical Weather Prediction (NWP) Output from the North Atlantic European (NAE) Part of the Met Office Unified Model (UM)", "abstract": "Data from the operational NWP (Numerical Weather Prediction) output from the North Atlantic European (NAE) part of the Met Office Unified Model. The NAE model runs on a grid centred around the UK. Analyses and first forecast steps are stored to give an hourly resolution for 6 hours following each analysis time-step. This archive currently holds data from January 2012 onwards but data will be back populated for earlier years." } ], "responsiblepartyinfo_set": [ 53006, 53007, 53011, 53008, 53009, 53012, 53013, 53010, 54833, 168624 ], "onlineresource_set": [ 8369 ] }, { "ob_id": 13837, "uuid": "184178016a654c7ba6d961593783f67e", "title": "Data from the 17km70lev configuration of the Met Office Global NWP model - Release 02/2015", "abstract": "Data from the operational NWP (Numerical Weather Prediction) output from the global atmospheric part of the Met Office Unified Model. Analyses and first forecast steps are stored to give an hourly time resolution for 6 hours following each analysis time-step. This archive currently holds data from January 2012 onwards but data will be back populated for earlier years.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-06-17T16:04:33.902076", "updateFrequency": "notPlanned", "dataLineage": "Following data transfer issues between the Met Office and the BADC, the Met Office NWP data updates were suspended on 18th January 2012. A new data transfer route was established and at the same time, CEDA-BADC decided to revamp the entire NWP archive and created a new NWP archive. 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This includes the occurrence of floods and droughts, of heat waves and cold spells. The project examines the largest source of year-to-year climate variability on Earth, namely, El Niño. The El Niño is a warm ocean current that appears off the coast of NW South America every 3-5 years, and it is a result of a much larger scale phenomenon involving changes to the winds, rainfall, temperature and ocean currents across the whole of the tropical Pacific. The larger scale phenomenon is known as the El Niño Southern Oscillation, a name which reflects the fact that it involves a natural cycle in the circulation of both the atmosphere and the surface ocean and how they interact. Although we know that ENSO originates in the tropical Pacific, it has near world-wide impacts because of the way it affects the circulation of the atmosphere, and hence the winds and transport of moisture from the tropics to the extra-tropics. Floods and droughts and changed incidence of storminess from El Niño directly affect the lives and livelihoods of well over a billion people, and major El Niño events are associated with tens of thousands of human deaths, billions of pounds of damage, and devastation to some natural ecosystems such as coral reefs. Even Europe experiences changed weather patterns associated with ENSO! Although we now understand quite well the basic mechanisms behind the ENSO cycle, some major questions remain. In particular, we do not understand why some El Niño events are much stronger than others, why some decades show much stronger El Niño activity, or how ENSO will respond to climate change. To help answer some of these questions, we will reconstruct changes in ENSO over the past 5,000 years by analysing growth rings in the skeletons of old dead ('fossil') corals that lived in the Galápagos. The Galápagos Islands experience extreme changes in weather associated with El Niño (warmer and wetter during events), and these changes are recorded in the chemistry of the skeletons of corals living in the surrounding ocean. Some of these corals live for up to a hundred years, or longer, laying down layers of skeleton a bit like tree rings. We will collect cores through old dead corals, including some that lived thousands of years ago. Then, by analysing the chemistry of their growth bands we will be able to reconstruct the changes in climate, and ENSO, that the corals experienced during their life time. By combining the records from many such corals we will build up a picture of the natural variability in ENSO, helping us see how often major events occurred, and how much decade-to-decade variability in ENSO occurred. These coral records can let us reconstruct the history of past changes in ENSO, but on their own they do not help us to understand the causes of the changes. Were they due to changes in the sun's radiation? Or due to the cooling effects of major volcanic eruptions? Or were they simply random variations that we should expect without any sort of trigger? To answer these questions, we need to use climate models. The same models that we now use to predict future climate can be used to research changes in ENSO. In our work, we used the most up-to-date climate models to see if they can correctly replicate the observed changes in ENSO over the past few thousand years as defined by our coral records. We can also saw what the effects are of changing volcanic eruptions, solar radiation and greenhouse gases in these models. By comparing the model results with the coral records we gained a better understanding of the nature and causes of changes in ENSO, and the skill of the models at predicting this. " } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 4385, 9042, 9043, 9045, 51157, 51158, 57181, 57182, 57183, 57184, 57185, 57186 ], "vocabularyKeywords": [], "identifier_set": [ 8727 ], "observationcollection_set": [ { "ob_id": 7448, "uuid": "6b71fed2cda829ade4dd61d0f2377d17", "short_code": "coll", "title": "QPENSO: HadCM3 model simulations output collection", "abstract": "Model simulations undertaken by the Quantifying variability of the El Nino Southern Oscillation on adaptation-relevant time scales using a novel palaeodata-modelling approach (QPENSO) project. These are coupled ocean-atmosphere experiments with a modified version of the HadCM3 (UM version 4.5) climate model. The model has been modified to include stable isotopes of oxygen in both the ocean and atmosphere sub-models, after Tindall et al., 2009. 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The six simulations represent an initial-condition ensemble over this interval.\r\nThis project was funded by NERC under grant NE/H009957/1." } ], "responsiblepartyinfo_set": [ 53052, 53053, 53051, 53055, 53056, 53057, 53054, 53059, 53058 ], "onlineresource_set": [ 8393 ] }, { "ob_id": 13845, "uuid": "4c810bfa53d14595a87a6e0eeb9c6d7d", "title": "Top‐down isoprene emissions over tropical South America inferred from SCIAMACHY and OMI formaldehyde columns: High-Resolution Chemistry Model Simulations and Analysis", "abstract": "The Quantifying the Amazon Isoprene Budget: Reconciling Top-down versus Bottom-up Emission Estimates project produced a unique high resolution model (GEOS-Chem version v8-03-01 - with modifications) for the Amazon, which simulated isoprene emissions and atmospheric chemistry. \r\n\r\nFormaldehyde (HCHO) vertical column measurements from the Scanning\r\nImaging Absorption spectrometer for Atmospheric Cartography (SCIAMACHY) and\r\nOzone Monitoring Instrument (OMI), and a nested-grid version of the GEOS-Chem\r\nchemistry transport model, are used to infer an ensemble of top-down isoprene emission estimates\r\nfrom tropical South America during 2006, using different model configurations and\r\nassumptions in the HCHO air-mass factor (AMF) calculation. Scenes affected by biomass\r\nburning are removed on a daily basis using fire count observations, and the local\r\nmodel sensitivity was used to identify locations where the impact of spatial smearing is small,\r\nthough this comprises spatial coverage over the region\r\n\r\nResults of this project are presented in the following publication:\r\n\r\nBarkley, M. P., et al. (2013), Top-down isoprene emissions over tropical South America inferred from SCIAMACHY and OMI formaldehyde columns, J. Geophys. Res. Atmos., 118, 6849–6868, doi:10.1002/jgrd.5055\r\n\r\nand model outputs associated to this project are archived at CEDA.\r\n\r\nThis was a NERC funded project.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2020-05-04T21:02:18", "updateFrequency": "notPlanned", "dataLineage": "Data provided as is by M. Barkley in March 2015.", "removedDataReason": "", "keywords": "amazon, isoprene, HCHO, AMF, GEOS-Chem, NERC", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "0.667 × 0.5", "status": "completed", "dataPublishedTime": "2015-12-19T14:31:25", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 773, "bboxName": "Barkley Amazon project", "eastBoundLongitude": -30.0, "westBoundLongitude": -85.0, "southBoundLatitude": -25.0, "northBoundLatitude": 14.0 }, "verticalExtent": null, "result_field": { "ob_id": 13846, "dataPath": "/badc/nerc-rm2010/data/amazon-isoprene/Barkley.jgr.2013", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 1486842655451, "numberOfFiles": 120140, "fileFormat": "Typically GEOS-Chem binary-punch outputs *.bpch.\r\nOther files are straight binary ending in *.bin." }, "timePeriod": { "ob_id": 3708, "startTime": "2006-01-01T00:00:00", "endTime": "2006-12-31T00:00:00" }, "resultQuality": { "ob_id": 952, "explanation": "", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-09-22" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 14309, "uuid": "b87ff15e75a04958be1b951893fbdeeb", "short_code": "comp", "title": "Quantifying the Amazon Isoprene Budget: GEOS-Chem Chemistry Transport Model", "abstract": "GEOS-Chem Chemistry Transport Model. The nest-grid has a horizontal resolution of 0.667° × 0.5° (longitude × latitude), and 47 vertical levels extending from the surface to 0.01 hPa. The model is driven using GEOS-5 meteorology, which is updated every 3–6 hours. Tracer mixing ratios from an off-line global 4° × 5° simulation provide 3-hourly boundary conditions to the grid-edges. Based on a previous model evaluation [Barkley et al., 2011], we use an updated chemical mechanism to simulate O3-NOx-VOC-aerosol photochemistry." }, "procedureCompositeProcess": null, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2543, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 12272, "uuid": "384c5deb0dd3431daa2e18dce94bede0", "short_code": "proj", "title": "Quantifying the Amazon Isoprene Budget: Reconciling Top-down versus Bottom-up Emission Estimates Project", "abstract": "The term climate change is now a household phrase and we are used to hearing about rising greenhouse gas levels and global warming. One of the first events that increased the public's awareness of environmental issues was the discovery of the Antarctic ozone hole in the 1980s. Ozone is a gas that comprises only a tiny fraction of all the gases that make up the atmosphere but it is very important in climate. At high altitudes (about 15 to 30 km), there is lots of ozone which is good thing for the planet, as it shields the Sun's harmful UV radiation. However, ozone is a toxic substance and if it builds up within the troposphere (the lowermost part of the atmosphere) and at the surface then this is not good. Tropospheric ozone is bad for us because it is (a) a greenhouse gas, and (b) and air pollutant that affects the human respiratory system and agricultural crop yields. Ozone is produced near the surface when substances known as volatile organic compounds (VOCs) are emitted from the surface and subsequently react within the atmosphere. VOCs can be emitted from human activities, but they are predominantly emitted by vegetation that grows on land. Of all the biogenic VOCs emitted into the atmosphere, none is more important than isoprene owing to its ability to quickly react with other compounds (to produce tropospheric ozone) and because it is emitted in large amounts. Isoprene is also important, as it is a source of very small particles called secondary organic aerosol (SOA) that scatter light, which influences how the Earth warms, and which also have adverse health effects. We need to know (a) when, (b) where and (c) how much isoprene is emitted into the atmosphere in order to better understand tropospheric ozone and SOA. Currently we use generic computer models that are based on observations to simulate the amount of isoprene emitted from different types of vegetation, such as trees or grasses. Isoprene emissions from the Amazon Basin, which contains the world's largest rain forest and is thought to be one of the biggest isoprene sources, are poorly quantified since it is very difficult to measure the emissions in this largely inaccessible and remote region. Satellite observations of a gas called formaldehyde (HCHO), contain information on isoprene emissions, and can be used to determine the amount of isoprene emitted from terrestrial vegetation. The overall goal of my proposal is to use satellite observations of HCHO to accurately quantify isoprene emissions from the Amazon Basin. To achieve this goal I will develop a new unique high resolution model for the Amazon, which will be able to simulate isoprene emissions and atmospheric chemistry at finer spatial scales than have been able previously. I will then compare the isoprene emissions from this 'bottom-up' model with the 'top-down' isoprene emissions inferred from the satellite observations of HCHO, to identify regions or time periods where there is significant disagreement between the model and the observations, which highlights where we have poor understanding of the isoprene emissions. I will then develop an improved isoprene emission model by fine tuning the 'bottom-up' emission model to the inferred 'top-down' emissions, taking into account individual scenes (utilizing the high spatial resolution of the nested-grid) and different seasons. By reconciling the differences between the 'bottom-up' model and the 'top-down' emissions we will gain a more accurate estimate of how much isoprene is emitted from the Amazon, and more importantly gain a better understanding of the factors that influence when it is emitted. This research is important because the Amazon Basin is also one of the regions identified as being most susceptible to climate change, and it is crucial we determine the key factors that influence its isoprene emissions in order to improve confidence in our ability to predict future climate. \r\n\r\nObjectives: \r\n\r\n1) Develop a high resolution, nested-grid chemistry-transport model, centred over the Amazon, which will be driven using two bottom-up isoprene emission models that are based on fundamentally different approaches to simulate isoprene fluxes \r\n\r\n2) Compare the simulated isoprene emissions and oxidation products, from the two bottom-up inventories, against each other and in situ observations to assess which is more accurate \r\n\r\n3) Optimally estimate Amazon isoprene emissions using a Bayesian approach constrained by satellite observations of formaldehyde \r\n\r\n4) Develop emission model parameterizations that will reconcile the spatial and temporal differences between the top-down and bottom-up estimates \r\n\r\n5) Quantify the difference of the bottom-up and top-down isoprene emissions on the Amazonian atmospheric chemistry\r\n\r\nThis project was funded by NERC under grant NE/G013810/1." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 21971 ], "vocabularyKeywords": [], "identifier_set": [ 8728 ], "observationcollection_set": [ { "ob_id": 3823, "uuid": "387ca240c6585dabd158a06b2ce4af4b", "short_code": "coll", "title": "Quantifying the Amazon Isoprene Budget: Reconciling Top-down versus Bottom-up Emission Estimates Project: High-Resolution Chemistry Model data for the Amazon basin.", "abstract": "The Quantifying the Amazon Isoprene Budget: Reconciling Top-down versus Bottom-up Emission Estimates project ran a unique high resolution model for the Amazon basin, able to simulate isoprene emissions and atmospheric chemistry. Model outputs are available through CEDA. This was a NERC funded project (NE/G013810/1)." } ], "responsiblepartyinfo_set": [ 53072, 53075, 53074, 53071, 53076, 53077, 53078, 53073, 54826 ], "onlineresource_set": [ 8401 ] }, { "ob_id": 13848, "uuid": "3ab1423a6b8d43afa7199b0331e1d65f", "title": "HADRT2.1: Bias adjusted global monthly fields of radiosonde temperature anomalies (1958-2004)", "abstract": "The HADRT2.1 data are global monthly fields of radiosonde temperature anomalies at standard pressure levels on a 5 degree latitude by 10 degree longitude grid from 1958 to July 2004. \r\nAnomalies are calculated with respect to 1971-1990 climatology. Anomalies are available for 9 standard levels (850, 700, 500, 300, 200, 150, 100, 50, 30hPa) as well as tropospheric (850 - 300hPa) and stratospheric (150 - 30hPa) averages.\r\nThe data are degree Celsius anomalies from 1970-1990 means. Anomalies are calculated for each of about 200 sonde stations worldwide and grid values derived from these. \r\n\r\nHADRT2.1 is as HadRT2.0 but with bias corrections made to many station time series world-wide. The adjustments were calculated by reference to MSU data products, but only for known changes in instrumental or operational procedures for the period post 1979. No data are available for the 30hPa level in this version. \r\n\r\nThis dataset has been superseded by the HadAT dataset also available from CEDA.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2004-11-29T16:57:21", "updateFrequency": "notPlanned", "dataLineage": "Data obtained for the period from 1958 to July 2004, were provided as is by the Met Office Hadley Centre, for archiving at the BADC.", "removedDataReason": "", "keywords": "Met Office, HADRT, radiosonde, temperature anomalies, Hadley", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "5x10 grid", "status": "obsolete", "dataPublishedTime": "2015-12-19T18:12:30", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13849, "dataPath": "/badc/ukmo-hadrt/data/HadRT2.1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 143952956, "numberOfFiles": 10, "fileFormat": "The data are ASCII formatted (plain text and \"human\" readable) see Met Office HadRT2.1 data format information in docs for more information.\r\n" }, "timePeriod": { "ob_id": 593, "startTime": "1958-01-01T00:00:00", "endTime": "2004-07-30T23:00:00" }, "resultQuality": { "ob_id": 517, "explanation": "Data quality controlled by the Met Office. Please see main reference paper for this dataset.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-06-09" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 14351, "uuid": "db186b9ce9804ab8a39be21087c7a938", "short_code": "cmppr", "title": "HadRT2.1: Composite data production process for HadRT2.1", "abstract": "HadRT2.1 data are radiosonde temperature anomalies." }, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2568, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "hadrt", "label": "restricted: hadrt group", "licence": { "ob_id": 12, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement.pdf", "licenceClassifications": [ { "ob_id": 4, "classification": "academic" } ] } } ], "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": [ 21787, 25388, 25877 ], "vocabularyKeywords": [], "identifier_set": [ 8731 ], "observationcollection_set": [ { "ob_id": 2207, "uuid": "05f97d2d38abf207abafe96871bca91f", "short_code": "coll", "title": "Met Office Global Radiosonde Gridded Temperature Anomalies (1958-July 2004) (HadRT) Dataset", "abstract": "The HADRT data are global radiosonde gridded temperature anomalies at standard levels in the troposphere and in the lower stratosphere from 1958 to July 2004. The data are degree Celsius anomalies from 1970-1990 means. Anomalies are calculated for each of about 200 sonde stations worldwide and grid values derived from these. \r\n\r\nSeveral versions of the HadRT data are available. The recommended HadRT product for most purposes is HadRT2.1s.\r\n\r\nThis dataset has been superseded by the HadAT dataset collection, also available from CEDA. These pages are provided for the benefit of existing and past users of HadRT. New and existing users are now encouraged to use the HadAT dataset collection instead. " } ], "responsiblepartyinfo_set": [ 53088, 53092, 53093, 53094, 53089, 53090, 53095, 53091, 53096, 55477, 148641 ], "onlineresource_set": [ 8819, 8831, 8820 ] }, { "ob_id": 13850, "uuid": "07ed7f0f45de4842bdba129f28446bb7", "title": "HADRT2.1s: Bias adjusted global monthly radiosonde temperature anomalies that is combined from HadRT2.0 and HadRT2.1 (1958-2004)", "abstract": "The HADRT2.1s data are global monthly fields of radiosonde temperature anomalies at standard pressure levels on a 5 degree latitude by 10 degree longitude grid from 1958 to July 2004. \r\nAnomalies are calculated with respect to 1971-1990 climatology. Anomalies are available for 9 standard levels (850, 700, 500, 300, 200, 150, 100, 50, 30hPa) as well as tropospheric (850 - 300hPa) and stratospheric (150 - 30hPa) averages.\r\nThe data are degree Celsius anomalies from 1970-1990 means. Anomalies are calculated for each of about 200 sonde stations worldwide and grid values derived from these. \r\n\r\nHADRT2.1s is a combination of HadRT2.0 in the troposphere (up to and including 200hPa) and HadRT2.1 in the stratosphere (above 200hPa). \r\n\r\nThis dataset has been superseded by the HadAT dataset also available from CEDA.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2004-11-29T16:59:27", "updateFrequency": "notPlanned", "dataLineage": "Data obtained for the period from 1958 to July 2004, were provided as is by the Met Office Hadley Centre, for archiving at the BADC.", "removedDataReason": "", "keywords": "Met Office, HADRT, radiosonde, temperature anomalies, Hadley", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "5x10 grid", "status": "obsolete", "dataPublishedTime": "2015-12-19T18:31:52", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13851, "dataPath": "/badc/ukmo-hadrt/data/HadRT2.1s", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 143952991, "numberOfFiles": 10, "fileFormat": "The data are ASCII formatted (plain text and \"human\" readable) see Met Office HadRT2.1s data format information in docs for more information.\r\n" }, "timePeriod": { "ob_id": 593, "startTime": "1958-01-01T00:00:00", "endTime": "2004-07-30T23:00:00" }, "resultQuality": { "ob_id": 517, "explanation": "Data quality controlled by the Met Office. Please see main reference paper for this dataset.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-06-09" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 14351, "uuid": "db186b9ce9804ab8a39be21087c7a938", "short_code": "cmppr", "title": "HadRT2.1: Composite data production process for HadRT2.1", "abstract": "HadRT2.1 data are radiosonde temperature anomalies." }, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2568, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "hadrt", "label": "restricted: hadrt group", "licence": { "ob_id": 12, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement.pdf", "licenceClassifications": [ { "ob_id": 4, "classification": "academic" } ] } } ], "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": [ 21787, 25388, 25877 ], "vocabularyKeywords": [], "identifier_set": [ 8732 ], "observationcollection_set": [ { "ob_id": 2207, "uuid": "05f97d2d38abf207abafe96871bca91f", "short_code": "coll", "title": "Met Office Global Radiosonde Gridded Temperature Anomalies (1958-July 2004) (HadRT) Dataset", "abstract": "The HADRT data are global radiosonde gridded temperature anomalies at standard levels in the troposphere and in the lower stratosphere from 1958 to July 2004. The data are degree Celsius anomalies from 1970-1990 means. Anomalies are calculated for each of about 200 sonde stations worldwide and grid values derived from these. \r\n\r\nSeveral versions of the HadRT data are available. The recommended HadRT product for most purposes is HadRT2.1s.\r\n\r\nThis dataset has been superseded by the HadAT dataset collection, also available from CEDA. These pages are provided for the benefit of existing and past users of HadRT. New and existing users are now encouraged to use the HadAT dataset collection instead. " } ], "responsiblepartyinfo_set": [ 53097, 53101, 53098, 53102, 53103, 53099, 53104, 53100, 53105, 55479, 148642 ], "onlineresource_set": [ 8410, 8411, 8822 ] }, { "ob_id": 13852, "uuid": "441a1bb6d9ad469eb86b76e61ab0ce6b", "title": "HADRT2.2: Reconstructed gridded data set of global monthly radiosonde temperature anomalies, derived from HadRT2.1 (1958-2000)", "abstract": "The HADRT2.2 data are global monthly fields of radiosonde temperature anomalies at standard pressure levels on a 10 degree latitude by 20 degree longitude grid from 1958 to 2000. \r\nAnomalies are calculated with respect to 1971-1990 climatology. Anomalies are available for 9 standard levels (850, 700, 500, 300, 200, 150, 100, 50, 30hPa) as well as tropospheric (850 - 300hPa) and stratospheric (150 - 30hPa) averages.\r\nThe data are degree Celsius anomalies from 1970-1990 means. Anomalies are calculated for each of about 200 sonde stations worldwide and grid values derived from these. \r\n\r\nHADRT2.2 is an eigenvector reconstructed grid data set from 1958 - 2000, on a 10 degree latitude by 20 degree longitude grid, created from HadRT2.1. The eigenvector reconstruction was used to infill missing seasons or years in boxes with 70% of seasonal or annual data available. \r\n\r\nThis dataset has been superseded by the HadAT dataset also available from CEDA.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2004-11-29T17:01:23", "updateFrequency": "notPlanned", "dataLineage": "Data obtained for the period from 1958 to July 2004, were provided as is by the Met Office Hadley Centre, for archiving at the BADC.", "removedDataReason": "", "keywords": "Met Office, HADRT, radiosonde, temperature anomalies, Hadley", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "10x20 grid", "status": "obsolete", "dataPublishedTime": "2015-12-19T18:38:41", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13853, "dataPath": "/badc/ukmo-hadrt/data/HadRT2.2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 6273826, "numberOfFiles": 9, "fileFormat": "The data are ASCII formatted (plain text and \"human\" readable) see Met Office HadRT2.2 data format information in docs for more information.\r\n" }, "timePeriod": { "ob_id": 3709, "startTime": "1958-01-01T00:00:00", "endTime": "2000-12-31T00:00:00" }, "resultQuality": { "ob_id": 517, "explanation": "Data quality controlled by the Met Office. Please see main reference paper for this dataset.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-06-09" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 14358, "uuid": "4124a1511431461b931a3ff12fcf6b84", "short_code": "cmppr", "title": "HadRT2.2: Composite data production process for HadRT2.2", "abstract": "HadRT2.2 data are radiosonde temperature anomalies." }, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2568, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "hadrt", "label": "restricted: hadrt group", "licence": { "ob_id": 12, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement.pdf", "licenceClassifications": [ { "ob_id": 4, "classification": "academic" } ] } } ], "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": [ 21787, 25388, 25877 ], "vocabularyKeywords": [], "identifier_set": [ 8733 ], "observationcollection_set": [ { "ob_id": 2207, "uuid": "05f97d2d38abf207abafe96871bca91f", "short_code": "coll", "title": "Met Office Global Radiosonde Gridded Temperature Anomalies (1958-July 2004) (HadRT) Dataset", "abstract": "The HADRT data are global radiosonde gridded temperature anomalies at standard levels in the troposphere and in the lower stratosphere from 1958 to July 2004. The data are degree Celsius anomalies from 1970-1990 means. Anomalies are calculated for each of about 200 sonde stations worldwide and grid values derived from these. \r\n\r\nSeveral versions of the HadRT data are available. The recommended HadRT product for most purposes is HadRT2.1s.