Observation Collection List
Get a list of Project objects. Projects have a 1:1 mapping with Observations.
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{ "count": 948, "next": "https://api.catalogue.ceda.ac.uk/api/v3/observationcollections/?format=api&limit=100&offset=400", "previous": "https://api.catalogue.ceda.ac.uk/api/v3/observationcollections/?format=api&limit=100&offset=200", "results": [ { "ob_id": 12404, "uuid": "9a1295858ff14fc6acea73e356a8842c", "short_code": "coll", "title": "GAUGE (Greenhouse gAs UK and Global Emissions) project : Ground based and airborne atmospheric measurement data collection", "abstract": "Collection of data produced by the GAUGE (Greenhouse gAs Uk and Global Emissions) Project.\r\n\r\nThe GAUGE project aimed to produce robust estimates of the UK Greenhouse Gas budget, using new and existing measurement networks and modelling activities at a range of scales. It aimed to integrate inter- calibrated information from ground-based, airborne, ferry-borne, balloon-borne, and space-borne sensors, including new sensor technology.\r\n\r\nGAUGE was part of the Greenhouse Gas Emissions and Feedback Programme funded by the Natural Environment Research Council (NERC).", "keywords": "GAUGE, FAAM, Chemistry, Gases", "publicationState": "published", "dataPublishedTime": "2015-06-29T14:11:00", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1142, "name": "NDGO0005" } ], "member": [ { "ob_id": 16561, "uuid": "684a3a05fccf4222b5ab27b0b39909fd", "short_code": "ob", "title": "FAAM B909 GAUGE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project." }, { "ob_id": 16101, "uuid": "c6d2c4beae3141e3a8a6f3a63753399c", "short_code": "ob", "title": "FAAM B866 GAUGE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project." }, { "ob_id": 16085, "uuid": "cb91e635ada54e939057a99b6c328c76", "short_code": "ob", "title": "FAAM B862 GAUGE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project." }, { "ob_id": 26761, "uuid": "3b1502730218439bb9ae01d4d2f6f55a", "short_code": "ob", "title": "GAUGE: Methane, Carbon Dioxide and Nitrous Oxide measurements taken from Heathfield Tower.", "abstract": "This dataset contains Methane, Carbon Dioxide and Nitrous Oxide measurements taken from Heathfield Tower at 50m and 100m. The measurements were taken using a Gas Chromatography-micro Electron Capture Detector (GC-ECD). This data was collected as part of the NERC GAUGE (Greenhouse gAs UK and Global Emissions) project (NE/K002449/1NERC and TRN1028/06/2015). \r\n\r\nThe GAUGE project aimed to produce robust estimates of the UK Greenhouse Gas budget, using new and existing measurement networks and modelling activities at a range of scales. It aimed to integrate inter- calibrated information from ground-based, airborne, ferry-borne, balloon-borne, and space-borne sensors, including new sensor technology." }, { "ob_id": 16109, "uuid": "1f0eaa660ad3480eb403c62fcc6d56a3", "short_code": "ob", "title": "FAAM B868 GAUGE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project." }, { "ob_id": 27614, "uuid": "b37470e2d12b4763a323a03d0f494f6a", "short_code": "ob", "title": "GAUGE: Methane, carbon dioxide and meteorological observations taken onboard Finlandia Seaways (2015-2017)", "abstract": "This dataset contains methane, carbon dioxide and meteorological observations taken onboard the commercial freight ferry Finlandia Seaways on route between Rosyth (Scotland, UK: 56°1'21.611''N 3°26'21.558'' W) and Zeebrugge (Belgium : 51°21'16.96''N 3°10'34.645''E) 2015-2017 by the Centre for Ecology and hydrology (CEH). The measurements were taken using a Picarro CRDS model G1301, Vaisala WXT510 weather station and Garmin GPS. \r\n\r\nThis data was collected as part of the Natural Environment Research Council (NERC) Greenhouse gAs Uk and Global Emissions (GAUGE) project (NE/K002449/1NERC) and NERC UK-SCAPE programme delivering National Capability (NE/R016429/1).\r\n\r\nThe GAUGE project aimed to determine the magnitude, spatial distribution, and uncertainties of the UK's Greenhouse Gas budget using new and existing measurement networks and modelling approaches at a range of scales." }, { "ob_id": 4499, "uuid": "1a3e640058a30a7ba3e23e2409bfb75d", "short_code": "ob", "title": "HYREX project: Telemetered tipping Bucket raingauge, Brue Catchment area", "abstract": "HYREX (Hydrological Radar Experiment) was a NERC (Natural Environment Research Council) special topic running from May 1993 to April 1997. Field experiments with an emphasis on radar, plus related interpretation and modelling, were carried out to investigate the short term forecasting and hydrological implications of precipitation. A special purpose-built dense rainguage network was established in Somerset as part of the project. Rainguage, radar and related meteorological data plus forecast data from the Met Office Unified Model are available through BADC." }, { "ob_id": 16113, "uuid": "80788753f5be46d5b249822687c7941b", "short_code": "ob", "title": "FAAM B869 GAUGE Transit flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project." }, { "ob_id": 16548, "uuid": "d171f049042e4b16b7efeb38b69f937d", "short_code": "ob", "title": "FAAM B906 GAUGE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project." }, { "ob_id": 27474, "uuid": "311d8ce894f742bb84fa7dd639ea1b2c", "short_code": "ob", "title": "GAUGE: Carbon Dioxide measurements taken from Tacolneston Tower", "abstract": "This dataset contains measurements of enrichment of 14C in carbon dioxide in air taken from Tacolneston tower. The samples were taken at 185m and analysed by Aerosol Mass Spectrometer (AMS) at Keck-Carbon Cycle AMS facility, University of California, Irvine.\r\n\r\nThis data was collected as part of the NERC GAUGE (Greenhouse gAs UK and Global Emissions) project (NE/K002449/1NERC and TRN1028/06/2015). The GAUGE project aimed to produce robust estimates of the UK Greenhouse Gas budget, using new and existing measurement networks and modelling activities at a range of scales. It aimed to integrate inter-calibrated information from ground-based, airborne, ferry-borne, balloon-borne, and space-borne sensors, including new sensor technology." }, { "ob_id": 16552, "uuid": "4fff6faf56db42d698798e49cfffa493", "short_code": "ob", "title": "FAAM B905 GAUGE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project." }, { "ob_id": 16025, "uuid": "18688ff287404882bdf9587970dd23d0", "short_code": "ob", "title": "FAAM B911 GAUGE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project." }, { "ob_id": 26760, "uuid": "a389a79fcb0b45fbae2c76aedeec6234", "short_code": "ob", "title": "GAUGE: Methane, Carbon Dioxide and Nitrous Oxide measurements taken from Bilsdale Tower.", "abstract": "This dataset contains methane, carbon dioxide and nitrous oxide measurements taken from Bilsdale Tower at 42, 108 and 248m. The measurements were taken using a Cavity Ring Down Spectrometer (CRDS). This data was collected as part of the NERC GAUGE (Greenhouse gAs UK and Global Emissions) project (NE/K002449/1NERC and TRN1028/06/2015). \r\n\r\nThe GAUGE project aimed to produce robust estimates of the UK Greenhouse Gas budget, using new and existing measurement networks and modelling activities at a range of scales. It aimed to integrate inter- calibrated information from ground-based, airborne, ferry-borne, balloon-borne, and space-borne sensors, including new sensor technology." }, { "ob_id": 16081, "uuid": "139592e8e19443169b0bd26fe58d8702", "short_code": "ob", "title": "FAAM B861 GAUGE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project." }, { "ob_id": 15920, "uuid": "333f18df8daa4f56a790090747dfed9d", "short_code": "ob", "title": "FAAM B948 GAUGE flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project." }, { "ob_id": 16105, "uuid": "e0c6513c0a28435cb74149170098c92f", "short_code": "ob", "title": "FAAM B867 GAUGE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project." }, { "ob_id": 16097, "uuid": "fdb0f57040d04ecfa9715ea85c8aba49", "short_code": "ob", "title": "FAAM B865 GAUGE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project." }, { "ob_id": 27786, "uuid": "ad00efa6f2b44d92aa1022e5b122bb22", "short_code": "ob", "title": "GAUGE: Ecotech Spectronus FTIR greenhouse gas concentrations on a landfill site near Great Blakenham, Suffolk, from 7th August 2014 to 15th August 2014", "abstract": "This dataset contains concentrations of methane, carbon dioxide, nitrous oxide, and carbon monoxide measured using an Ecotech Spectronus FTIR (Fourier transform infrared) spectrometer. The instrument operated from 7 August 2014 to 15 August 2014 on a landfill site near Great Blakenham, Suffolk. The measurement site was located at 52.112N, 1.082E, and the inlet was located 2m above the ground.\r\n\r\nThis data was collected as part of the Natural Environment Research Council (NERC) Greenhouse gAs Uk and Global Emissions (GAUGE) project.\r\n\r\nThe GAUGE project aimed to determine the magnitude, spatial distribution and uncertainties of the UK's Greenhouse Gas budget using new and existing measurement networks and modelling approaches at a range of scales." }, { "ob_id": 16093, "uuid": "f9d3608121b848c4b47a907d037f36e9", "short_code": "ob", "title": "FAAM B864 Instrument test flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects (Instrument test)." }, { "ob_id": 15578, "uuid": "aae04c03dac74b59b8ff1e46f765ed8e", "short_code": "ob", "title": "FAAM B850 GAUGE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project." }, { "ob_id": 27780, "uuid": "34660ad77b744572b70fe6a721cbd4f2", "short_code": "ob", "title": "GAUGE: Ecotech Spectronus FTIR greenhouse gas concentrations in Glatton, Cambridgeshire from October 2014 to April 2016", "abstract": "This dataset contains concentrations of methane, carbon dioxide, nitrous oxide, and carbon monoxide measured using an Ecotech Spectronus FTIR (Fourier transform infrared spectrometer) in Glatton, Cambridgeshire. The instrument operated from October 2014 to April 2016 in the tower of St Nicholas Church, Glatton. The church is located at 52.461N, 0.304W, and the inlet was located 20m above the ground.\r\n\r\nThis data was collected as part of the Natural Environment Research Council (NERC) Greenhouse gAs Uk and Global Emissions (GAUGE) project.\r\n\r\nThe GAUGE project aimed to determine the magnitude, spatial distribution, and uncertainties of the UK's Greenhouse Gas budget using new and existing measurement networks and modelling approaches at a range of scales." }, { "ob_id": 15586, "uuid": "b960b6fa1b794abebe96e19e5963964e", "short_code": "ob", "title": "FAAM B852 GAUGE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project." }, { "ob_id": 27483, "uuid": "eb3f1419034c42109e14ab94f4320f0c", "short_code": "ob", "title": "GAUGE: Carbon Dioxide measurements taken from Mace Head Tower", "abstract": "This dataset contains measurements of enrichment of 14C in carbon dioxide in air taken from the sampling tower at Mace Head Observatory. The samples were taken at 185m and analysed by Aerosol Mass Spectrometer (AMS) at Keck-Carbon Cycle AMS facility, University of California, Irvine.\r\n\r\nThis data was collected as part of the NERC GAUGE (Greenhouse gAs UK and Global Emissions) project (NE/K002449/1NERC and TRN1028/06/2015). The GAUGE project aimed to produce robust estimates of the UK Greenhouse Gas budget, using new and existing measurement networks and modelling activities at a range of scales. It aimed to integrate inter-calibrated information from ground-based, airborne, ferry-borne, balloon-borne, and space-borne sensors, including new sensor technology." } ], "identifier_set": [ 8948 ], "responsiblepartyinfo_set": [ 47326, 47327, 47328, 47329, 47332, 47333, 105388, 47330 ], "onlineresource_set": [ 5817 ], "project_set": [ 12409 ] }, { "ob_id": 12415, "uuid": "06cef537c5b14a2e871a333b9bc0b482", "short_code": "coll", "title": "GloboLakes: high-resolution global limnology data", "abstract": "This dataset collection holds high-resolution datasets related to in-land water for limnology (study of in-land waters) and remote sensing applications. These were produced by the Department of Meteorology at the University of Reading. \r\n\r\nInformation on distance-to-land for each water cell and the distance-to-water for each land cell has many potential applications in remote sensing, where the applicability of geophysical retrieval algorithms may be affected by the presence of water or land within a satellite field of view (image pixel).\r\n\r\nThe data was recorded over a 5 year period from 2005-2010 on a global scale. It is expected that new and updated datasets will be added in the future.\r\n\r\n", "keywords": "limnology, lake, freshwater, satellite, environmental change, surface water temperature", "publicationState": "published", "dataPublishedTime": "2015-07-21T09:32:55", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1142, "name": "NDGO0005" }, { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 12414, "uuid": "84d4f66b668241328df0c43f8f3b3e16", "short_code": "ob", "title": "GloboLakes: high-resolution global limnology dataset v1", "abstract": "These data are high-resolution datasets related to in-land water for limnology (study of in-land waters) and remote sensing applications. This includes: distance-to-land, distance-to-water, water-body identifier and lake-centre co-ordinates on a high-resolution (1/360x1/360 degree) grid, produced by the Department of Meteorology at the University of Reading. Data was derived using the ESA CCI Land Cover Map (see linked documentation). \r\n\r\nDatasets containing information to locate and identify water bodies have been generated from high-resolution (1/360x1/360 degree, about 300mx300m) data locating static-water-bodies recently released by the Land Cover Climate Change Initiative (LC CCI) of the European Space Agency. The new datasets provide: distance to land, distance to water, water body identifiers and lake centre locations. The lake identifiers (IDs) are from the Global Lakes and Wetlands Database (GLWD), and lake centres are defined for in-land waters for which GLWD IDs were determined. The new datasets therefore link recent lake/reservoir/wetlands extent to the GLWD, together with a set of coordinates which locates unambiguously the water bodies in the database. \r\n\r\nThe LC CCI water bodies dataset has been obtained from multi-temporal metrics based on time series of the backscattered intensity recorded by ASAR (Advanced Synthetic Aperture Radar) on Envisat between 2005 and 2010. Temporal change in water body extent is common. Future versions of the LC CCI dataset are planned to represent temporal variation, and this will permit these derived datasets to be updated.\r\n\r\nThe paper associated with this dataset is: \r\nL.Carrea O. Embury C.J. Merchant \"High-resolution datasets related to in-land water for limnology and remote sensing applications: distance-to-land, distance-to-water, water-body identifier and lake-centre co-ordinates\" Geoscience Data Journal, vol. 2 issue 2, pp. 83-97, November 2015. DOI: 10.1002/gdj3.32\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 47394, 47398, 47400, 47401, 47402, 47505, 47396, 47397, 47399, 47504, 47395 ], "onlineresource_set": [], "project_set": [ 12408 ] }, { "ob_id": 12422, "uuid": "87f43af9d02e42f483351d79b3d6162a", "short_code": "coll", "title": "UKCP09: Met Office gridded and regional land surface climate observation datasets", "abstract": "This collection contains datasets of climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The data sets cover the UK at 5 x 5 km resolution and span the period 1910 - 2015. They are available at daily, monthly and annual timescales, as well as long-term averages for the periods 1961 - 1990, 1971 - 2000, and 1981 - 2010. Baseline averages are also available at 25 x 25 km resolution to match the UKCP09 climate change projections. \r\n\r\nThe primary purpose of this data resource is to encourage and facilitate research into climate change impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Environment, Food and Rural Affairs (Defra) and are promoted within the UK Climate Projections (UKCP09). The UKCP09 report The climate of the UK and recent trends uses these gridded data sets to describe UK climatoloagies and regional trends.", "keywords": "UKCP09, Met Office, DEFRA, Climate, Observations, Historical, Climatology", "publicationState": "published", "dataPublishedTime": "2017-08-21T10:48:26", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 69 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 12487, "uuid": "319b3f878c7d4cbfbdb356e19d8061d6", "short_code": "ob", "title": "UKCP09: Met Office gridded land surface climate observations - daily temperature and precipitation at 5km resolution", "abstract": "This dataset contains a set of daily observations of temperature (daily maximum, daily minimum and daily mean temperature) and rainfall (24 hour accumulation) interpolated to a uniform 5km grid resolution covering the period 1960 to 2014.\r\n\r\nThe input station data originate from the Met Office Integrated Data Archive System - MIDAS - a database at the Met Office of observation station data stretching back to the 18th century. (A version of MIDAS is also available through CEDA, although incremental developments to the database such as quality control and data recovery activities may result in some differences compared to the database at the time of production of the UKCP09 data - see linked datasets for access to these equivalent datasets held by CEDA).\r\n \r\nThe input station data used provide observations relating to periods 0900 to 0900 UTC, so the gridded output stored against day \"dd\" are as follows:\r\n•\tMaximum temperature between 0900 on day dd and 0900 on day dd+1 (normally expect to occur during the afternoon of day dd)\r\n•\tMinimum temperature between 0900 on day dd-1 and 0900 on day dd (normally expect to occur just before dawn on day dd)\r\n•\tMean temperature that is the average of the maximum and minimum temperature\r\n•\tRainfall (or rainfall equivalent in cases of frozen precipitation) amount between 0900 day dd and 0900 day dd+1\r\n\r\nThe gridding process accounts for effects such as latitude, longitude, altitude, coastal influence, and the effect of urban land through the use of normalisation with respect to monthly 1961 – 1990 climate normals, and in the case of temperature, a regression model.\r\n\r\nThe data are provide in CF-1.5 compliant NetCDF format. The data are additionally provided in ESRI-ascii format, suitable for ingestion in GIS applications, and a simple timeseries format for users requiring a limited number of points." }, { "ob_id": 12421, "uuid": "94f757d9b28846b5ac810a277a916fa7", "short_code": "ob", "title": "UKCP09: Met Office gridded land surface climate observations - monthly climate variables at 5km resolution", "abstract": "This dataset contains a set of observed monthly climate variables on a 5km resolution grid. The observations are derived from 16 daily climate variables that have been averaged (e.g. daily maximum temperature) or summed (e.g. monthly total precipitation) over calendar months. The input station data originate from the Met Office Integrated Data Archive System (A version of MIDAS is also available through CEDA, although incremental developments to the database such as quality control and data recovery activities may result in some differences compared to the database at the time of production of the UKCP09 data).\r\n\r\nThe gridding process accounts for effects such as latitude, longitude, altitude, coastal influence, and the effect of urban land through the use of normalisation with respect to monthly 1961 – 1990 climate normals, and in the case of some variables a regression model. For more details about the construction see Perry and Hollis (2005). \r\n\r\nThe data are provide in CF-1.5 compliant NetCDF format. The data are additionally provided in ESRI-ascii format, suitable for ingestion in GIS applications, and a simple timeseries format for users requiring a limited number of points." }, { "ob_id": 12493, "uuid": "51132aea5ed0433ca338d32a912e3976", "short_code": "ob", "title": "UKCP09: Met Office regional land surface climate observations - long term averages for administrative regions and river basins", "abstract": "This dataset contains a set of reference long term averages for observed climate variables that have been spatially averaged over a set of 14 administrative regions and 23 river basins across the British Isles (see links to maps and lists below). Where possible, reference climatologies for each of the periods 1961-1990, 1971-2000 and 1981-2010 are available for each variable. The availability of a variable for a given reference period was dependant on sufficient data for that variable within the reference period. Each regional value is an average of the 5km x 5km grid cell values that fall within it. \r\n\r\nThe data were derived from the Met Office gridded land surface climate observations – long term averages at 5km resolution (See related dataset) and are provided as space delimited text files.\r\n\r\nThe 14 administrative regions used within UKCP09 were:\r\n- East Midlands \r\n- East of England \r\n- East Scotland \r\n- London \r\n- North East England \r\n- North Scotland \r\n- North West England \r\n- Northern Ireland \r\n- South East England \r\n- South West England \r\n- Wales \r\n- West Midlands \r\n- West Scotland \r\n- Yorkshire & The Humber \r\n\r\nThe 23 river basin regions used within UKCP09 were: \r\n- Anglian \r\n- Argyll \r\n- Clyde \r\n- Dee \r\n- Forth \r\n- Humber \r\n- Neagh Bann \r\n- North East Scotland \r\n- North Eastern Ireland \r\n- North Highland \r\n- North West England \r\n- North Western Ireland \r\n- Northumbria \r\n- Orkney and Shetland \r\n- Severn \r\n- Solway \r\n- South East England \r\n- South West England \r\n- Tay \r\n- Thames \r\n- Tweed \r\n- West Highland \r\n- Western Wales" }, { "ob_id": 12489, "uuid": "68dfe0967cea4320a3889c2594fb1e0f", "short_code": "ob", "title": "UKCP09: Met Office gridded land surface climate observations - precipitation and temperature indices at 5km resolution", "abstract": "This dataset contains a set of observed climate indices on a 5km resolution grid. The data are derived from daily temperature and precipitation grids (see related dataset) to provide annual indicies: 9 temperature based indices (for example summer heatwave duration); and 12 precipitation indices (for example maximum 1 day precipitation amount).\r\n\r\nThe data are provide in CF-1.5 compliant NetCDF format. The data are additionally provided in ESRI-ascii format, suitable for ingestion in GIS applications, and a simple timeseries format for users requiring a limited number of points.\r\n" }, { "ob_id": 12491, "uuid": "a7e005b4bdd54977aa54251f5f491801", "short_code": "ob", "title": "UKCP09: Met Office gridded land surface climate observations - long term averages at 25km resolution", "abstract": "This dataset contains a set of reference long term averages for observed climate variables on an approximately 25km resolution grid. This matches the resolution of the HadRM3 regional climate model and the UKCP09 climate projections. These data represent the baseline reference climate averages for the period 1961 – 1990. \r\n\r\nThe data were derived from the Met Office gridded land surface climate observations – long term averages at 5km resolution (see related dataset). Each 25 x 25km grid box value is an average of the 5 x 5 km grid cell values that fall within it. Averages have been calculated for each month, season and the year as a whole (17 data sets). For the days of frost and days of rain variables the seasonal and annual averages are the total of the individual monthly averages. For the remaining variables the seasonal and annual averages are the mean of the monthly averages (allowing for differences in month length). To facilitate combining the baseline data with the UKCP09 climate projections, the 25 km baseline averages for rainfall have been expressed in units of millimetres per day (rather than total millimetres, as for the 5 km data sets).\r\n\r\nThe data are provide in CF-1.5 compliant NetCDF format. The data are additionally provided in ESRI-ascii format, suitable for ingestion in GIS applications, and a simple timeseries format for users requiring a limited number of points." }, { "ob_id": 12424, "uuid": "620f6ed379d543098be1126769111007", "short_code": "ob", "title": "UKCP09: Met Office gridded land surface climate observations - long term averages at 5km resolution", "abstract": "This dataset contains a set of reference long term averages for observed climate variables on a 5km resolution grid. Where possible, reference climatologies are available for the periods 1961-1990, 1971-2000 and 1981-2010 for each variable. The availability of the variable for the given reference period was dependant on sufficient data being available for the variable for that period. \r\n\r\nThe data were derived from the Met Office gridded land surface climate observations - monthly variables at 5km resolution (see related dataset). The averages are calculated by averaging the 30 monthly or annual gridded datasets for each variable for each averaging period.\r\n\r\nThe data are provide in CF-1.5 compliant NetCDF format. The data are additionally provided in ESRI-ascii format, suitable for ingestion in GIS applications." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 47732, 47731, 47730, 47728, 47727, 47726, 47725, 47729, 51695, 51696 ], "onlineresource_set": [ 5964, 5965, 7954, 7955 ], "project_set": [ 12420 ] }, { "ob_id": 12683, "uuid": "bcef9e87740e4cbabc743d295afbe849", "short_code": "coll", "title": "ESA Fire Climate Change Initiative (Fire CCI) Dataset Collection", "abstract": "The ESA Fire Climate Change Initiative (Fire_cci) project is producing long-term datasets of burned area information from satellites, as part of the ESA Climate Change Initiative. The data is of use for those interested in historical burned patterns, fire management and emissions analysis and climate change research, by providing a consistent burned area time series. \r\n\r\nCurrent datasets consist of maps of global burned area for the years 1982 to 2019. Products are available at different spatial resolutions: the Pixel product (at the original resolution of the sensor data) and the Grid product (0.25 degrees resolution), the latter of which is produced from the Pixel product. They are based upon spectral information from different sensors, and in many cases also thermal information from active fires.\r\n\r\nGlobal products: \r\n\r\nFireCCI41: Medium Resolution Imaging Spectrometer (MERIS) reflectance, on board the ENVISAT ESA satellite, 300m spatial resolution, and MODIS active fires. Temporal resolution: 2005 – 2011.\r\nFireCCI50: Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and active fires, on board the TERRA satellite, 250m spatial resolution, temporal resolution: 2001 – 2016.\r\nFireCCI51: Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance and active fires, on board the TERRA satellite, 250m spatial resolution, temporal resolution: 2001 – 2019.\r\n\r\nFireCCILT10 (beta product): Advanced Very High Resolution Radiometer (AVHRR) Land Long Term Data Record (LTDR) reflectance. Provided only as grid product. Temporal resolution: 1982-2017.\r\n\r\nContinental products:\r\n\r\nFireCCISFD11: Multispectral Instrument (MSI) reflectance, on board the Sentinel-2A satellite, 20 spatial resolution, and MODIS active fires. Temporal resolution: 2016, spatial coverage: Sub-Saharan Africa.", "keywords": "ESA, CCI, Fire", "publicationState": "published", "dataPublishedTime": "2016-02-02T09:06:36", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26434, "uuid": "58f00d8814064b79a0c49662ad3af537", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): MODIS Fire_cci Burned Area Pixel product, version 5.1", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. These MODIS Fire_cci v5.1 pixel products are distributed as 6 continental tiles and are based upon data from the MODIS instrument onboard the TERRA satellite at 250m resolution for the period 2001-2020. This product supersedes the previously available MODIS v5.0 product. The v5.1 dataset was initially published for 2001-2017, and has later been periodically extended to include 2018 to 2022.\r\n\r\nThe Fire_cci v5.1 Pixel product described here includes maps at 0.00224573-degrees (approx. 250m) resolution. Burned area(BA) information includes 3 individual files, packed in a compressed tar.gz file: date of BA detection (labelled JD), the confidence level (CL, a probability value estimating the confidence that a pixel is actually burned), and the land cover (LC) information as defined in the Land_Cover_cci v2.0.7 product.\r\n\r\nFiles are in GeoTIFF format using a geographic coordinate system based on the World Geodetic System (WGS84) reference ellipsoid and using Plate Carrée projection with geographical coordinates of equal pixel size. For further information on the product and its format see the Fire_cci Product User Guide in the linked documentation." }, { "ob_id": 34730, "uuid": "c98515f1934a4db68d2007b47c5a8d04", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): Sentinel-3 SYN Burned Area Pixel product, version 1.0", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. The Sentinel-3 SYN Fire_cci v1.0 pixel product is distributed as 6 continental tiles and is based upon surface reflectance data from the OLCI and SLSTR instruments (combined as the Synergy (SYN) product) onboard the Sentinel-3 A&B satellites. This information is complemented by VIIRS thermal information. This product, called FireCCIS310 for short, is currently available for 2019, but it is foreseen to be extended for additional years.\r\n\r\nThe FireCCIS310 Pixel product described here includes maps at 0.002777-degree (approx. 300m) resolution. Burned area (BA) information includes 3 individual files, packed in a compressed tar.gz file: date of BA detection (labelled JD), the confidence level (CL, a probability value estimating the confidence that a pixel is actually burned), and the land cover (LC) information as defined in the Copernicus Climate Change Service (C3S) Land Cover v2.1.1 product. An unpacked version of the data is also available. For further information on the product and its format see the Product User Guide in the linked documentation." }, { "ob_id": 19674, "uuid": "3a3503a06f69429e8a4827592e23787e", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): Burned Area Pixel Product Version 4.1", "abstract": "The ESA Fire Climate Change Initiative (CCI) dataset consists of maps of global burned areas for years 2005 to 2011, developed from satellite observations. The products are distributed as 6 continental tiles and are based upon spectral information from the Medium Resolution Imaging Spectrometer (MERIS), on board the ESA ENVISAT satellite and thermal information from the MODIS active fires product.\r\n\r\nThe Pixel product includes maps at 0.00277778-degree (approx. 300m) resolution. Burned area (BA) information is included in 3 layers: date of BA detection, the confidence level (a probability value estimating the confidence that a pixel is actually burned), and the land cover information as defined in the Land Cover CCI v1.6.1 product.\r\n\r\nFiles are in GeoTIFF format using a geographic coordinate system based on the World Geodetic System (WGS84) reference ellipsoid and using Plate Carrée projection with geographical coordinates of equal pixel size. For further information on the product and its format see the Fire_cci Product User Guide in the linked documentation." }, { "ob_id": 40038, "uuid": "d441079fc77f49fabeb41330612b252f", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): Sentinel-3 SYN Burned Area Pixel product, version 1.1", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. The Sentinel-3 SYN Fire_cci v1.1 pixel product is distributed as 6 continental tiles and is based upon surface reflectance data from the OLCI and SLSTR instruments (combined as the Synergy (SYN) product) onboard the Sentinel-3 A&B satellites. This information is complemented by VIIRS thermal information. This product, called FireCCIS311 for short, is available for the years 2019 to 2024.\r\n\r\nThe FireCCIS311 Pixel product described here includes maps at 0.002777-degree (approx. 300m) resolution. Burned area (BA) information includes 3 individual files, packed in a compressed tar.gz file: date of BA detection (labelled JD), the confidence level (CL, a probability value estimating the confidence that a pixel is actually burned), and the land cover (LC) information as defined in the Copernicus Climate Change Service (C3S) Land Cover v2.1.1 product. An unpacked version of the data is also available. For further information on the product and its format see the Product User Guide in the linked documentation." }, { "ob_id": 34729, "uuid": "3aaaaf94813e48f18f2b83242a8dacbe", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): Sentinel-3 SYN Burned Area Grid product, version 1.0", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. The Sentinel-3 SYN Fire_cci v1.0 grid product described here contains gridded data on global burned area derived from surface reflectance data from the OLCI and SLSTR instruments (combined as the Synergy (SYN) product) onboard the Sentinel-3 A&B satellites, complemented by VIIRS thermal information. This product, called FireCCIS310 for short, is currently available for 2019, but it is foreseen to be extended for additional years.\r\n\r\nThis gridded dataset has been derived from the FireCCIS310 pixel product (also available) by summarising its burned area information into a regular grid covering the Earth at 0.25 x 0.25 degrees resolution and at monthly temporal resolution. Information on burned area is included in 22 individual quantities: sum of burned area, standard error, fraction of burnable area, fraction of observed area, and the burned area for 18 land cover classes, as defined by the Copernicus Climate Change Initiative(C3S) Land Cover v2.1.1 product. For further information on the product and its format see the Product User Guide in the linked documentation." }, { "ob_id": 32259, "uuid": "4c5feb539f1f44308ca7ec26e0bb7316", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): Small Fire Dataset (SFD) Burned Area pixel product for Sub-Saharan Africa, version 2.0", "abstract": "The ESA Fire Disturbance Climate Change Initiative (Fire_cci) project has produced maps of global burned area developed from satellite observations. The Small Fire Dataset (SFD) pixel products have been obtained by combining spectral information from Sentinel-2 MSI data and thermal information from VIIRS VNP14IMGML active fire products.\r\n\r\nThis dataset is part of v2.0 of the Small Fire Dataset (also known as FireCCISFD11), which covers Sub-Saharan Africa for the year 2019. Data is available here at pixel resolution (0.00017966259 degrees, corresponding to approximately 20m at the Equator). Gridded data products are also available in a separate dataset." }, { "ob_id": 40037, "uuid": "da8e669a74334c82a56e0b470bc4ef04", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): Sentinel-3 SYN Burned Area Grid product, version 1.1", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. The Sentinel-3 SYN Fire_cci v1.1 grid product described here contains gridded data on global burned area derived from surface reflectance data from the OLCI and SLSTR instruments (combined as the Synergy (SYN) product) onboard the Sentinel-3 A&B satellites, complemented by VIIRS thermal information. This product, called FireCCIS311 for short, is available for the years 2019 to 2024.\r\n\r\nThis gridded dataset has been derived from the FireCCIS311 pixel product (also available) by summarising its burned area information into a regular grid covering the Earth at 0.25 x 0.25 degrees resolution and at monthly temporal resolution. Information on burned area is included in 22 individual quantities: sum of burned area, standard error, fraction of burnable area, fraction of observed area, and the burned area for 18 land cover classes, as defined by the Copernicus Climate Change Initiative (C3S) Land Cover v2.1.1 product. For further information on the product and its format see the Product User Guide in the linked documentation." }, { "ob_id": 26188, "uuid": "4f377defc2454db9b2a6d032abfd0cbd", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): AVHRR-LTDR Burned Area Grid product, version 1.0", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. The AVHRR - LTDR Grid v1.0 product described here contains gridded data of global burned area derived from spectral information from the AVHRR (Advanced Very High Resolution Radiometer) Land Long Term Data Record (LTDR) v5 dataset produced by NASA.\r\n\r\nThe dataset provides monthly information on global burned area on a 0.25 x 0.25 degree resolution grid from 1982 to 2017. The year 1994 is omitted as there was not enough input data for this year. For further information on the product and its format see the product user guide.\r\n\r\nThis v1.0 product is released as a beta version; only the gridded version of the data is available." }, { "ob_id": 25111, "uuid": "f1c9c7aa210d4564bd61ed1a81d51130", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): MODIS Fire_cci Burned Area Grid product, version 5.0", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area developed from satellite observations. The MODIS Fire_cci v5.0 grid products described here are derived from the MODIS instrument onboard the TERRA satellite at 250m resolution for the period 2001 to 2016. This is the first time that MODIS 250m resolution images are used for global burned area (BA) mapping.\r\n\r\nThis dataset is a gridded product, derived from the MODIS Fire_cci v5.0 pixel product by summarising its burned area information into a regular grid covering the Earth for 15-day periods with 0.25 degree resolution. Information on burned area is included in 23 individual quantities: sum of burned area, standard error, fraction of burnable area, fraction of observed area, number of patches and the burned area for 18 land cover classes, as defined by the Land_Cover_cci v1.6.1 product. For further information on the product and its format see the Fire_cci product user guide in the linked documentation.\r\n\r\nPlease note, a new version of this dataset (v5.1) is now available." }, { "ob_id": 19672, "uuid": "fa493d62c2af4c5cb8e6e3c340cdbf0d", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): Burned Area Grid Product Version 4.1", "abstract": "The ESA Fire Climate Change Initiative (CCI) dataset collection consists of maps of global burned areas for years 2005 to 2011, developed from satellite observations. The products are based upon spectral information from the Medium Resolution Imaging Spectrometer (MERIS), on board the ESA ENVISAT satellite, and thermal information from the MODIS active fires product.\r\n\r\nThe Grid product is derived from the Pixel product by summarising its burned area information into a regular grid covering the Earth for 15-day periods with 0.25 degree resolution. Information on burned area is included in 22 individual layers: sum of burned area, standard error, fraction of observed area, number of patches and the burned area for 18 land cover classes, as defined by the Land Cover CCI v1.6.1 product. For further information on the product and its format see the Fire_cci product user guide in the linked documentation." }, { "ob_id": 26433, "uuid": "3628cb2fdba443588155e15dee8e5352", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): MODIS Fire_cci Burned Area Grid product, version 5.1", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. The MODIS Fire_cci v5.1 grid product described here contains gridded data on global burned area derived from the MODIS instrument onboard the TERRA satellite at 250m resolution for the period 2001 to 2019. This product supercedes the previously available MODIS v5.0 product. The v5.1 dataset was initially published for 2001-2017, and has later been periodically extended to include 2018 to 2022. \r\n\r\nThis gridded dataset has been derived from the MODIS Fire_cci v5.1 pixel product (also available) by summarising its burned area information into a regular grid covering the Earth at 0.25 x 0.25 degrees resolution and at monthly temporal resolution. Information on burned area is included in 23 individual quantities: sum of burned area, standard error, fraction of burnable area, fraction of observed area, number of patches and the burned area for 18 land cover classes, as defined by the Land_Cover_cci v2.0.7 product. For further information on the product and its format see the Fire_cci product user guide in the linked documentation." }, { "ob_id": 32258, "uuid": "01b00854797d44a59d57c8cce08821eb", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): Small Fire Database (SFD) Burned Area grid product for Sub-Saharan Africa, version 2.0", "abstract": "The ESA Fire Disturbance Climate Change Initiative (Fire_cci) project has produced maps of global burned area developed from satellite observations. The Small Fire Database (SFD) pixel products have been obtained by combining spectral information from Sentinel-2 MSI data and thermal information from VIIRS VNP14IMGML active fire products.\r\n\r\nThis gridded dataset has been derived from the Small Fire Database (SFD) Burned Area pixel product for Sub-Saharan Africa, v2.0 (also available), which covers Sub-Saharan Africa for the year 2019, by summarising its burned area information into a regular grid covering the Earth at 0.05 x 0.05 degrees resolution and at monthly temporal resolution." }, { "ob_id": 43179, "uuid": "593397b5f9654d76b5d37761e7566ca6", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): Long-term Small Fire Dataset (SFDL) Burned Area pixel product for Test Sites: Amazonia, Africa and Siberia, version 1.0", "abstract": "The ESA Fire Disturbance Climate Change Initiative (Fire_cci) project aims to generate burned area developed from satellite observations. The Long-Term Small Fire Dataset (SFDL) pixel products have been obtained using spectral information from Landsat sensors for three study areas located in different parts of the world (Amazon, Sahel and Siberia), and coinciding with the ESA CCI High Resolution Land Cover product.