\r\n\r\nThis dataset has been superseded by the HadAT dataset collection, also available from CEDA. These pages are provided for the benefit of existing and past users of HadRT. New and existing users are now encouraged to use the HadAT dataset collection instead. " } ], "responsiblepartyinfo_set": [ 53107, 53108, 53106, 53110, 53111, 53112, 53113, 53109, 53114, 55480, 148643 ], "onlineresource_set": [ 8413, 8414, 8821 ] }, { "ob_id": 13854, "uuid": "2ec6c091abad4241915f4bfdf8c9e33b", "title": "HADRT2.2u: Reconstructed gridded data set of global monthly radiosonde temperature anomalies derived from HadRT2.0 (1958-2000)", "abstract": "The HADRT2.2u data are global monthly fields of radiosonde temperature anomalies at standard pressure levels on a 10 degree latitude by 20 degree longitude grid from 1958 to 2000. \r\nAnomalies are calculated with respect to 1971-1990 climatology. 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All values are anomalies relative to the monthly 1966-95 climatology.\r\n\r\nThe gridded product is derived from 676 individual radiosonde stations with long-term records. Because of the criteria of data longevity the resulting dataset is limited to land areas and primarily Northern Hemisphere locations. Radiosondes are single launch instruments and there have been many changes in instruments and observing practices with time. HadAT has used a neighbour-based approach to attempt to adjust for these effects and produce a homogeneous product suitable for climate applications.\r\n\r\nZonal averages were created by averaging all available gridbox values in each 5 degree latitude band. Large scale mean timeseries for the globe and the tropics (defined here as 20N to 20S) are simply cos(lat) weighted zonal mean field values. This reduces the spatial sampling bias towards Northern Hemisphere mid-latitudes. Other plausible large-scale averaging techniques would impact the timeseries values calculated. \r\n\r\n Cautionary note from the Met Office Hadley Centre\r\n\r\nIt is important to note that significant uncertainty exists in radiosonde datasets reflecting the large number of choices available to researchers in their construction and the many heterogeneities in the data. To this end we strongly recommend that users consider, in addition to HadAT, the use of one or more of the following products to ensure their research results are robust. Currently, other radiosonde products of climate quality available from other centres for bona fide research purposes are:\r\n\r\n- Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC)\r\n- RAdiosonde OBservation COrrection using REanalyses and Radiosonde Innovation Composite Homogenization )\r\n- IUK (Iterative Universal Kriging) Radiosonde Analysis Project \r\n\r\nAlso see a comparison with Microwave Sounding Unit (MSU) data by Remote Sensing Systems (see links under Docs tab below) . " } ], "responsiblepartyinfo_set": [ 53143, 53144, 53147, 53148, 53149, 53145, 53150, 53146, 53151, 55423, 168759 ], "onlineresource_set": [ 8441, 8442, 8443, 8835, 8444 ] }, { "ob_id": 13862, "uuid": "a07c1595026845a4af1f81522f0ccb7d", "title": "HadAT2 - Met Office Globally gridded radiosonde temperature anomalies version 2 (1958 to 2012)", "abstract": "The HadAT2 data are global radiosonde gridded temperature anomalies at standard levels (850, 700, 500, 300, 200, 150, 100, 50, and 30hPa) in the troposphere and in the lower stratosphere from 1958 to December 2012. This monthly timeseries are available on a 10 degree longitude by 5 degree latitude basis. This dataset supersedes the HadRT dataset. All values are anomalies relative to the monthly 1966-95 climatology.\r\n\r\n\r\n", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-09-11T12:59:00", "updateFrequency": "notPlanned", "dataLineage": "Data files acquired as is from the Met Office Hadley centre, are stored at the BADC.\r\n", "removedDataReason": "", "keywords": "Met Office, HADAT, radiosonde, temperature anomalies, Hadley", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "10 deg longitude by 5 deg latitude", "status": "completed", "dataPublishedTime": "2013-04-16T14:38:07", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13863, "dataPath": "/badc/ukmo-hadat/data/HadAT2", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 119640373, "numberOfFiles": 36, "fileFormat": "The data are available in ASCII and NetCDF format" }, "timePeriod": { "ob_id": 3711, "startTime": "1958-01-01T00:00:00", "endTime": "2012-12-31T00:00:00" }, "resultQuality": { "ob_id": 1986, "explanation": "Data quality controlled by the Met Office (as per dataset documentation provided).", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-06-09" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 14395, "uuid": "0e321ce2055f40a39d836dc8e3390d58", "short_code": "cmppr", "title": "HadAT2: Composite data production process for HadAT2", "abstract": "HadAT2 data are global upper air temperature anomalies are similar to HadAT1 (where the data are constructed from a network of radiosondes with a nearest neighbour and quality control post-processing) but with an expanded station network." }, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2598, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "hadat", "label": "restricted: hadat group", "licence": { "ob_id": 12, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement.pdf", "licenceClassifications": [ { "ob_id": 4, "classification": "academic" } ] } } ], "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": [ 25877, 51981, 52192, 52193, 57629, 57630, 57631, 57632, 57633, 57634, 57635, 57636, 57637, 57638, 57639, 57640, 57641, 57642, 57643, 57644, 57645, 57646, 57647, 57648, 57649, 57650, 57651, 57652, 57653, 90457 ], "vocabularyKeywords": [], "identifier_set": [ 8739 ], "observationcollection_set": [ { "ob_id": 7371, "uuid": "1205818e121bd8c12a6029f9cbd11a18", "short_code": "coll", "title": "Met Office Globally gridded radiosonde temperature anomalies HadAT Datasets (1958-2012)", "abstract": "The HadAT data are global radiosonde gridded temperature anomalies at standard levels (850, 700, 500, 300, 200, 150, 100, 50, and 30hPa) in the troposphere and in the lower stratosphere from 1958 to December 2012. This monthly timeseries are available on a 10 degree longitude by 5 degree latitude basis. This dataset supersedes the HadRT dataset. All values are anomalies relative to the monthly 1966-95 climatology.\r\n\r\nThe gridded product is derived from 676 individual radiosonde stations with long-term records. Because of the criteria of data longevity the resulting dataset is limited to land areas and primarily Northern Hemisphere locations. Radiosondes are single launch instruments and there have been many changes in instruments and observing practices with time. HadAT has used a neighbour-based approach to attempt to adjust for these effects and produce a homogeneous product suitable for climate applications.\r\n\r\nZonal averages were created by averaging all available gridbox values in each 5 degree latitude band. Large scale mean timeseries for the globe and the tropics (defined here as 20N to 20S) are simply cos(lat) weighted zonal mean field values. This reduces the spatial sampling bias towards Northern Hemisphere mid-latitudes. Other plausible large-scale averaging techniques would impact the timeseries values calculated. \r\n\r\n Cautionary note from the Met Office Hadley Centre\r\n\r\nIt is important to note that significant uncertainty exists in radiosonde datasets reflecting the large number of choices available to researchers in their construction and the many heterogeneities in the data. To this end we strongly recommend that users consider, in addition to HadAT, the use of one or more of the following products to ensure their research results are robust. Currently, other radiosonde products of climate quality available from other centres for bona fide research purposes are:\r\n\r\n- Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC)\r\n- RAdiosonde OBservation COrrection using REanalyses and Radiosonde Innovation Composite Homogenization )\r\n- IUK (Iterative Universal Kriging) Radiosonde Analysis Project \r\n\r\nAlso see a comparison with Microwave Sounding Unit (MSU) data by Remote Sensing Systems (see links under Docs tab below) . " } ], "responsiblepartyinfo_set": [ 53152, 53156, 53157, 53158, 53159, 53153, 53154, 53155, 53160, 55422, 168758 ], "onlineresource_set": [ 8448, 8446, 8836, 8449, 8447 ] }, { "ob_id": 13864, "uuid": "c40bca21cdfb469493fc65f876a139ce", "title": "MSU equivalent measures from HadAT2 (1958 to 2005)", "abstract": "In the interests of having MSU-equivalent HadAT timeseries available for immediate comparisons with these satellite-derived data, the Hadley Centre have created a set of MSU equivalent measures under very specific criteria. Although justifiable, many of the decisions they have made are subjective and alternative choices could be made that would appear, at least initially, to be equally plausible. Final MSU equivalent measures for the monthly HadAT2 timeseries are available as well as a number of intermediate products required to produce these from the Temperature on Pressure Levels data.\r\n\r\nFor more information on the real MSU instruments, their measurements and their climate timeseries are available from the University of Alabama in Huntsville and Remote Sensing Systems (external links).", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2005-09-15T16:23:18", "updateFrequency": "notPlanned", "dataLineage": "Data files acquired as is from the Met Office Hadley centre, are stored at the BADC.", "removedDataReason": "", "keywords": "Met Office, HADAT, MSU, radiosonde, temperature anomalies, Hadley", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "10 deg longitude by 5 deg latitude", "status": "completed", "dataPublishedTime": "2015-12-20T15:50:13", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13865, "dataPath": "/badc/ukmo-hadat/data/MSU_equivalent", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 22303459, "numberOfFiles": 19, "fileFormat": "The data are available in ASCII and NetCDF format" }, "timePeriod": { "ob_id": 3712, "startTime": "1958-01-01T00:00:00", "endTime": "2005-12-31T00:00:00" }, "resultQuality": { "ob_id": 1986, "explanation": "Data quality controlled by the Met Office (as per dataset documentation provided).", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-06-09" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 14461, "uuid": "9e6e6341bf544571851db90748c5d259", "short_code": "comp", "title": "Computation for MSU equivalent measures from HadAT2", "abstract": "The MSU equivalent measures from HadAT2 are a composite of remotely sensed data that is then processed to be equivalent to HadAT2. Although justifiable, many of the decisions they have made are subjective and alternative choices could be made that would appear, at least initially, to be equally plausible. Final MSU equivalent measures for the monthly HadAT2 timeseries are available as well as a number of intermediate products required to produce these from the Temperature on Pressure Levels data." }, "procedureCompositeProcess": null, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2598, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "hadat", "label": "restricted: hadat group", "licence": { "ob_id": 12, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement.pdf", "licenceClassifications": [ { "ob_id": 4, "classification": "academic" } ] } } ], "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": [ 25877, 51981, 52192, 52193, 57629, 57634, 57636, 57637, 57638, 57639, 57649, 62340, 62341, 62342, 62343, 62344 ], "vocabularyKeywords": [], "identifier_set": [ 8740 ], "observationcollection_set": [ { "ob_id": 7371, "uuid": "1205818e121bd8c12a6029f9cbd11a18", "short_code": "coll", "title": "Met Office Globally gridded radiosonde temperature anomalies HadAT Datasets (1958-2012)", "abstract": "The HadAT data are global radiosonde gridded temperature anomalies at standard levels (850, 700, 500, 300, 200, 150, 100, 50, and 30hPa) in the troposphere and in the lower stratosphere from 1958 to December 2012. This monthly timeseries are available on a 10 degree longitude by 5 degree latitude basis. This dataset supersedes the HadRT dataset. All values are anomalies relative to the monthly 1966-95 climatology.\r\n\r\nThe gridded product is derived from 676 individual radiosonde stations with long-term records. Because of the criteria of data longevity the resulting dataset is limited to land areas and primarily Northern Hemisphere locations. Radiosondes are single launch instruments and there have been many changes in instruments and observing practices with time. HadAT has used a neighbour-based approach to attempt to adjust for these effects and produce a homogeneous product suitable for climate applications.\r\n\r\nZonal averages were created by averaging all available gridbox values in each 5 degree latitude band. Large scale mean timeseries for the globe and the tropics (defined here as 20N to 20S) are simply cos(lat) weighted zonal mean field values. This reduces the spatial sampling bias towards Northern Hemisphere mid-latitudes. Other plausible large-scale averaging techniques would impact the timeseries values calculated. \r\n\r\n Cautionary note from the Met Office Hadley Centre\r\n\r\nIt is important to note that significant uncertainty exists in radiosonde datasets reflecting the large number of choices available to researchers in their construction and the many heterogeneities in the data. To this end we strongly recommend that users consider, in addition to HadAT, the use of one or more of the following products to ensure their research results are robust. Currently, other radiosonde products of climate quality available from other centres for bona fide research purposes are:\r\n\r\n- Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC)\r\n- RAdiosonde OBservation COrrection using REanalyses and Radiosonde Innovation Composite Homogenization )\r\n- IUK (Iterative Universal Kriging) Radiosonde Analysis Project \r\n\r\nAlso see a comparison with Microwave Sounding Unit (MSU) data by Remote Sensing Systems (see links under Docs tab below) . " } ], "responsiblepartyinfo_set": [ 53162, 53163, 53161, 53165, 53166, 53167, 53168, 53164, 53169, 55421, 148609 ], "onlineresource_set": [ 8454, 8453, 8457, 8458, 8456, 8451, 8452 ] }, { "ob_id": 13866, "uuid": "21179cb9d6fe48929207d8473307f6f5", "title": "HadAT Uncertainty Estimates (1958-2002)", "abstract": "HadAT Uncertainty estimates are only available on seasonal products and up until the end of 2002.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2005-09-09T10:32:02", "updateFrequency": "notPlanned", "dataLineage": "Data files acquired as is from the Met Office Hadley centre, are stored at the BADC.", "removedDataReason": "", "keywords": "Met Office, HADAT, radiosonde, temperature anomalies, Hadley", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "10 deg longitude by 5 deg latitude", "status": "completed", "dataPublishedTime": "2015-12-20T16:11:37", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13867, "dataPath": "/badc/ukmo-hadat/data/Uncertainty", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 42993296, "numberOfFiles": 14, "fileFormat": "The data are available in ASCII and NetCDF format" }, "timePeriod": { "ob_id": 3713, "startTime": "1958-01-01T00:00:00", "endTime": "2002-12-31T00:00:00" }, "resultQuality": { "ob_id": 1986, "explanation": "Data quality controlled by the Met Office (as per dataset documentation provided).", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-06-09" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": null, "procedureCompositeProcess": { "ob_id": 14453, "uuid": "b365e8cc82c0450797fc0ced8de323be", "short_code": "cmppr", "title": "HadAT-Uncertainty: Composite data production process for HadAT Uncertainty Estimates", "abstract": "HadAT Uncertainty estimates are only available on seasonal products and up until the end of 2002." }, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2598, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "hadat", "label": "restricted: hadat group", "licence": { "ob_id": 12, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement.pdf", "licenceClassifications": [ { "ob_id": 4, "classification": "academic" } ] } } ], "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": [ 25877 ], "vocabularyKeywords": [], "identifier_set": [ 8741 ], "observationcollection_set": [ { "ob_id": 7371, "uuid": "1205818e121bd8c12a6029f9cbd11a18", "short_code": "coll", "title": "Met Office Globally gridded radiosonde temperature anomalies HadAT Datasets (1958-2012)", "abstract": "The HadAT data are global radiosonde gridded temperature anomalies at standard levels (850, 700, 500, 300, 200, 150, 100, 50, and 30hPa) in the troposphere and in the lower stratosphere from 1958 to December 2012. This monthly timeseries are available on a 10 degree longitude by 5 degree latitude basis. This dataset supersedes the HadRT dataset. All values are anomalies relative to the monthly 1966-95 climatology.\r\n\r\nThe gridded product is derived from 676 individual radiosonde stations with long-term records. Because of the criteria of data longevity the resulting dataset is limited to land areas and primarily Northern Hemisphere locations. Radiosondes are single launch instruments and there have been many changes in instruments and observing practices with time. HadAT has used a neighbour-based approach to attempt to adjust for these effects and produce a homogeneous product suitable for climate applications.\r\n\r\nZonal averages were created by averaging all available gridbox values in each 5 degree latitude band. Large scale mean timeseries for the globe and the tropics (defined here as 20N to 20S) are simply cos(lat) weighted zonal mean field values. This reduces the spatial sampling bias towards Northern Hemisphere mid-latitudes. Other plausible large-scale averaging techniques would impact the timeseries values calculated. \r\n\r\n Cautionary note from the Met Office Hadley Centre\r\n\r\nIt is important to note that significant uncertainty exists in radiosonde datasets reflecting the large number of choices available to researchers in their construction and the many heterogeneities in the data. To this end we strongly recommend that users consider, in addition to HadAT, the use of one or more of the following products to ensure their research results are robust. Currently, other radiosonde products of climate quality available from other centres for bona fide research purposes are:\r\n\r\n- Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC)\r\n- RAdiosonde OBservation COrrection using REanalyses and Radiosonde Innovation Composite Homogenization )\r\n- IUK (Iterative Universal Kriging) Radiosonde Analysis Project \r\n\r\nAlso see a comparison with Microwave Sounding Unit (MSU) data by Remote Sensing Systems (see links under Docs tab below) . " } ], "responsiblepartyinfo_set": [ 53174, 53175, 53176, 53177, 53170, 53171, 53172, 53173, 53178, 55425, 148636 ], "onlineresource_set": [ 8463, 8833, 8462, 8465, 8464 ] }, { "ob_id": 13868, "uuid": "5aa1248620a14e609341b6aa7d8d984f", "title": "Monthly and Seasonal Blended MOHSST6-Jones Land Surface Air Temperature Dataset (1856-2002)", "abstract": "Blending a sea-surface temperature (SST) dataset with land air temperature makes an implicit assumption that SST anomalies are a good surrogate for marine air temperature anomalies. It has been shown that this is the case, and that marine SST measurements provide more useful data and smaller sampling errors than marine air temperature measurements would. So blending SST anomalies with land air temperature anomalies is a sensible choice.\r\n\r\nThis dataset contains monthly and seasonal blended sea-surface temperatures (MOHSST6) with land air temperature data from the Climatic Research Unit (CRU) at the University of East Anglia (P.D. Jones). \r\n\r\nData are represented on 5 deg. grids from 1856 to May 2002. \r\n\r\nThe data were provided by the Met Office.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2002-07-16T17:24:23", "updateFrequency": "notPlanned", "dataLineage": "Data files acquired by the BADC from the Met Office Hadley Centre in 2000.", "removedDataReason": "", "keywords": "SST, MOHSST6, blended, CRU, UEA", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2015-12-20T22:46:27", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 1, "bboxName": "", "eastBoundLongitude": 180.0, "westBoundLongitude": -180.0, "southBoundLatitude": -90.0, "northBoundLatitude": 90.0 }, "verticalExtent": null, "result_field": { "ob_id": 13869, "dataPath": "/badc/ukmo-gosta/data/mohsst6_jones", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 861084, "numberOfFiles": 3, "fileFormat": "Data are ASCII formatted" }, "timePeriod": { "ob_id": 3716, "startTime": "1856-01-01T00:00:00", "endTime": "2002-05-30T23:00:00" }, "resultQuality": { "ob_id": 1595, "explanation": "Data quality controlled by the Met Office. See documentation provided.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-06-04" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 6081, "uuid": "2cdd64f120464bc9b0f3c775105cbb94", "short_code": "comp", "title": "MOHSST6 sea surface temperature anomalies data processing deployed on Met Office Hadley Centre Computers", "abstract": "This computation involved: MOHSST6 sea surface temperature anomalies data processing deployed on Met Office Hadley Centre Computers. Process used to create the MOHSST6 dataset." }, "procedureCompositeProcess": null, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2600, "accessConstraints": null, "accessCategory": "restricted", "accessRoles": "gosta", "label": "restricted: gosta group", "licence": { "ob_id": 12, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/ukmo_agreement.pdf", "licenceClassifications": [ { "ob_id": 4, "classification": "academic" } ] } } ], "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": [ 21894, 25900 ], "vocabularyKeywords": [], "identifier_set": [ 8752 ], "observationcollection_set": [ { "ob_id": 6069, "uuid": "fda780a7697f384010674ebb1d5e4f23", "short_code": "coll", "title": "Met Office Global Ice coverage and Sea Surface Temperatures (GISST), and Monthly night marine air temperature/SST anomalies (MOHMATN4)/(MOHSST6) Data (1856-2006)", "abstract": "This collection of datasets contains Sea Surface Temperature climatologies (GISST, Version 2.3b - This dataset is an updated version of GISST2.2 available on the GOSTAplus CD-Rom) and anomalies (MOHSST6), Night Marine Air temperature climatologies and anomalies (MOHMATN4), Sea Ice coverage (GICE) and Blended MOHSST6-Land data (in collaboration with the Climate Research Unit (CRU).\r\n\r\nThe data available is grouped into five sections:\r\n\r\n- Global Ocean Surface Temperature (GISST), a set of SST data in monthly 1° area grids, for 1871 to February 2003. This product is now replaced by the HadISST SST operational data.\r\n\r\n- Global sea-Ice content, (GICE), monthly 1° grids of ice coverage for 1871 to February 2003. This product is now replaced by the HadISST ICE operational data.\r\n\r\n- Met Office Historical Night Marine Air Temperature Anomalies, (MOHMATN4), monthly 5° grids of marine air temperature anomalies for 1856 to August 2006.\r\n\r\n- Met Office Historical Sea Surface Temperature Anomalies, (MOHSST6), monthly 5° grids of sea surface temperature anomalies for 1856 to August 2006. Please note that this data has now been superceded by HadSST2 data.\r\n\r\n- Met Office Blended MOHSST6-Land Surface data from the Climate Research Unit at the University of East Anglia.\r\n\r\nThis data was provided by the Met Office.\r\n" } ], "responsiblepartyinfo_set": [ 53192, 53193, 53194, 53196, 53197, 53198, 53199, 53195, 53200, 53201, 55488, 148611 ], "onlineresource_set": [] }, { "ob_id": 13870, "uuid": "37acfb4514ca4ef7b711e2cf568280a4", "title": "Monthly Mean, Minimum and Maximum Central England Temperature series", "abstract": "The longest available instrumental record of temperature in the world is now available at the BADC. The monthly data starts in 1659.\r\n\r\nThe mean, minimum and maximum datasets are updated monthly, with data for a month usually available by the 3rd of the next month. A provisional CET value for the current month is calculated on a daily basis. The mean monthly data series begins in 1659. Mean maximum and minimum daily and monthly data are also available, beginning in 1878. \r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London). \r\n\r\nThe following stations are used by the Met Office to compile the CET data: Rothamsted, Malvern, Squires Gate and Ringway.\r\n\r\nBut in November 2004, the weather station Stonyhurst replaced Ringway and revised urban warming and bias adjustments have now been applied to the Stonyhurst data after a period of reduced reliability from the station in the summer months. \r\n\r\nThe data set is compiled by the Met Office Hadley Centre.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-06-18T01:55:37", "updateFrequency": "notPlanned", "dataLineage": "HadCET was acquired in 1998 by the BADC from the Met Office Hadley Centre and was routinely updated until August 2022.", "removedDataReason": "", "keywords": "HadCET, temperature, Hadley, Met Office", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2007-01-06T00:01:04", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2, "bboxName": "", "eastBoundLongitude": 1.0, "westBoundLongitude": -4.0, "southBoundLatitude": 51.0, "northBoundLatitude": 54.0 }, "verticalExtent": null, "result_field": { "ob_id": 13871, "dataPath": "/badc/ukmo-cet/data/v1.0.0.0/monthly", "oldDataPath": [ 42 ], "storageLocation": "internal", "storageStatus": "online", "volume": 202473, "numberOfFiles": 8, "fileFormat": "ASCII" }, "timePeriod": { "ob_id": 13, "startTime": "1659-01-01T00:00:00", "endTime": "2022-07-31T23:59:59" }, "resultQuality": { "ob_id": 4, "explanation": "Data is quality-controlled by the Met Office.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-01-28" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 40, "uuid": "a4f4617005c54c79a578be4533963e6e", "short_code": "acq", "title": "Acquisition Process for: Daily Central England Temperature series", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Rothamsted temperature sensor, Malvern temperature sensor, Squires Gate Temperature sensor, Ringway temperature sensor, Stonyhurst temperature sensor, Met Office station temperature sensor; PLATFORMS: Met Office: Rothamsted, Met Office: Malvern, Met Office: Squires Gate, Met Office: Ringway, Met Office: Stonyhurst, partially unknown set of UK CET stations, Set of UK stations used by Parker et al.;" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2526, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 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": [ 23369, 23370, 23371 ], "vocabularyKeywords": [], "identifier_set": [ 8758 ], "observationcollection_set": [ { "ob_id": 24, "uuid": "a946415f9345f6da9bf4c475c19477b6", "short_code": "coll", "title": "Met Office Hadley Centre Central England Temperature (HadCET) Series", "abstract": "The Central England Temperature (CET) series is the longest available instrumental record of temperature in the world, with the monthly mean temperature extending back to 1659 and the daily mean temperature series extending back to 1772. The daily and monthly minimum and maximum temperature series extend back to 1878.