\r\n\r\nThe dataset uses surface reflectance information from the Landsat-4 and Landsat-5 TM, Landsat-7 ETM+ and Landsat-8 OLI sensors, and covers the period 1990 to 2019, with a spatial resolution of 0.00025 degrees (approximately 30 m at the Equator)." }, { "ob_id": 26189, "uuid": "4b0773a84e8142c688a628c9ce62d4ec", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): Small Fire Database (SFD) Burned Area grid product for Sub-Saharan Africa, version 1.1", "abstract": "The ESA Fire Disturbance Climate Change Initiative (Fire_cci) project has produced maps of global burned area developed from satellite observations. The Small Fire Database (SFD) pixel products have been obtained by combining spectral information from Sentinel-2 MSI data and thermal information from MODIS MOD14MD Collection 6 active fire products.\r\n\r\nThis gridded dataset has been derived from the Small Fire Database (SFD) Burned Area pixel product for Sub-Saharan Africa, v1.1 (also available), which covers Sub-Saharan Africa for the year 2016, by summarising its burned area information into a regular grid covering the Earth at 0.25 x 0.25 degrees resolution and at monthly temporal resolution." }, { "ob_id": 26187, "uuid": "065f6040ef08485db989cbd89d536167", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): Small Fire Dataset (SFD) Burned Area pixel product for Sub-Saharan Africa, version 1.1", "abstract": "The ESA Fire Disturbance Climate Change Initiative (Fire_cci) project has produced maps of global burned area developed from satellite observations. The Small Fire Dataset (SFD) pixel products have been obtained by combining spectral information from Sentinel-2 MSI data and thermal information from MODIS MOD14MD Collection 6 active fire products.\r\n\r\nThis dataset is part of v1.1 of the Small Fire Dataset (also known as FireCCISFD11), which covers Sub-Saharan Africa for the year 2016. Data is available here at pixel resolution (0.00017966259 degrees, corresponding to approximately 20m at the Equator). Gridded data products are also available in a separate dataset." }, { "ob_id": 12535, "uuid": "56224b6755a843298af463827e9832ae", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire CCI): Burned Area Pixel Product Version 3.1", "abstract": "The ESA Fire Climate Change Initiative (CCI) dataset consists of maps of global burned areas for years 2006 to 2008, developed from satellite observations. The products are distributed as 6 continental tiles and are based upon thermal information from MODIS active fires product and spectral information from the Medium Resolution Imaging Spectrometer (MERIS), on board the ENVISAT ESA satellite.\r\nThe Pixel product includes maps in raster format, at 300m resolution. Burned area (BA) information is included in 3 layers: date of BA detection, the land cover of the burned pixel and the confidence level, a probability value estimating the confidence that a pixel is actually burned.\r\n\r\nAll files are in standard zip compression format, each yearly compressed file holding a set of monthly compressed files. Files are in Geotiff format using a geographic coordinate system based on the World Geodetic System (WGS84) reference ellipsoid and using Plate Carree projection with geographical coordinates of equal pixel size. For further information on the product and its format see the Fire CCI product user guide in linked documentation." }, { "ob_id": 25112, "uuid": "9c666602b89e468493e1c907a4de62ff", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): MODIS Fire_cci Burned Area Pixel product, version 5.0", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. These MODIS Fire_cci v5.0 pixel products are distributed as 6 continental tiles and are based upon data from the MODIS instrument onboard the TERRA satellite at 250m resolution for the period 2001-2016. This is the first time that MODIS 250m resolution images are used for global burned area (BA) mapping.\r\n\r\nThe Fire_cci v5.0 Pixel product described here includes maps at 0.00224573-degrees (approx. 250m) resolution. Burned area(BA) information includes 3 individual files, packed in a compressed tar.gz file: date of BA detection (labelled JD), the confidence level (CL, a probability value estimating the confidence that a pixel is actually burned), and the land cover (LC) information as defined in the Land_Cover_cci v1.6.1 product.\r\n\r\nFiles are in GeoTIFF format using a geographic coordinate system based on the World Geodetic System (WGS84) reference ellipsoid and using Plate Carrée projection with geographical coordinates of equal pixel size. For further information on the product and its format see the Fire_cci Product User Guide in the linked documentation. \r\n\r\nPlease note, a new version of this product (v5.1) is now available." }, { "ob_id": 31987, "uuid": "b1bd715112ca43ab948226d11d72b85e", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): AVHRR-LTDR Burned Area Pixel product, version 1.1", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. The AVHRR - LTDR Pixel v1.1 product described here contains gridded data of global burned area derived from spectral information from the AVHRR (Advanced Very High Resolution Radiometer) Land Long Term Data Record (LTDR) v5 dataset produced by NASA.\r\n\r\nThe dataset provides monthly information on global burned area at 0.05-degree spatial resolution (the resolution of the AVHRR-LTDR input data) from 1982 to 2018. The year 1994 is omitted as there was not enough input data for this year. The dataset is distributed in monthly GeoTIFF files, packed in annual tar.gz files, and it includes 5 files: date of BA detection (labelled JD), confidence label (CL), burned area in each pixel (BA), number of observations in the month (OB) and a metadata file. For further information on the product and its format see the Product User Guide." }, { "ob_id": 31986, "uuid": "62866635ab074e07b93f17fbf87a2c1a", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): AVHRR-LTDR Burned Area Grid product, version 1.1", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. The AVHRR - LTDR Grid v1.1 product described here contains gridded data of global burned area derived from spectral information from the AVHRR (Advanced Very High Resolution Radiometer) Land Long Term Data Record (LTDR) v5 dataset produced by NASA.\r\n\r\nThe dataset provides monthly information on global burned area on a 0.25 x 0.25 degree resolution grid from 1982 to 2018. The year 1994 is omitted as there was not enough input data for this year. The dataset is distributed in NetCDF files, and it includes 4 layers: sum of burned area, standard error, fraction of burnable area and fraction of observed area. For further information on the product and its format see the Product User Guide." }, { "ob_id": 12543, "uuid": "9821980dc18047f09b9113d44fc2c20b", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire CCI): Burned Area Grid Product Version 3.1", "abstract": "The ESA Fire Climate Change Initiative (CCI) dataset collection consists of maps of global burned areas for years 2006 to 2008, developed from satellite observations. The products are based upon thermal information from the MODIS active fires product and spectral information from the Medium Resolution Imaging Spectrometer (MERIS), on board the ENVISAT ESA satellite.\r\n\r\nThe Grid product is derived from the Pixel product by summarizing its burned area information into a regular grid covering the Earth for 15-day periods with 0.5 degree resolution. Information on burned area is included in 22 individual layers: sum of burned area, standard error, fraction of observed area, number of patches and the burned area for 18 land cover classes, as defined by the Globcover (2005) product. For further information on the product and its format see the Fire CCI product user guide in linked documentation." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 48679, 54243, 48681, 48680, 105390, 105417, 105441, 54242, 130730, 48462 ], "onlineresource_set": [ 6114, 6113, 6115 ], "project_set": [ 13255 ] }, { "ob_id": 12684, "uuid": "56c94cb1410f4f2b8a41729c0e558617", "short_code": "coll", "title": "ESA Sea Level Climate Change Initiative (Sea Level CCI) dataset collection", "abstract": "As part of the European Space Agency's (ESA) Climate Change Initiative (CCI) programme, the Sea Level CCI project has produced a set of gridded multi-satellite merged products relating to the Sea Level Essential Climate Variable (ECV). These consist of a) a time series of monthly gridded Sea Level Anomalies (SLA) and b) Oceanic Indicators describing the evolution of the sea level anomalies.\r\n\r\nSea surface heights are measured above (or below) some reference level by altimeter satellites, surface height being the difference between a satellites position in orbit with respect to an arbitrary reference surface (the Earth's centre or a rough approximation of the Earth's surface: the reference ellipsoid) and the satellite-to-surface range (calculated by measuring the time taken for the signal to make the round trip). Through sending a microwave pulse to the ocean's surface, the satellites measured the surface heights through measuring the time taken for the pulse to return. \r\n\r\nThe current version is v1.1, and covers the period January 1993 - December 2014, and has been derived from the main altimeter missions: ERS-1, ERS-2, Envisat, TOPEX/Poseidon, Jason-1, Jason-2 and Geosat-Follow-On. A detailed description of the SL CCI project and the products can be found in Ablain et al., 2014, and further information is also provided in the Product User Guide. \r\n\r\nThe following DOI can be used to reference the product database (all products in the V1.1 release (as of December 2015)): DOI:10.5270/esa-sea_level_cci-1993_2014-v_1.1-201512. \r\n\r\n When using or referring to the SL_cci products, please mention the associated DOI (see above and the individual datasets) and also use the following citation where a detailed description of the SL_cci project and products can be found:\r\n\r\nAblain, M., Cazenave, A., Larnicol, G., Balmaseda, M., Cipollini, P., Faugère, Y., Fernandes, M. J., Henry, O., Johannessen, J. A., Knudsen, P., Andersen, O., Legeais, J., Meyssignac, B., Picot, N., Roca, M., Rudenko, S., Scharffenberg, M. G., Stammer, D., Timms, G., and Benveniste, J.: Improved sea level record over the satellite altimetry era (1993–2010) from the Climate Change Initiative project, Ocean Sci., 11, 67-82, doi:10.5194/os-11-67-2015, 2015.\r\n\r\nFor further information on the Sea Level CCI products, and to register your interest with the CCI team please email: info-sealevel@esa-sealevel-cci.org", "keywords": "ESA CCI SEA LEVEL", "publicationState": "published", "dataPublishedTime": "2016-03-08T16:40:00", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 12736, "uuid": "effd70debeb84e75a30cb98a76a48226", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): Oceanic Indicators of Mean Sea Level Changes, Version 1.1", "abstract": "As part of the European Space Agency's (ESA) Sea Level Climate Change Initiative (CCI) project, a number of oceanic indicators of mean sea level changes have been produced from merging satellite altimetry measurements of sea level anomalies. The oceanic indicators dataset consists of static files covering the whole altimeter period, describing the evolution of the project's monthly sea level anomaly gridded product (see separate dataset record).\r\n\r\nA number of indicators are provided including:\r\n- the temporal evolution of the global mean sea level (MSL) with the global slope DOI: DOI: 10.5270/esa-sea_level_cci-IND_MSL_MERGED-1993_2014-v_1.1-201512\r\n- the geographical distribution of MSL trends DOI: 10.5270/esa-sea_level_cci-IND_MSLTR_MERGED-1993_2014-v_1.1-201512\r\n- Maps of the amplitude and phase of the main periodic signals (annual, semi-annual) DOI: 10.5270/esa-sea_level_cci-IND_MSLAMPH_MERGED-1993_2014-v_1.1-201512\r\n\r\nThe complete collection of v1.1 products from the Sea Level CCI project can be referenced using the following DOI:10.5270/esa-sea_level_cci-1993_2014-v_1.1-201512.\r\n\r\nWhen using or referring to the SL_cci products, please mention the associated DOIs and also use the following citation where a detailed description of the SL_cci project and products can be found:\r\n\r\nAblain, M., Cazenave, A., Larnicol, G., Balmaseda, M., Cipollini, P., Faugère, Y., Fernandes, M. J., Henry, O., Johannessen, J. A., Knudsen, P., Andersen, O., Legeais, J., Meyssignac, B., Picot, N., Roca, M., Rudenko, S., Scharffenberg, M. G., Stammer, D., Timms, G., and Benveniste, J.: Improved sea level record over the satellite altimetry era (1993–2010) from the Climate Change Initiative project, Ocean Sci., 11, 67-82, doi:10.5194/os-11-67-2015, 2015.\r\n\r\nFor further information on the Sea Level CCI products, and to register your interest with the CCI team please email: info-sealevel@esa-sealevel-cci.org\r\n\r\n" }, { "ob_id": 33053, "uuid": "f24175ec280b4e1296bb80eb86f88f68", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): High Latitude Sea Level Anomalies from satellite altimetry (by DTU/TUM)", "abstract": "This dataset contains high latitude sea level anomalies produced by DTU (Technical University of Denmark) and TUM (Technical University of Munich) as part of the ESA Sea Level CCI (Climate Change Initiative) project, covering both the Arctic and Antarctic regions.\r\n\r\nThe data comprises weekly means from August 1991 to April 2017 and has been obtained using satellite altimetry data from four satellite missions: ERS1 (weeks 0 - 217); ERS2 (weeks 218 - 573); Envisat (weeks 574 - 1020); CryoSat-2 (weeks 1021 - 1336).\r\n\r\nTwo datasets are available: dataset #1 is based on the ALES+ retracking without correction of the inverse barometer whereas dataset #2 has been corrected for this effect.\r\n\r\nDataset #1 is provided both 'masked' and 'unmasked', where the masked data have been masked using sea ice concentrations downloaded from osisaf.met.no/p/ice. Dataset #2 is provided both 'masked' and 'unmasked', where the masked data have had data points retrieved over land removed from the files." }, { "ob_id": 20337, "uuid": "3ac333b828b54e3495c7749f5bce2fe3", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): Oceanic Indicators of Mean Sea Level Changes, Version 2.0", "abstract": "As part of the European Space Agency's (ESA) Sea Level Climate Change Initiative (CCI) project, a number of oceanic indicators of mean sea level changes have been produced from merging satellite altimetry measurements of sea level anomalies. The oceanic indicators dataset consists of static files covering the whole altimeter period, describing the evolution of the project's monthly sea level anomaly gridded product (see separate dataset record).\r\n\r\nThe oceanic indicators that are provided are: \r\n1) the temporal evolution of the global Mean Sea Level (MSL) DOI: 10.5270/esa-sea_level_cci-IND_MSL_MERGED-1993_2015-v_2.0-201612 ;\r\n2) the geographic distribution of Mean Sea Level changes (MSLTR) DOI: 10.5270/esa-sea_level_cci-IND_MSLTR_MERGED-1993_2015-v_2.0-201612 ;\r\n3) Maps of the amplitude and phase of the annual cycle (MSLAMPH) DOI: 10.5270/esa-sea_level_cci-IND_MSLAMPH_MERGED-1993_2015-v_2.0-201612.\r\n\r\nThe complete collection of v2.0 products from the Sea Level CCI project can be referenced using the following DOI: 10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612.\r\n\r\nWhen using or referring to the SL_cci products, please mention the associated DOIs and also use the following citation where a detailed description of the SL_cci project and products can be found:\r\n\r\nAblain, M., Cazenave, A., Larnicol, G., Balmaseda, M., Cipollini, P., Faugère, Y., Fernandes, M. J., Henry, O., Johannessen, J. A., Knudsen, P., Andersen, O., Legeais, J., Meyssignac, B., Picot, N., Roca, M., Rudenko, S., Scharffenberg, M. G., Stammer, D., Timms, G., and Benveniste, J.: Improved sea level record over the satellite altimetry era (1993–2010) from the Climate Change Initiative project, Ocean Sci., 11, 67-82, doi:10.5194/os-11-67-2015, 2015.\r\n\r\nFor further information on the Sea Level CCI products, and to register for these products please email: info-sealevel@esa-sealevel-cci.org\r\n\r\n" }, { "ob_id": 39803, "uuid": "90049a6555d1480bb5ce9637051dede8", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): New network of virtual altimetry stations for measuring sea level along the world coastlines from 2002 to 2019, v2.2", "abstract": "This dataset contains a 17-year-long (January 2002 to December 2019 ), high-resolution (20 Hz), along-track sea level dataset in coastal zones of: Northeast Atlantic, Mediterranean Sea, whole African continent, North Indian Ocean, Southeast Asia, Australia and North and South America. Up to now, satellite altimetry has provided global gridded sea level time series up to 10-15 km from the coast only, preventing the estimation of how sea level changes very close to the coast on interannual to decadal time scales. \r\n\r\nThis dataset has been derived from a new version of the ESA SL_cci+ dataset of coastal sea level anomalies which is based on the reprocessing of raw radar altimetry waveforms from the Jason-1, Jason-2 and Jason-3 satellite missions to derive satellite-sea surface ranges as close as possible to the coast (a process called ‘retracking’) and optimization of the geophysical corrections applied to the range measurements to produce sea level time series.\r\n\r\nThis large amount of coastal sea level estimates has been further analysed to produce the present dataset: a total of 756 altimetry-based virtual coastal stations have been selected and sea level anomalies time series together with associated coastal sea level trends have been computed over the study time span. \r\n\r\nThe main objective of this dataset is to analyze the sea level trends close to the coast and compare them with the sea level trends observed in the open ocean and to determine the causes of the potential differences.\r\n\r\nThe product has been developed within the sea level project of the extension phase of the European Space Agency (ESA) Climate Change Initiative (SL_cci+). See 'The Climate Change Coastal Sea Level Team (2020). Sea level anomalies and associated trends estimated from altimetry from 2002 to 2018 at selected coastal sites. Scientific Data (Nature), in press'.\r\n\r\nThis dataset is v2.2 of the data and is a copy of the v2.2 data published on the SEANOE (SEA scieNtific Open data Edition) website (https://doi.org/10.17882/74354#98856) \r\n\r\nThe dataset should be cited as: \tCazenave Anny, Gouzenes Yvan, Birol Florence, Legér Fabien, Passaro Marcello, Calafat Francisco M, Shaw Andrew, Niño Fernando, Legeais Jean François, Oelsmann Julius, Benveniste Jérôme (2022). New network of virtual altimetry stations for measuring sea level along the world coastlines. SEANOE. https://doi.org/10.17882/74354\r\n\r\nIn addition,it would be appreciated that the following work(s) be cited too, when using this dataset in a publication :\r\n\r\n - Cazenave Anny, Gouzenes Yvan, Birol Florence, Leger Fabien, Passaro Marcello, Calafat Francisco M., Shaw Andrew, Nino Fernando, Legeais Jean François, Oelsmann Julius, Restano Marco, Benveniste Jérôme (2022). Sea level along the world’s coastlines can be measured by a network of virtual altimetry stations. Communications Earth & Environment, 3 (1). https://doi.org/10.1038/s43247-022-00448-z\r\n\r\n - Benveniste Jérôme, Birol Florence, Calafat Francisco, Cazenave Anny, Dieng Habib, Gouzenes Yvan, Legeais Jean François, Léger Fabien, Niño Fernando, Passaro Marcello, Schwatke Christian, Shaw Andrew (2020). Coastal sea level anomalies and associated trends from Jason satellite altimetry over 2002–2018. Scientific Data, 7 (1). https://doi.org/10.1038/s41597-020-00694-w" }, { "ob_id": 31825, "uuid": "a386504aa8ae492f9f2af04c109346e9", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): A database of coastal sea level anomalies and associated trends from Jason satellite altimetry from 2002 to 2018", "abstract": "This dataset contains 17-year-long (June 2002 to May 2018 ), high-resolution (20 Hz), along-track sea level dataset in coastal zones of six regions: Mediterranean Sea, Northeast Atlantic, West Africa, North Indian Ocean, Southeast Asia and Australia. Up to now, satellite altimetry has provided global gridded sea level time series up to 10-15 km from the coast only, preventing the estimation of how sea level changes very close to the coast on interannual to decadal time scales. \r\n\r\nThis dataset has been derived from the ESA SL_cci+ v1.1 dataset of coastal sea level anomalies (also available in the catalogue, DOI:10.5270/esa-sl_cci-xtrack_ales_sla-200206_201805-v1.1-202005), which is based on the reprocessing of raw radar altimetry waveforms from the Jason-1, Jason-2 and Jason-3 satellite missions to derive satellite-sea surface ranges as close as possible to the coast (a process called ‘retracking’) and optimization of the geophysical corrections applied to the range measurements to produce sea level time series. This large amount of coastal sea level estimates has been further analysed to produce the present dataset: it consists in a selection of 429 portions of satellite tracks crossing land for which valid sea level time series are provided at monthly interval together with the associated sea level trends over the 17-year time span at each along-track 20-Hz point, from 20 km offshore to the coast.\r\n\r\nThe main objective of this dataset is to analyze the sea level trends close to the coast and compare them with the sea level trends observed in the open ocean and to determine the causes of the potential differences.\r\n\r\nThe product has been developed within the sea level project of the extension phase of the European Space Agency (ESA) Climate Change Initiative (SL_cci+). See 'The Climate Change Coastal Sea Level Team (2020). Sea level anomalies and associated trends estimated from altimetry from 2002 to 2018 at selected coastal sites. Scientific Data (Nature), in press'.\r\n\r\nThis dataset has a DOI: https://doi.org/10.17882/74354" }, { "ob_id": 20335, "uuid": "142052b9dc754f6da47a631e35ec4609", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): Time series of gridded Sea Level Anomalies (SLA), Version 2.0", "abstract": "As part of the European Space Agency's (ESA) Sea Level Climate Change Initiative (CCI) project, a multi-satellite merged time series of monthly gridded Sea Level Anomalies (SLA) has been produced from satellite altimeter measurements. The Sea Level Anomaly grids have been calculated after merging the altimetry mission measurements together into monthly grids, with a spatial resolution of 0.25 degrees. This version of the product is Version 2.0. \r\n\r\nThe following DOI can be used to reference the monthly Sea Level Anomaly product: DOI: 10.5270/esa-sea_level_cci-MSLA-1993_2015-v_2.0-201612\r\n\r\nThe complete collection of v2.0 products from the Sea Level CCI project can be referenced using the following DOI: 10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612\r\n\r\nWhen using or referring to the Sea Level cci products, please mention the associated DOIs and also use the following citation where a detailed description of the Sea Level_cci project and products can be found:\r\n\r\nAblain, M., Cazenave, A., Larnicol, G., Balmaseda, M., Cipollini, P., Faugère, Y., Fernandes, M. J., Henry, O., Johannessen, J. A., Knudsen, P., Andersen, O., Legeais, J., Meyssignac, B., Picot, N., Roca, M., Rudenko, S., Scharffenberg, M. G., Stammer, D., Timms, G., and Benveniste, J.: Improved sea level record over the satellite altimetry era (1993–2010) from the Climate Change Initiative project, Ocean Sci., 11, 67-82, doi:10.5194/os-11-67-2015, 2015.\r\n\r\nFor further information on the Sea Level CCI products, and to register for these projects please email: info-sealevel@esa-sealevel-cci.org\r\n" }, { "ob_id": 39804, "uuid": "91d1fbc572224b9c86f6c14ba9109479", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): Regional coastline profile of Vertical Land Motions in Europe and SE Asia/Oceania, v1", "abstract": "This dataset contains a regional coastline profile of Vertical Land Motions in Europe and SE Asia/Oceania produced as part of the ESA Climate Change Initiative Sea Level project.\r\n\r\nVertical Land Motions have been estimated as the difference between the altimeter coastal sea level v1.1 dataset (available from https://catalogue.ceda.ac.uk/uuid/222cf11f49a94d2da8a6da239df2efc4 ) and tide gauge measurements from the Permanent Service for Mean Sea Level (PMSML) network. Spatial interpolation has allowed the production of a regularly spaced coastline profile of vertical land movements together with their uncertainties.\r\n\r\nThe altimeter input data are from the Jason-1, Jason-2 and Jason-3 missions during the period Jan. 2002 - May 2018." }, { "ob_id": 12734, "uuid": "682e9b455aae4f8fb2275580e8e21f1f", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): Time series of gridded Sea Level Anomalies (SLA), Version 1.1", "abstract": "As part of the European Space Agency's (ESA) Sea Level Climate Change Initiative (CCI) project, a multi-satellite merged time series of monthly gridded Sea Level Anomalies (SLA) has been produced from satellite altimeter measurements. The Sea Level Anomaly grids have been calculated after merging the altimetry mission measurements together into monthly grids, with a spatial resolution of 0.25 degrees. This version of the product is Version 1.1. \r\n\r\nThe following DOI can be used to reference the monthly Sea Level Anomaly product: DOI: 10.5270/esa-sea_level_cci-MSLA-1993_2014-v_1.1-201512\r\n\r\nThe complete collection of v1.1 products from the Sea Level CCI project can be referenced using the following DOI:10.5270/esa-sea_level_cci-1993_2014-v_1.1-201512.\r\n\r\nWhen using or referring to the Sea Level cci products, please mention the associated DOIs and also use the following citation where a detailed description of the Sea Level_cci project and products can be found:\r\n\r\nAblain, M., Cazenave, A., Larnicol, G., Balmaseda, M., Cipollini, P., Faugère, Y., Fernandes, M. J., Henry, O., Johannessen, J. A., Knudsen, P., Andersen, O., Legeais, J., Meyssignac, B., Picot, N., Roca, M., Rudenko, S., Scharffenberg, M. G., Stammer, D., Timms, G., and Benveniste, J.: Improved sea level record over the satellite altimetry era (1993–2010) from the Climate Change Initiative project, Ocean Sci., 11, 67-82, doi:10.5194/os-11-67-2015, 2015.\r\n\r\nFor further information on the Sea Level CCI products, and to register for these projects please email: info-sealevel@esa-sealevel-cci.org\r\n" }, { "ob_id": 31822, "uuid": "222cf11f49a94d2da8a6da239df2efc4", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): Altimeter along-track high resolution sea level anomalies in some coastal regions (2002-2018) from the JASON satellites, v1.1", "abstract": "This dataset contains along-track sea level anomalies derived from satellite altimetry. Altimeter along-track sea level measurements from the Jason-1, Jason -2 and Jason-3 satellite missions have been processed to produce high resolution (20 Hz, corresponding to an along-track distance of ~300m) sea level anomalies, in order to provide long-term homogeneous sea level time series as close to the coast as possible in six different coastal regions (North-East Atlantic, Mediterranean Sea, Western Africa, North Indian Ocean, South-East Asia and Australia). These six time series cover the period from 15 January 2002 to 30 May 2018.\r\n\r\nThe product benefits from the spatial resolution provided by high-rate data, the Adaptive Leading Edge Subwaveform Retracker (ALES) and the post-processing strategy of the along-track (X-TRACK) algorithm, both developed for the processing of coastal altimetry data, as well as the best possible set of geophysical corrections. \r\n\r\nThe main objective of this product is to provide accurate altimeter Sea Level Anomalies (SLA) time series as close to the coast as possible in order to assess whether the coastal sea level trends experienced at the coast are similar to the observed sea level trends in the open ocean and to determine the causes of the potential discrepancies.\r\n\r\nThe product has been developed within the sea level project of the extension phase of the European Space Agency (ESA) Climate Change Initiative (SL_cci+). During the project, the product will be extended in spatial coverage and with additional altimeter missions. This version of the dataset is v1.1. (DOI: 10.5270/esa-sl_cci-xtrack_ales_sla-200206_201805-v1.1-202005)" }, { "ob_id": 45177, "uuid": "4be5091f70f04e50b1c1da79d2d89a97", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): New network of virtual altimetry stations for measuring sea level along the world coastlines from 2002 to 2021, v3.0", "abstract": "This dataset contains a 19.5-year-long (January 2002 to June 2021), high-resolution (20 Hz), along-track sea level dataset in most of the world coastal zones, including tropical islands. It has been developed within the sea level project of the European Space Agency (ESA) Climate Change Initiative (SL_cci). \r\n\r\nThe main objective of this dataset is to analyze the sea level trends as well as the inter-annual variability at local scale at an average of less than 2.5km from the coastline. It provides essential information in areas devoid of other sources of measurements, and it also allows filling the gaps in existing timeseries of tide gauges located nearby the stations.\r\n\r\nThis dataset of coastal sea level anomalies is based on the reprocessing of raw radar altimetry waveforms from the Jason-1, Jason-2 and Jason-3 satellite missions to derive satellite-sea surface ranges as close as possible to the coast (a process called ‘retracking’) and optimization of the geophysical corrections applied to the range measurements to produce sea level time series.\r\n\r\nThis large amount of coastal sea level estimates has been further analysed to produce the present dataset: a total of 1634 altimetry-based virtual coastal stations have been selected and sea level anomalies time series together with associated coastal sea level trends have been computed over the study time span.\r\n\r\nThe new updated version (v3.0; June 2025) of along-track coastal sea level time series and associated trends from January 2002 to June 2021 differs from the previous v2.4 product (released in November 2024) by a spatial extension. It also uses the new improved FES22 ocean tide model instead of FES14 model in the previous versions. The data editing (outlier removal) has slightly evolved, and a new variable has been added (sla_mean_10pts_filt). We strongly recommend the users to use this latest v3.0 product.\r\n\r\nFor the latest version of the documentation, see the 'Technical Coastal Sea Level' Key Documents section of the project's website (https://climate.esa.int/en/projects/sea-level/).\r\nThis dataset is v3.0 of the data and is a copy of the v3.0 data published on the SEANOE (SEA scieNtific Open data Edition) website (https://doi.org/10.17882/74354#122284).\r\n\r\nThe dataset should be cited as: Cazenave Anny, Gouzenes Yvan, Leclercq Lancelot, Birol Florence, Legér Fabien, Passaro Marcello, Calafat Francisco M, Shaw Andrew, Niño Fernando, Legeais Jean François, Oelsmann Julius, Benveniste Jérôme, Connors Sarah (2025). New network of virtual altimetry stations for measuring sea level along the world coastlines. SEANOE. https://doi.org/10.17882/74354\r\n\r\nIn addition, it would be appreciated that the following work(s) be cited too, when using this dataset in a publication :\r\n\r\n- Cazenave Anny, Gouzenes Yvan, Birol Florence, Leger Fabien, Passaro Marcello, Calafat Francisco M., Shaw Andrew, Nino Fernando, Legeais Jean François, Oelsmann Julius, Restano Marco, Benveniste Jérôme (2022). Sea level along the world’s coastlines can be measured by a network of virtual altimetry stations. Communications Earth & Environment, 3 (1). https://doi.org/10.1038/s43247-022-00448-z\r\n\r\n- Benveniste Jérôme, Birol Florence, Calafat Francisco, Cazenave Anny, Dieng Habib, Gouzenes Yvan, Legeais Jean François, Léger Fabien, Niño Fernando, Passaro Marcello, Schwatke Christian, Shaw Andrew (2020). Coastal sea level anomalies and associated trends from Jason satellite altimetry over 2002–2018. Scientific Data, 7 (1). https://doi.org/10.1038/s41597-020-00694-w" }, { "ob_id": 20339, "uuid": "2785ee1ec6274be39d11e7e7ce51b381", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): Fundamental Climate Data Records of sea level anomalies and altimeter standards, Version 2.0", "abstract": "As part of the European Space Agency's (ESA) Sea Level Climate Change Initiative (CCI) Project, Fundamental Climate Data Records (FCDRs) have been computed for all the altimeter missions used within the project. These FCDR's consist of along track values of sea level anomalies and altimeter standards for the period between 1993 and 2015. This version of the product is v2.0.\r\n\r\nThe FCDR's are mono-mission products, derived from the respective altimeter level-2 products. They have been produced along the tracks of the different altimeters, with a resolution of 1Hz, corresponding to a ground distance close to 6km. The dataset is separated by altimeter mission, and divided into files by altimetric cycle corresponding to the repetivity of the mission. \r\n\r\nWhen using or referring to the Sea Level cci products, please mention the associated DOIs and also use the following citation where a detailed description of the Sea Level_cci project and products can be found:\r\n\r\nAblain, M., Cazenave, A., Larnicol, G., Balmaseda, M., Cipollini, P., Faugère, Y., Fernandes, M. J., Henry, O., Johannessen, J. A., Knudsen, P., Andersen, O., Legeais, J., Meyssignac, B., Picot, N., Roca, M., Rudenko, S., Scharffenberg, M. G., Stammer, D., Timms, G., and Benveniste, J.: Improved sea level record over the satellite altimetry era (1993–2010) from the Climate Change Initiative project, Ocean Sci., 11, 67-82, doi:10.5194/os-11-67-2015, 2015.\r\n\r\nFor further information on the Sea Level CCI products, and to register for these projects please email: info-sealevel@esa-sealevel-cci.org\r\n" }, { "ob_id": 33045, "uuid": "2e3a3408af2f4e918458c09d4e5f7460", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): Altimeter along-track high resolution sea level anomalies in some coastal regions from ENVISAT (2002-2010) and SARAL (2013-2016) satellite altimetry, v1.1", "abstract": "This dataset contains along-track sea level anomalies derived from satellite altimetry. Altimeter along-track sea level measurements from the RA2 instrument on ENVISAT and the Altika instrument on SARAL satellite missions have been processed to produce high resolution (20 Hz, corresponding to an along-track distance of ~300m) sea level anomalies, in order to provide long-term homogeneous sea level time series as close to the coast as possible in six different coastal regions (North-East Atlantic, Mediterranean Sea, Western Africa, North Indian Ocean, South-East Asia and Australia). \r\n\r\nThe product benefits from the spatial resolution provided by high-rate data, the Adaptive Leading Edge Subwaveform Retracker (ALES) and the post-processing strategy of the along-track (X-TRACK) algorithm, both developed for the processing of coastal altimetry data, as well as the best possible set of geophysical corrections. \r\n\r\nThe main objective of this product is to provide accurate altimeter Sea Level Anomalies (SLA) time series as close to the coast as possible in order to assess whether the coastal sea level trends experienced at the coast are similar to the observed sea level trends in the open ocean and to determine the causes of the potential discrepancies.\r\n\r\nThe Envisat and SARAL/AltiKa missions have the same ground track but the temporal gap between both missions prevents from computing reliable trends during the total period between both missions.\r\n\r\nThis dataset has been produced by the Climate Change Initiative Coastal Sea Level team, within the extension phase of the European Sapce Agency (ESA) Climate Change Initiative." }, { "ob_id": 32847, "uuid": "b98db73607354c7b8ba9bc9347ceb9ed", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_level_cci): Arctic Sea Level Anomalies from ENVISAT and SARAL/Altika satellite altimetry missions (by CLS/PML)", "abstract": "This dataset contains estimations of Arctic sea level anomalies produced by the ESA Sea Level Climate Change Initiative project (Sea_level_cci), based on satellite altimetry from the ENVISAT and SARAL/Altika satellites. It has been produced by Collecte Localisation Satellites (CLS) and the Plymouth Marine Laboratory (PML).\r\n\r\nThe retrieval of sea level in the Arctic sea ice covered region requires specific processing steps of the satellite altimetry measurements. For this dataset, a specific radar waveform classification method has been applied based on a neural network approach, and the waveform retracking is based on a new adaptive retracking that is able to process both open ocean and peaky echoes measured in leads without introducing any bias between the two types of surfaces. Editing and mapping processing steps have been optimized for this dataset" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 50955, 48684, 48682, 48683, 105389, 105416, 105440, 55942, 48461 ], "onlineresource_set": [ 6120, 6122, 6118, 6119 ], "project_set": [ 13331 ] }, { "ob_id": 12808, "uuid": "0508f3dd991144aa80346007a415fb07", "short_code": "coll", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci) dataset collection", "abstract": "The Greenhouse Gases Climate Change Initiative (GHG_cci) data products are near-surface-sensitive dry-air column-averaged mole fractions (mixing ratios) of methane (CH4) and carbon dioxide (CO2), created as part of the European Space Agency's (ESA) Greenhouses Gases Essential Climate Variable (ECV) CCI project. Denoted XCO2 (in ppmv) and XCH4 (in ppbv), the products have been retrieved from the SCIAMACHY instrument on ENVISAT and TANSO-FTS onboard GOSAT, using ECV Core Algorithms (ECAs). Other satellite instruments such as IASI, MIPAS and ACE-FTS have also been used to provide constraints for upper layers, with their corresponding retrieval algorithms referred to as Additional Constraints Algorithms (ACAs). The GHG data products are typically updated annually, the corresponding datasets being called Climate Research Data Packages (CRDP). \r\n\r\nThe products have each been generated from individual sensors, a single merged product not having yet been created \"combining\" the products from different sensors to cover the entire available satellite time series. One merged product has however been generated using the EMMA algorithm, covering a limited time period. This EMMA product is mainly used as a comparison tool for products generated using individual algorithms, making up the collection of products used by EMMA. \r\n\r\nTypically the same product (e.g. XCO2 from GOSAT) has been generated using different retrieval algorithms. A baseline algorithm has been used to generate one recommended baseline product, for users unsure which product to choose. Other products are called alternative products. However an alternative product's quality may equal that of the corresponding baseline product. It typically depends upon the application for which a product is required, which product is best to use as methods involved in producing them typically have varying strength and weaknesses. \r\n\r\nFor further information on the products, such as details on the SCIAMACHY and TANSO instruments, the algorithms used to generate the data and the data's format, please see the Product Specification Document (PSD) in the documentation section.", "keywords": "ESA, GHG, Greenhouse Gases, CCI, ECV, Methane, Carbon Dioxide, ECA, ACA", "publicationState": "published", "dataPublishedTime": "2016-04-11T13:26:00", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 12811, "uuid": "2630314f738644c9b2a6bc3194d615b7", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): GOSAT CH4 Full Physics Level 2 Data Product (CH4_GOS_SRFP), version 2.3.6, generated with the SRFP (RemoTeC) algorithm", "abstract": "Created as part of The European Space Agency's (ESA) GHG CCI project, the XCH4 GOS Full Physics (FP) data product is a level 2, column-averaged mole fraction (mixing ratio) of methane (CH4). The product is part of Climate Research Data Package Number 2 (CRDP#2) and is based upon data generated for the years 2009-2013. It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). By contrast to the Proxy (PR) versions of the product generated with proxy algorithms, the record pages for which are provided in linked documentation, the FP products have been produced using full physics algorithms, in this case the RemoTeC SRFP baseline algorithm.\r\n\r\nThe data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. The product file contains the key products with and without bias correction. Information relevant for the use of the data is also included in the data file, such as the vertical layering and averaging kernels. Additionally, the parameters retrieved simultaneously with XCH4 are included (e.g. surface albedo), as well as retrieval diagnostics like retrieval errors and the quality of the fit. \r\n\r\nFor further information on the product, including the RemoTeC Full Physics algorithm and the TANSO-FTS instrument please see the Product User Guide (PUG) or the Algorithm Theoretical Basis Document in the documentation section. \r\n\r\nThe GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases.\r\nTo register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/" }, { "ob_id": 38313, "uuid": "6ecb706ac16c4e05aab75ed2cc3ec119", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from GOSAT-2, generated with the SRPR (RemoTeC) proxy retrieval algorithm (CH4_GO2_SRPR), version 2.0.0", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the Remote Sensing of Greenhouse Gases for Carbon Cycle Modeling (RemoTeC) SRON Proxy (SRPR) retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." }, { "ob_id": 25930, "uuid": "56f81895cb094bd8a1638aa12d6c7499", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged CH4 from GOSAT generated with the OCFP (UoL-FP) algorithm (CH4_GOS_OCFP), version 2.1", "abstract": "The CH4_GOS_OCFP dataset is comprised of level 2, column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT), using the University of Leicester Full-Physics Retrieval Algorithm. It has been generated as part of the European Space Agency (ESA) Greenhouse Gases Climate Change Initiative (GHG_cci) project. This version is version 2.1 and forms part of the Climate Research Data Package 4.\r\n\r\nThe University of Leicester Full-Physics Retrieval Algorithm is based on the original Orbiting Carbon Observatory (OCO) Full Physics Retrieval Algorithm and has been modified for use on GOSAT spectra. A second GOSAT CH4 product, generated using the SRFP algorithm, is also available.\r\n\r\nThe XCH4 product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further information, including details of the OCFP algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG)." }, { "ob_id": 14572, "uuid": "89a49c8e8dbb4a1bb8799589ffd39dc7", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG CCI): SCIAMACHY CH4 Level 2 Data Product (CH4_SCI_WFMD), version 3.9, generated with the WFMD algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 3 (CRDP#3), the XCH4 SCI product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. \r\n\r\nThis product has been derived by applying the Weighting Function Modified DOAS (WFMD) algorithm to the SCIAMACHY data, a least-squares method based on scaling pre-selected atmospheric vertical profiles. A second product is also available, which has been generated from the SCIAMACHY data using the IMAP algorithm. \r\n\r\nThe data product is stored per day in separate NetCDF-files (NetCDF-4 classic model). The product files contain the key products and other information relevant for the use of the data e.g. the averaging kernels. Note that the results since November 2005 are considered to be of reduced quality in comparison to the earlier results because the extended-wavelength part (1590-1770 nm) of SCIAMACHY's channel 6, covering the methane 2v3 absorption band used for the methane retrieval, is subject to irreversible displacement damage induced by high energy solar protons, which occurs from time to time at individual detector pixels. Therefore several affected detector pixels had to be excluded for the time period since November 2005. \r\n\r\nFor further information on the product, including details of the WFMD algorithm and the SCIAMACHY instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section\r\n\r\nThe GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/" }, { "ob_id": 32750, "uuid": "722fe4748da2487ead0a755f6d09e6ab", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from GOSAT-2, generated with the SRPR (RemoTeC) proxy retrieval algorithm, version 1.0.0", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2(TANSO-FTS-2) Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the RemoTeC SRPR Proxy Retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." }, { "ob_id": 32607, "uuid": "9252ff9ddeb249a2bd8433e9ae9dfe13", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged carbon dioxide from TANSAT, generated with the OCFP algorithm, for global land areas, version 1.0", "abstract": "This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (CO2), derived from the TANSAT satellite, using the University of Leicester Full-Physics Retrieval Algorithm (UoL-FP, also known as OCFP). This dataset is also referred to as CO2_TAN_OCFP. This version of the dataset provides data globally over land. For further information on the dataset, please see the linked documentation.\r\n\r\nInitially this dataset contains two months of data (June and August 2017), delivered as part of the GHG_cci Climate Research Data Package 6. Additional time periods will be added in the future.\r\n\r\n\r\nThis data has been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme, with support from the UK's National Centre for Earth Observation (NCEO)." }, { "ob_id": 12862, "uuid": "130450cdf1034235aa2a5107dc513d81", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): GOSAT CO2 Level 2 Data Product (CO2_GOS_OCFP) version 5.2, generated with the OCFP (UoL-FP) algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project, the XCO2 GOSAT product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). The University of Leicester Full-Physics Retrieval Algorithm has been applied to the TANSO-FTS data, based on the original Orbiting Carbon Observatory (OCO) Full Physics Retrieval Algorithm and modified for use on GOSAT spectra. A second product has also been generated from the data using the SRFP algorithm, and the link to this product's record page is provided in the documentation section. \r\n\r\nThe XCO2 product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further information, including details of the OCFP algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) in the documentation section or the Algorithm Theoretical Basis Document for version 5.1 of the product (no ATBD is yet available for version 5.2)." }, { "ob_id": 14585, "uuid": "f94a00d0282d4bd1b3a7dd07777c874d", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG CCI): GOSAT CH4 Full Physics Level 2 Data Product, version 1.0 (CH4_GOS_OCFP) generated with the OCFP (UoL-FP) algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 3 (CRDP#3), the XCH4 GOS Full Physics product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). \r\n\r\nThis version of the full physics product (version 1.0) has been generated using the OCFP University of Leicester Full-Physics Methane Retrieval Algorithm, based on the original Orbiting Carbon Observatory (OCO) Full Physics Retrieval Algorithm and modified for use on GOSAT spectra baseline algorithm. This algorithm has been designated as an 'alternative' algorithm for the GHG CCI full physics methane retrievals. A second product has also been generated from the TANSO-FTS data by applying the baseline GHG CCI full physics algorithm, the RemoTeC SRFP algorithm. It is advised that users who aren't sure whether to use the baseline or alternative product use the baseline product generated with the SRFP baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage.\r\n\r\nThe product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further details on the product, including the UoL-FP algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section.\r\n\r\nThe GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/" }, { "ob_id": 14563, "uuid": "3c098ba124a347678a00b0102bab9f0a", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG CCI): GOSAT CO2 Level 2 Data Product (CO2_GOS_OCFP) version 6.0, generated with the OCFP (UoL-FP) algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project, the XCO2 GOSAT product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). The University of Leicester Full-Physics Retrieval Algorithm has been applied to the TANSO-FTS data, based on the original Orbiting Carbon Observatory (OCO) Full Physics Retrieval Algorithm and modified for use on GOSAT spectra. A second product, generated using the SRFP algorithm, is also available.\r\n\r\nThe XCO2 product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further information, including details of the OCFP algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) in the documentation section.\r\n\r\nThe GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/" }, { "ob_id": 25916, "uuid": "e493802d83c846c8b76f817866fb74cc", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged CO2 from SCIAMACHY generated with the WFMD algorithm (CO2_SCI_WFMD), v4.0", "abstract": "The CO2_SCI_WFMD dataset comprises level 2, column-averaged dry-air mole fractions (mixing ratios) of carbon dioxide (XCO2) from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. It has been produced using the Weighting Function Modified DOAS (WFM-DOAS) algorithm, by the ESA Greenhouse Gases Climate Change Initiative (GHG_cci) project.\r\n\r\nThe WFM-DOAS algorithm is a least-squares method based on scaling pre-selected atmospheric vertical profiles. Note that this has been designated as an 'alternative' algorithm for the GHG_cci and another XCO2 product has also been generated from the SCIAMACHY data using the baseline algorithm (the Bremen Optimal Estimation DOAS (BESD) algorithm). It is advised that users who aren't sure whether to use the baseline or alternative product use the product generated with the BESD baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage. \r\n\r\nThe data product is stored per day in seperate NetCDF-files (NetCDF-4 classic model). The product files contain the key products, i.e. the retrieved column-averaged dry air mole fractions for XCO2, several other useful parameters and additional information relevant to using the data e.g. the averaging kernels. For further information on the product, including details of the WFMD algorithm, the SCIAMACHY instrument and issues associated with the data please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section." }, { "ob_id": 14552, "uuid": "0fb6a635c881494ea1a22fce7718d2b2", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG CCI): GOSAT CH4 Full Physics Level 2 Data Product (CH4_GOS_SRFP), version 2.3.7, generated with the SRFP (RemoTeC) algorithm", "abstract": "Created as part of The European Space Agency's (ESA) GHG CCI project, the XCH4 GOS Full Physics (FP) data product is a level 2, column-averaged mole fraction (mixing ratio) of methane (CH4). The product is part of Climate Research Data Package Number 3 (CRDP#3) and is based upon data generated for the years 2009-2013. It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). By contrast to the Proxy (PR) versions of the product generated with proxy algorithms, the FP products have been produced using full physics algorithms, in this case the RemoTeC SRFP baseline algorithm.\r\n\r\nThe data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. The product file contains the key products with and without bias correction. Information relevant for the use of the data is also included in the data file, such as the vertical layering and averaging kernels. Additionally, the parameters retrieved simultaneously with XCH4 are included (e.g. surface albedo), as well as retrieval diagnostics like retrieval errors and the quality of the fit. \r\n\r\nFor further information on the product, including the RemoTeC Full Physics algorithm and the TANSO-FTS instrument please see the Product User Guide (PUG) or the Algorithm Theoretical Basis Document in the documentation section. \r\n\r\nThe GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases.\r\nTo register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/" }, { "ob_id": 41425, "uuid": "c14874e943cc453a8e63ce5841ecc9b0", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from GOSAT-2, generated with the SRFP (RemoTeC) full physics retrieval algorithm (CH4_GO2_SRFP), version 2.0.2", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the Remote Sensing of Greenhouse Gases for Carbon Cycle Modeling (RemoTeC) SRON Full Physics (SRFP) retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." }, { "ob_id": 12968, "uuid": "b3ae3b0d11c9481bab3c9c914a6c80aa", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): SCIAMACHY CO2 Level 2 Data Product (CO2_SCI_BESD), version 02.00.08, generated with the BESD algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 2 (CRDP#2), the BESD XCO2 SCIAMACHY product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced using data acquired from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. \r\n\r\nThis product has been produced with the Bremen Optimal Estimation DOAS (BESD) algorithm, a full physics algorithm which uses measurements in the O2-A absorption band to retrieve scattering information of clouds and aerosols. This is the GHG CCI baseline algorithm for deriving SCIAMACHY XCO2 data: A product has also been generated from the SCIAMACHY data using an alternative algorithm: the WFMD algorithm, the link to this product's record page being provided in the documentation section. It is advised that users who aren't sure whether to use the baseline or alternative product use this product generated with the BESD baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage in the documentation section. \r\n\r\nFor further information on the product, including details of the BESD algorithm and the SCIAMACHY instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section." }, { "ob_id": 19813, "uuid": "586ae7b2386741babc69c03a244264fd", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Merged SCIAMACHY and GOSAT Level 3 gridded atmospheric column-average methane (XCH4) product in Obs4MIPs format", "abstract": "This dataset contains satellite-derived atmospheric column-average dry-air mole fractions of methane (XCH4), and is a Level 3 gridded product in Obs4MIPs format. It has been derived by the Greenhouse Gases CCI (GHG_cci) project as part of the European Space Agency's (ESA's) Climate Change Initiative (CCI) programme, and was obtained from an ensemble of individual Level 2 (i.e. swath) XCH4 products, retrieved from the satellite sensors SCIAMACHY / ENVISAT and TANSO-FTS / GOSAT. The versions of the Level 2 GHG-CCI data products used as input for this product are those of the GHG_cci \"Climate Research Data Package No. 3\" (CRDP#3).\r\n\r\nThis Level 3 Obs4MIPs XCH4 product has been specifically generated for comparisons with climate model output in the context of the CMIP5/CMIP6/IPCC experiments." }, { "ob_id": 25926, "uuid": "8f5623a85d2e4b9b8ab5313f65a7c994", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged CH4 from SCIAMACHY generated with the IMAP-DOAS algorithm (CH4_SCI_IMAP), v7.2", "abstract": "The CH4_SCI_IMAP dataset is comprised of level 2, column-averaged dry-air mole fractions (mixing ratios) of methane (CH4). It has been produced using data acquired from the SWIR spectra (channel 6) of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's (ESA's) environmental research satellite ENVISAT using the IMAP-DOAS algorithm. It has been generated as part of ESA Greenhouse Gases Climate Change Initiative (GHG_cci) project. This version of the dataset is v7.2 and forms part of the Climate Research Data Package 4.\r\n\r\nThe IMAP-DOAS algorithm has been developed at the University of Heidelberg and SRON, and has been applied here to the SCIAMACHY data. This procedure and the algorithms validity are thoroughly described in Frankenberg et al (2011). A second product is also available which has been generated using the Weighting Function Modified DOAS (WFM-DOAS) algorithm. \r\n\r\nThe data product is stored per orbit in a single NetCDF4 file. Retrieval results are provided for the individual SCIAMACHY spatial footprints, no averaging having been applied. The product file contains the key products and information relevant to using the data, such as the vertical layering and averaging kernels. For further details on the product, including the IMAP algorithm and the SCIAMACHY instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Document." }, { "ob_id": 14575, "uuid": "0ecfa9cc4f81459bba840aead5eda6cd", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG CCI): SCIAMACHY CO2 Level 2 Data Product (CO2_SCI_BESD), version 02.01.01, generated with the BESD algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 3 (CRDP#3), the BESD XCO2 SCIAMACHY product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced using data acquired from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. \r\n\r\nThis product has been produced with the Bremen Optimal Estimation DOAS (BESD) algorithm, a full physics algorithm which uses measurements in the O2-A absorption band to retrieve scattering information of clouds and aerosols. This is the GHG CCI baseline algorithm for deriving SCIAMACHY XCO2 data: A product has also been generated from the SCIAMACHY data using an alternative algorithm: the WFMD algorithm. It is advised that users who aren't sure whether to use the baseline or alternative product use this product generated with the BESD baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage in the documentation section. \r\n\r\nFor further information on the product, including details of the BESD algorithm and the SCIAMACHY instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section.\r\n\r\nThe GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/" }, { "ob_id": 12855, "uuid": "91a09803bd5a42aeb5d3fd530409b15e", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): SCIAMACHY CH4 Level 2 Data Product (CH4_SCI_IMAP), version 7.0, generated with the IMAP-DOAS algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 2 (CRDP#2), the XCH4 SCI product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the SWIR spectra (channel 6) of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. \r\n\r\nThis product has been derived by applying the IMAP-DOAS algorithm developed at the University of Heidelberg and SRON to the SCIAMACHY data. This procedure and the algorithms validity are thoroughly described in Frankenberg et al (2011), a link to which is provided in linked documentation. A second product has also been generated from the SCIAMACHY data using the Weighting Function Modified DOAS (WFM-DOAS) algorithm, and the link to this product's record page is provided in the documentation section. \r\n\r\nThe data product is stored per orbit in a single NetCDF4 file. Retrieval results are provided for the individual SCIAMACHY spatial footprints, no averaging having been applied. The product file contains the key products and information relevant to using the data, such as the vertical layering and averaging kernels. For further details on the product, including the IMAP algorithm and the SCIAMACHY instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Document in the documentation section." }, { "ob_id": 25920, "uuid": "e61704b00267405082fbd41bb710dd74", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged CO2 from GOSAT generated with the SRFP (RemoTeC) algorithm (CO2_GOS_SRFP), v2.3.8", "abstract": "The CO2_GOS_SRFP dataset comprises level 2, column-averaged dry-air mole fractions (mixing ratios) for carbon dioxide (XCO2), from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). It has been produced using the RemoTeC Full Physics (SRFP) algorithm, v2.3.8, by the Greenhouse Gases Climate Change Initiative (GHG_cci) project. This forms part of the GHG_cci Climate Research Data Package Number 4 (CRDP#4).\r\n\r\nThe RemoTeC Full Physics (SRFP) algorithm has been jointly developed at SRON and KIT. A second product, generated using the OCFP (University of Leicester Full Physics) algorithm, is also available, and is considered the GHG_cci baseline product, whilst the SRFP product forms an 'alternative' product. It is advised that users who aren't sure whether to use the baseline or alternative product use the OCFP product. For more information on the differences between baseline and alternative algorithms please see the Greenhouse Gases CCI data products webpage. \r\n\r\nThe data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. The product file contains the key standard products, i.e. the retrieved column averaged dry air mixing ratio XCO2 with bias correction, averaging kernels and quality flags, as well as secondary products specific for the RemoTeC algorithm. For further information, including details of the SRFP algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Document." }, { "ob_id": 32748, "uuid": "fdd90615b0df45489d9ca47708d98325", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from GOSAT-2, generated with the SRFP (RemoTeC) full physics retrieval algorithm, version 1.0.0", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the RemoTeC SRFP Full Physics Retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." }, { "ob_id": 41358, "uuid": "8175ede3a1d642deba8f4cce49d7bda8", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from Sentinel-5P, generated with the WFM-DOAS algorithm, version 1.8, November 2017 - October 2023", "abstract": "This product is the column-average dry-air mole fraction of atmospheric methane, denoted XCH4. It has been retrieved from radiance measurements from the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite in the 2.3 µm spectral range of the solar spectral range, using the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS or WFMD) retrieval algorithm. This dataset is also referred to as CH4_S5P_WFMD. This version of the product is version 1.8, and covers the period from November 2017 - October 2023. \r\n\r\nThe WFMD algorithm is based on iteratively fitting a simulated radiance spectrum to the measured spectrum using a least-squares method. The algorithm is very fast as it is based on a radiative transfer model based look-up table scheme. The product is limited to cloud-free scenes on the Earth's day side.\r\n\r\nThese data were produced as part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project.\r\n\r\nWhen citing this dataset, please also cite the following peer-reviewed publication: \r\nSchneising, O., Buchwitz, M., Hachmeister, J., Vanselow, S., Reuter, M., Buschmann, M., Bovensmann, H., and Burrows, J. P.: Advances in retrieving XCH4 and XCO from Sentinel-5 Precursor: improvements in the scientific TROPOMI/WFMD algorithm, Atmos. Meas. Tech., 16, 669–694, https://doi.org/10.5194/amt-16-669-2023, 2023." }, { "ob_id": 25924, "uuid": "aa09603e91b44f3cb1573c9dd415e8a8", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged CH4 from SCIAMACHY generated with the WFMD algorithm (CH4_SCI_WFMD), version 4.0", "abstract": "The CH4_SCI_WFMD dataset comprises level 2, column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using data acquired from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's (ESA's) environmental research satellite ENVISAT, as part of the ESA's Greenhouse Gases Climate Change Initiative (GHG_cci) project. This version of the data is version 4.0, and forms part of the Climate Research Data Package 4.\r\n\r\nThe Weighting Function Modified DOAS (WFMD) algorithm is a least-squares method based on scaling pre-selected atmospheric vertical profiles. A second product is also available, which has been generated from the SCIAMACHY data using the IMAP algorithm. \r\n\r\nThe data product is stored per day in separate NetCDF-files (NetCDF-4 classic model). The product files contain the key products and other information relevant for the use of the data e.g. the averaging kernels. Note that the results since November 2005 are considered to be of reduced quality in comparison to the earlier results because the extended-wavelength part (1590-1770 nm) of SCIAMACHY's channel 6, covering the methane 2v3 absorption band used for the methane retrieval, is subject to irreversible displacement damage induced by high energy solar protons, which occurs from time to time at individual detector pixels. Therefore several affected detector pixels had to be excluded for the time period since November 2005. \r\n\r\nFor further information on the product, including details of the WFMD algorithm and the SCIAMACHY instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents." }, { "ob_id": 14579, "uuid": "3e06538585d04d9e8c848215eedeb5a4", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG CCI): Merged CO2 Level 2 Data Product (CO2_EMMA), version 2.1, generated with the EMMA algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG), the XCO2 EMMA product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced by applying the ensemble median algorithm EMMA to level 2 data of 7 XCO2 retrievals from the Japanese Greenhouse gases Observing Satellite (GOSAT) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. This is therefore a merged SCIAMACHY and GOSAT XCO2 Level 2 product, primarily used as a comparison tool to assess the level of agreement / disagreement of the various input products (for model-independent global comparison, i.e. for comparisons not restricted to TCCON validation sites and independent of global model data). This version of the product covers 4 years. \r\n\r\nFor further information on the product and the EMMA algorithm please see the EMMA website, the GHG-CCI Data Products webpage or the Product Validation and Intercomparison Report (PVIR) in the documentation section.\r\n\r\nThe GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/" }, { "ob_id": 38315, "uuid": "169c76a05fa247eebc5ee53f239871a7", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged carbon dioxide from GOSAT-2, derived using the SRFP (RemoTeC) full physics algorithm (CO2_GO2_SRFP), version 2.0.0", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of carbon dioxide (XCO2). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the Remote Sensing of Greenhouse Gases for Carbon Cycle Modeling (RemoTeC) SRON Full Physics (SRFP) retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." }, { "ob_id": 19981, "uuid": "d864a8a9776f4b46af29a292fcf4556c", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Merged SCIAMACHY and GOSAT Level 3 gridded atmospheric column-average carbon dioxide (XCO2) product in Obs4MIPs format", "abstract": "This dataset contains satellite-derived atmospheric column-average dry-air mole fractions of carbon dioxide (XCO2), and is a Level 3 gridded product in Obs4MIPs format. It has been derived by the Greenhouse Gases CCI (GHG_cci) project as part of the European Space Agency's (ESA's) Climate Change Initiative (CCI) programme, and has been obtained from an ensemble of individual Level 2 (i.e. swath) XCO2 products, retrieved from the satellite sensors SCIAMACHY / ENVISAT and TANSO-FTS / GOSAT. The versions of the Level 2 GHG_cci data products used as input for this product are those of the GHG_cci \"Climate Research Data Package No. 3\" (CRDP#3).\r\n\r\nThis Level 3 Obs4MIPs XCO2 product has been specifically generated for comparisons with climate model output in the context of the CMIP5/CMIP6/IPCC experiments." }, { "ob_id": 41429, "uuid": "3fc7927499fa49e0b6ace6c807972259", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from GOSAT-2, generated with the SRPR (RemoTeC) proxy retrieval algorithm (CH4_GO2_SRPR), version 2.0.2", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the Remote Sensing of Greenhouse Gases for Carbon Cycle Modeling (RemoTeC) SRON Proxy (SRPR) retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." }, { "ob_id": 41427, "uuid": "875f25069b5d4bd9a7101ca1206ee4f0", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged carbon dioxide from GOSAT-2, derived using the SRFP (RemoTeC) full physics algorithm (CO2_GO2_SRFP), version 2.0.2", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of carbon dioxide (XCO2). It has been produced using Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the Remote Sensing of Greenhouse Gases for Carbon Cycle Modeling (RemoTeC) SRON Full Physics (SRFP) retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." }, { "ob_id": 14565, "uuid": "c00d02a4c7fa4fbea2d6d8ebbc3be5c0", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG CCI): GOSAT CO2 Level 2 Data Product (CO2_GOS_SRFP) version 2.3.7, generated with the SRFP (RemoTeC) algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and Climate Research Data Package Number 2 (CRDP#3), the XCO2 GOSAT product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). In this case, the RemoTeC Full Physics (SRFP) algorithm, jointly developed at SRON and KIT, has been applied to the TANSO-FTS data. A second product, generated using the OCFP (University of Leicester Full Physics) algorithm, is also available.\r\n\r\nThe data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. The product file contains the key standard products, i.e. the retrieved column averaged dry air mixing ratio XCO2 with bias correction, averaging kernels and quality flags, as well as secondary products specific for the RemoTeC algorithm. For further information, including details of the SRFP algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Document in the documentation section.\r\n\r\nThe GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/" }, { "ob_id": 30126, "uuid": "3534bbf43fa14e40bc61944eaf664511", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from Sentinel-5P, generated with the WFM-DOAS algorithm, version 1.2", "abstract": "This product is the column-average dry-air mole fraction of atmospheric methane, denoted XCH4. It has been retrieved from radiance measurements from the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite in the 2.3 µm spectral range of the solar spectral range, using the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS or WFMD) retrieval algorithm. This dataset is also referred to as CH4_S5P_WFMD.\r\n\r\nThe WFMD algorithm is based on iteratively fitting a simulated radiance spectrum to the measured spectrum using a least-squares method. The algorithm is very fast as it is based on a radiative transfer model based look-up table scheme. The product is limited to cloud-free scenes on the Earth's day side.\r\n\r\nThis data was produced as part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project." }, { "ob_id": 14568, "uuid": "33cd85fdc2454d2796c64c673b9427c9", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG CCI): SCIAMACHY CH4 Level 2 Data Product (CH4_SCI_IMAP), version 7.1, generated with the IMAP-DOAS algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 3 (CRDP#3), the XCH4 SCI product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the SWIR spectra (channel 6) of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. \r\n\r\nThis product has been derived by applying the IMAP-DOAS algorithm developed at the University of Heidelberg and SRON to the SCIAMACHY data. This procedure and the algorithms validity are thoroughly described in Frankenberg et al (2011). A second product is also available which has been generated using the Weighting Function Modified DOAS (WFM-DOAS) algorithm. \r\n\r\nThe data product is stored per orbit in a single NetCDF4 file. Retrieval results are provided for the individual SCIAMACHY spatial footprints, no averaging having been applied. The product file contains the key products and information relevant to using the data, such as the vertical layering and averaging kernels. For further details on the product, including the IMAP algorithm and the SCIAMACHY instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Document in the documentation section.\r\n\r\nThe GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/" }, { "ob_id": 12860, "uuid": "999f83c401fe4e47a0d3393b4c25c53f", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Merged CO2 Level 2 Data Product (CO2_EMMA), version 2.0, generated with the EMMA algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG), the XCO2 EMMA product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced by applying the ensemble median algorithm EMMA to level 2 data of 7 XCO2 retrievals from the Japanese Greenhouse gases Observing Satellite (GOSAT) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. This is therefore a merged SCIAMACHY and GOSAT XCO2 Level 2 product, primarily used as a comparison tool to assess the level of agreement / disagreement of the various input products (for model-independent global comparison, i.e. for comparisons not restricted to TCCON validation sites and independent of global model data). This version of the product covers 4 years. \r\n\r\nFor further information on the product and the EMMA algorithm please see the EMMA website, the GHG-CCI Data Products webpage or the Product Validation and Intercomparison Report (PVIR) in the documentation section." }, { "ob_id": 32751, "uuid": "f1b19872c12d477abfeb229f060a0969", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged carbon dioxide from GOSAT-2, derived using the SRFP (RemoTeC) full physics algorithm, version 1.0.0", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of carbon dioxide (XCO2). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) Near Infrared(NIR) and Shortwave Infrared (SWIR) spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the RemoTeC SRFP Full Physics Retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." }, { "ob_id": 25928, "uuid": "f9154243fd8744bdaf2a59c39033e659", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged CH4 from GOSAT generated with the OCPR (UoL-PR) Proxy algorithm (CH4_GOS_OCPR), v7.0", "abstract": "This CH4_GOS_OCPR dataset is comprised of level 2, column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4.) The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT), using the OCPR University of Leicester Proxy Retrieval Algorithm. It has been generated as part of the European Space Agency (ESA) Greenhouse Gases Climate Change Initiative (GHG_cci). This version of the data is v7.0 and forms part of the Climate Research Data Package 4.\r\n\r\nThis algorithm has been designated the baseline algorithm for the GHG CCI proxy methane retrievals. A second product has also been generated from the TANSO-FTS data using an alternative algorithm, the RemoTeC Proxy algorithm. It is advised that users who aren't sure whether to use the baseline or alternative product use this product generated with the OCPR baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage.\r\n\r\nThe product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further details on the product, including the UoL-PR algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents." }, { "ob_id": 12857, "uuid": "5518ef811d4c45da9474056986c78cfd", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): SCIAMACHY CH4 Level 2 Data Product (CH4_SCI_WFMD), version 3.7, generated with the WFMD algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 2 (CRDP#2), the XCH4 SCI product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. \r\n\r\nThis product has been derived by applying the Weighting Function Modified DOAS (WFMD) algorithm to the SCIAMACHY data, a least-squares method based on scaling pre-selected atmospheric vertical profiles. A second product has also been generated from the SCIAMACHY data using the IMAP algorithm, and the link to this product's record page is provided in the documentation section. \r\n\r\nThe data product is stored per day in separate NetCDF-files (NetCDF-4 classic model). The product files contain the key products and other information relevant for the use of the data e.g. the averaging kernels. Note that the results since November 2005 are considered to be of reduced quality in comparison to the earlier results because the extended-wavelength part (1590-1770 nm) of SCIAMACHY's channel 6, covering the methane 2v3 absorption band used for the methane retrieval, is subject to irreversible displacement damage induced by high energy solar protons, which occurs from time to time at individual detector pixels. Therefore several affected detector pixels had to be excluded for the time period since November 2005. \r\n\r\nFor further information on the product, including details of the WFMD algorithm and the SCIAMACHY instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section" }, { "ob_id": 14556, "uuid": "4774bc5719754c44add5c6f209fc25ae", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG CCI): GOSAT CH4 Proxy Level 2 Data Product, (CH4_GOS_OCPR), version 6.0, generated with the OCPR (UoL-PR) algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 3 (CRDP#3), the XCH4 GOS PR (Proxy) product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). \r\n\r\nThis version of the proxy product (version 6.0) has been generated using the OCPR University of Leicester Full-Physics Retrieval Algorithm, based on the original Orbiting Carbon Observatory (OCO) Full Physics Retrieval Algorithm and modified for use on GOSAT spectra baseline algorithm. This algorithm has been designated the baseline algorithm for the GHG CCI proxy methane retrievals. A second product has also been generated from the TANSO-FTS data using an alternative algorithm, the RemoTeC Proxy algorithm. It is advised that users who aren't sure whether to use the baseline or alternative product use this product generated with the OCPR baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage.\r\n\r\nThe product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further details on the product, including the UoL-PR algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section.\r\n\r\nThe GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/" }, { "ob_id": 25932, "uuid": "46d136149d0a4f1cb8de7efbe8abf4b2", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged CH4 from GOSAT generated with the SRFP (RemoTeC) Full Physics algorithm (CH4_GOS_SRFP), version 2.3.8", "abstract": "The CH4_GOS_SRFP dataset is comprised of level 2, column-averaged mole fractiona (mixing ratioa) of methane (XCH4). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra onboard the Japanese Greenhouse gases Observing Satellite (GOSAT) using the SRFP (RemoTec) algorithm. It has been generated as part of the European Space Agency (ESA) Greenhouse Gases Climate Change Initiative (GHG_cci). This version of the dataset is v2.3.8 and forms part of the Climate Research Data Package 4.\r\n\r\nThe RemoTeC SRFP baseline algorithm is a Full Physics algorithm. The data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. The product file contains the key products with and without bias correction. Information relevant for the use of the data is also included in the data file, such as the vertical layering and averaging kernels. Additionally, the parameters retrieved simultaneously with XCH4 are included (e.g. surface albedo), as well as retrieval diagnostics like retrieval errors and the quality of the fit. \r\n\r\nFor further information on the product, including the RemoTeC Full Physics algorithm and the TANSO-FTS instrument please see the Product User Guide (PUG) or the Algorithm Theoretical Basis Document." }, { "ob_id": 25918, "uuid": "9255faeb392f41debf5402caa40dada8", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG CCI): Column-averaged CO2 from GOSAT generated with the OCFP (UoL-FP) algorithm (CO2_GOS_OCFP), v7.0", "abstract": "The CO2_GOS_OCFP dataset comprises level 2, column-averaged dry-air mole fractions (mixing ratios) of carbon dioxide (XCO2) from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). It has been produced using the University of Leicester Full-Physics Retrieval Algorithm, which is based on the original Orbiting Carbon Observatory (OCO) Full Physics Retrieval Algorithm and modified for use on GOSAT spectra. A second product, generated using the alternative SRFP algorithm, is also available. The OCFP product is considered the GHG_cci baseline product and it is advised that users who aren't sure which of the two products to use, use this product. For more information regarding the differences between baseline and alternative algorithms please see the Greenhouse Gases CCI data products webpage.\r\n\r\nThe XCO2 product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further information, including details of the OCFP algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG)." }, { "ob_id": 24693, "uuid": "294b4075ddbc4464bb06742816813bdc", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged CO2 from SCIAMACHY generated with the BESD algorithm (CO2_SCI_BESD), v02.01.02", "abstract": "The CO2_SCI_BESD dataset comprises level 2, column-averaged dry-air mole fractions (mixing ratios) of carbon dioxide (CO2) from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument on board the European Space Agency's (ESA's) environmental research satellite ENVISAT. It has been produced using the Bremen Optimal Estimation DOAS (BESD) algorithm, by the ESA Greenhouse Gases Climate Change Initiative (GHG_cci) project.\r\n\r\nThe Bremen Optimal Estimation DOAS (BESD) algorithm is a full physics algorithm which uses measurements in the O2-A absorption band to retrieve scattering information about clouds and aerosols. This is the Greenhouse Gases CCI baseline algorithm for deriving SCIAMACHY XCO2 data. A product has also been generated from the SCIAMACHY data using an alternative algorithm: the WFMD algorithm. It is advised that users who aren't sure whether to use the baseline or alternative product use this BESD product. For more information regarding the differences between baseline and alternative algorithms please see the Greenhouse Gases CCI data products webpage.\r\n\r\nFor further information on the product, including details of the BESD algorithm and the SCIAMACHY instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents." }, { "ob_id": 43488, "uuid": "198d56f5fbbf4144b8fd4932328be462", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column averaged carbon dioxide from OCO-2 generated with the FOCAL algorithm, version 11.0", "abstract": "This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (XCO2) data, generated using the fast atmospheric trace gas retrieval for OCO2 (FOCAL-OCO2). The FOCAL-OCO2 algorithm has been setup to retrieve XCO2 by analysing hyper spectral solar backscattered radiance measurements from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite. FOCAL includes a radiative transfer model which has been developed to approximate light scattering effects by multiple scattering at an optically thin scattering layer. This reduces the computational costs by several orders of magnitude. FOCAL's radiative transfer model is utilised to simulate the radiance in all three OCO-2 spectral bands allowing the simultaneous retrieval of CO2, H2O, and solar induced chlorophyll fluorescence. The product is limited to cloud-free scenes on the Earth's day side. This dataset is also referred to as CO2_OC2_FOCA.\r\n\r\nThis version of the data (v11) was produced as part of the European Space Agency's (ESA) \r\nClimate Change Initiative (CCI) Greenhouse Gases (GHG) project (GHG-CCI+, http://cci.esa.int/ghg).\r\nThe FOCAL OCO-2 XCO2 retrieval development, data processing and analysis has received co-funding from ESA’s Climate Change Initiative (CCI+) via project GHG-CCI+ (contract 4000126450/19/I-NB, https://climate.esa.int/en/projects/ghgs) EUMETSAT via the FOCAL-CO2M study (contract EUM/CO/19/4600002372/RL), the European Union via the Horizon 2020 (H2020) projects VERIFY (Grant Agreement No. 776810, http://verify.lsce.ipsl.fr) and CHE (Grant Agreement No. 776186, https://www.che-project.eu) and by the State and the University of Bremen.\r\n\r\nWhen citing this data, please also cite the following peer-reviewed publications:\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, V.Rozanov, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 1: Radiative Transfer and a Potential OCO-2 XCO2 Retrieval Setup, Remote Sensing, 9(11), 1159; doi:10.3390/rs9111159, 2017\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 2: Application to XCO2 Retrievals from OCO-2, Remote Sensing, 9(11), 1102; doi:10.3390/rs9111102, 2017" }, { "ob_id": 12813, "uuid": "0b1f65b7aee1462eb01c7c2c416c3454", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): GOSAT CH4 Proxy Level 2 Data Product, version 5.2 (CH4_GOS_OCPR) generated with the OCPR (UoL-PR) algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 2 (CRDP#2), the XCH4 GOS PR (Proxy) product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). \r\n\r\nThis version of the proxy product has been generated using version 5.2 of the OCPR University of Leicester Full-Physics Retrieval Algorithm, based on the original Orbiting Carbon Observatory (OCO) Full Physics Retrieval Algorithm and modified for use on GOSAT spectra baseline algorithm. This algorithm has been designated the baseline algorithm for the GHG CCI proxy methane retrievals. A second product has also been generated from the TANSO-FTS data using an alternative algorithm, the RemoTeC Proxy algorithm, and the link to this product's record page is provided in the documentation section. It is advised that users who aren't sure whether to use the baseline or alternative product use this product generated with the OCPR baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage.\r\n\r\nThe product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further details on the product, including the UoL-PR algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section." }, { "ob_id": 38312, "uuid": "0f51318b226546c3a13e7d8a1451bbd3", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from Sentinel-5P, generated with the WFM-DOAS algorithm, version 1.5, November 2017 - December 2020", "abstract": "This product is the column-average dry-air mole fraction of atmospheric methane, denoted XCH4. It has been retrieved from radiance measurements from the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite in the 2.3 µm spectral range of the solar spectral range, using the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS or WFMD) retrieval algorithm. This dataset is also referred to as CH4_S5P_WFMD. This version of the product is version 1.5, and covers the period from November 2017 - December 2020. \r\n\r\nThe WFMD algorithm is based on iteratively fitting a simulated radiance spectrum to the measured spectrum using a least-squares method. The algorithm is very fast as it is based on a radiative transfer model based look-up table scheme. The product is limited to cloud-free scenes on the Earth's day side.\r\n\r\nThese data were produced as part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project.\r\n\r\nWhen citing this dataset, please also cite the following peer-reviewed publication: \r\nSchneising, O., Buchwitz, M., Reuter, M., Bovensmann, H., Burrows, J. P., Borsdorff, T., Deutscher, N. M., Feist, D. G., Griffith, D. W. T., Hase, F., Hermans, C., Iraci, L. T., Kivi, R., Landgraf, J., Morino, I., Notholt, J., Petri, C., Pollard, D. F., Roche, S., Shiomi, K., Strong, K., Sussmann, R., Velazco, V. A., Warneke, T., and Wunch, D.: A scientific algorithm to simultaneously retrieve carbon monoxide and methane from TROPOMI onboard Sentinel-5 Precursor, Atmos. Meas. Tech., 12, 6771–6802, https://doi.org/10.5194/amt-12-6771-2019, 2019." }, { "ob_id": 12864, "uuid": "61424ae2a8364db2bb9cb077d644872e", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): GOSAT CO2 Level 2 Data Product (CO2_GOS_SRFP) version 2.3.6, generated with the SRFP (RemoTeC) algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and Climate Research Data Package Number 2 (CRDP#2), the XCO2 GOSAT product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). In this case, the RemoTeC Full Physics (SRFP) algorithm, jointly developed at SRON and KIT, has been applied to the TANSO-FTS data. A second product has also been generated from the data using the OCFP (University of Leicester Full Physics) algorithm, and the link to this product's record page can be found in the documentation section. \r\n\r\nThe data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. The product file contains the key standard products, i.e. the retrieved column averaged dry air mixing ratio XCO2 with bias correction, averaging kernels and quality flags, as well as secondary products specific for the RemoTeC algorithm. For further information, including details of the SRFP algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Document in the documentation section." }, { "ob_id": 14577, "uuid": "95b804971495428285e136edaa6ac066", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG CCI): SCIAMACHY CO2 Level 2 Data Product (CO2_SCI_WFMD), version 3.9, generated with the WFMD algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 3 (CRDP#3), the WFMD XCO2 SCIAMACHY product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced using data acquired from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. \r\n\r\nThis product has been derived using the Weighting Function Modified DOAS (WFM-DOAS) algorithm, a least-squares method based on scaling pre-selected atmospheric vertical profiles. Note that this has been designated as an 'alternative' algorithm for the GHG CCI, and another XCO2 product has also been generated from the SCIAMACHY data using the baseline algorithm (the Bremen Optimal Estimation DOAS (BESD) algorithm). It is advised that users who aren't sure whether to use the baseline or alternative product use the product generated with the BESD baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage provided in the documentation section. \r\n\r\nThe data product is stored per day in seperate NetCDF-files (NetCDF-4 classic model). The product files contain the key products, i.e. the retrieved column-averaged dry air mole fractions for XCO2, several other useful parameters and additional information relevant to using the data e.g. the averaging kernels. For further information on the product, including details of the WFMD algorithm, the SCIAMACHY instrument and issues associated with the data please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section.\r\n\r\nThe GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/" }, { "ob_id": 32744, "uuid": "1c9c816d0b8a4fbf878e7e0bfef5d79f", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from Sentinel-5P, generated with the WFM-DOAS algorithm, version 1.2, November 2017 - July 2020", "abstract": "This product is the column-average dry-air mole fraction of atmospheric methane, denoted XCH4. It has been retrieved from radiance measurements from the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite in the 2.3 µm spectral range of the solar spectral range, using the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS or WFMD) retrieval algorithm. This dataset is also referred to as CH4_S5P_WFMD. This version of the product is version 1.2, and covers the period from November 2017 - July 2020. \r\n\r\nThe WFMD algorithm is based on iteratively fitting a simulated radiance spectrum to the measured spectrum using a least-squares method. The algorithm is very fast as it is based on a radiative transfer model based look-up table scheme. The product is limited to cloud-free scenes on the Earth's day side.\r\n\r\nThese data were produced as part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project.\r\n\r\nWhen citing this dataset, please also cite the following peer-reviewed publication: \r\nSchneising, O., Buchwitz, M., Reuter, M., Bovensmann, H., Burrows, J. P., Borsdorff, T., Deutscher, N. M., Feist, D. G., Griffith, D. W. T., Hase, F., Hermans, C., Iraci, L. T., Kivi, R., Landgraf, J., Morino, I., Notholt, J., Petri, C., Pollard, D. F., Roche, S., Shiomi, K., Strong, K., Sussmann, R., Velazco, V. A., Warneke, T., and Wunch, D.: A scientific algorithm to simultaneously retrieve carbon monoxide and methane from TROPOMI onboard Sentinel-5 Precursor, Atmos. Meas. Tech., 12, 6771–6802, https://doi.org/10.5194/amt-12-6771-2019, 2019." }, { "ob_id": 12837, "uuid": "623e56750f394a37aafafce42217e032", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): GOSAT CH4 Proxy Level 2 Data Product (CH4_GOS_SRPR), version 2.3.6, generated with the SRPR (RemoTeC) algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 2 (CRDP#2), the XCH4 GOS SRPR (Proxy) product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). \r\n\r\nThis proxy version of the product has been generated using the RemoTeC SRPR algorithm, which is being jointly developed at SRON and KIT. This has been designated as an 'alternative' GHG CCI algorithm, and a separate product has also been generated by applying the baseline GHG CCI proxy algorithm (the University of Leicester OCPR algorithm). The link to this product's record page is provided in the documentation section. However, it is advised that users who aren't sure whether to use the baseline or alternative product use the OCPR product generated with the baseline algorithm. For more information regarding the differences between the baseline and alternative algorithms please see the GHG-CCI data products webpage. \r\n\r\nThe data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. As well as containing the key product, the product file contains information relevant for the use of the data, such as the vertical layering and averaging kernels. The parameters which are retrieved simultaneously with XCH4 are also included (e.g. surface albedo), in addition to retrieval diagnostics like quality of the fit and retrieval errors. For further details on the product, including the RemoTeC algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section." }, { "ob_id": 24692, "uuid": "9ed2813d2eda4d958e92ab3ce1ab1fe6", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged CH4 Merged Product generated with the EMMA algorithm (CH4_EMMA), version 1.2", "abstract": "The CH4_EMMA dataset is comprised of level 2, column-averaged dry-air mole fractions (mixing ratios) for methane (XCH4). It has been produced using the ensemble median algorithm EMMA to several different versions of the Japanes Greenhouse gases Observing Satellite (GOSAT) XCH4 data, as part of the ESA Greenhouse Gases Climate Change Initiative (GHG_cci) project. This version of the product is v1.2, and forms part of the Climate Research Data Package 4.\r\n\r\nThe ensemble median algorithm EMMA has been applied to level 2 data of several different retrieval products from the Japanese Greenhouse gases Observing Satellite (GOSAT) This is therefore a merged GOSAT XCH4 Level 2 product, which is primarily used as a comparison tool to assess the level of agreement / disagreement of the various input products (for model-independent global comparison, i.e. for comparisons not restricted to TCCON validation sites and independent of global model data). \r\n\r\nFor further information on the product and the EMMA algorithm please see the EMMA website, the GHG-CCI Data Products webpage or the Product Validation and Intercomparison Report (PVIR)." }, { "ob_id": 25922, "uuid": "9f002827ba7d48f59019fcfd3577a57e", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column averaged CO2 Merged Product generated with the EMMA algorithm (CO2_EMMA), v2.2", "abstract": "The CO2_EMMA dataset comprises of level 2, column-averaged dry-air mole fractions (mixing ratios) of carbon dioxide (XCO2). It has been produced using the ensample median algorithm EMMA to produce a merged SCIAMACHY and GOSAT XCO2 Level 2 product, as part of the ESA Greenhouse Gases Climate Change Initiative (GHG_cci) project. This version of the product is v2.2, and forms part of the Climate Research Data Package 4.\r\n\r\nThe EMMA algorithm has been applied to level 2 data from multiple XCO2 retrievals from the Japanese Greenhouse gases Observing Satellite (GOSAT) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. This merged SCIAMACHY and GOSAT XCO2 Level 2 product is primarily used as a comparison tool to assess the level of agreement / disagreement of the various input products (for model-independent global comparison, i.e. for comparisons not restricted to TCCON validation sites and independent of global model data). \r\n\r\nFor further information on the product and the EMMA algorithm please see the EMMA website, the GHG-CCI Data Products webpage or the Product Validation and Intercomparison Report (PVIR)." }, { "ob_id": 25934, "uuid": "96d5b75ea29946c5aab8214ddbab252b", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged CH4 from GOSAT generated with the SRPR (RemoTeC) Proxy Retrieval algorithm (CH4_GOS_SRPR), version 2.3.8", "abstract": "The CH4_GOS_SRPR dataset is comprised of Level 2, column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT), using the RemoTeC SRPR Proxy Retrieval algorithm. It has been generated as part of the European Space Agency (ESA) Greenhouse Gases Climate Change Initiative (GHG_cci) project. This version of the data is version 2.3.8, and forms part of the Climate Research Data Package 4. \r\n\r\nThis Proxy Retrieval product has been generated using the RemoTeC SRPR algorithm, which is being jointly developed at SRON and KIT. This has been designated as an 'alternative' GHG CCI algorithm, and a separate product has also been generated by applying the baseline GHG CCI proxy algorithm (the University of Leicester OCPR algorithm). It is advised that users who aren't sure whether to use the baseline or alternative product use the OCPR product generated with the baseline algorithm. For more information regarding the differences between the baseline and alternative algorithms please see the GHG-CCI data products webpage. \r\n\r\nThe data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. As well as containing the key product, the product file contains information relevant for the use of the data, such as the vertical layering and averaging kernels. The parameters which are retrieved simultaneously with XCH4 are also included (e.g. surface albedo), in addition to retrieval diagnostics like quality of the fit and retrieval errors. For further details on the product, including the RemoTeC algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents." }, { "ob_id": 14554, "uuid": "cca6035bb0f240ffbb035e9355f09fe1", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG CCI): GOSAT CH4 Proxy Level 2 Data Product (CH4_GOS_SRPR), version 2.3.7, generated with the SRPR (RemoTeC) algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 3 (CRDP#3), the XCH4 GOS SRPR (Proxy) product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT). \r\n\r\nThis proxy version of the product has been generated using the RemoTeC SRPR algorithm, which is being jointly developed at SRON and KIT. This has been designated as an 'alternative' GHG CCI algorithm, and a separate product has also been generated by applying the baseline GHG CCI proxy algorithm (the University of Leicester OCPR algorithm). It is advised that users who aren't sure whether to use the baseline or alternative product use the OCPR product generated with the baseline algorithm. For more information regarding the differences between the baseline and alternative algorithms please see the GHG-CCI data products webpage. \r\n\r\nThe data product is stored per day in a single NetCDF file. Retrieval results are provided for the individual GOSAT spatial footprints, no averaging having been applied. As well as containing the key product, the product file contains information relevant for the use of the data, such as the vertical layering and averaging kernels. The parameters which are retrieved simultaneously with XCH4 are also included (e.g. surface albedo), in addition to retrieval diagnostics like quality of the fit and retrieval errors. For further details on the product, including the RemoTeC algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section.\r\n\r\nThe GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases.\r\nTo register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/" }, { "ob_id": 14581, "uuid": "ccd65d303e7241f6b969b19b4be6a925", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG CCI): Merged CH4 Level 2 Data Product (CH4_EMMA), version 1.0, generated with the EMMA algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG), the XCH4 EMMA product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for methane (CH4). The product has been produced by applying the ensemble median algorithm EMMA to level 2 data of several different retrieval products from the Japanese Greenhouse gases Observing Satellite (GOSAT) This is therefore a merged GOSAT XCH4 Level 2 product, primarily used as a comparison tool to assess the level of agreement / disagreement of the various input products (for model-independent global comparison, i.e. for comparisons not restricted to TCCON validation sites and independent of global model data). \r\n\r\nFor further information on the product and the EMMA algorithm please see the EMMA website, the GHG-CCI Data Products webpage or the Product Validation and Intercomparison Report (PVIR) in the documentation section.\r\n\r\nThe GHG-CCI team encourage all users of their products to register with them to receive information on any updates or issues regarding the data products and to receive notification of new product releases. To register, please use the following link: http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/CRDP_REG/" }, { "ob_id": 30178, "uuid": "b06213c3f3934a689f89ab22aa50e471", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column averaged carbon dioxide from OCO-2 generated with the FOCAL algorithm, version 08", "abstract": "This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (XCO2), using the fast atmospheric trace gas retrieval for OCO2 (FOCAL-OCO2). The FOCAL-OCO2 algorithm which has been setup to retrieve XCO2 by analysing hyper spectral solar backscattered radiance measurements from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite. FOCAL includes a radiative transfer model which has been developed to approximate light scattering effects by multiple scattering at an optically thin scattering layer. This reduces the computational costs by several orders of magnitude. FOCAL's radiative transfer model is utilised to simulate the radiance in all three OCO-2 spectral bands allowing the simultaneous retrieval of CO2, H2O, and solar induced chlorophyll fluorescence. The product is limited to cloud-free scenes on the Earth's day side. This dataset is also referred to as CO2_OC2_FOCA.\r\n\r\nThis version of the data was produced as part of the European Space Agency's (ESA) \r\nClimate Change Initiative (CCI) Greenhouse Gases (GHG) project (GHG-CCI+, http://cci.esa.int/ghg)\r\nand got co-funding from the Univ. Bremen and EU H2020 projects CHE (grant agreement no. 776186) and VERIFY (grant agreement no. 776810).\r\n\r\nWhen citing this dataset, please also cite the following peer-review publications:\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, V.Rozanov, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 1: Radiative Transfer and a Potential OCO-2 XCO2 Retrieval Setup, Remote Sensing, 9(11), 1159; doi:10.3390/rs9111159, 2017\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 2: Application to XCO2 Retrievals from OCO-2, Remote Sensing, 9(11), 1102; doi:10.3390/rs9111102, 2017" }, { "ob_id": 38314, "uuid": "c8037223dfff49db9fcdd8a9f6dd8d41", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from GOSAT-2, generated with the SRFP (RemoTeC) full physics retrieval algorithm (CH4_GO2_SRFP), version 2.0.0", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the Remote Sensing of Greenhouse Gases for Carbon Cycle Modeling (RemoTeC) SRON Full Physics (SRFP) retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." }, { "ob_id": 32609, "uuid": "b0de069568a141b0b074ca0f7cee004b", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column averaged carbon dioxide from OCO-2 generated with the FOCAL algorithm, version 09", "abstract": "This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (XCO2), using the fast atmospheric trace gas retrieval for OCO2 (FOCAL-OCO2). The FOCAL-OCO2 algorithm which has been setup to retrieve XCO2 by analysing hyper spectral solar backscattered radiance measurements from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite. FOCAL includes a radiative transfer model which has been developed to approximate light scattering effects by multiple scattering at an optically thin scattering layer. This reduces the computational costs by several orders of magnitude. FOCAL's radiative transfer model is utilised to simulate the radiance in all three OCO-2 spectral bands allowing the simultaneous retrieval of CO2, H2O, and solar induced chlorophyll fluorescence. The product is limited to cloud-free scenes on the Earth's day side. This dataset is also referred to as CO2_OC2_FOCA.\r\n\r\nThis version of the data (v09) was produced as part of the European Space Agency's (ESA) \r\nClimate Change Initiative (CCI) Greenhouse Gases (GHG) project (GHG-CCI+, http://cci.esa.int/ghg)\r\nand got co-funding from the Univ. Bremen and EU H2020 projects CHE (grant agreement no. 776186) and VERIFY (grant agreement no. 776810).\r\n\r\nWhen citing this data, please also cite the following peer-reviewed publications:\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, V.Rozanov, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 1: Radiative Transfer and a Potential OCO-2 XCO2 Retrieval Setup, Remote Sensing, 9(11), 1159; doi:10.3390/rs9111159, 2017\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 2: Application to XCO2 Retrievals from OCO-2, Remote Sensing, 9(11), 1102; doi:10.3390/rs9111102, 2017" }, { "ob_id": 12868, "uuid": "ce524139de81430e840d9a33daab3385", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): SCIAMACHY CO2 Level 2 Data Product (CO2_SCI_WFMD), version 3.8, generated with the WFMD algorithm", "abstract": "Part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project and the Climate Research Data Package Number 2 (CRDP#2), the WFMD XCO2 SCIAMACHY product comprises a level 2, column-averaged dry-air mole fraction (mixing ratio) for carbon dioxide (CO2). The product has been produced using data acquired from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) on board the European Space Agency's environmental research satellite ENVISAT. \r\n\r\nThis product has been derived using the Weighting Function Modified DOAS (WFM-DOAS) algorithm, a least-squares method based on scaling pre-selected atmospheric vertical profiles. Note that this has been designated as an 'alternative' algorithm for the GHG CCI, and another XCO2 product has also been generated from the SCIAMACHY data using the baseline algorithm (the Bremen Optimal Estimation DOAS (BESD) algorithm). The link to this product's record page is provided in the documentation section. It is advised that users who aren't sure whether to use the baseline or alternative product use the product generated with the BESD baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage provided in the documentation section. \r\n\r\nThe data product is stored per day in seperate NetCDF-files (NetCDF-4 classic model). The product files contain the key products, i.e. the retrieved column-averaged dry air mole fractions for XCO2, several other useful parameters and additional information relevant to using the data e.g. the averaging kernels. For further information on the product, including details of the WFMD algorithm, the SCIAMACHY instrument and issues associated with the data please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents in the documentation section." }, { "ob_id": 41262, "uuid": "2c1cb1d606c4421e9339a3028839a41f", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column averaged carbon dioxide from OCO-2 generated with the FOCAL algorithm, version 10.1", "abstract": "This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (XCO2), using the fast atmospheric trace gas retrieval for OCO2 (FOCAL-OCO2). The FOCAL-OCO2 algorithm which has been setup to retrieve XCO2 by analysing hyper spectral solar backscattered radiance measurements from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite. FOCAL includes a radiative transfer model which has been developed to approximate light scattering effects by multiple scattering at an optically thin scattering layer. This reduces the computational costs by several orders of magnitude. FOCAL's radiative transfer model is utilised to simulate the radiance in all three OCO-2 spectral bands allowing the simultaneous retrieval of CO2, H2O, and solar induced chlorophyll fluorescence. The product is limited to cloud-free scenes on the Earth's day side. This dataset is also referred to as CO2_OC2_FOCA.\r\n\r\nThis version of the data (v10.1) was produced as part of the European Space Agency's (ESA) \r\nClimate Change Initiative (CCI) Greenhouse Gases (GHG) project (GHG-CCI+, http://cci.esa.int/ghg)\r\nand got co-funding from the University of Bremen and EU H2020 projects CHE (grant agreement no. 776186) and VERIFY (grant agreement no. 776810).\r\n\r\nWhen citing this data, please also cite the following peer-reviewed publications:\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, V.Rozanov, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 1: Radiative Transfer and a Potential OCO-2 XCO2 Retrieval Setup, Remote Sensing, 9(11), 1159; doi:10.3390/rs9111159, 2017\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 2: Application to XCO2 Retrievals from OCO-2, Remote Sensing, 9(11), 1102; doi:10.3390/rs9111102, 2017" }, { "ob_id": 31872, "uuid": "2cc63301f1854239aa61c70e58c61207", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged carbon dioxide from TANSAT, generated with the OCFP algorithm, for selected validation sites, version 1.0", "abstract": "This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (CO2), derived from the TANSAT satellite, using the University of Leicester Full-Physics Retrieval Algorithm (UoL-FP, also known as OCFP). This dataset is also referred to as CO2_TAN_OCFP. The data covers the period from March 2017 to May 2018 and is provided for TCCON (Total Carbon Column Observing Network) validation sites only. A full global dataset is in production. For further information on the dataset, please see the linked documentation.\r\n\r\nThis data has been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme, with support from the UK's National Centre for Earth Observation (NCEO)." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 48948, 48947, 48946, 48945, 105391, 105418, 105442, 56689 ], "onlineresource_set": [ 6342, 6340, 6341, 6343 ], "project_set": [ 13295 ] }, { "ob_id": 12877, "uuid": "6e4abd45503d44f09c74ee3a0e8fefb7", "short_code": "coll", "title": "ESA Soil Moisture (SM) Climate Change Initiative (CCI) Dataset Collection", "abstract": "As part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project, three surface soil moisture datasets have been created. The 'Active' and 'Passive' products have been created by fusing scatterometer and radiometer soil moisture products respectively. In the case of the 'Active' product, these have been derived from AMI-WS and ASCAT instruments and for the 'Passive' product from the instruments SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, SMOS and SMAP (dependent on version). The 'Combined Product' is then a blended product based on the former two data sets. The Ancillary datasets involved in their production are also available. \r\n\r\nThe homogenized and merged products present a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The products are provided as global daily images, in NetCDF-4 classic file format, the Passive and Combined products covering the period (yyyy-mm-dd) 1978-11-01 to 2017-12-31 and the Active product covering 1991-08-05 to 2017-12-31 (dependent on version). The soil moisture data for the Passive and the Combined product are provided in volumetric units [m3 m-3], while the active soil moisture data are expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the datasets, please see the Algorithm Theoretical Baseline Document (ATBD) or the papers cited below. Other additional documentation and information documentation relating to the datasets can also be found on the CCI Soil Moisture project web site or in the Product Specification Document.\r\n\r\nThe data set should be cited using the complete references as follows:\r\nVersion 2.1 and v2.2\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321\r\n\r\nVersion 3.2 onwards:\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014", "keywords": "ESA, Soil Moisture, CCI", "publicationState": "old", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 14401, "uuid": "953545f5c4454952a26db065bbca004f", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Passive' Product, Version 02.2", "abstract": "The Soil Moisture CCI 'Passive' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing radiometer soil moisture products, merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. 'Active' and 'Combined' products have also been created, the 'Active' product being a fusion of AMI-WS and ASCAT derived scatterometer products and the 'Combined Product' being a blended product based on the former two data sets. \r\n\r\nThe v02.2 Passive product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2014-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version or the paper by Wagner 2012, both available in the documentation section. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321" }, { "ob_id": 12881, "uuid": "a1ff285fb94c4c359269b1a12df957ec", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Passive' Product, Version 02.1", "abstract": "The Soil Moisture CCI Passive dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer and radiometer soil moisture products, merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. 'Active' and 'Combined' products have also been created, the 'Active' product being a fusion of AMI-WS and ASCAT derived scatterometer and radiometer soil moisture products and the 'Combined Product' being a blended product based on the former two data sets. \r\n\r\nThe v02.1 Passive product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2013-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version or the paper by Wagner 2012, both available in the documentation section. An overview of all known errors of the dataset is provided in the Comprehensive Error Characterization Report. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three following references:\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321" }, { "ob_id": 12890, "uuid": "4eec83c4bbec4c8ea873188d90fc243f", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 02.1", "abstract": "Ancillary datasets were used in the production of the \"Active\", \"Passive\" and \"Combined\" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v02.1 Soil Moisture CCI data.\r\n\r\nFor further information on these and the references associated with them please see the Product Specification Document (PSD), a link to which is provided in linked documentation. The \"Active\" \"Passive\" and \"Combined\" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website or within the Product Specification Document." }, { "ob_id": 24841, "uuid": "c4f117ba38544e8a80338b6cf1000a91", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 03.2", "abstract": "These ancillary datasets were used in the production of the \"Active\", \"Passive\" and \"Combined\" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v03.2 Soil Moisture CCI data.\r\n\r\nThe \"Active\" \"Passive\" and \"Combined\" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 12878, "uuid": "515df65d974541df82740062974212aa", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 02.1", "abstract": "The Soil Moisture CCI 'Active' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v02.1 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2013-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version 2.0 or the paper by Wagner 2012, both available in the documentation section. An overview of all known errors of the dataset is provided in the Comprehensive Error Characterization Report. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three following references:\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321" }, { "ob_id": 24714, "uuid": "71e20f6a7d6e4ec392f9afcbce14eced", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Passive' Product, Version 03.2", "abstract": "The Soil Moisture CCI 'Passive' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing radiometer soil moisture products, merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. 'Active' and 'Combined' products have also been created, the 'Active' product being a fusion of AMI-WS and ASCAT derived scatterometer products and the 'Combined Product' being a blended product based on the former two data sets. \r\n\r\nThe v03.2 Passive product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2015-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 24715, "uuid": "7c7a38b2d2ce448b99194bff85a85248", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Combined' Product, Version 03.2", "abstract": "The Soil Moisture CCI 'Combined' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these being respectively fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satelllite instruments. \r\n\r\nThe product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2015-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version 2.0 or the paper by Wagner 2012, both available in the documentation section. An overview of all known errors associated with it is provided in the Comprehensive Error Characterization Report. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 26173, "uuid": "0f4570c780ba41b19a362e774509c883", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Combined' Product, Version 03.3", "abstract": "The Soil Moisture CCI 'Combined' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these being respectively fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. \r\n\r\nThe v03.3 Combined product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 14397, "uuid": "33ac39755cad49e38e34b048678a67aa", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 02.2", "abstract": "These ancillary datasets were used in the production of the \"Active\", \"Passive\" and \"Combined\" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v02.2 Soil Moisture CCI data.\r\n\r\nFor further information on these and the references associated with them please see the Product Specification Document (PSD), a link to which is provided in the documentation section. The \"Active\" \"Passive\" and \"Combined\" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website or within the Product Specification Document." }, { "ob_id": 24712, "uuid": "c657ee46354d480b8cf668addf0b43f2", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 03.2", "abstract": "The Soil Moisture CCI 'Active' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2,. and SMOS satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v03.2 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2015-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, { "ob_id": 14403, "uuid": "663a557e848a4a9f8f0d205c6b3cb7f6", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 02.2", "abstract": "The Soil Moisture CCI 'Active' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v02.2 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2014-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version 2.0 or the paper by Wagner 2012, both available in the documentation section. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321" }, { "ob_id": 14399, "uuid": "c89cb1c86f42456bb84e49ea06621c7e", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Combined' Product, Version 02.2", "abstract": "The Soil Moisture CCI 'Combined' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these being respectively fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. \r\n\r\nThe v02.2 product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2014-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version 2.0 or the paper by Wagner 2012, both available in the documentation section. An overview of all known errors associated with it is provided in the Comprehensive Error Characterization Report. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321" }, { "ob_id": 12886, "uuid": "2cc1cbc906444322845e6a51916a1f03", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Combined' Product, Version 02.1", "abstract": "The Combined Soil Moisture CCI dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by merging the \"Active\" and \"Passive\" datasets which were created for the project, these both being fusions of scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, and AMSR2 satellite instruments. \r\n\r\nThe v02.1 product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2013-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document version 2.0 or the paper by Wagner 2012, both available in the documentation section. An overview of all known errors associated with it is provided in the Comprehensive Error Characterization Report. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three following references:\r\n1. Liu, Y. Y., W. A. Dorigo, et al. (2012). \"Trend-preserving blending of passive and active microwave soil moisture retrievals.\" Remote Sensing of Environment 123: 280-297.\r\n2. Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrology and Earth System Sciences, 15, 425-436\r\n3. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012). Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 49196, 49194, 49193, 49195, 105392, 105419, 105443, 55929 ], "onlineresource_set": [ 6626, 6635, 6708, 8887, 24915, 24916, 24917, 6629 ], "project_set": [] }, { "ob_id": 12888, "uuid": "4f93de2997f44452bef9acdfa425a0d1", "short_code": "coll", "title": "ACSOE OXICOA LTERM: Chemical Climatology Data from Mace Head Atmospheric Research Centre", "abstract": "The Atmospheric Chemistry Studies in the Oceanic Environment (ACSOE) OXIdising Capacity of the Ocean Atmosphere (OXICOA) Long-Term Studies of chemical Climatology (LTERM) is the longer term studies of the Eastern Atlantic Spring/Summer Experiments (EASE-96 and EASE-97). The longer term data includes DMS, ozone and chemicals involved in its cycle, carbon and hydrocarbons to help interpreting the data collected over the ACSOE campaign by providing insights on seasonal changes of chemicals.", "keywords": "ACSOE, OXICOA, LTERM", "publicationState": "published", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 39 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 12884, "uuid": "c8b8ff6fe0d147999e53169ab4a32d03", "short_code": "ob", "title": "ACSOE OXICOA LTERM: Chemical Climatology Data from Mace Head Atmospheric Research Centre", "abstract": "The Atmospheric Chemistry Studies in the Oceanic Environment (ACSOE) OXIdising Capacity of the Ocean Atmosphere (OXICOA) Long-Term Studies of chemical Climatology (LTERM) is the longer term studies of the Eastern Atlantic Spring/Summer Experiments (EASE-96 and EASE-97). The longer term data includes DMS, ozone and chemicals involved in its cycle, carbon and hydrocarbons." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 49242, 49243, 49244, 49249, 49251, 49257, 49247, 49246, 49313, 49245, 49248, 49250, 49252, 49253, 49254, 49255, 49256, 49258, 49259, 49260, 49261, 49262, 49263, 49264, 49265, 49266, 49267, 49268, 49269, 49270, 49271, 49272, 49273, 49274, 49311, 49275, 49276, 49277, 49278, 49279, 49280, 49281, 49282, 49283, 49284, 49285, 49286, 49287, 49288, 49289, 49290, 49291, 49292, 49293, 49294, 49295, 49296, 49297, 49298, 49299, 49300, 49301, 49302, 49303, 49304, 49305, 49306, 49307, 49308, 49309, 49310, 49312 ], "onlineresource_set": [ 6726, 6729, 6724, 6727 ], "project_set": [ 12887 ] }, { "ob_id": 12893, "uuid": "5aeeae2bd877479c9617c45c4345ff51", "short_code": "coll", "title": "ALPHASAT: KA/Q band radio propagation measurements collection from European sites using the TDP5 Propagation Beacon", "abstract": "A collection of measurements of radio propagation in the KA/Q band measured from various European sites using the Aldo Paradoni Payload (TDP5) propagation beacon.\r\n\r\nMeasurements were made at 20 and 40 GHz frequencies.\r\n\r\nThe measurements were made as part of the ESA funded ASALASCA (Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon) project. \r\n\r\nThe collection is additionally supplemented by surface meteorological measurements from the Chilbolton Observatory, Hampshire, UK for use in conjunction with the radio propagation measurements made at Chilbolton.\r\n\r\nMeasurements began in July 2016 and are presently ongoing.", "keywords": "ALPHASAT, radio propagation, ESA, ASALASCA, KA/Q Band", "publicationState": "published", "dataPublishedTime": "2017-04-24T13:26:20", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 3482, "uuid": "614747245770927bbe7565b690945ec3", "short_code": "ob", "title": "Chilbolton Facility for Atmospheric and Radio Research (CFARR) Multiple Raingauges Data, Chilbolton Site", "abstract": "Data were collected by Chilbolton Facility for Atmospheric and Radio Research (CFARR) Raingauges from 2001 to the present at Chilbolton, Hampshire. The dataset contains measurements of rainfall accumulation as measured by multiple instruments." }, { "ob_id": 25386, "uuid": "e4b4e5d29fcc48308c3a8f09e4ca766b", "short_code": "ob", "title": "ALPHASAT: preprocessed radio propagation measurements at 40 GHz at NTUA Campus, Athens, Greece v1", "abstract": "Radio propagation measurements at 40 GHz at National Technical University of Athens (NTUA) Campus, Athens, Greece collected in support of the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 3611, "uuid": "e490cd13d86d832bd2d62f1650d7b265", "short_code": "ob", "title": "Chilbolton Facility for Atmospheric and Radio Research (CFARR) Campbell Scientific PWS100 present weather sensor data", "abstract": "The Campbell Scientific PWS100 present weather sensor deployed at the Chilbolton Observatory, Hampshire, detects and classifies precipitation by observing the scattering of a laser beam 20 degrees off the forward direction in the horizontal and vertical planes. The detected signals depend on the size, shape, optical properties, concentration and velocity of the particles. The instrument is mounted approximately 10m above ground on the roof of a cabin at the Chilbolton Observatory site. It is operated continuously. Data include: counts as a function of size of hydrometeors in 300 bins from 0.1 to 30.0 mm, the number of hydrometeors in 9 type categories. visibility, air temperature, relative humidity, rainfall rate, rainfall accumulation, average hydrometeor velocity, average hydrometeor size and reports the World Meteorological Organisation (WMO) present weather code for the site. Data are archived as netCDF files." }, { "ob_id": 12889, "uuid": "3c3345982d4f4d9ab5d0155bee0277d5", "short_code": "ob", "title": "ESA ALPHASAT: preprocessed radio propagation measurements at 40 GHz at Chilbolton, Hampshire v1", "abstract": "Radio propagation measurements at 40 GHz at Chilbolton, Hampshire for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 12918, "uuid": "0d22f50676b64a9d96fd03b7944c51ea", "short_code": "ob", "title": "ESA ALPHASAT: preprocessed radio propagation measurements at 40 GHz at Chilton, Oxfordshire v1", "abstract": "Radio propagation measurements at 40 GHz at Chilton, Oxfordshire for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 12908, "uuid": "d9c043a8d61048568268d7c1dbaa26b0", "short_code": "ob", "title": "ESA ALPHASAT: raw radio propagation measurements at 20 GHz at Vigo, Spain", "abstract": "Radio propagation measurements at 20 GHz at Vigo, Spain for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 12914, "uuid": "ed2711acb7a34863be02d32d4d797e60", "short_code": "ob", "title": "ESA ALPHASAT: preprocessed radio propagation measurements at 20 GHz at NTUA Campus, Athens, Greece v1", "abstract": "Radio propagation measurements at 20 GHz at National Technical University of Athens (NTUA) Campus, Athens, Greece for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 12909, "uuid": "170b951435b1476c813c5d623abd8516", "short_code": "ob", "title": "ESA ALPHASAT: preprocessed radio propagation measurements at 20 GHz at Vigo, Spain v1", "abstract": "Radio propagation measurements at 20 GHz at Vigo, Spain for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 12917, "uuid": "917f7dde3cbc454ab3c24bf2d76d1994", "short_code": "ob", "title": "ESA ALPHASAT: raw radio propagation measurements at 40 GHz at Aveiro, Portugal", "abstract": "Radio propagation measurements at 40 GHz at Aveiro, Portugal for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 3535, "uuid": "b5b96f48a8ea9493fedad621dbc1fc5d", "short_code": "ob", "title": "Chilbolton Facility for Atmospheric and Radio Research (CFARR) Disdrometer Data, Sparsholt College Site", "abstract": "Data were collected by the Chilbolton Facility for Atmospheric and Radio Research (CFARR) Disdrometer from the 1st of July 2004 to the present at Sparsholt College, Hampshire. The dataset contains measurements of the drop size distribution of rain." }, { "ob_id": 12915, "uuid": "0f0b7be794c14f649ada3ad7d0f807a1", "short_code": "ob", "title": "ESA ALPHASAT: raw radio propagation measurements at 20 GHz at Lavrion, Greece", "abstract": "Radio propagation measurements at 20 GHz at Lavrion, Greece for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 12904, "uuid": "73a39939d50d46fbb2d65616c6ba302e", "short_code": "ob", "title": "ALPHASAT: Raw beacon radio propagation measurements at 20 and 40 GHz (KA/Q bands) made at Chilbolton, Hampshire", "abstract": "Raw beacon radio propagation measurements at 20 and 40 GHz (KA/Q bands) made at Chilbolton, Hampshire, UK, for the ESA funded 'Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 propagation beacon signal (ASALASCA)' project.