\r\n\r\nThese historical temperature series have been constructed to provide a long running temperature record for the Central England region, a roughly triangular area of the United Kingdom enclosed by Somerset, Lancashire and London. The CET value is then calculated as an average of the recorded temperatures for a few stations which are selected as representative of the region as a whole. Although the selected stations have changed over time, due primarily to station closures, the series is homogenised to ensure that it remains consistent.\r\n\r\nStations used in the construction of the CET series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick.\r\n\r\nStations used in the construction of the CET series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College.\r\n\r\nGordon Manley (1953, 1974) compiled most of the monthly series from 1659 to 1973, and the mean temperature series is adjusted up to 1973 to align with Manley's recorded daily mean temperature values. The series data were updated to 1991 by Parker et al (1992) and comprise the V2 series which is updated with the latest values.\r\n\r\nThe version controlled CET series is updated annually, with the previous complete year’s values refreshed to ensure that data acquisition and quality control procedures have been completed and ensure the most accurate station temperature values are used. Each version of the dataset will include data up until the end of the previous complete year and an incremental version number will be updated.\r\n\r\nIf more comprehensive changes are made to the construction of the series, this may constitute a minor/major version number update.\r\n\r\nA provisional version of the CET series, with recent data up to the previous day, is available for download on the Met Office Hadley Centre webpage: https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html\r\n\r\nThe v1.0.0.0 datasets within the collection were originally pulled over monthly from the Met Office Hadley Centre website on a monthly basis until summer 2022 with data available in the CEDA archive copy to end of July 2022." }, { "ob_id": 43588, "uuid": "f1e8696c6d5746e694fde4d6022e5a36", "short_code": "coll", "title": "Met Office Hadley Centre Central England Temperature (HadCET) All Versions Collection", "abstract": "The Central England Temperature (CET) series is the longest available instrumental record of temperature in the world, with the monthly mean temperature extending back to 1659 and the daily mean temperature series extending back to 1772. The daily and monthly minimum and maximum temperature series extend back to 1878.\r\n\r\nThese historical temperature series have been constructed to provide a long running temperature record for the Central England region, a roughly triangular area of the United Kingdom enclosed by Somerset, Lancashire and London. The CET value is then calculated as an average of the recorded temperatures for a few stations which are selected as representative of the region as a whole. Although the selected stations have changed over time, due primarily to station closures, the series is homogenised to ensure that it remains consistent.\r\n\r\nStations used in the construction of the CET series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick.\r\n\r\nStations used in the construction of the CET series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College.\r\n\r\nGordon Manley (1953, 1974) compiled most of the monthly series from 1659 to 1973, and the mean temperature series is adjusted up to 1973 to align with Manley's recorded daily mean temperature values. The series data were updated to 1991 by Parker et al (1992) and comprise the V2 series which is updated with the latest values. For latest updates please see Legg et al (2025).\r\n\r\nAfter 1973, the series is adjusted to extend the alignment with Manley's series. Further adjustments are applied to homogenise the current station selection to that used by Manley as well as to account for urbanisation.\r\n\r\nThe version controlled CET series is updated annually (February-March), with the previous complete year’s values refreshed to ensure that data acquisition and quality control procedures have been completed and ensure the most accurate station temperature values are used. Each version of the dataset will include data up until the end of the previous complete year and an incremental version number will be updated.\r\n\r\nThe CET datasets employ the following version control protocol: \r\n\r\nVersion Vx.y.z.a:\r\n• x – major changes – e.g. change in scientific methodology\r\n• y – minor changes – e.g. small bug fixes or updates to diagnostics pages\r\n• z – incremental changes\r\n• a – reserved for use internally\r\n\r\nThe standard annual release cycle of CET will constitute an incremental release (z). However, if more substantial\r\nchanges have been made to the codebase, scientific methodology or source data values, then this may warrant a minor (y) or major (x) version release. (Note, these are applied to a cohort of datasets together - i.e. apply to the seasonal, monthly, daily and adjustment datasets as a coordinated version release).\r\n\r\nThis new version of the datasets will supersede the previous version.\r\n\r\nA provisional version of the CET series, with recent data up to the previous day, is available for download on the Met Office Hadley Centre webpage: https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html . Link also available in the list of online resources on this record.\r\n\r\nNote: the v1.0.0.0 datasets within the collection on the CEDA archive were originally pulled over monthly from the Met Office Hadley Centre website on a monthly basis until the end of July 2022." } ], "responsiblepartyinfo_set": [ 53210, 53211, 53209, 53213, 53214, 53215, 53216, 53212, 53217, 55474, 148610 ], "onlineresource_set": [ 8510, 8511, 8512, 8516, 8515, 8513, 8514, 8517 ] }, { "ob_id": 13872, "uuid": "268cfd67e1d148fe8120655c6b8de402", "title": "Seasonal Mean, Minimum and Maximum Central England Temperature series", "abstract": "The longest available instrumental record of temperature in the world is now available at the BADC. The seasonal data starts in 1659.\r\n\r\nThe mean, minimum and maximum datasets are updated monthly, with data for a month usually available by the 3rd of the next month. A provisional CET value for the current month is calculated on a daily basis. The mean monthly data series begins in 1659. Mean maximum and minimum daily and monthly data are also available, beginning in 1878. \r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London). \r\n\r\nThe following stations are used by the Met Office to compile the CET data: Rothamsted, Malvern, Squires Gate and Ringway.\r\n\r\nBut in November 2004, the weather station Stonyhurst replaced Ringway and revised urban warming and bias adjustments have now been applied to the Stonyhurst data after a period of reduced reliability from the station in the summer months. \r\n\r\nThe data set is compiled by the Met Office Hadley Centre.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57", "latestDataUpdateTime": "2025-01-23T14:26:20", "updateFrequency": "notPlanned", "dataLineage": "HadCET was acquired in 1998 by the BADC from the Met Office Hadley Centre and was routinely updated until August 2022.", "removedDataReason": "", "keywords": "HadCET, temperature, Hadley, Met Office", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2007-01-06T00:01:46", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 2, "bboxName": "", "eastBoundLongitude": 1.0, "westBoundLongitude": -4.0, "southBoundLatitude": 51.0, "northBoundLatitude": 54.0 }, "verticalExtent": null, "result_field": { "ob_id": 13873, "dataPath": "/badc/ukmo-cet/data/v1.0.0.0/seasonal", "oldDataPath": [ 45 ], "storageLocation": "internal", "storageStatus": "online", "volume": 71957, "numberOfFiles": 7, "fileFormat": "ASCII" }, "timePeriod": { "ob_id": 13, "startTime": "1659-01-01T00:00:00", "endTime": "2022-07-31T23:59:59" }, "resultQuality": { "ob_id": 4, "explanation": "Data is quality-controlled by the Met Office.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-01-28" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 40, "uuid": "a4f4617005c54c79a578be4533963e6e", "short_code": "acq", "title": "Acquisition Process for: Daily Central England Temperature series", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Rothamsted temperature sensor, Malvern temperature sensor, Squires Gate Temperature sensor, Ringway temperature sensor, Stonyhurst temperature sensor, Met Office station temperature sensor; PLATFORMS: Met Office: Rothamsted, Met Office: Malvern, Met Office: Squires Gate, Met Office: Ringway, Met Office: Stonyhurst, partially unknown set of UK CET stations, Set of UK stations used by Parker et al.;" }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2526, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 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": [ 23369, 23370, 23371 ], "vocabularyKeywords": [], "identifier_set": [ 8759 ], "observationcollection_set": [ { "ob_id": 24, "uuid": "a946415f9345f6da9bf4c475c19477b6", "short_code": "coll", "title": "Met Office Hadley Centre Central England Temperature (HadCET) Series", "abstract": "The Central England Temperature (CET) series is the longest available instrumental record of temperature in the world, with the monthly mean temperature extending back to 1659 and the daily mean temperature series extending back to 1772. The daily and monthly minimum and maximum temperature series extend back to 1878.\r\n\r\nThese historical temperature series have been constructed to provide a long running temperature record for the Central England region, a roughly triangular area of the United Kingdom enclosed by Somerset, Lancashire and London. The CET value is then calculated as an average of the recorded temperatures for a few stations which are selected as representative of the region as a whole. Although the selected stations have changed over time, due primarily to station closures, the series is homogenised to ensure that it remains consistent.\r\n\r\nStations used in the construction of the CET series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick.\r\n\r\nStations used in the construction of the CET series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College.\r\n\r\nGordon Manley (1953, 1974) compiled most of the monthly series from 1659 to 1973, and the mean temperature series is adjusted up to 1973 to align with Manley's recorded daily mean temperature values. The series data were updated to 1991 by Parker et al (1992) and comprise the V2 series which is updated with the latest values.\r\n\r\nThe version controlled CET series is updated annually, with the previous complete year’s values refreshed to ensure that data acquisition and quality control procedures have been completed and ensure the most accurate station temperature values are used. Each version of the dataset will include data up until the end of the previous complete year and an incremental version number will be updated.\r\n\r\nIf more comprehensive changes are made to the construction of the series, this may constitute a minor/major version number update.\r\n\r\nA provisional version of the CET series, with recent data up to the previous day, is available for download on the Met Office Hadley Centre webpage: https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html\r\n\r\nThe v1.0.0.0 datasets within the collection were originally pulled over monthly from the Met Office Hadley Centre website on a monthly basis until summer 2022 with data available in the CEDA archive copy to end of July 2022." }, { "ob_id": 43588, "uuid": "f1e8696c6d5746e694fde4d6022e5a36", "short_code": "coll", "title": "Met Office Hadley Centre Central England Temperature (HadCET) All Versions Collection", "abstract": "The Central England Temperature (CET) series is the longest available instrumental record of temperature in the world, with the monthly mean temperature extending back to 1659 and the daily mean temperature series extending back to 1772. The daily and monthly minimum and maximum temperature series extend back to 1878.\r\n\r\nThese historical temperature series have been constructed to provide a long running temperature record for the Central England region, a roughly triangular area of the United Kingdom enclosed by Somerset, Lancashire and London. The CET value is then calculated as an average of the recorded temperatures for a few stations which are selected as representative of the region as a whole. Although the selected stations have changed over time, due primarily to station closures, the series is homogenised to ensure that it remains consistent.\r\n\r\nStations used in the construction of the CET series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick.\r\n\r\nStations used in the construction of the CET series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College.\r\n\r\nGordon Manley (1953, 1974) compiled most of the monthly series from 1659 to 1973, and the mean temperature series is adjusted up to 1973 to align with Manley's recorded daily mean temperature values. The series data were updated to 1991 by Parker et al (1992) and comprise the V2 series which is updated with the latest values. For latest updates please see Legg et al (2025).\r\n\r\nAfter 1973, the series is adjusted to extend the alignment with Manley's series. Further adjustments are applied to homogenise the current station selection to that used by Manley as well as to account for urbanisation.\r\n\r\nThe version controlled CET series is updated annually (February-March), with the previous complete year’s values refreshed to ensure that data acquisition and quality control procedures have been completed and ensure the most accurate station temperature values are used. Each version of the dataset will include data up until the end of the previous complete year and an incremental version number will be updated.\r\n\r\nThe CET datasets employ the following version control protocol: \r\n\r\nVersion Vx.y.z.a:\r\n• x – major changes – e.g. change in scientific methodology\r\n• y – minor changes – e.g. small bug fixes or updates to diagnostics pages\r\n• z – incremental changes\r\n• a – reserved for use internally\r\n\r\nThe standard annual release cycle of CET will constitute an incremental release (z). However, if more substantial\r\nchanges have been made to the codebase, scientific methodology or source data values, then this may warrant a minor (y) or major (x) version release. (Note, these are applied to a cohort of datasets together - i.e. apply to the seasonal, monthly, daily and adjustment datasets as a coordinated version release).\r\n\r\nThis new version of the datasets will supersede the previous version.\r\n\r\nA provisional version of the CET series, with recent data up to the previous day, is available for download on the Met Office Hadley Centre webpage: https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html . Link also available in the list of online resources on this record.\r\n\r\nNote: the v1.0.0.0 datasets within the collection on the CEDA archive were originally pulled over monthly from the Met Office Hadley Centre website on a monthly basis until the end of July 2022." } ], "responsiblepartyinfo_set": [ 53219, 53220, 53218, 53222, 53223, 53224, 53225, 53221, 53226, 55475, 169580 ], "onlineresource_set": [ 8523, 8524, 8525, 8521, 8526, 8520, 8522, 8519 ] }, { "ob_id": 13875, "uuid": "8ad776840f484c06abdaf69f250f48c1", "title": "Airborne Southern Hemisphere Ozone Experiment (ASHOE) / Measurements for Assessing the Effects of Stratospheric Aircraft (MAESA): Model data", "abstract": "Airborne Southern Hemisphere Ozone Experiment and Measurements for Assessing the Effects of Stratospheric Aircraft (ASHOE/MAESA) was a combined experiment which was conducted in four phases between March and November 1994 at NASA Ames Research Center, California; Barbers Point, Hawaii; and Christchurch, New Zealand. This dataset contains 00 Z and 12 Z analyses of meteorological parameters on isentropic and isobaric surfaces. From the GSFC Assimilation Model with each file containing analyses for one time period.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "1999-03-27T21:05:22", "updateFrequency": "notPlanned", "dataLineage": "Data were collected onboard the NASA ER-2 aircraft and SAGE II satellite. CD-ROM published and obtained from NASA for archiving at the BADC.", "removedDataReason": "", "keywords": "ASHOE, MAESA, Model, Meteorology", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2007-01-29T14:59:55", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 16, "bboxName": "", "eastBoundLongitude": 173.0, "westBoundLongitude": -122.0, "southBoundLatitude": -44.0, "northBoundLatitude": 37.0 }, "verticalExtent": null, "result_field": { "ob_id": 13876, "dataPath": "/badc/CDs/ashoe94/data/model", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 34498206, "numberOfFiles": 64, "fileFormat": "Data are NASA Ames formatted" }, "timePeriod": { "ob_id": 316, "startTime": "1994-01-03T00:00:00", "endTime": "1994-03-14T00:00:00" }, "resultQuality": { "ob_id": 295, "explanation": "See Documentation provided as part of this dataset.", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-01-26" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 13877, "uuid": "8766588d093841a29a8c13aabe4fcd9f", "short_code": "comp", "title": "Airborne Southern Hemisphere Ozone Experiment (ASHOE) / Measurements for Assessing the Effects of Stratospheric Aircraft (MAESA): Model data", "abstract": "The model contains 00 Z and 12 Z analyses of meteorological parameters on isentropic and isobaric surfaces. From the GSFC Assimilation Model with each file containing analyses for one time period. The GSFC Assimilation was rubn on a GG2%5x2 grid data on theta surfaces" }, "procedureCompositeProcess": null, "imageDetails": [ 21 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2521, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 2, "licenceURL": "https://artefacts.ceda.ac.uk/licences/missing_licence.pdf", "licenceClassifications": [ { "ob_id": 2, "classification": "unstated" } ] } } ], "projects": [ { "ob_id": 1078, "uuid": "d13ab45d5eb43b79782b4db436596e86", "short_code": "proj", "title": "Airborne Southern Hemisphere Ozone Experiment (ASHOE) / Measurements for Assessing the Effects of Stratospheric Aircraft (MAESA)", "abstract": "The Airborne Southern Hemisphere Ozone Experiment (ASHOE) is designed to examine the causes of ozone loss in the Southern Hemisphere lower stratosphere and to investigate how the loss is related to polar, mid-latitude, and tropical processes. ASHOE will be conducted in concert with the campaign, Measurements for Assessing the Effects of Stratospheric Aircraft (MAESA), whose focus is to provide information about stratospheric photochemistry and transport forassessing the potential environmental effects of stratospheric aircraft. These combined objectives will be met by a series of flights of the National Aeronautics and Space Administration (NASA) ER-2 high-altitude research aircraft from Christchurch, New Zealand, and on transit flights from Moffett Field, California, to Christchurch via Hawaii and Fiji. Flights of the remotely piloted vehicle Perseus, or possibly balloons, to higher altitudes in the tropics and mid-latitudes will also be made. There are several compelling reasons to study processes relating to ozone depletion in the Southern Hemisphere and tropical lower stratosphere." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 21758, 21764, 21771, 21778, 21779, 21780, 21817, 21823, 22320, 22321, 22341, 22390, 22422, 22424, 22432, 22443, 22444, 22445, 22589, 22890, 23106, 23127, 23128, 23130, 23131, 23132, 23133, 23134, 25381, 25383, 25385, 25387, 25388, 25390, 25391, 25392, 25393, 25394, 25396, 25398, 25399, 25404, 25843, 25846, 25850, 25852, 25853, 25854, 25855, 25856, 25857, 25858, 25859, 25860, 25863, 25864 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 1075, "uuid": "106eccb296d2729af8612541156a5f29", "short_code": "coll", "title": "Airborne Southern Hemisphere Ozone Experiment (ASHOE) / Measurement for Assessing the Effects of Stratospheric Aircraft (MAESA): In-situ Airborne and Ground-based and Remotely Sensed Atmospheric Measurements", "abstract": "This CD-ROM contains data from the combined experiment: Airborne Southern Hemisphere Ozone Experiment; and Measurements for Assessing the Effects of Stratospheric Aircraft (ASHOE/MAESA). 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Theory teams provided calculations of: meteorological parameters in the form of partial hemispheric analyses, cross-sections along the ER-2 flight track, interpolations to the ER-2 flight path, and back- trajectories of selected parcels along the ER-2 flight path; photodissociation rates of selected chemical species along the ER-2 flight path; and cloud properties along the ER-2 flight track." } ], "responsiblepartyinfo_set": [ 53228, 53229, 53227, 53233, 53234, 53235, 53236, 53230, 53231, 53232 ], "onlineresource_set": [] }, { "ob_id": 13879, "uuid": "4b2ae137815b4128aee88363a51421e9", "title": "Stratospheric Photochemistry, Aerosols and Dynamics Expedition (SPADE) Project: Radiosonde measurements", "abstract": "The Stratospheric Photochemistry, Aerosols and Dynamics Expedition (SPADE) was based at the NASA Ames Research Centre in California during portions of 1992 and 1993. 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The project operated a high density air temperature-sensor network and will lead to a number of research projects examining Birmingham's UHI in more detail than ever-before possible.\r\n\r\nThe long-term aim of the HiTemp project was to identify, model and promote adaptation to the impacts of urban heat and climate change on the people and infrastructure of major conurbations (i.e. health, society, infrastructure and energy).\r\n\r\nHiTemp installed networks of meteorological sensors within the Birmingham conurbation: Approximately 250 low-cost, battery-powered WiFi air temperature sensors (Figure 2) and 30 full automatic weather stations (AWS), measuring temperature, precipitation, relative humidity, wind speed and direction, pressure, solar radiation. The design was based around a nested network of sensors:\r\n\r\n Network 1 (coarse array): 30 AWS sited in primary electricity sub-stations (average spacing of 3km)\r\n Network 2 (wide array): 150 air temperature sensors located on schools (one in every medium super output area (MSOA), or areas containing a population of 7,200)\r\n Network 3 (fine array): 100 air temperature sensors located on lampposts in the CBD (50/km2)\r\n\r\nBoth of the air temperature sensor networks utilise existing WiFi networks (i.e. school and public WiFi networks), whilst the AWS network will utilise either GPRS or wired internet connections. The project will ultimately provide a series of demonstration sensor networks for measuring air temperature and other meteorological parameters.\r\n\r\nIndustrial project partners include Birmingham City Council, who are interested in assessing heat health risk across Birmingham; E.ON/Western Power, who are interested in examining the impacts of heat and climate change on transformers; Campbell Scientific, who are supplying some of the meteorological equipment; and Aginova, who are developing and supplying the bespoke WiFi air temperature sensor." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 69538, 69539, 69540, 69541 ], "vocabularyKeywords": [], "identifier_set": [ 8761, 8801 ], "observationcollection_set": [ { "ob_id": 14315, "uuid": "5391a10e4f644229bc138f8a95ca42f1", "short_code": "coll", "title": "HiTemp: High Density Temperature and Meteorological measurements within the Urban Birmingham Conurbation.", "abstract": "The NERC-funded HiTemp project was conducted by the Birmingham Urban Climate Laboratory (BUCL) research team to examine Birmingham's Urban Heat Island (UHI). The project operated a high density air temperature-sensor network and has lead to a number of research projects examining Birmingham's UHI in more detail than ever-before possible.\r\n\r\nThis dataset collection temperature, dew point, relative humidity, pressure, solar radiation, precipitation, wind and hail measurements from a high density network of meteorological sensors installed within the Birmingham conurbation. This includes 73 Aginova Sentinel Micro air temperature sensors and 25 Vaisala WXT520 weather transmitters between 2012-14.\r\n\r\nThese measurements have been made by the Birmingham Urban Climate Laboratory (BUCL) for the HiTemp (High Density Measurements within the Urban Environment) project in order to study the Birmingham Urban Heat Island (UHI)" } ], "responsiblepartyinfo_set": [ 53459, 53460, 53462, 53463, 53474, 53472, 53475, 53473, 55770, 55771, 55772, 55773, 55774 ], "onlineresource_set": [ 8530, 8533, 8744, 8745, 87790 ] }, { "ob_id": 13924, "uuid": "04b023e8d39544fd9e89b666e1e69fe0", "title": "Greenland Flow Distortion EXperiment (GFDex): Radiosonde measurements", "abstract": "The Greenland Flow Distortion EXperiment investigates the role of Greenland in defining the structure and the predictability of both local and downstream weather systems, through a programme of aircraft-based observation and numerical modelling. The Greenland Flow Distortion Experiment (GFDex) will provide some of the first detailed in situ observations of the intense atmospheric forcing events that are thought to be important in modifying the ocean in this area (but are presently poorly understood): namely tip jets, barrier winds and mesoscale cyclones. The dataset contains radiosonde measurements from various sites around Greenland.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2024-03-09T01:47:54", "updateFrequency": "notPlanned", "dataLineage": "Remote and in situ measurements, and data collected onboard the Facility for Airborne Atmospheric Measurements (FAAM) Bae-146 aircraft are available through the GFDex archive at the BADC. Forecast predictions from the Met Office and High Resolution Limited Area Model (HIRLAM) are also stored.", "removedDataReason": "", "keywords": "GFDex, Radiosonde", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2007-12-10T16:56:39", "doiPublishedTime": null, "removedDataTime": null, "geographicExtent": { "ob_id": 8, "bboxName": "", "eastBoundLongitude": -11.0, "westBoundLongitude": -74.0, "southBoundLatitude": 59.0, "northBoundLatitude": 84.0 }, "verticalExtent": null, "result_field": { "ob_id": 13925, "dataPath": "/badc/gfdex/data/radiosonde", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 321322884, "numberOfFiles": 588, "fileFormat": "Data are ASCII formatted" }, "timePeriod": { "ob_id": 200, "startTime": "2007-02-17T00:00:00", "endTime": "2007-03-12T00:00:00" }, "resultQuality": { "ob_id": 186, "explanation": "Research data", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-01-26" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 13926, "uuid": "e1b3747c2dab43ae901a067fa3d72e2c", "short_code": "acq", "title": "Greenland Flow Distortion EXperiment (GFDex): Radiosonde", "abstract": "Greenland Flow Distortion EXperiment (GFDex): Radiosonde " }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 10 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2526, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 643, "uuid": "8254273ca7985d4c3d447aa8cf317488", "short_code": "proj", "title": "Greenland Flow Distortion EXperiment (GFDex)", "abstract": "The Greenland Flow Distortion experiment (GFDex) is an international fieldwork and modelling-based project to investigate the role that Greenland plays in distorting atmospheric flow over and around it: affecting local and remote weather systems and, via air-sea interaction processes, the coupled climate system." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 640, "uuid": "77a24c3705599d03825ce9005a8610f8", "short_code": "coll", "title": "Greenland Flow Distortion EXperiment (GFDex): In-situ Observations of High-impact Weather Systems and Their Associated Air-sea Fluxes in the Coastal Seas of Greenland", "abstract": "The Greenland Flow Distortion EXperiment, based in Keflavik, Iceland, took place during February 2007. Its aim was to improve the understanding and ability to predict interactions between the atmospheric circulation and the topography of Greenland, both locally and downstream over Western Europe. Hitherto rare in situ observations of high-impact weather systems and their associated air-sea fluxes in the coastal seas of Greenland, were obtained and will be used to improve the numerical modelling and prediction of these weather systems, and thus improve the quality of the atmospheric forcing fields that are essential for accurate atmosphere-ocean coupling and the thermohaline circulation. These measurements will also be used to improve the numerical modelling and prediction of high-impact weather systems over Europe through the use of targeted observations upstream in sensitive areas of the flow.\r\n\r\nThis project investigates the role of Greenland in defining the structure and the predictability of both local and downstream weather systems, through a programme of aircraft-based observation and numerical modelling. The Greenland Flow Distortion Experiment (GFDex) will provide some of the first detailed in situ observations of the intense atmospheric forcing events that are thought to be important in modifying the ocean in this area (but are presently poorly understood): namely tip jets, barrier winds and mesoscale cyclones. Tip jets form at the southern tip of Greenland, at Cape Farewell, through the forcing of flow over and around the topography. Barrier winds occur when the large-scale flow is piled up against the southeast coast of Greenland, forcing winds parallel to the coast. While located off this southeast coast is an area of frequent mesoscale cyclogenesis. GFDex will also investigate Greenlands role in atmospheric flow predictability by carrying out upstream observations that are targeted at investigating the sensitivity of the downstream flow to the details of the upstream flow and at improving subsequent forecasts over Europe. Greenlands flow distortion can trigger large-scale atmospheric Rossby waves which influence weather systems thousands of kilometres away and several days later. These waves are by nature predictable, so by adapting our observing strategy to target specific areas, improvements in subsequent forecasts over the United Kingdom are possible.\r\n\r\nNumerical modelling experiments after the field campaign will be used to assess any improvements from the additional targeted observations. While further numerical modelling studies of the high impact local weather systems will be evaluated and refined using the aircraft-based observations. This will increase our understanding of these systems and, through comparisons with other observations and data sets, provide accurate fields of air-sea heat and moisture fluxes for driving ocean and climate models." } ], "responsiblepartyinfo_set": [ 53465, 53466, 53464, 53468, 53469, 53470, 53471, 53467 ], "onlineresource_set": [] }, { "ob_id": 13928, "uuid": "c65ce27928f34ebd92224c451c2a8bed", "title": "ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI): Analysis long term product version 1.1", "abstract": "The ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI) dataset accurately maps the surface temperature of the global oceans over the period 1991 to 2010, using observations from many satellites. The data provides an independently quantified SST to a quality suitable for climate research.\r\n\r\nThe ESA SST CCI Analysis Long Term Product consists of daily, spatially complete fields of sea surface temperature (SST), obtained by combining the orbit data from the AVHRR and ATSR ESA SST CCI Long Term Products, using optimal interpolation to provide SSTs where there were no measurements. These data cover the period between 09/1991 and 12/2010.\r\n\r\nThe Version 1.1 data is an update of the Version 1.0 dataset.\r\n\r\nVersion 1.0 of this dataset is cited in: Merchant, C. J., Embury, O., Roberts-Jones, J., Fiedler, E., Bulgin, C. E., Corlett, G. K., Good, S., McLaren, A., Rayner, N., Morak-Bozzo, S. and Donlon, C. (2014), Sea surface temperature datasets for climate applications from Phase 1 of the European Space Agency Climate Change Initiative (SST CCI). Geoscience Data Journal. doi: 10.1002/gdj3.20", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2015-11-06T10:50:24", "updateFrequency": "notPlanned", "dataLineage": "Data were processed by the ESA CCI SST project team and supplied to CEDA by the UK Met Office.", "removedDataReason": "", "keywords": "SST CCI", "publicationState": "citable", "nonGeographicFlag": false, "dontHarvestFromProjects": true, "language": "English", "resolution": "", "status": "superseded", "dataPublishedTime": "2015-12-23T14:53:08", "doiPublishedTime": "2016-11-22T17:40:00", "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": 13929, "dataPath": "/neodc/esacci/sst/data/lt/Analysis/L4/v01.1", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 135555430626, "numberOfFiles": 7063, "fileFormat": "The CCI SST Analysis Product consists of daily, spatially complete fields of SST, obtained by combining the orbit data from the AVHRR (Advanced Very High Resolution Radiometer) and ATSR (Along Track Scanning Radiometer) Long Term products, using optimal interpolation to provide SSTs where there were no measurements (a single file per day; 0.05° regular latitude- longitude grid). These data start in September 1991. The SSTs correspond approximately to the daily average of the temperature of the water at 20 cm depth. Uncertainty estimates are provided for each value.\r\n\r\nThe data are stored in NetCDF-4 format files. Data arrays in NetCDF files are known as ‘variables’ and each variable has metadata stored with it. Please read the ESA CCI SST Product User Guide, available in the linked documentation before using the data. There is also a Quick Start Guide." }, "timePeriod": { "ob_id": 3057, "startTime": "1991-09-01T00:00:00", "endTime": "2010-12-31T00:00:00" }, "resultQuality": { "ob_id": 2843, "explanation": "", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2014-09-18" }, "validTimePeriod": null, "procedureAcquisition": null, "procedureComputation": { "ob_id": 11010, "uuid": "2d125dda9d6e44ed804191a3b7b41bc5", "short_code": "comp", "title": "CCI SST Processor", "abstract": "This computation involved: CCI SST Processor. This processor was developed in the ESA Climate Change Initiative, Sea Surface Temperature Project" }, "procedureCompositeProcess": null, "imageDetails": [ 137 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1139, "name": "CLIPC" }, { "ob_id": 1140, "name": "ESACCI" } ], "permissions": [ { "ob_id": 2556, "accessConstraints": null, "accessCategory": "public", "accessRoles": null, "label": "public: None group", "licence": { "ob_id": 28, "licenceURL": "https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_sst_terms_and_conditions.pdf", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 11008, "uuid": "05fb7c9964b4172991a72082c46a3376", "short_code": "proj", "title": "Sea Surface Temperature Climate Change Initiative Project", "abstract": "The Sea Surface Temperature Climate Change Initiative (SST_cci) project is part of the European Space Agency's Climate Change Initiative programme, It aims to accurately mapping the surface temperature of the global oceans using observations from many satellites, and to independently quantify SST to a quality suitable for climate research.\r\n\r\nThe team brings together European expertise in creating climate quality records of ocean temperatures from satellite data, with expertise in climate applications and computer engineering. Through the ESA funded Climate Change Initiative, the team have created a climate record of global sea surface temperature (SST) for the period 1981 to 2016. Based on satellite data, this record is independent of thermometer based measurements from ships and buoys. The new climate SST record complements and challenges existing knowledge of how ocean temperatures have evolved. \r\n\r\nThe project started in August 2010. It is part of a wider initiative by the European Space Agency (ESA) addressing several essential climate variables in addition to SST." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 6814, 6816, 9567, 9569, 9580, 9797, 11955, 11956, 11957, 11958, 11959 ], "vocabularyKeywords": [ { "ob_id": 10961, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platformProg/plat_noaa_5th", "resolvedTerm": "NOAA-5th" }, { "ob_id": 10390, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_noaa_4th", "resolvedTerm": "NOAA-4th" }, { "ob_id": 10890, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_noaa_17", "resolvedTerm": "NOAA-17" }, { "ob_id": 10649, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/dataType/dtype_sstDepth", "resolvedTerm": "sea water temperature" }, { "ob_id": 10495, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_noaa_17", "resolvedTerm": "NOAA-17" }, { "ob_id": 10808, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_envisat", "resolvedTerm": "Envisat" }, { "ob_id": 10673, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/ecv/cciecv_sst", "resolvedTerm": "sea surface temperature" }, { "ob_id": 10493, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_metop", "resolvedTerm": "Metop" }, { "ob_id": 10988, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/procLev/proc_level4", "resolvedTerm": "Level 4" }, { "ob_id": 10469, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_envisat_prog", "resolvedTerm": "Environmental Satellite" }, { "ob_id": 10192, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/procLev/proc_level4", "resolvedTerm": "Level 4" }, { "ob_id": 10885, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_noaa_12", "resolvedTerm": "NOAA-12" }, { "ob_id": 11088, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_atsr2", "resolvedTerm": "ATSR-2" }, { "ob_id": 10204, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/dataType/dtype_sstDepth", "resolvedTerm": "sea water temperature" }, { "ob_id": 10433, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_noaa_15", "resolvedTerm": "NOAA-15" }, { "ob_id": 10809, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_ers1", "resolvedTerm": "ERS-1" }, { "ob_id": 10857, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_metOpA", "resolvedTerm": "Metop-A" }, { "ob_id": 10467, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platformProg/plat_noaa_5th", "resolvedTerm": "NOAA-5th" }, { "ob_id": 10562, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/L22/current/TOOL1072/", "resolvedTerm": "Along Track Scanning Radiometer - 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1" }, { "ob_id": 10960, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platformProg/plat_noaa_4th", "resolvedTerm": "NOAA-4th" }, { "ob_id": 10888, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_noaa_15", "resolvedTerm": "NOAA-15" }, { "ob_id": 10473, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/platform/plat_noaa_12", "resolvedTerm": "NOAA-12" }, { "ob_id": 10555, "vocabService": "nerc_skos_vocab", "uri": "http://vocab.nerc.ac.uk/collection/L22/current/TOOL1061/", "resolvedTerm": "Advanced Along-Track Scanning Radiometer" }, { "ob_id": 11087, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_atsr", "resolvedTerm": "ATSR" }, { "ob_id": 10889, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/platform/plat_noaa_16", "resolvedTerm": "NOAA-16" }, { "ob_id": 10155, "vocabService": "clipc_skos_vocab", "uri": "http://vocab-test.ceda.ac.uk/collection/cci/sensor/sens_atsr", "resolvedTerm": "ATSR" }, { "ob_id": 11090, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_avhrr2", "resolvedTerm": "AVHRR-2" }, { "ob_id": 11091, "vocabService": "clipc_skos_vocab", "uri": "http://vocab.ceda.ac.uk/collection/cci/sensor/sens_avhrr3", "resolvedTerm": "AVHRR-3" } ], "identifier_set": [ 9007 ], "observationcollection_set": [ { "ob_id": 11005, "uuid": "1dc189bbf94209b48ed446c0e9a078af", "short_code": "coll", "title": "Collection of Sea Surface Temperature (SST) Data of the Global Oceans as part of the ESA Climate Change Initiative (CCI)", "abstract": "The ESA Sea Surface Temperature Climate Change Initiative (ESA SST_cci) datasets accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nThe latest version (v2.1) of the data are described in the data paper: Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x\r\n\r\nData are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ . To comply with the attribution aspect, please cite the above reference and the dataset citation given on the relevant dataset page." }, { "ob_id": 30128, "uuid": "7fe9f59731ab47b6a20e792e0cba4641", "short_code": "coll", "title": "National Centre for Earth Observation (NCEO) partnered datasets", "abstract": "The National Centre for Earth Observation (NCEO) has a proud tradition of being involved with some of the most successful international collaborations in the Earth observation. This Collection contains dataset generated and/or archived with the support of NCEO resource or scientific expertise. Some notable collaboration which generated data within this collection are as follows:\r\n\r\nThe European Space Agency (ESA)'s Climate Change Initiative (CCI) program. The program goal is to provide stable, long-term, satellite-based Essential Climate Variable (ECV) data products for climate modelers and researchers.