\r\n\r\nThese are signals measured by the two receivers located at Chilbolton received from the Aldo Paradoni Payload (TDP5) beacon on board ESA's ALPHASAT telecommunications satellite.\r\n\r\nMeasurements began in July 2016." }, { "ob_id": 12916, "uuid": "04b3e83644334f3b94bac275c60b8a54", "short_code": "ob", "title": "ESA ALPHASAT: preprocessed radio propagation measurements at 40 GHz at Aveiro, Portugal v1", "abstract": "Radio propagation measurements at 40 GHz at Aveiro, Portugal for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 12907, "uuid": "a28c24d917e147dfab1abab37d3f6e06", "short_code": "ob", "title": "ESA ALPHASAT: preprocessed radio propagation measurements at 20 GHz at Chilton, Oxfordshire v1", "abstract": "Radio propagation measurements at 20 GHz at Chilton, Oxfordshire for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 12919, "uuid": "4554e7ec68df40618f268c191b397313", "short_code": "ob", "title": "ESA ALPHASAT: preprocessed radio propagation measurements at 40 GHz at Vigo, Spain v1", "abstract": "Radio propagation measurements at 40 GHz at Vigo, Spain for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 3471, "uuid": "45b25a7c531563f4422afcaeea0f07a7", "short_code": "ob", "title": "Chilbolton Facility for Atmospheric and Radio Research (CFARR) Meteorological Sensor Data, Chilbolton Site", "abstract": "Data were collected by the Chilbolton Facility for Atmospheric and Radio Research (CFARR) Meteorological Sensor from 2001 to present at Chilbolton, Hampshire. The standard meteorological measurements are made at Chilbolton in support of all experiments at the Observatory. The data are automatically recorded every 10 seconds from a range of different sensors. The dataset contains measurements including temperature, dew point, pressure, wind speed and wind direction." }, { "ob_id": 3531, "uuid": "aac5f8246987ea43a68e3396b530d23e", "short_code": "ob", "title": "Chilbolton Facility for Atmospheric and Radio Research (CFARR) Disdrometer Data, Chilbolton Site", "abstract": "Data were collected by the Chilbolton Facility for Atmospheric and Radio Research (CFARR) Disdrometer from the 1st of April 2003 to the present at Chilbolton, Hampshire. The dataset contains measurements of the drop size distribution of rain." }, { "ob_id": 12921, "uuid": "fbd1af3d905b41ff852cff339d88d70b", "short_code": "ob", "title": "ESA ALPHASAT: raw radio propagation measurements at 40 GHz at Vigo, Spain", "abstract": "Radio propagation measurements at 40 GHz at Vigo, Spain for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 12911, "uuid": "46ea21d4fcd1425eb538a7a3c9787e3e", "short_code": "ob", "title": "ESA ALPHASAT: raw radio propagation measurements at 20 GHz at Bilbao, Spain", "abstract": "Radio propagation measurements at 20 GHz at Bilbao, Spain for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 12913, "uuid": "c29ed94dd7644f5fb1de2228c6d5f71f", "short_code": "ob", "title": "ESA ALPHASAT: raw radio propagation measurements at 20 and 40 GHz at NTUA Campus, Athens, Greece", "abstract": "Radio propagation measurements at 20 and 40 GHz at the National Technical University of Athens (NTUA) Campus, Athens, Greece for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 12906, "uuid": "95797587b812438495af983b1ea356db", "short_code": "ob", "title": "ALPHASAT: raw beacon radio propagation measurements at 20 and 40 GHz (KA/Q bands) made at Chilton, Oxfordshire", "abstract": "Raw beacon radio propagation measurements at 20 and 40 GHz (KA/Q bands) made at Chilton, Oxfordshire, UK, for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal (ASALASCA) project.\r\n\r\nThese are signals measured by the two receivers located at Chilbolton received from the Aldo Paradoni Payload (TDP5) beacon on board ESA's ALPHASAT telecommunications satellite. Measurements were made from July 2016 to present." }, { "ob_id": 12905, "uuid": "9c06a768ebfe40edb8fc5c846d4d0106", "short_code": "ob", "title": "ESA ALPHASAT: preprocessed radio propagation measurements at 20 GHz at Chilbolton, Hampshire v1", "abstract": "Radio propagation measurements at 20 GHz at Chilbolton, Hampshire for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." }, { "ob_id": 12925, "uuid": "626505cde8c54ad2a0544d86e60ee6e5", "short_code": "ob", "title": "ESA ALPHASAT: raingauge data from Vigo, Spain", "abstract": "Raingauge data collected as part of the ESA Funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon project (ASALASCA). The rain gauge instrument was a Young 52203 tipping bucket rain gauge." }, { "ob_id": 12912, "uuid": "a0319be9011a4c8fb5f2d556e4a10ae8", "short_code": "ob", "title": "ESA ALPHASAT: preprocessed radio propagation measurements at 20 GHz at Bilbao, Spain v1", "abstract": "Radio propagation measurements at 20 GHz at Bilbao, Spain for the ESA funded Large Scale Assessment of KA/Q band atmospheric channel using the ALPHASAT TDP5 Propagation beacon signal." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 49466, 49332, 49331, 49330, 98436, 98438, 105445, 98437, 98439 ], "onlineresource_set": [], "project_set": [ 12892 ] }, { "ob_id": 12986, "uuid": "65e424f8d8c845a4b60ef6808d179313", "short_code": "coll", "title": "ESA-DUE GlobAlbedo Broadband Bi-directional Reflectance Distribution Functions (BRDF)", "abstract": "\r\n\r\nSpectral BRDF, is the fundamental description of surface reflectance, being the ratio of reflected spectral radiance (Wm-2sr-1nm-1) exiting around a direction vector Ω (relative to a surface normal vector) to the spectral irradiance (Wm-2nm-1) incident on the surface from direction Ω at some wavelength λ.", "keywords": "ESA, GlobAlbedo, Albedo, ", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [], "discoveryKeywords": [], "member": [ { "ob_id": 12984, "uuid": "6a81b77693c847929e0d31a6ce84a821", "short_code": "ob", "title": "ESA GlobAlbedo Broadband BRDF (Bi-directional Reflectance Distribution Functions) merge - Version 1.0", "abstract": "ESA GlobAlbedo Broadband BRDF\r\n\r\n3.2.6 Merged BRDF Product\r\nAs output from the BBDR (Broadband Directional Reflectance) to BRDF processing chain, a final ‘merged’ BRDF product is generated. This product merges the two BRDF products for Snow/NoSnow pixels as described above into one product. The merged product serves as input for the final albedo retrieval as well as for the resampling and the mosaicking of the tile-based BRDF uncertainties into a global product." }, { "ob_id": 12983, "uuid": "4425b0c4e5b346008cd4b1a09b5b96e3", "short_code": "ob", "title": "ESA GlobAlbedo Broadband BRDF (Bi-directional Reflectance Distribution Functions) inversion - Version 1.0", "abstract": "As output from the BBDR (Braodband Directional Reflectance) to BRDF processing chain, a BRDF product is generated. This product contains all BRDF model parameters as derived from the Globalbedo inversion algorithm. \r\n\r\nSpectral BRDF, is the fundamental description of surface reflectance, being the ratio of reflected spectral radiance (Wm-2sr-1nm-1) exiting around a direction vector Ω (relative to a surface normal vector) to the spectral irradiance (Wm-2nm-1) incident on the surface from direction Ω at some wavelength λ." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 50781, 49736, 105382, 105393, 105420, 105444, 105378 ], "onlineresource_set": [ 7810 ], "project_set": [ 12987 ] }, { "ob_id": 13034, "uuid": "d7e02c75191a4515a28a208c8a069e70", "short_code": "coll", "title": "UK ICE-D: atmospheric measurements dataset collection", "abstract": "This dataset collection holds datasets from the FAAM BAe-146 aircraft and ground-based measurements taken in Cape Verde off the coast of Senegal, Africa during 2015 and 2016 in support of the UK Ice in Clouds Experiment - Dust (UK ICE-D) project.", "keywords": "dust, convective clouds, aerosol, cloud droplets, supercooled raindrops, ice particles, cloud condensation nuclie", "publicationState": "published", "dataPublishedTime": "2015-10-16T13:01:46", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 18675, "uuid": "daab5cf137bb45c78bf07f82457953b5", "short_code": "ob", "title": "FAAM B927 ICE-D flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) project." }, { "ob_id": 15569, "uuid": "43d0c0bce57141d991354cb3dc798d2a", "short_code": "ob", "title": "FAAM B917 ICE-D Test flight, number 2: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft during flight 2 for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) project." }, { "ob_id": 18655, "uuid": "684e82a84fd4400d9b336121ee93028a", "short_code": "ob", "title": "FAAM B920 ICE-D flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) project." }, { "ob_id": 18651, "uuid": "ac1ef7bf8ac742edbd69221a064fb168", "short_code": "ob", "title": "FAAM B921 ICE-D flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) project." }, { "ob_id": 18679, "uuid": "d1d660aa1a1f4de6a66e6d70aa0965d2", "short_code": "ob", "title": "FAAM B926 ICE-D flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) project." }, { "ob_id": 17627, "uuid": "1c08bcbdae7e40aa8596951c885e1215", "short_code": "ob", "title": "FAAM B930 ICE-D flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) project." }, { "ob_id": 17623, "uuid": "80b63fe2053f4554865c3c1b2bddf240", "short_code": "ob", "title": "FAAM B933 ICE-D flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) project." }, { "ob_id": 17619, "uuid": "52d601437cd5442fa323bb2375ca86d0", "short_code": "ob", "title": "FAAM B932 AER-D flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) (AER-D) project." }, { "ob_id": 15560, "uuid": "f688968f4e3d40b08b59843daff0dea8", "short_code": "ob", "title": "FAAM B915 ICE-D Test flight, number 1: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 1 for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) project." }, { "ob_id": 25109, "uuid": "55b5d76a7edb42e39933c1edc37f7b90", "short_code": "ob", "title": "ICE-D: NCAS mobile X-band radar scan data from the Praia International Airport, Santiago, Cape Verde, Version 1", "abstract": "This dataset contains scan data from the National Centre for Atmospheric Science's (NCAS) mobile X-band radar collected at Praia International Airport, Santiago, Cape Verde between July and August 2015 as part of the Ice in Clouds Experiment - Dust (ICE-D). The radar has Doppler and dual-polarisation capability and measures the location and intensity of precipitation, radial winds and polarisation parameters.\r\n\r\nThe X-band radar is operated as part of the NCAS Atmospheric Measurement Facility (AMF)." }, { "ob_id": 17631, "uuid": "2f3508a0652d49608f0c7c4a16b170fb", "short_code": "ob", "title": "FAAM B931 ICE-D flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) project." }, { "ob_id": 18667, "uuid": "1a7309712d08412680d906e5dc4ced16", "short_code": "ob", "title": "FAAM B925 ICE-D flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) project." }, { "ob_id": 16224, "uuid": "6000a8121fe04c6998ade98ed022f99b", "short_code": "ob", "title": "FAAM B922 ICE-D flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) project." }, { "ob_id": 18639, "uuid": "c6183599921d41ca9f37a3e14fa7851a", "short_code": "ob", "title": "FAAM B929 ICE-D flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) project." }, { "ob_id": 16049, "uuid": "cc6658a3c2f64d32832040984194dd2f", "short_code": "ob", "title": "FAAM B919 ICE-D flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) project." }, { "ob_id": 18659, "uuid": "b03368b21e2d499b85722769b7c5bbaf", "short_code": "ob", "title": "FAAM B923 AER-D flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) (AER-D) project." }, { "ob_id": 18671, "uuid": "b9d0869032e7422ca8676419c40eec09", "short_code": "ob", "title": "FAAM B924 AER-D flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The UK Ice in Clouds Experiment -- Dust (UK ICE-D) (AER-D) project." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 49921, 72499, 72498, 102920, 102921, 102923, 102924, 102922, 111858, 49920 ], "onlineresource_set": [], "project_set": [ 12454 ] }, { "ob_id": 13060, "uuid": "38fd6c7841d84a6686ca663fcdd61a3f", "short_code": "coll", "title": "Snowdon Mountain Railway Global Navigation Satellite Systems (GNSS): Repeatable Kinematic Dataset Collection from Snowdonia", "abstract": "This dataset collection holds a repeatable kinematic dataset taken from Global Navigation Satellite Systems (GNSS) stations on moving platforms at the Snowdon Mountain Railway (SMR). The datasets include profiles of 950m of the lower atmosphere over a 50 day period in 2011. \r\n\r\nThere are three different locations used in the dataset as it was mounted on a train of the Snowdon Mountain Railway (SNTR) as it travelled up and down the mountain, with two static reference stations at the base of the railway at Llanberis (SNLB) and at the summit (SNSU). \r\n\r\nThree instruments were used to collect the data including; Paroscientific 745, Paroscientific Met 4 and Leica GS10 GNSS receivers. Respectively measuring pressure, pressure/temperature, dual frequency GPS and GLONASS code and carrier phase satellite to receiver measurements. ", "keywords": "GPS, GLONASS, pressure, temperature, snowdon, snowdon mountain railway, snowdon-gnss", "publicationState": "citable", "dataPublishedTime": "2015-09-22T08:51:17", "doiPublishedTime": "2015-09-22T23:00:00", "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1142, "name": "NDGO0005" }, { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 13066, "uuid": "b4b1918baf664d6da3e9507f0c57a28e", "short_code": "ob", "title": "Snowdon Mountain Railway Global Navigation Satellite Systems (GNSS): surface meteorological and GPS data from a moving train on Snowdon, North Wales", "abstract": "This dataset contains Global Navigation Satellite Systems (GNSS) and meteorological data from instruments mounted on a train of the Snowdon Mountain Railway (SNTR) as it travelled up and down the mountain. \r\n\r\nThe data were collected from 28th August 2011 to 16th October 2011 (50 days). \r\n\r\nTwo instruments collected data from the summit including; Paroscientific 745 (ncl-paro-745) and Leica GS10 GNSS (ncl-leica-gnss). The ncl-leica-gnss measured dual frequency GPS and GLONASS code and carrier phase satellite to receiver measurements, whilst the ncl-paro-745 sensor recorded pressure data. \r\n" }, { "ob_id": 13064, "uuid": "38785e3d2736475e9db984481758fb66", "short_code": "ob", "title": "Snowdon Mountain Railway Global Navigation Satellite Systems (GNSS): surface meteorological and GPS data from the base of the railway at Llanberis, North Wales", "abstract": "This dataset contains Global Navigation Satellite Systems (GNSS) and meteorological data from a static reference station at the base of the Snowdon Mountain Railway at Llanberis (SNLB). \r\n\r\nThe data were collected from 28th August 2011 to 16th October 2011 (50 days). \r\n\r\nTwo instruments collected data from the base including; Paroscientific Met 4 (ncl-met-4) and Leica GS10 GNSS (ncl-leica-gnss). The ncl-leica-gnss measured dual frequency GPS and GLONASS code and carrier phase satellite to receiver measurements, whilst the ncl-met-4 sensor recorded pressure and temperature. \r\n\r\n" }, { "ob_id": 13065, "uuid": "67b7a894ddee4b4b93daa65f9a4e9030", "short_code": "ob", "title": "Snowdon Mountain Railway Global Navigation Satellite Systems (GNSS): surface meteorological and GPS data from the summit of the railway at Snowdon, North Wales", "abstract": "This dataset contains Global Navigation Satellite Systems (GNSS) and meteorological data from instruments at a static reference station at the summit (SNSU) of Snowdon Mountain Railway. \r\n\r\nThe data were collected from 28th August 2011 to 16th October 2011 (50 days). \r\n\r\nTwo instruments collected data from the summit including; Paroscientific Met 4 (ncl-met-4) and Leica GS10 GNSS (ncl-leica-gnss). The ncl-leica-gnss measured dual frequency GPS and GLONASS code and carrier phase satellite to receiver measurements, whilst the ncl-met-4 sensor recorded pressure and temperature. " } ], "identifier_set": [ 8523, 8525 ], "responsiblepartyinfo_set": [ 50043, 50178, 50181, 50075, 50074, 50082, 50179, 50180, 50076, 50233, 50042 ], "onlineresource_set": [ 6945, 6946 ], "project_set": [ 13057 ] }, { "ob_id": 13111, "uuid": "2f068226c7164a799cf202d1e7af07b2", "short_code": "coll", "title": "European Space Agency (ESA) GlobSnow Snow Water Equivalent (SWE) v2.0 products", "abstract": "The GlobSnow SWE product is the first satellite based daily SWE dataset for the non-alpine northern hemisphere that extends from 1979 to 2014. The previous existing daily SWE records have spanned a shorter time period (2002-2014) or described the snow conditions on a monthly basis for a similar period (1978-2014). \r\n\r\nThe GlobSnow SWE record utilizes a novel data-assimilation based approach for SWE estimation which combines weather station measurements of snow depth with satellite passive microwave measurements. This approach was shown to be superior to alternative algorithms which solely utilize satellite data through comparison with extensive ground reference datasets.\r\n\r\nThe GlobSnow-1 and -2 projects have developed a long term data record of SWE products covering the non-alpine Northern Hemisphere, based on a time series of remotely sensed observations from the Nimbus-7 SMMR, DMSP F8/F11/F13/F17 SSM/I(S) instruments and ground-based weather station measurements from 1979 until 2014. \r\n\r\nThere are three SWE products (all on the EASE model grid; see Armstrong and Brodzik, 1995):\r\n\r\n- Daily Snow Water Equivalent (Daily L3A SWE), snow water equivalent (mm) for each grid cell for all evaluated land areas of the Northern Hemisphere.\r\n\r\n- Weekly Aggregated Snow Water Equivalent (Weekly L3B SWE), calculated for each day based on a 7-day sliding time window aggregation of the daily SWE product.\r\n\r\n- Monthly Aggregated Snow Water Equivalent (Monthly L3B SWE), a single product for each calendar month, providing the average and maximum SWE, calculated from the weekly aggregated SWE product.\r\n\r\nThe GlobSnow-1 project resulted in two versions of the data record, SWE v1.0 and SWE v1.3 (available from FMI). The dataset produced in GlobSnow-2 is identified as the GlobSnow SWE v2.0 data record.\r\n\r\nIn addition to the SWE retrievals, the SWE products include information on the overall extent of snow cover. The information on snow extent is included in the product by utilizing the following coding for the SWE product, whereby SWE values of:\r\n - 0 mm denotes snow-free areas (Snow Extent 0%)\r\n - 0.001 mm denote areas with melting snow (Snow Extent undefined between 0% and 100%; no SWE retrieval because of the wet state of the snow cover)\r\n - > 0.001 mm denote areas with full snow cover (Snow Extent 100%)\r\n\r\nThe areas that have been flagged as snow-free or melted are identified using a time-series melt detection approach described in Takala et al. (2009). The areas that are identified as wet snow or have no SWE retrieval, but are identified as snow covered with the time-series melt-detection approach, are denoted with a SWE value of 0.001 mm. The areas that are determined as snow-free or melted by the melt-detection approach, are denoted with a SWE value of 0 mm. All the other areas show a retrieved SWE value (that is in all cases greater than 0.001 mm).\r\n\r\nThe project was coordinated by the Finnish Meteorological Institute (FMI). Other project partners involved are NR (Norwegian Computing Centre), ENVEO IT GmbH, GAMMA Remote Sensing AG, Finnish Environment Institute (SYKE), Environment Canada (EC), Northern Research Institute (Norut), University of Bern, Meteoswiss and ZAMG.\r\n", "keywords": "esa, globsnow, snow, climate, swe", "publicationState": "published", "dataPublishedTime": "2015-09-22T20:44:17", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 152 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 13544, "uuid": "48d69bd4dd89464fb1f32c3669bfaa94", "short_code": "ob", "title": "European Space Agency (ESA) GlobSnow L3B mean STD of 7 day running mean Snow Water Equivalent (SWE) Estimates (1979-2013)", "abstract": "The ESA funded GlobSnow project produced snow water equivalent (SWE) 7-day estimates and standard errors for the Northern Hemisphere for the years 1979-2013. \r\n\r\nSWE describes the amount of liquid water in the snow pack that would be formed if the snow pack was completely melted. Weekly Aggregated Snow Water Equivalent (Weekly L3B SWE) were calculated for each day based on a 7-day sliding time window aggregation of the daily SWE product.\r\n\r\nThe SWE product shall cover the Northern Hemisphere, excluding the mountainous areas, Greenland, the glaciers and snow on ice (lakes/seas/oceans)\r\n\r\nThe spatial resolution of the product is 25 km on EASE-grid projection. \r\n\r\nConstruction of the 30 years historical data set will be carried out using SMMR, SSM/I and SSMI/S data along with ground-based weather station data. The data are utilized for the different years as follows:\r\n\r\n1979/09/11 - 1987/10/30 SMMR (Scanning Multichannel Microwave Radiometer onboard Nimbus-7 satellite)\r\n1987/11/01 - 2008/12/31 SSM/I (Special Sensor Microwave/Imager onboard the DMSP satellite series F8/F11/F13)\r\n2009/01/01 - present SSM/I(S) (Special Sensor Microwave/Imager (Sounder) onboard the DMSP satellite series F17/F18/)\r\n\r\nThese data may be redistributed and used without restriction." }, { "ob_id": 13546, "uuid": "93bd163433a2430d841a77518d7a40e0", "short_code": "ob", "title": "European Space Agency (ESA) GlobSnow Snow Water Equivalent (SWE) v2.0 L3B Monthly Aggregated Maximum value data (1979-2013)", "abstract": "The ESA funded GlobSnow project produced snow water equivalent (SWE) monthly estimates for the Northern Hemisphere for the years 1979-2013. \r\n\r\nSWE describes the amount of liquid water in the snow pack that would be formed if the snow pack was completely melted. \r\n\r\nThe monthly aggregate, a single product for each month, is calculated by determining the mean and the maximum of the weekly SWE samples. This dataset presents the monthly maximum value of SWE only.\r\n\r\nThe SWE product shall cover the Northern Hemisphere, excluding the mountainous areas, Greenland, the glaciers and snow on ice (lakes/seas/oceans).\r\n\r\nThe spatial resolution of the product is 25 km on EASE-grid projection. \r\n\r\nConstruction of the 30 years historical data set will be carried out using SMMR, SSM/I and SSMI/S data along with ground-based weather station data. The data are utilized for the different years as follows:\r\n\r\n1979/09/11 - 1987/10/30 SMMR (Scanning Multichannel Microwave Radiometer onboard Nimbus-7 satellite)\r\n1987/11/01 - 2008/12/31 SSM/I (Special Sensor Microwave/Imager onboard the DMSP satellite series F8/F11/F13)\r\n2009/01/01 - present SSM/I(S) (Special Sensor Microwave/Imager (Sounder) onboard the DMSP satellite series F17/F18/)\r\n\r\nThese data may be redistributed and used without restriction." }, { "ob_id": 13114, "uuid": "08fc9775b3954a719d4f093b59cf194d", "short_code": "ob", "title": "European Space Agency (ESA) GlobSnow Snow Water Equivalent (SWE) v2.0 L3B Monthly data (1979-2013)", "abstract": "The ESA funded GlobSnow project produced snow water equivalent (SWE) monthly estimates for the Northern Hemisphere for the years 1979-2013. \r\n\r\nSWE describes the amount of liquid water in the snow pack that would be formed if the snow pack was completely melted. \r\n\r\nThe monthly aggregate, a single product for each month, is calculated by determining the mean and the maximum of the weekly SWE samples.\r\n\r\nThe SWE product shall cover the Northern Hemisphere, excluding the mountainous areas, Greenland, the glaciers and snow on ice (lakes/seas/oceans).\r\n\r\nThe spatial resolution of the product is 25 km on EASE-grid projection. \r\n\r\nConstruction of the 30 years historical data set will be carried out using SMMR, SSM/I and SSMI/S data along with ground-based weather station data. The data are utilized for the different years as follows:\r\n\r\n1979/09/11 - 1987/10/30 SMMR (Scanning Multichannel Microwave Radiometer onboard Nimbus-7 satellite)\r\n1987/11/01 - 2008/12/31 SSM/I (Special Sensor Microwave/Imager onboard the DMSP satellite series F8/F11/F13)\r\n2009/01/01 - present SSM/I(S) (Special Sensor Microwave/Imager (Sounder) onboard the DMSP satellite series F17/F18/)\r\n\r\nThese data may be redistributed and used without restriction." }, { "ob_id": 13115, "uuid": "0710e8e5e584473fb292bb69b7fbf8a7", "short_code": "ob", "title": "European Space Agency (ESA) GlobSnow Snow Water Equivalent (SWE) v2.0 L3B Weekly aggregated data (1979-1994)", "abstract": "The ESA funded GlobSnow project produced snow water equivalent (SWE) 7-day estimates for the Northern Hemisphere for the years 1979-2013. \r\n\r\nSWE describes the amount of liquid water in the snow pack that would be formed if the snow pack was completely melted. Weekly Aggregated Snow Water Equivalent (Weekly L3B SWE) were calculated for each day based on a 7-day sliding time window aggregation of the daily SWE product.\r\n\r\nThe SWE product shall cover the Northern Hemisphere, excluding the mountainous areas, Greenland, the glaciers and snow on ice (lakes/seas/oceans)\r\n\r\nThe spatial resolution of the product is 25 km on EASE-grid projection. \r\n\r\nConstruction of the 30 years historical data set will be carried out using SMMR, SSM/I and SSMI/S data along with ground-based weather station data. The data are utilized for the different years as follows:\r\n\r\n1979/09/11 - 1987/10/30 SMMR (Scanning Multichannel Microwave Radiometer onboard Nimbus-7 satellite)\r\n1987/11/01 - 2008/12/31 SSM/I (Special Sensor Microwave/Imager onboard the DMSP satellite series F8/F11/F13)\r\n2009/01/01 - present SSM/I(S) (Special Sensor Microwave/Imager onboard the DMSP satellite series F17/F18/)\r\n\r\nThese data may be redistributed and used without restriction." }, { "ob_id": 13112, "uuid": "552cdad62fd14f54ba8ddbab38977cbc", "short_code": "ob", "title": "European Space Agency (ESA) GlobSnow Snow Water Equivalent (SWE) v2.0 L3A Daily data (1979-2013)", "abstract": "The ESA funded GlobSnow project produced snow water equivalent (SWE) daily estimates for the Northern Hemisphere for the years 1978-2014. \r\n\r\nSWE describes the amount of liquid water in the snow pack that would be formed if the snow pack was completely melted. \r\n\r\nThe SWE product shall cover the Northern Hemisphere, excluding the mountainous areas, Greenland, the glaciers and snow on ice (lakes/seas/oceans).\r\n\r\nThe spatial resolution of the product is 25 km on EASE-grid projection. \r\n\r\nConstruction of the 30 years historical data set will be carried out using SMMR, SSM/I and SSMI/S data along with ground-based weather station data. The data are utilized for the different years as follows:\r\n\r\n1979/09/11 - 1987/10/30 SMMR (Scanning Multichannel Microwave Radiometer onboard Nimbus-7 satellite)\r\n1987/11/01 - 2008/12/31 SSM/I (Special Sensor Microwave/Imager onboard the DMSP satellite series F8/F11/F13)\r\n2009/01/01 - present SSM/I(S) (Special Sensor Microwave/Imager (Sounder) onboard the DMSP satellite series F17/F18/)\r\n\r\nThese data may be redistributed and used without restriction." }, { "ob_id": 13542, "uuid": "977ab7f3767346dd9311a0c57a608054", "short_code": "ob", "title": "European Space Agency (ESA) GlobSnow L3A STD of daily Snow Water Equivalent (SWE) Estimates (1979-2013)", "abstract": "The ESA funded GlobSnow project produced snow water equivalent (SWE) daily standard errors (Variance estimates) for the Northern Hemisphere for the years 1979-2013. \r\n\r\nSWE describes the amount of liquid water in the snow pack that would be formed if the snow pack was completely melted. \r\n\r\nThe SWE product shall cover the Northern Hemisphere, excluding the mountainous areas, Greenland, the glaciers and snow on ice (lakes/seas/oceans).\r\n\r\nThe spatial resolution of the product is 25 km on EASE-grid projection. \r\n\r\nConstruction of the 30 years historical data set will be carried out using SMMR, SSM/I and SSMI/S data along with ground-based weather station data. The data are utilized for the different years as follows:\r\n\r\n1979/09/11 - 1987/10/30 SMMR (Scanning Multichannel Microwave Radiometer onboard Nimbus-7 satellite)\r\n1987/11/01 - 2008/12/31 SSM/I (Special Sensor Microwave/Imager onboard the DMSP satellite series F8/F11/F13)\r\n2009/01/01 - present SSM/I(S) (Special Sensor Microwave/Imager (Sounder) onboard the DMSP satellite series F17/F18/)\r\n\r\nThese data may be redistributed and used without restriction." } ], "identifier_set": [ 8518 ], "responsiblepartyinfo_set": [ 50190, 50189, 50188, 50186, 50185, 50184, 50183, 50187, 54785, 168610 ], "onlineresource_set": [ 7007, 7013, 9378, 9380, 9381, 9379, 9382 ], "project_set": [ 13110 ] }, { "ob_id": 13147, "uuid": "b7d3fffe79a34394becbb43feb163e7b", "short_code": "coll", "title": "High accuracy line intensity data for carbon dioxide", "abstract": "High accuracy line intensity for carbon dioxide project was NERC (Natural Environment Research Council) funded. The aim of the project was to provide an accurate theoretical solution to the problem of CO2 line intensities based on the application of high accuracy, first principles quantum mechanical calculations for the intensities and experimental data for the line positions. \r\n\r\nThis dataset collection contains measurements of high accuracy line intensity for carbon dioxide.\r\n\r\nAtmospheric CO2 concentrations are being closely monitored by remote sensing experiments which rely on knowing line intensities with an uncertainty of 0.5% or better. Most available laboratory measurements have uncertainties much larger than this. The generated data is a result of a joint experimental and theoretical study providing rotation-vibration line intensities with the required accuracy. The calculations are extendable to all atmospherically important bands of CO2 and to its isotologues. As such, they will form the basis for detailed CO2 spectroscopic line lists for future studies.", "keywords": "CO2 , carbon dioxide, nerc, line intensities", "publicationState": "published", "dataPublishedTime": "2015-10-06T21:15:52", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1142, "name": "NDGO0005" }, { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 12292, "uuid": "6d2cbe9f93404c5e9152f4f92ea6cbdb", "short_code": "ob", "title": "High accuracy line intensity data for carbon dioxide", "abstract": "High accuracy line intensity for carbon dioxide project was NERC (Natural Environment Research Council) funded. The aim of the project was to provide an accurate theoretical solution to the problem of CO2 line intensities based on the application of high accuracy, first principles quantum mechanical calculations for the intensities and experimental data for the line positions.\r\n\r\nThis dataset contains measurements of high accuracy line intensity for carbon dioxide." }, { "ob_id": 26712, "uuid": "b8cbc75bfaa1414fa4431cff170a9e99", "short_code": "ob", "title": "High accuracy room temperature line lists for the isotopologues of carbon dioxide", "abstract": "This dataset contains room temperature spectral line lists for 13 isotopologues of CO2, which have been calculated as part of the NERC (Natural Environment Research Council) funded 'High accuracy line intensity for carbon dioxide' project. These high accuracy line lists were derived for use in remote sensing of CO2 in the atmosphere. The dataset has been calculated from a theoretical model using the AMES potential energy surface and an accurate ab initio dipole moment surface. Data is provided in HITRAN format." } ], "identifier_set": [ 8542 ], "responsiblepartyinfo_set": [ 50347, 50348, 50349, 50350, 50352, 50353, 50354, 50351 ], "onlineresource_set": [ 7065, 23735, 23736, 23737 ], "project_set": [ 12148 ] }, { "ob_id": 13167, "uuid": "70d627f22d3c44d5ac64d9727c9d1a13", "short_code": "coll", "title": "Sentinel 2A: High-resolution optical imaging data from the Multispectral Instrument (MSI)", "abstract": "This dataset collection contains land monitoring data from the Multispectral Instrument (MSI) on the European Space Agency (ESA) Sentinel 2A satellite. Sentinel 2A was launched on 23rd June 2015 and provides sun-synchronous platform for the multispectral imaging data. The instrument uses 13 spectral bands from visible to the near infrared to obtain images with a swath width of 290km. Level 1C processing provides Top-Of-Atmosphere (TOA) reflectances in cartographic geometry. A further processing level, bottom-of-atmosphere (BOA) reflectance in cartographic geometry (prototype product) can be produced by the user with the Sentinel 2 toolbox. The BOA mode allows for the accurate assessment of biophysical parameters e.g. Leaf Area Index, with reduced cloud interference. ", "keywords": "Sentinel, Multispectral Instrument, MSI", "publicationState": "published", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 148 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 13172, "uuid": "9edbe5a1f7f5496cbc5863e53335b4a9", "short_code": "ob", "title": "Sentinel 2A Multispectral Instrument (MSI) Level 1C data", "abstract": "This dataset contains Top-of Atmosphere (TOA) reflectances in cartographic geometry (level 1C) processed data, from the Multispectral Instrument (MSI) aboard the European Space Agency (ESA) Sentinel 2A satellite. Sentinel 2A was launched on 23rd June 2015 and provides multispectral images of the earth’s surface as a continuation and enhancement of the Landsat and SPOT missions. Data are provided by the European Space Agency (ESA) and are made available via CEDA to any registered user in the UK.\r\n\r\nCEDA have switched to provide Sentinel 2 data for the UK and Dependencies along with data needed per project basis as of April 2019. Please contact us if you need data outside these areas and we will see what we can do." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 50477, 50478, 50480, 50479, 105394, 105408, 105421, 50481, 50946 ], "onlineresource_set": [ 7117, 7118, 7119 ], "project_set": [ 12321 ] }, { "ob_id": 13297, "uuid": "8cf12c9d19db4797a7549c74cef6c03e", "short_code": "coll", "title": "ESA Cloud Climate Change Initiative (CCI) Dataset Collection", "abstract": "This dataset collection contains cloud products produced by the Cloud project within the ESA Climate Change Initiative (CCI). \r\n\r\nThe ultimate objective of the ESA Cloud Climate Change Initiative (Cloud_cci) project is to provide long-term coherent cloud property datasets exploiting the synergic capabilities of different Earth observation missions allowing for improved accuracies and enhanced temporal and spatial sampling better than those provided by the single sources.\r\n\r\nCC4CL (Community Cloud Retrieval for Climate) and FAME-C (Freie Universität Berlin AATSR MERIS Cloud) are optimal estimation based retrieval systems providing GCOS cloud property Essential Climate Variables (ECVs) including uncertainty estimates. These global datasets contain cloud fraction, cloud top level estimates (pressure, height, and temperature), cloud thermodynamic phase, spectral cloud albedo, cloud effective radius, cloud optical thickness as well as cloud liquid and ice water content.\r\n\r\nThe AATSR-MODIS-AVHRR heritage product family obtained by CC4CL is based on measurements from ATSR-2/ERS-2, AATSR/ENVISAT, MODIS/AQUA, MODIS/TERRA, and AVHRR on-board NOAA-7, 9, 11, 12, 14, 15,16, 17, 18,19, and MetOp-A. The second product family contains cloud properties derived from ENVISAT’s AATSR and MERIS observations using the synergetic retrieval system FAME-C.\r\n\r\nIn the first phase (2010 – 2013) of the Cloud_cci project prototype retrieval versions have been established leading to preliminary results covering 2007, 2008, and 2009, herein referred to as demonstrator datasets. In Phase 2 (2014 – 2016) both retrieval schemes have been substantially improved enhancing the data quality of the cloud products spanning the time period from Jan 1st 1982 to Dec 31st 2014.\r\n\r\nConsiderations for climate applications:\r\nDue to the short period (i.e. 3 years) of the current available demonstrator datasets, it is not possible to perform long-term data comparisons or to support long-term climate analysis.\r\n\r\nPlease be aware of the fact that by the end of 2016 at the latest these prototype datasets will be replaced by the complete multi-decadal Cloud_cci climatology (1982 – 2014) together with updated Product User Guide (PUG) and Product Validation and Intercomparison Report (PVIR) documents. \r\n\r\nWe would like to stress that one of the main objectives in the second phase of the Cloud_cci project has been the further development and improvement of both retrieval schemes and their processing systems. As a consequence, the quality and accuracy of the final cloud products have been considerably improved compared to the currently available demonstrator datasets.", "keywords": "ESA,Cloud, CCI, ECV", "publicationState": "published", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 30067, "uuid": "004fd44ff5124174ad3c03dd2c67d548", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud_cci): AVHRR-PM monthly gridded cloud properties, version 3.0", "abstract": "The Cloud_cci AVHRR-PMv3 dataset (covering 1982-2016) was generated within the Cloud_cci project, which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is one of the 6 datasets generated in Cloud_cci; all of them being based on passive-imager satellite measurements.