\r\n\r\nThe EUSTACE (EU Surface Temperature for All Corners of Earth) project is produced publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques.\r\n\r\nFIDUCEO has created new climate datasets from Earth Observations with a rigorous treatment of uncertainty informed by the discipline of metrology. This response to the need for enhanced credibility for climate data, to support rigorous science, decision-making and climate services. The project approach was to develop methodologies for generating Fundamental Climate Data Records (FCDRs) and Climate Data Records (CDRs) that are widely applicable and metrologically rigorous. \r\n\r\nThe “BACI” project translates satellite data streams into novel “essential biodiversity variables” by integrating ground-based observations. The trans-disciplinary project offers new insights into the functioning and state of ecosystems and biodiversity. BACI enables the user community to detect abrupt and transient changes of ecosystems and quantify the implications for regional biodiversity.\r\n\r\nThe UK Natural Environment Research Council has established a knowledge transfer network called NCAVEO (Network for Calibration and Validation of EO data - NCAVEO) which has as its aim the promotion and support of methodologies based upon quantitative, traceable measurements in Earth observation. \r\n\r\nThe Geostationary Earth Radiation Budget 1 & 2 instruments (GERB-1 and GERB-2) make accurate measurements of the Earth Radiation Budget. They are specifically designed to be mounted on a geostationary satellite and are carried onboard the Meteosat Second Generation satellites operated by EUMETSAT. They were produced by a European consortium led by the UK (NERC) together with Belgium, Italy, and EUMETSAT, with funding from national agencies.\r\n\r\nGloboLakes analysed 20 years of data from more than 1000 large lakes across the globe to determine 'what controls the differential sensitivity of lakes to environmental perturbation'. This was an ambitious project that was only possible by bringing together a consortium of scientists with complementary skills. These include expertise in remote sensing of freshwaters and processing large volumes of satellite images, collation and analysis of large-scale environmental data, environmental statistics and the assessment of data uncertainty, freshwater ecology and mechanisms of environmental change and the ability to produce lake models to forecast future lake conditions.\r\n\r\nThis SPEI collaboration consists of high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset over the whole of Africa at different time scales from 1 month to 48 months. It is calculated based on precipitation estimates from the satellite-based Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and potential evaporation estimates by the Global Land Evaporation Amsterdam Model (GLEAM)." } ], "responsiblepartyinfo_set": [ 53476, 53479, 53477, 53478, 53482, 53484, 53486, 53480, 53481, 53483, 53485, 53487, 53488, 53489, 53490, 53491, 53492 ], "onlineresource_set": [ 8542, 8538, 8539, 8540, 8537, 8541, 14980, 15819, 16449, 8536, 87707, 87708 ] }, { "ob_id": 13934, "uuid": "b7a85765c1bc413a96e38ef851ecf9e3", "title": "Cape Verde Atmospheric Observatory: Particle Number Size Distribution (2008-2009)", "abstract": "Data from observations made at the Cape Verde Atmospheric Observatory (CVAO) which exists to advance understanding of climatically significant interactions between the atmosphere and ocean and to provide a regional focal point and long-term data. \r\n\r\nThe observatory is based on Calhau Island of São Vicente, Cape Verde at 16.848N, 24.871W, in the tropical Eastern North Atlantic Ocean, a region which is data poor but plays a key role in atmosphere-ocean interactions of climate-related and biogeochemical parameters including greenhouse gases. It is an open-ocean site that is representative of a region likely to be sensitive to future climate change, and is minimally influenced by local effects and intermittent continental pollution. \r\n\r\nThe dataset contains Particle Number Size Distribution measured using a SMPS and an APS.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2012-02-03T09:02:00", "updateFrequency": "asNeeded", "dataLineage": "Data collected at Cape Verde Atmospheric Observatory before being transmitted back to UK where NCAS staff prepare data for archiving at BADC.", "removedDataReason": "", "keywords": "Cape Verde, Carbon monoxide, Aerolaser", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "completed", "dataPublishedTime": "2010-09-14T13:14:18", "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": 13935, "dataPath": "/badc/capeverde/data/cv-aerosol-phys", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 19826460, "numberOfFiles": 31, "fileFormat": "Data are NASA Ames formatted" }, "timePeriod": { "ob_id": 3725, "startTime": "2008-02-01T00:00:00", "endTime": "2009-06-30T22:59:59" }, "resultQuality": { "ob_id": 226, "explanation": "Data from Cape Verde observatory are for research", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2012-09-10" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 13936, "uuid": "5f6970ed9b2e40e8b65a2d31e5f8cf7c", "short_code": "acq", "title": "Acquisition Process for: cv-aerosol-phys at Cape Verde", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Particle Number Size Distribution measured using a SMPS and an APS; PLATFORMS: Cape Verde Observatory; " }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 13 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2522, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 875, "uuid": "d5422d54d519ed056cc17e97037732b8", "short_code": "proj", "title": "Cape Verde Atmospheric Observatory Measurements", "abstract": "Measurements conducted at Cape Verde Atmospheric Observatory (CVAO)\r\n\r\nThe CVAO (16° 51' 49 N, 24° 52' 02 W), exists to advance understanding of climatically-significant interactions between the atmosphere and ocean and to provide a regional focal point and long-term data context for field campaigns. Measurements of O3, CO, NO, NO2, NOy and VOCs began at the site in October 2006. Chemical characterisation of aerosol measurements and flask sampling of greenhouse gases began in November 2006, halocarbon measurements in May 2007, and physical measurements of aerosol in June 2008. On-line measurements of greenhouse gases began in October 2008." } ], "inspireTheme": [], "topicCategory": [], "phenomena": [ 21764, 62313 ], "vocabularyKeywords": [], "identifier_set": [], "observationcollection_set": [ { "ob_id": 5007, "uuid": "dccb03b976696e2dfee42ef259a546a2", "short_code": "coll", "title": "UK SOLAS Cape Verde Observatory Measurement Campaign (2006-2009)", "abstract": "The UK SOLAS Cape Verde Atmospheric Observatory (16.848N, 24.871W) exists to advance understanding of climatically significant interactions between the atmosphere and ocean and to provide a regional focal point and long-term data context for SOLAS field campaigns. The observatory is based on Calhau Island of São Vicente, Cape Verde in the tropical Eastern North Atlantic Ocean, a region which is data poor but plays a key role in atmosphere-ocean interactions of climate-related and biogeochemical parameters including greenhouse gases. It is an open-ocean site that is representative of a region likely to be sensitive to future climate change, and is minimally influenced by local effects and intermittent continental pollution. Measurements began at the site in October 2006 and are continuing to this day. Note that only observations for the period 2006-2009 were used in the context of the SOLAS project." }, { "ob_id": 872, "uuid": "81693aad69409100b1b9a247b9ae75d5", "short_code": "coll", "title": "Continuous Cape Verde Atmospheric Observatory Observations", "abstract": "Data from observations made at the Cape Verde Atmospheric Observatory (CVAO) which exists to advance understanding of climatically significant interactions between the atmosphere and ocean and to provide a regional focal point and long-term data.\r\n\r\nThe observatory is based on Calhau Island of São Vicente Cape Verde at 16.848N, 24.871W, in the tropical Eastern North Atlantic Ocean, a region which is data poor but plays a key role in atmosphere-ocean interactions of climate-related and biogeochemical parameters including greenhouse gases. It is an open-ocean site that is representative of a region likely to be sensitive to future climate change, and is minimally influenced by local effects and intermittent continental pollution.\r\n\r\nThe dataset collection contains mixing ratio measurements of Ozone, CO, ethane, propane, iso-butane, acetylene, iso-pentane, and halocarbons. Meteorological measurements (wind speed, wind direction, atmospheric pressure, air temperature, relative humidity, solar radiation, rainfall) and aerosol concentrations are also contained in the data set. \r\n\r\nThe Cape Verde Observatory was previously used during the SOLAS (Surface Ocean / Lower Atmosphere Study) project, from which the present day continuous observations have evolved. As such the earlier SOLAS measurements are also included within this collection. Additionally, back trajectory plots for the site are also within this collection." } ], "responsiblepartyinfo_set": [ 53508, 53509, 53512, 53513, 53514, 53510, 53515, 53511, 55565 ], "onlineresource_set": [] }, { "ob_id": 13937, "uuid": "7b1677b1c05b45cba3f39f48e0c4de28", "title": "Cape Verde Atmospheric Observatory: Halocarbon measurements (2007-2008)", "abstract": "Data from observations made at the Cape Verde Atmospheric Observatory (CVAO) which exists to advance understanding of climatically significant interactions between the atmosphere and ocean and to provide a regional focal point and long-term data. \r\n\r\nThe observatory is based on Calhau Island of São Vicente, Cape Verde at 16.848N, 24.871W, in the tropical Eastern North Atlantic Ocean, a region which is data poor but plays a key role in atmosphere-ocean interactions of climate-related and biogeochemical parameters including greenhouse gases. It is an open-ocean site that is representative of a region likely to be sensitive to future climate change, and is minimally influenced by local effects and intermittent continental pollution. \r\n\r\nThe dataset contains Halocarbon measurements made using a pre-concentration system coupled with a GCMS.", "creationDate": "2022-07-22T09:15:57.183554", "lastUpdatedDate": "2022-07-22T09:15:57.272326", "latestDataUpdateTime": "2008-09-15T11:56:06", "updateFrequency": "asNeeded", "dataLineage": "Data collected at Cape Verde Atmospheric Observatory before being transmitted back to UK where NCAS staff prepare data for archiving at BADC.", "removedDataReason": "", "keywords": "Cape Verde, Chemistry", "publicationState": "published", "nonGeographicFlag": false, "dontHarvestFromProjects": false, "language": "English", "resolution": "", "status": "ongoing", "dataPublishedTime": "2010-09-14T13:14:12", "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": 13938, "dataPath": "/badc/capeverde/data/cv-gc-ms/", "oldDataPath": [], "storageLocation": "internal", "storageStatus": "online", "volume": 235687, "numberOfFiles": 9, "fileFormat": "Data are NASA Ames formatted" }, "timePeriod": { "ob_id": 3726, "startTime": "2007-05-08T23:00:00", "endTime": "2008-01-31T23:59:59" }, "resultQuality": { "ob_id": 230, "explanation": "Data from Cape Verde observatory are for research", "passesTest": true, "resultTitle": "CEDA Data Quality Statement", "date": "2012-09-10" }, "validTimePeriod": null, "procedureAcquisition": { "ob_id": 13939, "uuid": "52344572c72a4f70b2cb5a4802ae5bfa", "short_code": "acq", "title": "Acquisition Process for: cv-gc-ms at Cape Verde", "abstract": "This acquisition is comprised of the following: INSTRUMENTS: Halocarbon measurements made using a pre-concentration system coupled with a GCMS; PLATFORMS: Cape Verde Observatory; " }, "procedureComputation": null, "procedureCompositeProcess": null, "imageDetails": [ 13 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "permissions": [ { "ob_id": 2522, "accessConstraints": null, "accessCategory": "registered", "accessRoles": null, "label": "registered: None group", "licence": { "ob_id": 3, "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/", "licenceClassifications": [ { "ob_id": 3, "classification": "any" } ] } } ], "projects": [ { "ob_id": 875, "uuid": "d5422d54d519ed056cc17e97037732b8", "short_code": "proj", "title": "Cape Verde Atmospheric Observatory Measurements", "abstract": "Measurements conducted at Cape Verde Atmospheric Observatory (CVAO)\r\n\r\nThe CVAO (16° 51' 49 N, 24° 52' 02 W), exists to advance understanding of climatically-significant interactions between the atmosphere and ocean and to provide a regional focal point and long-term data context for field campaigns. 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