\r\n\r\nThis dataset is based on measurements from AVHRR (onboard the NOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19 satellites) and contains a variety of cloud properties which were derived employing the Community Cloud retrieval for Climate (CC4CL; Sus et al., 2018; McGarragh et al., 2018) retrieval framework. The core cloud properties contained in the Cloud_cci AVHRR-PMv3 dataset are cloud mask/fraction, cloud phase, cloud top pressure/height/temperature, cloud optical thickness, cloud effective radius and cloud liquid/ice water path. Spectral cloud albedo is also included as experimental product. The cloud properties are available at different processing levels: This particular dataset contains Level-3C (monthly averages and histograms) data, while Level-3U (globally gridded, unaveraged data fields) is also available as a separate dataset. Pixel-based uncertainty estimates come along with all properties and have been propagated into the Level-3C data. \r\n\r\nThe data in this dataset are a subset of the AVHRR-PM L3C / L3U cloud products version 3.0 dataset produced by the ESA Cloud_cci project available from https://dx.doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V003. To cite the full dataset, please use the following citation: Stengel, Martin; Sus, Oliver; Stapelberg, Stefan; Finkensieper, Stephan; Würzler, Benjamin; Philipp, Daniel; Hollmann, Rainer; Poulsen, Caroline (2019): ESA Cloud Climate Change Initiative (ESA Cloud_cci) data: Cloud_cci AVHRR-PM L3C/L3U CLD_PRODUCTS v3.0, Deutscher Wetterdienst (DWD), DOI:10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V003." }, { "ob_id": 20379, "uuid": "47e5104f93764a0b997d8b7976613e97", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud_cci): AVHRR-PM monthly gridded cloud properties, version 2.0", "abstract": "The Cloud_cci AVHRR-PM dataset was generated within the Cloud_cci project (http://www.esa-cloud-cci.org) which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is one of the 6 datasets generated in Cloud_cci; all of them being based on passive-imager satellite measurements. This dataset is based on AVHRR (onboard NOAA-7, NOAA-9, NOAA-11, NOAA-14, NOAA-16, NOAA-18, NOAA-19) measurements and contains a variety of cloud properties which were derived employing the Community Cloud retrieval for Climate (CC4CL) retrieval system. The core cloud properties contained in the Cloud_cci AVHRR-PM dataset are cloud mask/fraction, cloud phase, cloud top pressure/height/temperature, cloud optical thickness, cloud effective radius and cloud liquid/ice water path. Spectral cloud albedo is also included as experimental product. Level-3C product files contain monthly averages and histograms of the mentioned cloud properties together with propagated uncertainty measures." }, { "ob_id": 20376, "uuid": "1ea3b2e391e4441daa57100a02b98691", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud_cci): ATSR2-AASTR monthly gridded cloud properties, version 2.0", "abstract": "The Cloud_cci ATSR2-AATSR dataset was generated within the Cloud_cci project (http://www.esa-cloud-cci.org) which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is one of the 6 datasets generated in Cloud_cci; all of them being based on passive-imager satellite measurements. This dataset is based on ATSR2 and AATSR (onboard ERS2 and ENVISAT) measurements and contains a variety of cloud properties which were derived employing the Community Cloud retrieval for Climate (CC4CL) retrieval system. The core cloud properties contained in the Cloud_cci ATSR2-AATSR dataset are cloud mask/fraction, cloud phase, cloud top pressure/height/temperature, cloud optical thickness, cloud effective radius and cloud liquid/ice water path. Spectral cloud albedo is also included as experimental product. Level-3C product files contain monthly averages and histograms of the mentioned cloud properties together with propagated uncertainty measures." }, { "ob_id": 30055, "uuid": "326bf808aedd41fd85594fc06678d20a", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud_cci): ATSR2-AATSR monthly gridded cloud properties, version 3.0", "abstract": "The Cloud_cci ATSR2-AATSRv3 dataset (covering 1995-2012) was generated within the Cloud_cci project, which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is one of the 6 datasets generated in Cloud_cci; all of them being based on passive-imager satellite measurements. \r\n\r\nThis dataset is based on measurements from the ATSR2 and AATSR instruments (onboard the ERS2 and ENVISAT satellites) and contains a variety of cloud properties which were derived employing the Community Cloud retrieval for Climate (CC4CL; Sus et al., 2018; McGarragh et al., 2018) retrieval framework. The core cloud properties contained in the Cloud_cci ATSR2-AATSRv3 dataset are cloud mask/fraction, cloud phase, cloud top pressure/height/temperature, cloud optical thickness, cloud effective radius and cloud liquid/ice water path. Spectral cloud albedo is also included as experimental product. The cloud properties are available at different processing levels: This particular dataset contains Level-3C (monthly averages and histograms) data, while Level-3U (globally gridded, unaveraged data fields) is also available as a separate dataset. Pixel-based uncertainty estimates come along with all properties and have been propagated into the Level-3C data. \r\n\r\nThe data in this dataset are a subset of the ATSR2-AATSR L3C / L3U cloud products version 3.0 dataset produced by the ESA Cloud_cci project available from https://dx.doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003. \r\nTo cite the full dataset, please use the following citation: Poulsen, Caroline; McGarragh, Greg; Thomas, Gareth; Stengel, Martin; Christensen, Matthew; Povey, Adam; Proud, Simon; Carboni, Elisa; Hollmann, Rainer; Grainger, Don (2019): ESA Cloud Climate Change Initiative (ESA Cloud_cci) data: Cloud_cci ATSR2-AATSR L3C/L3U CLD_PRODUCTS v3.0, Deutscher Wetterdienst (DWD) and Rutherford Appleton Laboratory (Dataset Producer), DOI:10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V003" }, { "ob_id": 30059, "uuid": "fb3750f5b2544403873f8788b3ed7817", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud CCI): AVHRR-AM monthly gridded cloud properties, version 3.0", "abstract": "The Cloud_cci AVHRR-AMv3 dataset (covering 1991-2016) was generated within the Cloud_cci project which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is one of the 6 datasets generated in Cloud_cci; all of them being based on passive-imager satellite measurements. \r\n\r\nThis dataset is based on AVHRR (onboard NOAA-12, NOAA-15, NOAA-17, Metop-A) measurements and contains a variety of cloud properties which were derived employing the Community Cloud retrieval for Climate (CC4CL; Sus et al., 2018; McGarragh et al., 2018) retrieval framework. The core cloud properties contained in the Cloud_cci AVHRR-AMv3 dataset are cloud mask/fraction, cloud phase, cloud top pressure/height/temperature, cloud optical thickness, cloud effective radius and cloud liquid/ice water path. Spectral cloud albedo is also included as experimental product. The cloud properties are available at different processing levels: This particular dataset contains Level-3C (monthly averages and histograms) data, while Level-3U (globally gridded, unaveraged data fields) is also available as a separate dataset. Pixel-based uncertainty estimates come along with all properties and have been propagated into the Level-3C data. \r\n\r\nThe data in this dataset are a subset of the AVHRR-AM L3C / L3U cloud products version 3.0 dataset produced by the ESA Cloud_cci project available from https://dx.doi.org/doi:10.5676/DWD/ESA_Cloud_cci/AVHRR-AM/V003. To cite the full dataset, please use the following citation: Stengel, Martin; Sus, Oliver; Stapelberg, Stefan; Finkensieper, Stephan; Würzler, Benjamin; Philipp, Daniel; Hollmann, Rainer; Poulsen, Caroline (2019): ESA Cloud Climate Change Initiative (ESA Cloud_cci) data: Cloud_cci AVHRR-AM L3C/L3U CLD_PRODUCTS v3.0, Deutscher Wetterdienst (DWD), DOI:10.5676/DWD/ESA_Cloud_cci/AVHRR-AM/V003." }, { "ob_id": 20381, "uuid": "f1ab07b5292f4813bd3090b51d270aa8", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud_cci): MODIS-TERRA monthly gridded cloud properties, version 2.0", "abstract": "The Cloud_cci MODIS-Terra dataset was generated within the Cloud_cci project (http://www.esa-cloud-cci.org) which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is one of the 6 datasets generated in Cloud_cci; all of them being based on passive-imager satellite measurements. This dataset is based on MODIS (onboard Terra) measurements and contains a variety of cloud properties which were derived employing the Community Cloud retrieval for Climate (CC4CL) retrieval system. The core cloud properties contained in the Cloud_cci MODIS-Terra dataset are cloud mask/fraction, cloud phase, cloud top pressure/height/temperature, cloud optical thickness, cloud effective radius and cloud liquid/ice water path. Spectral cloud albedo is also included as experimental product. Level-3C product files contain monthly averages and histograms of the mentioned cloud properties together with propagated uncertainty measures." }, { "ob_id": 20378, "uuid": "d7237ccf38f048debdbeae3f1f253618", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud_cci): AVHRR-AM monthly gridded cloud properties, version 2.0", "abstract": "The Cloud_cci AVHRR-AM dataset was generated within the Cloud_cci project (http://www.esa-cloud-cci.org) which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is one of the 6 datasets generated in Cloud_cci; all of them being based on passive-imager satellite measurements. This dataset is based on AVHRR (onboard NOAA-12, NOAA-15, NOAA-17, Metop-A) measurements and contains a variety of cloud properties which were derived employing the Community Cloud retrieval for Climate (CC4CL) retrieval system. The core cloud properties contained in the Cloud_cci AVHRR-AM dataset are cloud mask/fraction, cloud phase, cloud top pressure/height/temperature, cloud optical thickness, cloud effective radius and cloud liquid/ice water path. Spectral cloud albedo is also included as experimental product. Level-3C product files contain monthly averages and histograms of the mentioned cloud properties together with propagated uncertainty measures.\r\n\r\nThe L3C data here form a subset of the AVHRR-AM products produced by the Cloud CCI, and which are collectively referenced by the following DOI: Stengel, Martin; Sus, Oliver; Stapelberg, Stefan; Schlundt, Cornelia; Poulsen, Caroline; Hollmann, Rainer (2017): ESA Cloud Climate Change Initiative (ESA Cloud_cci) data: Cloud_cci AVHRR-AM L3C/L3U CLD_PRODUCTS v2.0, Deutscher Wetterdienst (DWD), DOI:10.5676/DWD/ESA_Cloud_cci/AVHRR-AM/V002" }, { "ob_id": 20380, "uuid": "7dd46ee62153409f8e1b2b7b251177c1", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud_cci): MODIS-AQUA monthly gridded cloud properties, version 2.0", "abstract": "The Cloud_cci MODIS-Aqua dataset was generated within the Cloud_cci project (http://www.esa-cloud-cci.org) which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is one of the 6 datasets generated in Cloud_cci; all of them being based on passive-imager satellite measurements. This dataset is based on MODIS (onboard Aqua) measurements and contains a variety of cloud properties which were derived employing the Community Cloud retrieval for Climate (CC4CL) retrieval system. The core cloud properties contained in the Cloud_cci MODIS-Aqua dataset are cloud mask/fraction, cloud phase, cloud top pressure/height/temperature, cloud optical thickness, cloud effective radius and cloud liquid/ice water path. Spectral cloud albedo is also included as experimental product. Level-3C product files contain monthly averages and histograms of the mentioned cloud properties together with propagated uncertainty measures." }, { "ob_id": 20377, "uuid": "2f423ac3eb244567a12b283894b869de", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud_cci): MERIS+AATSR monthly gridded cloud properties, Version 2.0", "abstract": "The Cloud_cci MERIS+AATSR dataset was generated within the Cloud_cci project (http://www.esa-cloud-cci.org) which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is one of the 6 datasets generated in Cloud_cci; all of them being based on passive-imager satellite measurements. This dataset is based on MERIS and AATSR (onboard ENVISAT) measurements and contains a variety of cloud properties which were derived employing the Freie Universität Berlin AATSR MERIS Cloud (FAME-C) retrieval system. The core cloud properties contained in the Cloud_cci MERIS+AATSR dataset are cloud mask/fraction, cloud phase, cloud top pressure/height/temperature, cloud optical thickness, cloud effective radius and cloud liquid/ice water path. Spectral cloud albedo is also included as experimental product. Level-3C product files contain monthly averages and histograms of the mentioned cloud properties together with propagated uncertainty measures." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 50865, 50867, 50868, 75217, 105397, 105424, 105448, 54167, 75218, 75238, 75228, 75224, 75230, 75234, 75232, 75235, 75225, 75229, 75239, 75226, 75222, 75227, 75221, 75220, 75237, 75231, 75219, 75223, 75236, 75233 ], "onlineresource_set": [ 7359, 7350 ], "project_set": [ 13339 ] }, { "ob_id": 13300, "uuid": "b05d478170e14356bbe2c3cce3f7bf67", "short_code": "coll", "title": "ESA Glaciers Climate Change Initiative (Glaciers CCI) Dataset Collection", "abstract": "The ESA Glaciers Climate Change Initiative (CCI) dataset consists of data produced by the ESA CCI Glaciers Project. The main objective of the Glaciers_cci project is to contribute to the efforts of creating a globally complete and detailed glacier inventory as requested in action T2.1 by GCOS (2006). This activity has two major parts: One is data creation (glacier outlines) in selected and currently still missing key regions, and the other one is in establishing a more consistent framework for glacier entity identification to enhance the integrity and error characterization of the available data sets. As meltwater from glaciers and ice caps provide a substantial contribution to global sea-level rise, the project will also create two additional products in selected key regions, elevation changes and velocity fields", "keywords": "ESA, CCI, Glaciers", "publicationState": "published", "dataPublishedTime": "2016-04-12T14:26:41", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 13302, "uuid": "5daf1ff8dd2941a18bb4120ceea95721", "short_code": "ob", "title": "ESA Glaciers Climate Change Initiative (Glaciers CCI): Randolph Glacier Inventory gridded data product, v5.0", "abstract": "The Randolph Glacier Inventory (RGI 5.0) is a global inventory of glacier outlines. It is supplemental to the Global Land Ice Measurements from Space initiative (GLIMS). Production of the RGI was motivated by the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Future updates will be made to the RGI and the GLIMS Glacier Database in parallel during a transition period. As all these data are incorporated into the GLIMS Glacier Database and as download tools are developed to obtain GLIMS data in the RGI data format, the RGI will evolve into a downloadable subset of GLIMS, offering complete one-time coverage, version control, and a standard set of attributes.\r\n\r\nThe product provided here is a converted raster version of the Randolph Glacier Inventory (RGI 5.0) data, provided by the ESA Climate Change Initiative (CCI) Glaciers project. The CCI Glaciers project is one of a number of contributors to the RGI 5.0 dataset. For more details, and for a complete list of contributors, please see the RGI 5.0 Technical Report in the Documentation section below.\r\n\r\nThe following reference is recommended when citing RGI version 5.0:\r\nArendt, A., A. Bliss, T. Bolch, J.G. Cogley, A.S. Gardner, J.-O. Hagen, R. Hock, M. Huss, G. Kaser, C. Kienholz, W.T. Pfeffer, G. Moholdt, F. Paul, V. Radić, L. Andreassen, S. Bajracharya, N.E. Barrand, M. Beedle, E. Berthier, R. Bhambri, I. Brown, E. Burgess, D. Burgess, F. Cawkwell, T. Chinn, L. Copland, B. Davies, H. De Angelis, E. Dolgova, L. Earl, K. Filbert, R. Forester, A.G. Fountain, H. Frey, B. Giffen, N. Glasser, W.Q. Guo, S. Gurney, W. Hagg, D. Hall, U.K. Haritashya, G. Hartmann, C. Helm, S. Herreid, I. Howat, G. Kapustin, T. Khromova, M. König, J. Kohler, D. Kriegel, S. Kutuzov, I. Lavrentiev, R. LeBris, S.Y. Liu, J. Lund, W. Manley, R. Marti, C. Mayer, E.S. Miles, X. Li, B. Menounos, A. Mercer, N. Mölg, P. Mool, G. Nosenko, A. Negrete, T. Nuimura, C. Nuth, R. Pettersson, A. Racoviteanu, R. Ranzi, P. Rastner, F. Rau, B. Raup, J. Rich, H. Rott, A. Sakai, C. Schneider, Y. Seliverstov, M. Sharp, O. Sigurðsson, C. Stokes, R.G. Way, R. Wheate, S. Winsvold, G. Wolken, F. Wyatt, N. Zheltyhina, 2015, Randolph Glacier Inventory – A Dataset of Global Glacier Outlines: Version 5.0. Global Land Ice Measurements from Space, Boulder Colorado, USA. Digital Media." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 54251, 50874, 50875, 50876, 105396, 105423, 105447, 54250, 50877 ], "onlineresource_set": [ 7357, 7356 ], "project_set": [ 13301 ] }, { "ob_id": 13330, "uuid": "f1a4a1d1208244c682603502d554bc12", "short_code": "coll", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Version 1.0 Data", "abstract": "A collection of Version 1.0 datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI). The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490 nm. Information on uncertainties is also provided.\r\n\r\nThis dataset collectionrefers to the Version 1.0 data products products held in the CEDA archive and available from ftp://anon-ftp.ceda.ac.uk/neodc/esacci/ocean_colour/data/v1-release . Links to the individual datasets that make up this collection are given in the record below. \r\n\r\n Note, these data have now been superseded and later versions of the dataset are available", "keywords": "ESA, Ocean Colour, CCI, ECV", "publicationState": "citable", "dataPublishedTime": null, "doiPublishedTime": "2016-12-20T17:56:08", "dontHarvestFromProjects": true, "imageDetails": [ 147 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 13363, "uuid": "a70b70e7635342cdaa4451c17fd4bd87", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global ocean colour data products gridded on a sinusoidal projection (All Products), Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 1.0 generated ocean colour products on a sinusoidal projection at 4 km spatial resolution and at a daily time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)" }, { "ob_id": 13346, "uuid": "45278227a3804ab2a601fa2d3b1ec2fd", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global dataset of inherent optical properties (IOP) gridded on a geographic projection, Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 1.0 inherent optical properties (IOP) product (in mg/m3) on a geographic projection at approximately 4 km spatial resolution and at a daily time resolution. Note, this dataset is also included in the 'All Products' dataset.\r\n\r\nThe inherent optical properties (IOP) dataset consists of the total absorption and particle backscattering coefficients, and, additionally, the fraction of detrital & dissolved organic matter absorption and phytoplankton absorption. The total absorption (units m-1), the total backscattering (m-1), the absorption by detrital and coloured dissolved organic matter, the backscattering by particulate matter, and the absorption by phytoplankton share the same spatial resolution of ~4 km. The values of IOP are reported for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm). \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n" }, { "ob_id": 13337, "uuid": "47e646778ba44138846306789e3a3054", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Monthly global ocean colour data products gridded on a geographic projection (All Products), Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 1.0 generated ocean colour products on a geographic projection at 4 km spatial resolution and at a monthly time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)" }, { "ob_id": 13359, "uuid": "be3edba3aefd42ebbebea241a71d608e", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Monthly global ocean colour data products gridded on a sinusoidal projection (All Products), Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 1.0 generated ocean colour products on a sinusoidal projection at 4 km spatial resolution and at a monthly time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)" }, { "ob_id": 13355, "uuid": "5ce3092e823a403dad8122ff8ec93612", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global attenuation coefficient for downwelling irradiance (Kd490) gridded on a sinusoidal projection, Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 1.0 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a sinusoidal projection at approximately 4 km spatial resolution and at a daily time resolution. It is computed from the Ocean Colour CCI Version 1 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, this dataset is also contained within the 'All Products' dataset.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n" }, { "ob_id": 13333, "uuid": "0f29b5f7ca774bd590a2ade5f94e9ddb", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global ocean colour data products gridded on a geographic projection (All Products), Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 1.0 generated ocean colour products on a geographic projection at 4 km spatial resolution and at a daily time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n" }, { "ob_id": 13357, "uuid": "f7d1890865bb47b383a013cd9fede042", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global chlorophyll-a data products gridded on a sinusoidal projection, Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 1.0 chlorophyll-a product (in mg/m3) on a sinusoidal projection at 4 km spatial resolution and at a daily time resolution. Note, this dataset is also included in the 'All Products' dataset.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n" }, { "ob_id": 13351, "uuid": "70be18893edb498785e22bed288cfd54", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global remote sensing reflectance gridded on a geographic projection, Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 1.0 Remote Sensing Reflectance product on a geographic projection at approximately 4 km spatial resolution and at a daily time resolution. Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data. Note, this dataset is also contained within the 'All Products' dataset.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection).\r\n" }, { "ob_id": 13342, "uuid": "22c0948d2c5b4f4dbf9606541a671274", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Yearly global ocean colour data products gridded on a geographic projection (All Products), Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 1.0 generated ocean colour products on a geographic projection at 4 km spatial resolution and at a yearly time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320." }, { "ob_id": 13335, "uuid": "7f31695e4b6d4ff5af71ccae213c910b", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): 8-day global ocean colour data products gridded on a geographic projection (All Products), Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 1.0 generated ocean colour products on a geographic projection at 4 km spatial resolution and at an 8-day time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n" }, { "ob_id": 13344, "uuid": "a526fdfb91954f1ab4360978e86f3b2b", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global chlorophyll-a data products gridded on a geographic projection, Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 1.0 chlorophyll-a product (in mg/m3) on a geographic projection at 4 km spatial resolution and at a daily time resolution. Note, this dataset is also included in the 'All Products' dataset. \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n" }, { "ob_id": 13349, "uuid": "06e4e74e2cb24ec582cdce05e2ff1c87", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global attenuation coefficient for downwelling irradiance (Kd490) gridded on a geographic projection, Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 1.0 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a geographic projection at approximately 4 km spatial resolution and at a daily time resolution. It is computed from the Ocean Colour CCI Version 1 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, this dataset is also contained within the 'All Products' dataset.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection).\r\n" }, { "ob_id": 13353, "uuid": "a456b6c4c290453d8bb436e45e616f78", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global remote sensing reflectance gridded on a sinusoidal projection, Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 1.0 Remote Sensing Reflectance product on a sinusoidal projection at approximately 4 km spatial resolution and at a daily time resolution. Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data. Note, this dataset is also contained within the 'All Products' dataset.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n" }, { "ob_id": 13361, "uuid": "ea0729b565014b08b5d5b5efe499edba", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): 8-day global ocean colour data products gridded on a sinusoidal projection (All Products), Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 1.0 generated ocean colour products on a sinusoidal projection at 4 km spatial resolution and at an 8-day time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a sinusoidal projection.)" } ], "identifier_set": [ 9009 ], "responsiblepartyinfo_set": [ 50948, 50949, 50950, 76559, 141859, 141860, 141861, 52473, 76585, 76611, 76637, 76663, 76689, 76715, 76741, 76767, 76793, 76819, 76845, 76871, 76897, 76923, 76949, 76975, 77001, 77027, 77053, 77079, 77105, 77131, 77157, 77183, 77209, 77235, 77261, 77287, 77313, 77339, 77365, 77391, 77417, 77443, 77469, 77495, 77521, 77547, 77573, 77599, 77625, 77651, 77677, 77703, 77729, 77755, 77781, 77807, 77833, 77859, 77885, 77911, 77937, 77963, 77989, 78015, 78041, 78067, 78093, 78119, 78145, 78171, 78197, 78223, 78249, 78275 ], "onlineresource_set": [ 7445, 7437, 7440, 7441, 87711 ], "project_set": [ 13365 ] }, { "ob_id": 13340, "uuid": "8e1662bfe93d4720adfcfd8925862bad", "short_code": "coll", "title": "ESA Aerosol Climate Change Initiative (CCI) Dataset Collection", "abstract": "Datasets of aerosol products produced by the Aerosol project within the ESA Climate Change Initiative (CCI). \r\n\r\nThe primary products produced in the aerosol_cci project are level 2 (daily 10km and 50km pixel products) and level 3 (aggregated monthly gridded datasets) multi-spectral AOD and associated probabilities of pre-defined aerosol types for a number of European satellite instruments (ATSR-2, AATSR, MERIS, POLDER, GOME, SCIAMACHY, OMI, GOME-2, AVHRR/3); stratospheric aerosols are observed with GOMOS (and tested for SCIAMACHY).", "keywords": "ESA, Aerosol, CCI, ECV", "publicationState": "published", "dataPublishedTime": "2015-12-18T06:30:04", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 147 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 13304, "uuid": "c1d5e11760e94c85a738ff22c36ef4b9", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 2 aerosol products from AATSR (SU Algorithm), Version 4.2", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 2 aerosol products from AATSR, using the Swansea University (SU) algorithm, version 4.2. \r\n\r\nFor further details about these data products please see the documentation." }, { "ob_id": 19106, "uuid": "828e521e9ebe4df896341736bff0f369", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from the Multi-Sensor UVAI algorithm (MS UVAI), Version 1.5.7", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises Level 3 Absorbing Aerosol Index (AAI) products, using the Multi-Sensor UVAI algorithm, Version 1.5.7. L3 products are provided as Daily and Monthly gridded products as well as a monthly climatology. \r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 13310, "uuid": "57b63f8d9e6f478aaf8cd35e7a6f1f44", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 2 aerosol products from ATSR2 (SU algorithm), Version 4.2", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 2 aerosol products from ATSR-2, using the Swansea University (SU) algorithm, version 4.2. \r\n\r\nFor further details about these data products please see the documentation." }, { "ob_id": 19114, "uuid": "59f3a38819e140b49ffe46f32176709e", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 2 aerosol products from AATSR (SU Algorithm), Version 4.21", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 2 aerosol products from AATSR, using the Swansea University (SU) algorithm, version 4.21. \r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 13316, "uuid": "67a411e3fa24477eab54500519af4514", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol monthly products from GOMOS (AERGOM algorithm), Version 2.1", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol monthly products from GOMOS, using the AERGOM algorithm, version 2.1 and was produced by BIRA (Belgian Institute for Space Aeronomy). \r\n\r\nThe data are stored as monthly averages and standard deviations of a range of aerosol variables, on global 2.5 degree x 10 degree latitutude/longitude grids, and in NetCDF format. The horizontal resolution is 0.5km. \r\n\r\nThe variables included are: Stratospheric Aerosol Optical Depth (AOD), Angstrom coefficient, extinction profile. \r\n\r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 19118, "uuid": "411a1599c96e43659a8141749c277ef4", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from AATSR (ORAC algorithm), Version 3.02", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol products from AATSR, using the ORAC algorithm, version 3.02. Both daily and monthly gridded products are available\r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 13305, "uuid": "1e3e5f0f0f53409b838e5dbfe99a3b01", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol daily products from AATSR (SU algorithm), Version 4.2", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol daily products from AATSR, using the Swansea University (SU) algorithm, version 4.2. \r\n\r\nFor further details about these data products please see the documentation." }, { "ob_id": 13308, "uuid": "696aa71b351842a1b6a65d1f930c2600", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol monthly products from AATSR (SU algorithm), Version 4.2", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol monthly products from AATSR, using the Swansea University (SU) algorithm, version 4.2. \r\n\r\nFor further details about these data products please see the documentation." }, { "ob_id": 19112, "uuid": "91a7029627754d60912e58255b686836", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from GOMOS (AERGOM algorithm), Version 2.19", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol monthly products from GOMOS, using the AERGOM algorithm, version 2.19 and was produced by BIRA (Belgian Institute for Space Aeronomy). \r\n\r\nThe data are stored as 5 day averages and standard deviations of a range of aerosol variables, on global 2.5 degree x 10 degree latitutude/longitude grids, and in NetCDF format. The horizontal resolution is 0.5km. \r\n\r\nThe variables included are: Stratospheric Aerosol Optical Depth (AOD), Angstrom coefficient, extinction profile. \r\n\r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 19122, "uuid": "77f30941f1b54120a290ac9a191d22bd", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 2 aerosol products from AATSR (ADV Algorithm), Version 2.30", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 2 aerosol products from AATSR, using the ADV algorithm, version 2.30. \r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 19126, "uuid": "b6751acb59b242bfa33af689c4778abd", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 2 aerosol products from ATSR2 (ORAC algorithm), Version 3.02", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 2 aerosol products from ATSR-2, using the ORAC algorithm, version 3.02. \r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 13318, "uuid": "1657cead89a343ab9b95b1983f07a1a1", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): aerosol climatology images from MS UVAI, Version 1.4.7", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises images of Absorbing Aerosol Index (AAI) climatology, using the Multi-Sensor UVAI algorithm, Version 1.4.7. \r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 13320, "uuid": "188641a64d634827b2a40aff009a702b", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): aerosol monthly images (MS UVAI algorithm), Version 1.4.7", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises monthly images of Absorbing Aerosol Index (AAI), using the Multi-Sensor UVAI algorithm, Version 1.4.7. \r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 19828, "uuid": "a6efcb0868664248b9cb212aba44313d", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 2 aerosol products from MERIS (ALAMO algorithm), Version 2.2", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 2 aerosol products from MERIS for 2008, using the ALAMO algorithm, version 2.2. The data have been provided by Hygeos.\r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 19130, "uuid": "6609ab72c29d49a4b45223cd15104fdd", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from ATSR2 (SU algorithm), Version 4.21", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol products from ATSR-2, using the Swansea University (SU) algorithm, version 4.2. Both daily and monthly gridded products are available.\r\n\r\nFor further details about these data products please see the documentation." }, { "ob_id": 13328, "uuid": "337661f6cb6a438ea305869ae00463fb", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol monthly products (MS UVAI algorithm), Version 1.4.7", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises monthly products of Absorbing Aerosol Index (AAI), produced using the Multi-Sensor UVAI algorithm, Version 1.4.7. \r\n\r\nFor further details about these data products please see the documentation section." }, { "ob_id": 19120, "uuid": "c41e248db8d74e22be25ce6b79e04bb6", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 2 aerosol products from AATSR (ORAC Algorithm), Version 3.02", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 2 aerosol products from AATSR, using the ORAC algorithm, version 3.02. \r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 19831, "uuid": "11c5f6df1abc41968d0b28fe36393c9d", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from MERIS (ALAMO algorithm), Version 2.2", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol daily and monthly gridded products from MERIS for 2008, using the ALAMO algorithm, version 2.2. The data have been provided by Hygeos.\r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 13312, "uuid": "54bff8b538ac441b80f3e35059f11f0f", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol daily products from ATSR2 (SU algorithm), Version 4.2", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol daily products from ATSR-2, using the Swansea University (SU) algorithm, version 4.2. \r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 13326, "uuid": "f15aa17184884515a860a92634aa73ff", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol daily products (MS UVAI algorithm), Version 1.4.7", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises daily Level 3 Absorbing Aerosol Index (AAI) products, using the Multi-Sensor UVAI algorithm, Version 1.4.7. \r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 19136, "uuid": "ab9f7510268840ef9ec3e9692a0f129d", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 2 aerosol products from ATSR2 (SU algorithm), Version 4.21", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 2 aerosol products from ATSR-2, using the Swansea University (SU) algorithm, version 4.21. \r\n\r\nFor further details about these data products please see the documentation." }, { "ob_id": 19132, "uuid": "5673d414c1094d9ab16a7f106b1c6b36", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from ATSR2 (ORAC algorithm), Version 3.02", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol products from ATSR-2, using the ORAC algorithm, version 3.02. Both daily and monthly gridded products are available\r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 19134, "uuid": "c4d4c347455341aa938bedfefa2964a1", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from ATSR2 (ADV algorithm), Version 2.30", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol products from ATSR-2, using the ADV algorithm, version 2.30. Both daily and monthly gridded products are available\r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 13322, "uuid": "4724ecae7b104fbfb678e3aa7a630553", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol climatology products (MS UVAI algorithm), Version 1.4.7", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises monthly Absorbing Aerosol Index (AAI) climatology products, using the Multi-Sensor UVAI algorithm, Version 1.4.7. \r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 19116, "uuid": "5dd3881e89c8419bbdba4ab06aa91112", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from AATSR (SU algorithm), Version 4.21", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol products from AATSR, using the Swansea University (SU) algorithm, version 4.21. Both daily and monthly gridded products are available.\r\n\r\nFor further details about these data products please see the documentation." }, { "ob_id": 19128, "uuid": "9659f50c3cc34a1e9f017ccba69dbe5c", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 2 aerosol products from ATSR2 (ADV algorithm), Version 2.30", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 2 aerosol products from ATSR-2, using the ADV algorithm, version 2.30. \r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 19108, "uuid": "62f131e965914db6aaf685d89efffa3a", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Images of Aerosol Absorbing Index produced by the Multi-Sensor UVAI (MS UVAI) algorithm, Version 1.5.7", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises images of Absorbing Aerosol Index (AAI) products, using the Multi-Sensor UVAI algorithm, Version 1.5.7. Images are available for monthly and climatology products.\r\n\r\nFor further details about these data products please see the linked documentation." }, { "ob_id": 13314, "uuid": "62fae7fa0c33421db2fef0d65e374779", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol monthly products from ATSR2 (SU algorithm), Version 4.2", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol monthly products from ATSR-2, using the Swansea University (SU) algorithm, version 4.2. \r\n\r\nFor further details about these data products please see the documentation." }, { "ob_id": 19124, "uuid": "baae936d9ccf477e86fb1ed88df5a70f", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from AATSR (ADV algorithm), Version 2.30", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol products from AATSR, using the ADV algorithm, version 2.30. Both daily and monthly gridded products are available\r\n\r\nFor further details about these data products please see the linked documentation." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 50973, 50974, 50975, 50977, 105395, 105422, 105446, 54516, 50976, 50972 ], "onlineresource_set": [ 7493, 7511, 7495, 7494 ], "project_set": [ 13341 ] }, { "ob_id": 13521, "uuid": "f579035b3c954475922e4b13705a7669", "short_code": "coll", "title": "HadISD: global sub-daily station data for climate extremes", "abstract": "HadISD is a station based dataset comprising 6103 stations covering 1973-present. These stations are a subset of the stations available in the Integrated Surface Database (ISD), and are ones selected to be those most useful for climate studies (long records and high reporting frequency). Individual stations within the ISD were composited when it was appropriate to do so to improve the coverage.\r\n \r\nHadISD is a multi-variate dataset, where the following fields are available: temperature, dewpoint temperature, sea-level pressure, wind speed, wind direction and cloud data (total, low, mid and high levels). These variables are all quality controlled using an automatic suite of tests, the code for which is available on request. The QC tests were designed to remove bad data whilst keeping true extremes. A number of other variables are also carried through to the final NetCDF files, but have not been quality controlled (e.g. precipitation period, precipitation depth, sunshine duration).", "keywords": "HadOBS, HadISD, temperature, dew point, sea-level pressure, wind speed, wind direction, cloud data", "publicationState": "published", "dataPublishedTime": "2016-07-28T07:33:46", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 39557, "uuid": "60c28523d8c54c58831b2608164cf35e", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2022, v3.3.0.2022f", "abstract": "This is version v3.3.0.2022f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data.\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20230101_v3.3.1.2022f.nc. The station codes can be found under the docs tab. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note.\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 34674, "uuid": "f0f32cf3e7884950a585b7a4fda9dcb6", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1973-2015, v1.0.4.2015f", "abstract": "This is version 1.0.4.2015f of HadISD (27 April 2015) the Met Office Hadley Centre's global sub-daily data, extending v1.0.3.2014f to span 1/1/1973 - 31/12/2015. \r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed in the quality control process are also provided along with a station listing with IDs, names and location information. The data are provided as one NetCDF file per station. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20151231_v1-0-4-2015f.nc (note, the filenames incorrectly show the start date of 19310101, instead of 19730101). The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Climate of the Past\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 20357, "uuid": "de98d82f34d14e888bde6d56aaf5420c", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2016, v2.0.1.2016p", "abstract": "This is version 2.0.1.2016p of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data that extends HadISD v2.0.0.2015p to span 1931-2016 and includes an increase in the number of stations and an updated methodology. \r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20151231_v2-0-1-2016p.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 32100, "uuid": "f5a674c74cdd427594b6f3793b536cd0", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2020, v3.1.1.2020f", "abstract": "This is version 3.1.1.2020f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data that extends HadISD v3.1.0.2019f to include 2020 and so spans 1931-2020.\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20210101_v3-1-1-2020f.nc. The station codes can be found under the docs tab. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note.\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 30000, "uuid": "e488dccd09e1446d90978b75036475e2", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2019, v3.1.0.2019f", "abstract": "This is version 3.1.0.2019f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data that extends HadISD v3.0.0.2018f to include 2019 and so spans 1931-2019.\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20200101_v3-1-0-2019f.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note.\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 44902, "uuid": "f60cd72eae8b409fbfe4aa84aa04e97b", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2025, v3.4.3.2025f", "abstract": "This is the final version, v3.4.3.2025f, of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data. The parent dataset of HadISD, the Integrated Surface Database at NOAA, stopped being updated on 29th August 2025. Therefore there will be no further updates to this dataset, and the final year will remain incomplete, going up to 29th August 2025 only\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20250829_v3-4-3-2025f. The station codes can be found under the docs tab. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note.\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 20040, "uuid": "4c44bc7beac5428aa1af2f3aca1a2055", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1973-2013, v1.0.2.2013f", "abstract": "This is version 1.0.2.2013f of HadISD the Met Office Hadley Centre's global sub-daily data, extending v1.0.1.2012p to span 1/1/1973 - 31/12/2013. \r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19730101-20131231_v1-0-2-2013f.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 20041, "uuid": "c1b593ad0a9945e18fa8d975908f19f0", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2015, v2.0.0.2015p", "abstract": "This is version 2.0.0.2015p of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data that extends HadISD v1.0.4.2015p to span 1931-2015 and includes an increase in the number of stations and an updated methodology. \r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20151231_v2-0-0-2015p.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 25976, "uuid": "acee665e3e664a73b8ad247e99b343d5", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2017, v2.0.2.2017f", "abstract": "This is version 2.0.2.2017f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data that extends HadISD v2.0.1.2016p to include 2017 and so spans 1931-2017, it replaces the preliminary version (v2.0.2.2017p) as the ISD data for 2017 are now finalised.\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20171231_v2-0-2-2017f.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nFor a more detailed description of precipitation see: http://hadisd.blogspot.co.uk/2018/03/precipitation-in-hadisd.html\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 25833, "uuid": "3c67dfe728594fadabb920564af4df4a", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2017, v2.0.2.2017p", "abstract": "This is version 2.0.2.2017p of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data that extends HadISD v2.0.1.2016f to include 2017 and so spans 1931-2017. These data include an update to the station selected and contain 8103 stations. These are the preliminary data for this version, a finalised version will be released in a few months with any station updates.\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20171231_v2-0-2-2017p.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 19173, "uuid": "7b6993cbf7ec45f9ad01b86bed537e4c", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1973-2015, v1.0.4.2015p", "abstract": "This is version 1.0.4.2015p of HadISD (27 April 2015) the Met Office Hadley Centre's global sub-daily data, extending v1.0.3.2014f to span 1/1/1973 - 31/12/2015. \r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, their quality and completness cannot be guaranteed. Quality control flags and data values which have been removed in the quality control process are also provided along with a station listing with IDs, names and location information. The data are provided as one NetCDF file per station. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20151231_v1-0-4-2015p.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Climate of the Past\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 13557, "uuid": "229b53d2e44741ecbe70ba6299875a30", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1973-2014, v1.0.3.2014f", "abstract": "This is version 1.0.3.2014f of HadISD (27 April 2015) the Met Office Hadley Centre's global sub-daily data, extending v1.0.2.2013f to span 1/1/1973 - 31/12/2014.\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19730101-20141231_v1-0-3-2014f.nc T. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 20034, "uuid": "522c2801b6994745a32b6b63a03891f0", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1973-2011, v1.0.0.2011f", "abstract": "This is version 1.0.0.2011f of HadISD the Met Office Hadley Centre's global sub-daily data spanning 1/1/1973 - 31/12/2011. \r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19730101-20111231_v1-0-0-2011f.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1" }, { "ob_id": 23991, "uuid": "aeedfad6a2f345a8a0b50f40f4c0787f", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2016, v2.0.1.2016f", "abstract": "This is version 2.0.1.2016f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data that extends HadISD v2.0.0.2015p to span 1931-2016 and includes an increase in the number of stations and an updated methodology and is the final version of the 2016 data. \r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20151231_v2-0-1-2016p.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 41388, "uuid": "b82b58d085d0433b821f4ae31cb608de", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2023, v3.4.0.2023f", "abstract": "This is version v3.4.0.2023f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data.\r\n\r\nThis update (v3.4.0.2023f) to HadISD corrects a long-standing bug which was discovered in autumn 2023 whereby the neighbour checks (and associated [un]flagging for some other tests) were not being implemented. For more details see the posts on the HadISD blog: https://hadisd.blogspot.com/2023/10/bug-in-buddy-checks.html & https://hadisd.blogspot.com/2024/01/hadisd-v3402023f-future-look.html\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20240101_v3.4.1.2023f.nc. The station codes can be found under the docs tab. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note.\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 34664, "uuid": "5fb94c8e37f64c95b671278b0e55cdd4", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2021, v3.2.0.2021f", "abstract": "This is version v3.2.0.2021f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data.\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20220101_v3.2.1.2021f.nc. The station codes can be found under the docs tab. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note.\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 27098, "uuid": "61392a37ab614f349a4c20df4d08871c", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2018, v3.0.0.2018f", "abstract": "This is version 3.0.0.2018f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data that extends HadISD v2.0.2.2017f to include 2018 and so spans 1931-2018.\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20181231_v3-0-0-2018f.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 43669, "uuid": "2a01faf75de64308b2bf4c7b43d393ef", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2024, v3.4.1.2024f", "abstract": "This is version v3.4.1.2024f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data.\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20250101_v3.4.1.2024f.nc. The station codes can be found under the docs tab. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note.\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, { "ob_id": 20039, "uuid": "64ee8b9d6e0048cfa903f1c21937b83a", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1973-2012, v1.0.1.2012p", "abstract": "This is version 1.0.1.2012p of HadISD the Met Office Hadley Centre's global sub-daily data, extending v1.0.0.2011f to span 1/1/1973 - 31/12/2012. \r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19730101-20121231_v1-0-1-2012p.nc. The station codes can be found under the docs tab or on the archive beside the station_data folder. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1" } ], "identifier_set": [ 8588 ], "responsiblepartyinfo_set": [ 51651, 51652, 51815, 51672, 74198, 75093, 75094, 75095, 51673, 168078, 52386, 168079, 52401, 168080, 52402 ], "onlineresource_set": [ 7924, 15323, 16830, 16831 ], "project_set": [ 13164 ] }, { "ob_id": 13522, "uuid": "251474c7b09449d8b9e7aeaf1461858f", "short_code": "coll", "title": "HadISDH: global surface humidity data", "abstract": "HadISDH (Integrated Surface Database Humidity) is a monthly 5° by 5° gridded global surface humidity climate monitoring dataset created from in-situ sub-daily synoptic data. The data have been quality controlled and homogenised (land), bias adjusted (marine) and buddy checked (marine). \r\n\r\nMonthly mean climate anomalies are provided alongside uncertainty estimates, actual values, climatological means and standard deviations for specific humidity, relative humidity, vapour pressure, dew point temperature, wet bulb temperature, dew point depression in addition to the simultaneously observed temperature.", "keywords": "HadISDH, humidity, surface, land, marine, blend, gridded, station, specific humidity, relative humidity, temperature, dew point temperature, wet bulb temperature, dew point depression, vapour pressure, in-situ", "publicationState": "published", "dataPublishedTime": "2016-07-28T07:19:30", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 32371, "uuid": "82b0164a4d06467ab450ff67006729c1", "short_code": "ob", "title": "HadISDH land: gridded global monthly land surface humidity data version 4.3.1.2020f", "abstract": "This is the HadISDH land 4.3.1.2020f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH-land is a near-global gridded monthly mean land surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from weather stations. The observations have been quality controlled and homogenised. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2020. \r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the 4.2.0.2019f version to the end of 2020 and constitutes a minor update to HadISDH due to changing some of the code base from IDL and Python 2.7 to Python 3, detecting and fixing a bug in the process, and retrieving the missing April 2015 station data. These have led to small changes in regional and global average values and coverage. All other processing steps for HadISDH remain identical. Users are advised to read the update document in the Docs section for full details.\r\n\r\nAs in previous years, the annual scrape of NOAAs Integrated Surface Dataset for HadISD.3.1.2.202101p, which is the basis of HadISDH.land, has pulled through some historical changes to stations. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E.,\r\nJones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and\r\ntemperature record for climate monitoring, Clim. Past, 10, 1983-2006,\r\ndoi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more\r\ndetail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de\r\nPodesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface\r\nspecific humidity product for climate monitoring. Climate of the Past, 9, 657-677,\r\ndoi:10.5194/cp-9-657-2013." }, { "ob_id": 41768, "uuid": "c844fc58615a422aa2e7d2fc8bd8cccf", "short_code": "ob", "title": "HadISDH.land: gridded global monthly land surface humidity data version 4.6.0.2023f", "abstract": "This is the HadISDH.land 4.6.0.2023f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.land is a near-global gridded monthly mean land surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from weather stations. The observations have been quality controlled and homogenised. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2023. \r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the previous version to the end of 2023. Users are advised to read the update document in the Docs section for full details on all changes from the previous release.\r\n\r\nAs in previous years, the annual scrape of NOAAs Integrated Surface Dataset for HadISD.3.4.0.2023f, which is the basis of HadISDH.land, has pulled through some historical changes to stations. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E.,\r\nJones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and\r\ntemperature record for climate monitoring, Clim. Past, 10, 1983-2006,\r\ndoi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more\r\ndetail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de\r\nPodesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface\r\nspecific humidity product for climate monitoring. Climate of the Past, 9, 657-677,\r\ndoi:10.5194/cp-9-657-2013." }, { "ob_id": 32373, "uuid": "8e90b16ddd2a484897ab9737c46d6204", "short_code": "ob", "title": "HadISDH blend: gridded global monthly land and ocean surface humidity data version 1.1.1.2020f", "abstract": "This is the HadISDH blend 1.1.1.2020f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH-blend is a near-global gridded monthly mean surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships and weather stations. The observations have been quality controlled and homogenised / bias adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2020.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the 1.0.0.2019f version to the end of 2020. It combines HadISDH.land.4.3.1.2020f and HadISDH.marine.1.1.0.2020f and therefore their respective update notes. Users are advised to read the update documents in the Docs section for full details.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of\r\nthe HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,\r\n12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,\r\nBerry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,\r\nRayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to\r\nthe historical marine climate record. International Journal of Climatology.\r\ndoi:10.1002/joc.4775.\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E.,\r\nJones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and\r\ntemperature record for climate monitoring, Clim. Past, 10, 1983-2006,\r\ndoi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more\r\ndetail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de\r\nPodesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface\r\nspecific humidity product for climate monitoring. Climate of the Past, 9, 657-677,\r\ndoi:10.5194/cp-9-657-2013." }, { "ob_id": 13528, "uuid": "fd038d5dcba14f58ac2770ad47acf39c", "short_code": "ob", "title": "HadISDH: gridded global monthly land surface humidity data version 2.0.1.2014p", "abstract": "This is the 2.0.1.2014p version of the HadISDH land data. The data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2014.\r\n\r\nMonthly gridded (5 degree by 5 degree) and station products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in either NetCDF or ASCII format.\r\n\r\nUncertainty estimates are provided at the station and gridbox level covering station uncertainty (climatological, homogenisation and measurement uncertainty), gridbox spatial and temporal sampling uncertainty and combined station and sampling uncertainty.\r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014. \r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more detail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013." }, { "ob_id": 19171, "uuid": "f34f97696cd94946b6ace2e8738df805", "short_code": "ob", "title": "HadISDH: gridded global monthly land surface humidity data version 3.0.0.2016p", "abstract": "This is the 3.0.0.2016p version of the HadISDH land data. The data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2016. \r\n\r\nThe data are monthly gridded (5 degree by 5 degree) and station products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in either NetCDF or ASCII format.\r\n\r\nThis version extends the 2.1.0.2015p version to the end of 2016 and constitutes a major update to HadISDH due to a major update of the source data HadISD. Improvements in this version include increased numbers of stations (~8000) and updated methodologies. Users are advised to read the update document in the docs section for full details.\r\n\r\nUncertainty estimates are provided at the station and gridbox level covering station uncertainty (climatological, homogenisation and measurement uncertainty), gridbox spatial and temporal sampling uncertainty and combined station and sampling uncertainty.\r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014. \r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more detail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013." }, { "ob_id": 40168, "uuid": "2d1613955e1b4cd1b156e5f3edbd7e66", "short_code": "ob", "title": "HadISDH.extremes: gridded global monthly land surface wet bulb and dry bulb temperature extremes index data version 1.0.0.2022f", "abstract": "This is the HadISDH.extremes 1.0.0.2022f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.extremes is a near-global gridded monthly land surface extremes index climate monitoring product. It is created from in situ sub-daily observations of wet bulb (converted from dew point temperature) and dry bulb temperature from weather stations. The observations have been quality controlled at the hourly level with strict temporal completeness thresholds applied at daily, monthly, annual, climatological and whole period scales to minimise biases. Gridbox months are assessed for inhomogeneity and scores provided (see Homogeneity Score Document in Docs). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2022.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for 27 different heat extremes indices based on the ET-SCI (Expert Team on Sector-Specific Climate Indices; https://public.wmo.int/en/events/meetings/expert-team-sector-specific-climate-indices-et-sci) framework. These indices capture a range of moderate to severe extremes. They utilise the daily maximum and minimum values of sub-daily dry bulb and wet bulb temperature observations. Note that these will most likely underestimate the true extremes even when hourly data are available. The data are designed for assessing large scale features over long time scales, ideally using the anomaly fields as these are less affected by sampling biases. Users are advised to cross-compare with national datasets other supporting evidence when assessing small scale localised features.\r\n\r\nThis version is the first with annual updates envisaged. An update record will be maintained in the Docs section.\r\n\r\nHadISD.3.3.0.2022f is the basis of HadISDH.extremes.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K, in press: HadISDH.extremes Part 1: a gridded wet bulb temperature extremes index product for climate monitoring. Advances in Atmospheric Sciences, doi: 10.1007/s00376-023-2347-8. http://www.iapjournals.ac.cn/aas/en/article/doi/10.1007/s00376-023-2347-8\r\n\r\nWillett, K. in press: HadISDH.extremes Part 2: exploring humid heat extremes using wet bulb temperature indices. Advances in Atmospheric Sciences, doi: 10.1007/s00376-023-2348-7. http://www.iapjournals.ac.cn/aas/en/article/doi/10.1007/s00376-023-2348-7\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1" }, { "ob_id": 30290, "uuid": "3e9f387293294f3b8a850524fcfc0c9c", "short_code": "ob", "title": "HadISDH land: gridded global monthly land surface humidity data version 4.2.0.2019f", "abstract": "This is the 4.2.0.2019f version of the HadISDH (Integrated Surface Database Humidity) land data. These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2019. \r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in either NetCDF or ASCII format.\r\n\r\nThis version extends the 4.1.0.2018f version to the end of 2019 and constitutes a minor update to HadISDH due to changing some of the code base from IDL to Python 3 and detecting and fixing various bugs in the process. These have led to small changes in regional and global average values and coverage. All other processing steps for HadISDH remain identical. Users are advised to read the update document in the Docs section for full details. \r\n\r\nAs in previous years, the annual scrape of NOAA’s Integrated Surface Dataset for HadISD.3.1.0.2019f, which is the basis of HadISDH.land, has pulled through some historical changes to stations. This, and the additional year of data, results in small changes to station selection. There has been an issue with data for April 2015 whereby it is missing for most of the globe. This will hopefully be resolved by next year’s update. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more detail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013." }, { "ob_id": 44293, "uuid": "e0ca70c643264ea0a68d04008499b87d", "short_code": "ob", "title": "HadISDH.land: gridded global monthly land surface humidity data version 4.6.1.2024f", "abstract": "This is the HadISDH.land 4.6.1.2024f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.land is a near-global gridded monthly mean land surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from weather stations. The observations have been quality controlled and homogenised. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2024. \r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the previous version to the end of 2024. Users are advised to read the update document in the Docs section for full details on all changes from the previous release.\r\n\r\nAs in previous years, the annual scrape of NOAAs Integrated Surface Dataset for HadISD.3.4.1.2024f, which is the basis of HadISDH.land, has pulled through some historical changes to stations. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E.,\r\nJones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and\r\ntemperature record for climate monitoring, Clim. Past, 10, 1983-2006,\r\ndoi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more\r\ndetail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de\r\nPodesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface\r\nspecific humidity product for climate monitoring. Climate of the Past, 9, 657-677,\r\ndoi:10.5194/cp-9-657-2013." }, { "ob_id": 20359, "uuid": "844b55466c9044b5a8cb35037992790b", "short_code": "ob", "title": "HadISDH: gridded global monthly land surface humidity data version 2.1.0.2015p", "abstract": "This is the 2.1.0.2015p version of the HadISDH land data. The data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2015. \r\n\r\nThis version extends the 2.0.1.2014p version to the end of 2015 and includes some minor updates users are advised to read the update document in the docs section for full details. \r\n\r\nThe data are monthly gridded (5 degree by 5 degree) and station products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in either NetCDF or ASCII format.\r\n\r\nUncertainty estimates are provided at the station and gridbox level covering station uncertainty (climatological, homogenisation and measurement uncertainty), gridbox spatial and temporal sampling uncertainty and combined station and sampling uncertainty.\r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014. \r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more detail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013." }, { "ob_id": 32372, "uuid": "c928ef392244426b9473af92a16b0daf", "short_code": "ob", "title": "HadISDH marine: gridded global monthly ocean surface humidity data version 1.1.0.2020f", "abstract": "This is the HadISDH marine 1.1.0.2020f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH-marine s a near-global gridded monthly mean marine surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships. The observations have been quality controlled and bias-adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2020.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the 1.0.0.2019f version to the end of 2020 and constitutes a minor update to HadISDH due to change in method for calculating gridbox monthly means. All other processing steps for HadISDH remain identical. Users are advised to read the update document in the Docs section for full details.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of\r\nthe HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,\r\n12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,\r\nBerry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,\r\nRayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to\r\nthe historical marine climate record. International Journal of Climatology.\r\ndoi:10.1002/joc.4775." }, { "ob_id": 25974, "uuid": "de33ae6e5b724a41be34d0f107a65ce2", "short_code": "ob", "title": "HadISDH: gridded global monthly land surface humidity data version 4.0.0.2017f", "abstract": "This is the 4.0.0.2017f version of the HadISDH land data. These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2017. \r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in either NetCDF or ASCII format.\r\n\r\nThis version extends the 3.0.0.2016p version to the end of 2017 and constitutes a major update to HadISDH due to a change to using the 1981-2010 period as its climatological reference period both to make it more consistent with other monitoring products and to maximise station coverage now that it uses the larger station database of HadISD2. Users are advised to read the update document in the docs section for full details. This version now uses the 1981-2010 period as its climatological reference period both to make it more consistent with other monitoring products and to maximise station coverage now that it uses the larger station database of HadISD2. \r\n\r\nAdditionally, there has been a small methodological change. Stations with large adjustments made during homogenisation are removed based on thresholds for q (>3g/kg), RH (>15%rh), T (>5degC) and Td (>5degC) rather than just T and Td. This results in 54 stations being removed as opposed to 29 last year. All other processing steps for HadISDH remain identical. \r\n\r\nThe new version of HadISD2 (2.0.2.2017p) has pulled through some historical changes to stations which are passed on to HadISDH. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data. \r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014. \r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more detail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013." }, { "ob_id": 40166, "uuid": "8956cf9e31334914ab4991796f0f645a", "short_code": "ob", "title": "HadISDH.land: gridded global monthly land surface humidity data version 4.5.1.2022f", "abstract": "This is the HadISDH.land 4.5.1.2022f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.land is a near-global gridded monthly mean land surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from weather stations. The observations have been quality controlled and homogenised. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2022. \r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the previous version to the end of 2022. Users are advised to read the update document in the Docs section for full details on all changes from the previous release.\r\n\r\nAs in previous years, the annual scrape of NOAAs Integrated Surface Dataset for HadISD.3.3.0.2022f, which is the basis of HadISDH.land, has pulled through some historical changes to stations. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E.,\r\nJones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and\r\ntemperature record for climate monitoring, Clim. Past, 10, 1983-2006,\r\ndoi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more\r\ndetail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de\r\nPodesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface\r\nspecific humidity product for climate monitoring. Climate of the Past, 9, 657-677,\r\ndoi:10.5194/cp-9-657-2013." }, { "ob_id": 40621, "uuid": "c3c1526fba8f4a5382d2f9fb86966d82", "short_code": "ob", "title": "HadISDH.blend: gridded global monthly land and ocean surface humidity data version 1.4.1.2022f", "abstract": "This is the HadISDH.blend 1.4.1.2022f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.blend is a near-global gridded monthly mean surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships and weather stations. The observations have been quality controlled and homogenised / bias adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2022.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the previous version to the end of 2022. It combines the latest version of HadISDH.land and HadISDH.marine. and therefore their respective update notes. Users are advised to read the update documents in the Docs section for full details.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of\r\nthe HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,\r\n12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,\r\nBerry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,\r\nRayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to\r\nthe historical marine climate record. International Journal of Climatology.\r\ndoi:10.1002/joc.4775.\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E.,\r\nJones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and\r\ntemperature record for climate monitoring, Clim. Past, 10, 1983-2006,\r\ndoi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more\r\ndetail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de\r\nPodesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface\r\nspecific humidity product for climate monitoring. Climate of the Past, 9, 657-677,\r\ndoi:10.5194/cp-9-657-2013." }, { "ob_id": 30533, "uuid": "d38d5949dfb1438185894321095583f4", "short_code": "ob", "title": "HadISDH blend: gridded global monthly ocean surface humidity data version 1.0.0.2019f", "abstract": "This is the 1.0.0.2019f version of the HadISDH (Integrated Surface Database Humidity) blend data. It combines HadISDH.land.4.2.0.2019f and HadISDH.marine.1.0.0.2019f. These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2019.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in NetCDF format.\r\n\r\nThis version is the first available. \r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I.: Development of the HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data, in review, doi:XX.XXXX/essd-XX-XXXX-2020, 2020.\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E., Berry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J., Rayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to the historical marine climate record. International Journal of Climatology. doi:10.1002/joc.4775.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1" }, { "ob_id": 44295, "uuid": "d3c7c95a586649d78bd20b4ae8eb3caf", "short_code": "ob", "title": "HadISDH.blend: gridded global monthly land and ocean surface humidity data version 1.5.1.2024f", "abstract": "This is the HadISDH.blend 1.5.1.2024f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.blend is a near-global gridded monthly mean surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships and weather stations. The observations have been quality controlled and homogenised / bias adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2024.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the previous version to the end of 2024. It combines the latest version of HadISDH.land and HadISDH.marine and therefore their respective update notes. Users are advised to read the update documents in the Docs section for full details.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of\r\nthe HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,\r\n12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,\r\nBerry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,\r\nRayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to\r\nthe historical marine climate record. International Journal of Climatology.\r\ndoi:10.1002/joc.4775.\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E.,\r\nJones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and\r\ntemperature record for climate monitoring, Clim. Past, 10, 1983-2006,\r\ndoi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more\r\ndetail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de\r\nPodesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface\r\nspecific humidity product for climate monitoring. Climate of the Past, 9, 657-677,\r\ndoi:10.5194/cp-9-657-2013." }, { "ob_id": 37289, "uuid": "062942e96a6e4567b2bc47045be910a7", "short_code": "ob", "title": "HadISDH.land: gridded global monthly land surface humidity data version 4.4.0.2021f", "abstract": "This is the HadISDH.land 4.4.0.2021f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.land is a near-global gridded monthly mean land surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from weather stations. The observations have been quality controlled and homogenised. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2021. \r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the previous version to the end of 2021. Users are advised to read the update document in the Docs section for full details on all changes from the previous release.\r\n\r\nAs in previous years, the annual scrape of NOAAs Integrated Surface Dataset for HadISD.3.1.2.202101p, which is the basis of HadISDH.land, has pulled through some historical changes to stations. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E.,\r\nJones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and\r\ntemperature record for climate monitoring, Clim. Past, 10, 1983-2006,\r\ndoi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more\r\ndetail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de\r\nPodesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface\r\nspecific humidity product for climate monitoring. Climate of the Past, 9, 657-677,\r\ndoi:10.5194/cp-9-657-2013." }, { "ob_id": 30532, "uuid": "463b2fcd6a264a39b1e3249dab16c177", "short_code": "ob", "title": "HadISDH marine: gridded global monthly ocean surface humidity data version 1.0.0.2018f", "abstract": "This is the 1.0.0.2018f version of the HadISDH (Integrated Surface Database Humidity) marine data and the first version to be produced. These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2018.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in NetCDF format.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I.: Development of the HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data, in review, doi:XX.XXXX/essd-XX-XXXX-2020, 2020.\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E., Berry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J., Rayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to the historical marine climate record. International Journal of Climatology. doi:10.1002/joc.4775." }, { "ob_id": 37290, "uuid": "54d3408edd9e41bca226924754619812", "short_code": "ob", "title": "HadISDH.marine: gridded global monthly ocean surface humidity data version 1.3.0.2021f", "abstract": "This is the HadISDH.marine 1.3.0.2021f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.marine is a near-global gridded monthly mean marine surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships. The observations have been quality controlled and bias-adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2021.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the previous version to the end of 2021. Users are advised to read the update document in the Docs section for full details on all changes from the previous release.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of\r\nthe HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,\r\n12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,\r\nBerry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,\r\nRayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to\r\nthe historical marine climate record. International Journal of Climatology.\r\ndoi:10.1002/joc.4775." }, { "ob_id": 37291, "uuid": "563cb665bc6e43f99b355a9bb8134317", "short_code": "ob", "title": "HadISDH.blend: gridded global monthly land and ocean surface humidity data version 1.3.0.2021f", "abstract": "This is the HadISDH.blend 1.3.0.2021f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.blend is a near-global gridded monthly mean surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships and weather stations. The observations have been quality controlled and homogenised / bias adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2021.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the previous version to the end of 2021. It combines the latest version of HadISDH.land and HadISDH.marine. and therefore their respective update notes. Users are advised to read the update documents in the Docs section for full details.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of\r\nthe HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,\r\n12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,\r\nBerry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,\r\nRayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to\r\nthe historical marine climate record. International Journal of Climatology.\r\ndoi:10.1002/joc.4775.\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E.,\r\nJones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and\r\ntemperature record for climate monitoring, Clim. Past, 10, 1983-2006,\r\ndoi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more\r\ndetail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de\r\nPodesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface\r\nspecific humidity product for climate monitoring. Climate of the Past, 9, 657-677,\r\ndoi:10.5194/cp-9-657-2013." }, { "ob_id": 30531, "uuid": "ffeb0c718baf49ad845f30677944610a", "short_code": "ob", "title": "HadISDH marine: gridded global monthly ocean surface humidity data version 1.0.0.2019f", "abstract": "This is the 1.0.0.2019f version of the HadISDH (Integrated Surface Database Humidity) marine data. These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2019.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in either NetCDF or ASCII format.\r\n\r\nThis version extends the 1.0.0.2018f version to the end of 2019 and constitutes with no changes other than the addition of 2019 data. Users are advised to read the update document in the Docs section for full details. \r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I.: Development of the HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data, in review, doi:XX.XXXX/essd-XX-XXXX-2020, 2020.\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E., Berry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J., Rayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to the historical marine climate record. International Journal of Climatology. doi:10.1002/joc.4775." }, { "ob_id": 40618, "uuid": "755bc61b5524498db67f9468a92d8cfc", "short_code": "ob", "title": "HadISDH.marine: gridded global monthly ocean surface humidity data version 1.4.1.2022f", "abstract": "This is the HadISDH.marine 1.4.1.2022f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.marine is a near-global gridded monthly mean marine surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships. The observations have been quality controlled and bias-adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2022.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the previous version to the end of 2022. Users are advised to read the update document in the Docs section for full details on all changes from the previous release.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of\r\nthe HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,\r\n12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,\r\nBerry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,\r\nRayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to\r\nthe historical marine climate record. International Journal of Climatology.\r\ndoi:10.1002/joc.4775." }, { "ob_id": 41767, "uuid": "0a36ca390a5844578905780ed4c78ded", "short_code": "ob", "title": "HadISDH.extremes: gridded global monthly land surface wet bulb and dry bulb temperature extremes index data version 1.1.0.2023f", "abstract": "This is the HadISDH.extremes 1.1.0.2023f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.extremes is a near-global gridded monthly land surface extremes index climate monitoring product. It is created from in situ sub-daily observations of wet bulb (converted from dew point temperature) and dry bulb temperature from weather stations. The observations have been quality controlled at the hourly level with strict temporal completeness thresholds applied at daily, monthly, annual, climatological and whole period scales to minimise biases. Gridbox months are assessed for inhomogeneity and scores provided (see Homogeneity Score Document in Docs). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2023.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for 27 different heat extremes indices based on the ET-SCI (Expert Team on Sector-Specific Climate Indices) framework. These indices capture a range of moderate to severe extremes. They utilise the daily maximum and minimum values of sub-daily dry bulb and wet bulb temperature observations. Note that these will most likely underestimate the true extremes even when hourly data are available. The data are designed for assessing large scale features over long time scales, ideally using the anomaly fields as these are less affected by sampling biases. Users are advised to cross-compare with national datasets other supporting evidence when assessing small scale localised features.\r\n\r\nThis version is the first with annual updates envisaged. An update record will be maintained in the Docs section.\r\n\r\nHadISD.3.4.0.2023f is the basis of HadISDH.extremes.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K, 2023: HadISDH.extremes Part 1: a gridded wet bulb temperature extremes index product for climate monitoring. Advances in Atmospheric Sciences, 40, 1952–1967, doi: 10.1007/s00376-023-2347-8. https://link.springer.com/article/10.1007/s00376-023-2347-8\r\n\r\nWillett, K. 2023: HadISDH.extremes Part 2: exploring humid heat extremes using wet bulb temperature indices. Advances in Atmospheric Sciences, 40, 1968–1985, doi: 10.1007/s00376-023-2348-7. https://link.springer.com/article/10.1007/s00376-023-2348-7\r\n\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1" }, { "ob_id": 41766, "uuid": "1de7b50d827b4b4f966bd4e3ec5516ea", "short_code": "ob", "title": "HadISDH.blend: gridded global monthly land and ocean surface humidity data version 1.5.0.2023f", "abstract": "This is the HadISDH.blend 1.5.0.2023f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.blend is a near-global gridded monthly mean surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships and weather stations. The observations have been quality controlled and homogenised / bias adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2023.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the previous version to the end of 2023. It combines the latest version of HadISDH.land and HadISDH.marine and therefore their respective update notes. Users are advised to read the update documents in the Docs section for full details.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of\r\nthe HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,\r\n12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,\r\nBerry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,\r\nRayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to\r\nthe historical marine climate record. International Journal of Climatology.\r\ndoi:10.1002/joc.4775.\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E.,\r\nJones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and\r\ntemperature record for climate monitoring, Clim. Past, 10, 1983-2006,\r\ndoi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more\r\ndetail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de\r\nPodesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface\r\nspecific humidity product for climate monitoring. Climate of the Past, 9, 657-677,\r\ndoi:10.5194/cp-9-657-2013." }, { "ob_id": 44294, "uuid": "b3f6a88ffe24443494f92e5977965a1c", "short_code": "ob", "title": "HadISDH.extremes: gridded global monthly land surface wet bulb and dry bulb temperature extremes index data version 1.2.0.2024f", "abstract": "This is the HadISDH.extremes 1.2.0.2024f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.extremes is a near-global gridded monthly land surface extremes index climate monitoring product. It is created from in situ sub-daily observations of wet bulb (converted from dew point temperature) and dry bulb temperature from weather stations. The observations have been quality controlled at the hourly level with strict temporal completeness thresholds applied at daily, monthly, annual, climatological and whole period scales to minimise biases. Gridbox months are assessed for inhomogeneity and scores provided (see Homogeneity Score Document in Docs). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2024.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for 27 different heat extremes indices based on the ET-SCI (Expert Team on Sector-Specific Climate Indices) framework. These indices capture a range of moderate to severe extremes. They utilise the daily maximum and minimum values of sub-daily dry bulb and wet bulb temperature observations. Note that these will most likely underestimate the true extremes even when hourly data are available. The data are designed for assessing large scale features over long time scales, ideally using the anomaly fields as these are less affected by sampling biases. Users are advised to cross-compare with national datasets other supporting evidence when assessing small scale localised features.\r\n\r\nThis version is the first with annual updates envisaged. An update record will be maintained in the Docs section.\r\n\r\nHadISD.3.4.1.2024f is the basis of HadISDH.extremes.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K, 2023: HadISDH.extremes Part 1: a gridded wet bulb temperature extremes index product for climate monitoring. Advances in Atmospheric Sciences, 40, 1952–1967, doi: 10.1007/s00376-023-2347-8. https://link.springer.com/article/10.1007/s00376-023-2347-8\r\n\r\nWillett, K. 2023: HadISDH.extremes Part 2: exploring humid heat extremes using wet bulb temperature indices. Advances in Atmospheric Sciences, 40, 1968–1985, doi: 10.1007/s00376-023-2348-7. https://link.springer.com/article/10.1007/s00376-023-2348-7\r\n\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station\r\ndata from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent\r\nDevelopments and Partnerships. Bulletin of the American Meteorological Society, 92,\r\n704-708, doi:10.1175/2011BAMS3015.1" }, { "ob_id": 44269, "uuid": "3fcb9e23c9bf47bc8a9762c03e13ba0b", "short_code": "ob", "title": "HadISDH.marine: gridded global monthly ocean surface humidity data version 1.6.1.2024f", "abstract": "This is the HadISDH.marine 1.6.1.2024f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.marine is a near-global gridded monthly mean marine surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships. The observations have been quality controlled and bias-adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2024.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the previous version to the end of 2024. Users are advised to read the update document in the Docs section for full details on all changes from the previous release.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of\r\nthe HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,\r\n12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,\r\nBerry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,\r\nRayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to\r\nthe historical marine climate record. International Journal of Climatology.\r\ndoi:10.1002/joc.4775." }, { "ob_id": 41769, "uuid": "2fdc37a517b54376ba19d5c7432457d5", "short_code": "ob", "title": "HadISDH.marine: gridded global monthly ocean surface humidity data version 1.6.0.2023f", "abstract": "This is the HadISDH.marine 1.6.0.2023f version of the Met Office Hadley Centre Integrated Surface Dataset of Humidity (HadISDH). HadISDH.marine is a near-global gridded monthly mean marine surface humidity climate monitoring product. It is created from in situ observations of air temperature and dew point temperature from ships. The observations have been quality controlled and bias-adjusted. Uncertainty estimates for observation issues and gridbox sampling are provided (see data quality statement section below). The data are provided by the Met Office Hadley Centre and this version spans 1/1/1973 to 31/12/2023.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).\r\n\r\nThis version extends the previous version to the end of 2023. Users are advised to read the update document in the Docs section for full details on all changes from the previous release.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link\r\nto the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I., 2020: Development of\r\nthe HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data,\r\n12, 2853-2880, https://doi.org/10.5194/essd-12-2853-2020\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E.,\r\nBerry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J.,\r\nRayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to\r\nthe historical marine climate record. International Journal of Climatology.\r\ndoi:10.1002/joc.4775." } ], "identifier_set": [ 8591 ], "responsiblepartyinfo_set": [ 51654, 51653, 51684, 105383, 105399, 105426, 105450, 132119, 51685, 132120, 168081, 168082, 132121, 132122, 168083, 132123, 132124, 132125, 132126, 132127, 132128 ], "onlineresource_set": [ 7925, 8206, 8207, 8208, 8209, 16832, 16833, 15746, 37883, 37884 ], "project_set": [ 13164 ] }, { "ob_id": 13523, "uuid": "f7189fabb084452c9818ba41e59ccabd", "short_code": "coll", "title": "HadCRUT: gridded dataset of global historical surface temperature anomalies", "abstract": "HadCRUT is a gridded dataset of global historical surface temperature anomalies, relative to a 1961-1990 reference period. \r\n\r\nData are available for each month since January 1850, on a 5 degree grid.\r\nThe gridded data are a blend of the CRUTEM land-surface air temperature dataset and the HadSST sea-surface temperature (SST) dataset. The dataset is presented as an ensemble of 100 dataset realisations that sample the distribution of uncertainty in the global temperature record.", "keywords": "HadCRUT4, HadCRUT", "publicationState": "published", "dataPublishedTime": "2019-05-03T13:29:07", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 157 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 24943, "uuid": "22a878b3ada24590970974588642f585", "short_code": "ob", "title": "HadCRUT4: gridded dataset of global historical surface temperature anomalies, version 4.5.0.0", "abstract": "This is the HadCRUT.4.5.0.0 version of the HadCRUT4 data. \r\n\r\nData are available for each month since January 1850, on a 5 degree grid. \r\nThe gridded data are a blend of the CRUTEM4 land-surface air temperature dataset and the HadSST3 sea-surface temperature (SST) dataset. The dataset is presented as an ensemble of 100 dataset realisations that sample the distribution of uncertainty in the global temperature record. \r\n\r\nThe data consist of 100 ensemble members and the ensemble median, each are available as a separate file where the fourth component of the filename denotes the ensemble member or median. In addition, the variance information is provided under the name uncorrelated. Full error covariance data are available from the Met Office (see the link to the HadCRUT4 homepage in Docs) \r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following paper (see Docs for link to the publication) and this dataset (using the \"citable as\" reference) :\r\n\r\nMorice, C. P., J. J. Kennedy, N. A. Rayner, and P. D. Jones (2012), Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 dataset, J. Geophys. Res., 117, D08101, doi:10.1029/2011JD017187" }, { "ob_id": 13532, "uuid": "b347afd27083431480739e3b07945327", "short_code": "ob", "title": "HadCRUT4: gridded dataset of global historical surface temperature anomalies. Version 4.4.0.0", "abstract": "This is the HadCRUT.4.4.0.0 version of the HadCRUT4 data. \r\n\r\nData are available for each month since January 1850, on a 5 degree grid. \r\nThe gridded data are a blend of the CRUTEM4 land-surface air temperature dataset and the HadSST3 sea-surface temperature (SST) dataset. The dataset is presented as an ensemble of 100 dataset realisations that sample the distribution of uncertainty in the global temperature record. The ensemble median is provided and is provided as r0.\r\n\r\nError covariance information are available from the Met Office (see the link to the HadCRUT4 homepage in Docs) \r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following paper (see Docs for link to the publication) and this dataset (using the \"citable as\" reference) :\r\n\r\nMorice, C. P., J. J. Kennedy, N. A. Rayner, and P. D. Jones (2012), Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 dataset, J. Geophys. Res., 117, D08101, doi:10.1029/2011JD017187" }, { "ob_id": 32020, "uuid": "b9698c5ecf754b1d981728c37d3a9f02", "short_code": "ob", "title": "HadCRUT.5.0.0.0: Ensemble near-surface temperature anomaly grids and time series", "abstract": "HadCRUT5 (Met Office Hadley Centre/Climatic Research Unit global surface temperature anomalies, version 5) is a gridded dataset of global historical near-surface air temperature anomalies since the year 1850. It has been developed and maintained by the Met Office Hadley Centre and University of East Anglia Climatic Research Unit. Air temperature information over land is derived from CRUTEM5 monthly average meteorological station temperature series, an expanded compilation of station series with revised quality control methods. Temperatures over ocean are derived from the HadSST4 sea-surface temperature dataset, including revised assessments of instrumental biases. Temperature data are presented as monthly average near-surface temperature anomalies, relative to the 1961-1990 period, on a regular 5° latitude by 5° longitude grid from 1850 to 2018, with derived global and hemispheric time series.\r\n\r\nTwo variants of the dataset are provided. The first represents temperature anomaly data on a grid for locations where measurement data are available. The second, more spatially complete, variant uses a Gaussian process based statistical method to make better use of the available observations, extending temperature anomaly estimates into regions for which the underlying measurements are informative. Each is provided as a 200‐member ensemble accompanied by additional uncertainty information.\r\n\r\nMonthly updates to HadCRUT5 are available from the Met Office Hadobs website (see documentation links)." } ], "identifier_set": [ 8607 ], "responsiblepartyinfo_set": [ 51830, 51656, 51655, 141876, 141877, 141878, 141879, 51831, 168763, 51829, 168764, 52399 ], "onlineresource_set": [ 7926, 7946, 7947, 16838 ], "project_set": [ 13164 ] }, { "ob_id": 13548, "uuid": "93aecb2607294e25bc4638adc800f8e7", "short_code": "coll", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI) Dataset Collection", "abstract": "Datasets produced by the Ocean Colour project of the ESA Climate Change Inititative (CCI). The Ocean Colour CCI is producing long-term multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490 nm. Information on uncertainties is also provided.\r\n\r\nThis dataset collection currently holds Version 1.0 data products, and later versions will be added in the future. Note, version 2.0 data products are now currently available directly from the Ocean Colour CCI team (see link in the documentation section).", "keywords": "ESA, Ocean Colour, CCI, ECV", "publicationState": "published", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 147 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 25363, "uuid": "584d4028633a4b7e9fa36da72dbd91c7", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global dataset of inherent optical properties (IOP) gridded on a sinusoidal projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 3.1 inherent optical properties (IOP) product (in mg/m3) on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, the IOP data are also included in the 'All Products' dataset. \r\n\r\nThe inherent optical properties (IOP) dataset consists of the total absorption and particle backscattering coefficients, and, additionally, the fraction of detrital & dissolved organic matter absorption and phytoplankton absorption. The total absorption (units m-1), the total backscattering (m-1), the absorption by detrital and coloured dissolved organic matter, the backscattering by particulate matter, and the absorption by phytoplankton share the same spatial resolution of ~4 km. The values of IOP are reported for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm). \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 25377, "uuid": "159649796f2943689a836999016188f0", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a sinusoidal projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 3.1 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). It is computed from the Ocean Colour CCI Version 3.1 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, these data are also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 13363, "uuid": "a70b70e7635342cdaa4451c17fd4bd87", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global ocean colour data products gridded on a sinusoidal projection (All Products), Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 1.0 generated ocean colour products on a sinusoidal projection at 4 km spatial resolution and at a daily time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)" }, { "ob_id": 19889, "uuid": "3ba980b6cfba4bb48a5fe9c4efdeffe9", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global chlorophyll-a data products gridded on a geographic projection, Version 2.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 2.0 chlorophyll-a product (in mg/m3) on a geographic projection at 4 km spatial resolution and at number of time resolutions (daily, 5day, 8day and monthly composites). Note, this chlor_a data is also included in the 'All Products' dataset. \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 13346, "uuid": "45278227a3804ab2a601fa2d3b1ec2fd", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global dataset of inherent optical properties (IOP) gridded on a geographic projection, Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 1.0 inherent optical properties (IOP) product (in mg/m3) on a geographic projection at approximately 4 km spatial resolution and at a daily time resolution. Note, this dataset is also included in the 'All Products' dataset.\r\n\r\nThe inherent optical properties (IOP) dataset consists of the total absorption and particle backscattering coefficients, and, additionally, the fraction of detrital & dissolved organic matter absorption and phytoplankton absorption. The total absorption (units m-1), the total backscattering (m-1), the absorption by detrital and coloured dissolved organic matter, the backscattering by particulate matter, and the absorption by phytoplankton share the same spatial resolution of ~4 km. The values of IOP are reported for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm). \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n" }, { "ob_id": 13337, "uuid": "47e646778ba44138846306789e3a3054", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Monthly global ocean colour data products gridded on a geographic projection (All Products), Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 1.0 generated ocean colour products on a geographic projection at 4 km spatial resolution and at a monthly time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)" }, { "ob_id": 13359, "uuid": "be3edba3aefd42ebbebea241a71d608e", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Monthly global ocean colour data products gridded on a sinusoidal projection (All Products), Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 1.0 generated ocean colour products on a sinusoidal projection at 4 km spatial resolution and at a monthly time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)" }, { "ob_id": 13355, "uuid": "5ce3092e823a403dad8122ff8ec93612", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global attenuation coefficient for downwelling irradiance (Kd490) gridded on a sinusoidal projection, Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 1.0 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a sinusoidal projection at approximately 4 km spatial resolution and at a daily time resolution. It is computed from the Ocean Colour CCI Version 1 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, this dataset is also contained within the 'All Products' dataset.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n" }, { "ob_id": 25370, "uuid": "edaa7e7324e849f683d3726088a0c7bd", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global dataset of inherent optical properties (IOP) gridded on a geographic projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 3.1 inherent optical properties (IOP) product (in mg/m3) on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, this the IOP data is also included in the 'All Products' dataset. \r\n\r\nThe inherent optical properties (IOP) dataset consists of the total absorption and particle backscattering coefficients, and, additionally, the fraction of detrital & dissolved organic matter absorption and phytoplankton absorption. The total absorption (units m-1), the total backscattering (m-1), the absorption by detrital and coloured dissolved organic matter, the backscattering by particulate matter, and the absorption by phytoplankton share the same spatial resolution of ~4 km. The values of IOP are reported for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm). \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 25379, "uuid": "915d2340b178494f987a6942e263a2eb", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global chlorophyll-a data products gridded on a sinusoidal projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 3.1 chlorophyll-a product (in mg/m3) on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, the chlorophyll-a data are also included in the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 13333, "uuid": "0f29b5f7ca774bd590a2ade5f94e9ddb", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global ocean colour data products gridded on a geographic projection (All Products), Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 1.0 generated ocean colour products on a geographic projection at 4 km spatial resolution and at a daily time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n" }, { "ob_id": 13357, "uuid": "f7d1890865bb47b383a013cd9fede042", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global chlorophyll-a data products gridded on a sinusoidal projection, Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 1.0 chlorophyll-a product (in mg/m3) on a sinusoidal projection at 4 km spatial resolution and at a daily time resolution. Note, this dataset is also included in the 'All Products' dataset.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n" }, { "ob_id": 20081, "uuid": "b70578ae62b745ec9dc2ba42d2ee1311", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global dataset of inherent optical properties (IOP) gridded on a sinusoidal projection, Version 2.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 2.0 inherent optical properties (IOP) product (in mg/m3) on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, the IOP data are also included in the 'All Products' dataset. \r\n\r\nThe inherent optical properties (IOP) dataset consists of the total absorption and particle backscattering coefficients, and, additionally, the fraction of detrital & dissolved organic matter absorption and phytoplankton absorption. The total absorption (units m-1), the total backscattering (m-1), the absorption by detrital and coloured dissolved organic matter, the backscattering by particulate matter, and the absorption by phytoplankton share the same spatial resolution of ~4 km. The values of IOP are reported for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm). \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 19886, "uuid": "aaf1d54282e94d5483356521f1b76434", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global remote sensing reflectance gridded on a geographic projection, Version 2.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 2.0 Remote Sensing Reflectance product on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data. Note, this dataset is also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection).\r\n\r\nPlease note, this dataset has been superseded. Later version of the data are now available." }, { "ob_id": 25373, "uuid": "806b30b9dc7f44e6bd56a46d8bccf279", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global remote sensing reflectance gridded on a geographic projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 3.1 Remote Sensing Reflectance product on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data. Note, this dataset is also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 25368, "uuid": "12d6f4bdabe144d7836b0807e65aa0e2", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global chlorophyll-a data products gridded on a geographic projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 3.1 chlorophyll-a product (in mg/m3) on a geographic projection at 4 km spatial resolution and at number of time resolutions (daily, 5day, 8day and monthly composites). Note, this chlor_a data is also included in the 'All Products' dataset. \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 13351, "uuid": "70be18893edb498785e22bed288cfd54", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global remote sensing reflectance gridded on a geographic projection, Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 1.0 Remote Sensing Reflectance product on a geographic projection at approximately 4 km spatial resolution and at a daily time resolution. Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data. Note, this dataset is also contained within the 'All Products' dataset.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection).\r\n" }, { "ob_id": 25375, "uuid": "b64b1a0ad7874fb39791e99c57b944bc", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global remote sensing reflectance gridded on a sinusoidal projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 3.1 Remote Sensing Reflectance product on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data. Note, these data are also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 19892, "uuid": "a897196a8e2b4c30ab8d22dbfe8f98c7", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global ocean colour data products gridded on a geographic projection (All Products), Version 2.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 2.0 generated ocean colour products on a geographic projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Data are also available as monthly climatologies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 19883, "uuid": "7852b8af4bda446ab12290b7b106cc3c", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global chlorophyll-a data products gridded on a sinusoidal projection, Version 2.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 2.0 chlorophyll-a product (in mg/m3) on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, the chlorophyll-a data are also included in the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 13342, "uuid": "22c0948d2c5b4f4dbf9606541a671274", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Yearly global ocean colour data products gridded on a geographic projection (All Products), Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 1.0 generated ocean colour products on a geographic projection at 4 km spatial resolution and at a yearly time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320." }, { "ob_id": 13335, "uuid": "7f31695e4b6d4ff5af71ccae213c910b", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): 8-day global ocean colour data products gridded on a geographic projection (All Products), Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 1.0 generated ocean colour products on a geographic projection at 4 km spatial resolution and at an 8-day time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n" }, { "ob_id": 25371, "uuid": "52266ccfbc3348a8afc27b67d6bbc6c2", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a geographic projection, Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 3.1 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). It is computed from the Ocean Colour CCI Version 3.1 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, these data are also contained within the 'All Products' dataset.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 19884, "uuid": "b548475d0a5d4a2b8de40e7b1fa40d7a", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a sinusoidal projection, Version 2.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 2.0 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). It is computed from the Ocean Colour CCI Version 2.0 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, these data are also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 19888, "uuid": "a2cd1cefc5b84b86bbaa09bb3832e497", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global dataset of inherent optical properties (IOP) gridded on a geographic projection, Version 2.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 2.0 inherent optical properties (IOP) product (in mg/m3) on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, this the IOP data is also included in the 'All Products' dataset. \r\n\r\nThe inherent optical properties (IOP) dataset consists of the total absorption and particle backscattering coefficients, and, additionally, the fraction of detrital & dissolved organic matter absorption and phytoplankton absorption. The total absorption (units m-1), the total backscattering (m-1), the absorption by detrital and coloured dissolved organic matter, the backscattering by particulate matter, and the absorption by phytoplankton share the same spatial resolution of ~4 km. The values of IOP are reported for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm). \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 13344, "uuid": "a526fdfb91954f1ab4360978e86f3b2b", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global chlorophyll-a data products gridded on a geographic projection, Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 1.0 chlorophyll-a product (in mg/m3) on a geographic projection at 4 km spatial resolution and at a daily time resolution. Note, this dataset is also included in the 'All Products' dataset. \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n" }, { "ob_id": 25381, "uuid": "55c20c0cb35b4a7c8ef8b65694fe46e2", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global ocean colour data products gridded on a sinusoidal projection (All Products), Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 3.1 generated ocean colour products on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). \r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 19887, "uuid": "49bcb6f29c824ae49e41d2d3656f11be", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a geographic projection, Version 2.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 2.0 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). It is computed from the Ocean Colour CCI Version 2.0 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, these data are also contained within the 'All Products' dataset.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 19880, "uuid": "76ad6afa787d4c469122f0b472a988c0", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global ocean colour data products gridded on a sinusoidal projection (All Products), Version 2.0.", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 2.0 generated ocean colour products on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). \r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later version of the data are now available." }, { "ob_id": 13349, "uuid": "06e4e74e2cb24ec582cdce05e2ff1c87", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global attenuation coefficient for downwelling irradiance (Kd490) gridded on a geographic projection, Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 1.0 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a geographic projection at approximately 4 km spatial resolution and at a daily time resolution. It is computed from the Ocean Colour CCI Version 1 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, this dataset is also contained within the 'All Products' dataset.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection).\r\n" }, { "ob_id": 13353, "uuid": "a456b6c4c290453d8bb436e45e616f78", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): Daily global remote sensing reflectance gridded on a sinusoidal projection, Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 1.0 Remote Sensing Reflectance product on a sinusoidal projection at approximately 4 km spatial resolution and at a daily time resolution. Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data. Note, this dataset is also contained within the 'All Products' dataset.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n" }, { "ob_id": 19885, "uuid": "8b087afe9d53471ea98ffa092867d289", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global remote sensing reflectance gridded on a sinusoidal projection, Version 2.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 2.0 Remote Sensing Reflectance product on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data. Note, these data are also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n\r\nPlease note, this dataset has been superseded. Later version of the data are now available." }, { "ob_id": 25366, "uuid": "97aebb95404a4bde8405e9cf7e32b9f8", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global ocean colour data products gridded on a geographic projection (All Products), Version 3.1", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 3.1 generated ocean colour products on a geographic projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Data are also available as monthly climatologies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, { "ob_id": 13361, "uuid": "ea0729b565014b08b5d5b5efe499edba", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean Colour CCI): 8-day global ocean colour data products gridded on a sinusoidal projection (All Products), Version 1.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 1.0 generated ocean colour products on a sinusoidal projection at 4 km spatial resolution and at an 8-day time resolution.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a sinusoidal projection.)" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 51755, 51756, 51754, 76560, 105398, 105425, 105449, 52472, 76586, 76612, 76638, 76664, 76690, 76716, 76742, 76768, 76794, 76820, 76846, 76872, 76898, 76924, 76950, 76976, 77002, 77028, 77054, 77080, 77106, 77132, 77158, 77184, 77210, 77236, 77262, 77288, 77314, 77340, 77366, 77392, 77418, 77444, 77470, 77496, 77522, 77548, 77574, 77600, 77626, 77652, 77678, 77704, 77730, 77756, 77782, 77808, 77834, 77860, 77886, 77912, 77938, 77964, 77990, 78016, 78042, 78068, 78094, 78120, 78146, 78172, 78198, 78224, 78250, 78276 ], "onlineresource_set": [ 7978, 7980, 7979 ], "project_set": [ 13365 ] }, { "ob_id": 13600, "uuid": "726ce54c74a0479a965a9231744c3eae", "short_code": "coll", "title": "UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) FAAM Aircraft campaign", "abstract": "The UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project aimed at quantifying the chemical and microphysical properties of Saharan dust in the tropical Atlantic region.\r\n\r\nCase studies were conducted using in situ measurements made by the FAAM BAe-146 aircraft to predict dust deposition to the northern hemisphere Atlantic Ocean. These studies aimed at describing how changing chemical and physical properties in the dust affect its long range transport and also assessed the radiative impact of the dust and its effect on sea surface temperatures in nutrient rich waters of the Atlantic Ocean. The dust sources were fingerprinted using single particle characterisation and by assessing their main composition. The climatological representativeness of the studies will be assessed and used to predict the seasonal footprint of dust deposition to the north Atlantic Ocean. \r\n\r\nTwo aircraft campaigns using the Facility for Airborne Atmospheric Measurements (FAAM) aircraft were conducted:\r\n\r\n- DODO 1 in association with the DABEX campaign from Dakar in Jan-Feb. 2006 \r\n- DODO2 in association with the AMMA campaign from Dakar in Sep-Oct. 2006.\r\n\r\nMeasurements have included Chemical composition, microphysics and optical properties of aerosols, Radiative fluxes, Trace gas chemistry.\r\n", "keywords": "DODO, AMMA, DABEX, SOLAS, Africa, aerosols, FAAM", "publicationState": "published", "dataPublishedTime": "2006-12-10T03:17:16", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 71 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1142, "name": "NDGO0005" } ], "member": [ { "ob_id": 18837, "uuid": "c801d0b21def42bdb00ed47fdf1df14a", "short_code": "ob", "title": "FAAM B173 DODO flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." }, { "ob_id": 17125, "uuid": "8e88a61f4e86478aba316c8aaaff0bfa", "short_code": "ob", "title": "FAAM B241 DODO flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." }, { "ob_id": 17121, "uuid": "3b942ad9a45a41bc89cfe10e7d9e28ff", "short_code": "ob", "title": "FAAM B240 DODO flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." }, { "ob_id": 17020, "uuid": "7bed64a035f347cf86b7dee9ed5a9875", "short_code": "ob", "title": "FAAM B236 DODO flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." }, { "ob_id": 18085, "uuid": "277b9e63090046e58dfefdc49cf965db", "short_code": "ob", "title": "FAAM B171 DODO flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." }, { "ob_id": 18075, "uuid": "adc1c56942aa4ea19b299a5e4e00ec36", "short_code": "ob", "title": "FAAM B170 DODO flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." }, { "ob_id": 17016, "uuid": "c0274251dc1a43f991c30abd197bd752", "short_code": "ob", "title": "FAAM B237 DODO flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." }, { "ob_id": 16228, "uuid": "840e3b1e7b69403e86e4939b44c376b8", "short_code": "ob", "title": "FAAM B169 DODO flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." }, { "ob_id": 17129, "uuid": "4ce5240afe964d9c8a66f879781e22e4", "short_code": "ob", "title": "FAAM B242 DODO flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." }, { "ob_id": 18857, "uuid": "9a7be227a1464c33b3e8a7915af23334", "short_code": "ob", "title": "FAAM B174 DODO flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." }, { "ob_id": 16964, "uuid": "78562eec4d84499e93587eec9797f15d", "short_code": "ob", "title": "FAAM B238 DODO flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." }, { "ob_id": 18861, "uuid": "5ee22bd6e1c74bb3abc4368722103057", "short_code": "ob", "title": "FAAM B175 DODO flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." }, { "ob_id": 16232, "uuid": "03a70c044b4f4f618c31f0043d379712", "short_code": "ob", "title": "FAAM B168 DODO flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." }, { "ob_id": 18833, "uuid": "318c76815a2d40e6ac39d49a97be8182", "short_code": "ob", "title": "FAAM B172 DODO flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." }, { "ob_id": 16960, "uuid": "eaba665d470c42da95ffd4e73b084fbf", "short_code": "ob", "title": "FAAM B239 DODO flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for UK SOLAS Dust Outflow and Deposition to the Ocean (DODO) project." } ], "identifier_set": [ 8944, 8627 ], "responsiblepartyinfo_set": [ 52034, 52035, 52036, 52037, 52041, 52043, 52044, 52040, 52038, 52039, 55021 ], "onlineresource_set": [ 8104, 8103, 8094, 8097, 8098 ], "project_set": [ 13598 ] }, { "ob_id": 13605, "uuid": "62123bccce294d9ca34efaf5a0bdc695", "short_code": "coll", "title": "UK SOLAS Chemical and Physical Structure of the Lower Atmosphere of the Tropical Eastern North Atlantic (SLATEA) campaign", "abstract": "The UK SOLAS Chemical and Physical Structure of the Lower Atmosphere of the Tropical\r\nEastern North Atlantic (SLATEA) campaign aimed at investigating the chemical structure of the lowermost atmosphere in remote marine boundary layer regions with high ocean productivity and at quantifying chemical gradients induced at the interfacial region.\r\n\r\nFieldwork activities have included participation in the UK SOLAS RHaMBLe cruise (D319), and concurrent aircraft surveys using the NERC Dornier 228 (operated by ARSF) to determine the vertical\r\ndistribution of reactive trace gases at Cape Verde and near to the RHaMBLe cruise paths. Resulting data have included trace gases such as ozone, carbon monoxide, oxides of nitrogen, halocarbons, and volatile organic compounds (microDiracFMW, TEI 49I UV ozone analyser, Aerolaser AL 5002 fast CO analyser onboard Dornier aircraft) and Fine aerosol particles\r\n\r\n", "keywords": "SLATEA, SOLAS, Africa, aerosols, ARSF, Dornier", "publicationState": "published", "dataPublishedTime": "2006-12-10T03:17:16", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 71 ], "discoveryKeywords": [ { "ob_id": 1142, "name": "NDGO0005" }, { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 5091, "uuid": "458f1f38122cde0d1e560a6bd0333ea9", "short_code": "ob", "title": "SOLAS-SLATEA: York Ethane and Propane measurements made on board the NERC-ARSF Dornier aircraft - Cape Verde", "abstract": "The overall aim of the UK Surface Ocean / Lower Atmosphere Study (UK SOLAS) is to advance understanding of environmentally significant interactions between the atmosphere and ocean, focusing on material exchanges that involve ocean productivity, atmospheric composition and climate. The knowledge obtained will improve the predictability of climate change and give insights into the distribution and fate of persistent pollutants. The dataset contains biological and chemical measurements such as: major nutrients and trace metal concentrations in aerosol and rain samples, chemical analyses of inorganic micro-nutrients, dissolved and particulate trace metal and carbon analyses, dissolved nitrogen and organic phosphate, biological measurements including phytoplankton pigments, bacteria, picoplankton and larger phytoplankton abundance." }, { "ob_id": 5084, "uuid": "271b0a66ed2afba3e1fc5355a45ab7be", "short_code": "ob", "title": "SOLAS-SLATEA: Meteorology and chemistry measurements made on board the NERC-ARSF Dornier aircraft - Cape Verde", "abstract": "The overall aim of the UK Surface Ocean / Lower Atmosphere Study (UK SOLAS) is to advance understanding of environmentally significant interactions between the atmosphere and ocean, focusing on material exchanges that involve ocean productivity, atmospheric composition and climate. The knowledge obtained will improve the predictability of climate change and give insights into the distribution and fate of persistent pollutants. The dataset contains biological and chemical measurements such as: major nutrients and trace metal concentrations in aerosol and rain samples, chemical analyses of inorganic micro-nutrients, dissolved and particulate trace metal and carbon analyses, dissolved nitrogen and organic phosphate, biological measurements including phytoplankton pigments, bacteria, picoplankton and larger phytoplankton abundance." }, { "ob_id": 5079, "uuid": "17b49dadc38ad340fcd927c232088d4b", "short_code": "ob", "title": "SOLAS-SLATEA: Green House Gas measurements from the Cambridge microDirac instrument on board the NERC-ARSF Dornier aircraft - Cape Verde", "abstract": "The overall aim of the UK Surface Ocean / Lower Atmosphere Study (UK SOLAS) is to advance understanding of environmentally significant interactions between the atmosphere and ocean, focusing on material exchanges that involve ocean productivity, atmospheric composition and climate. The knowledge obtained will improve the predictability of climate change and give insights into the distribution and fate of persistent pollutants. The dataset contains biological and chemical measurements such as: major nutrients and trace metal concentrations in aerosol and rain samples, chemical analyses of inorganic micro-nutrients, dissolved and particulate trace metal and carbon analyses, dissolved nitrogen and organic phosphate, biological measurements including phytoplankton pigments, bacteria, picoplankton and larger phytoplankton abundance." } ], "identifier_set": [ 8634 ], "responsiblepartyinfo_set": [ 52085, 52086, 52087, 52088, 52092, 52093, 52094, 52090, 52089, 52091, 52095, 55022, 52096 ], "onlineresource_set": [ 8116, 8117, 8118 ], "project_set": [ 13599 ] }, { "ob_id": 13606, "uuid": "e661035fa87f414ea2615b2b46596acb", "short_code": "coll", "title": "UK SOLAS Reactive halogens in the marine boundary layer (RHaMBLe) campaign at Roscoff, Brittany, France (July-August 2006)", "abstract": "The UK SOLAS Reactive halogens in the marine boundary layer (RHaMBLe) campaign aimed at quantifying marine halogen cycling and investigating its spatial variability. The aim was also to determine the effects of marine halogen cycling on atmospheric oxidative chemistry.\r\n\r\nCoastal observations were made during the summer of 2006 at Roscoff Bay,Brittany, France. \r\n\r\nMeasurements included trace molecules and radicals, aerosol characteristics and distribution.\r\n\r\nThe coastal component of RHaMBle, carried out in Roscoff bay provided direct observational linkage\r\nbetween new particle formation and reactive halogens, resulting in the development of a new\r\nparameterisation for use in large-scale models.\r\n\r\n", "keywords": "Rhamble, SOLAS, brittany, Roscoff, aerosols", "publicationState": "published", "dataPublishedTime": "2006-12-10T03:17:16", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 71 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1142, "name": "NDGO0005" } ], "member": [ { "ob_id": 5101, "uuid": "10d7fdf1b467b8b5629bb1150ef5dcf8", "short_code": "ob", "title": "SOLAS-Rhamble: Roscoff experiment Halocarbon measurements", "abstract": "The overall aim of the UK Surface Ocean / Lower Atmosphere Study (UK SOLAS) is to advance understanding of environmentally significant interactions between the atmosphere and ocean, focusing on material exchanges that involve ocean productivity, atmospheric composition and climate. The knowledge obtained will improve the predictability of climate change and give insights into the distribution and fate of persistent pollutants. The dataset contains biological and chemical measurements such as: major nutrients and trace metal concentrations in aerosol and rain samples, chemical analyses of inorganic micro-nutrients, dissolved and particulate trace metal and carbon analyses, dissolved nitrogen and organic phosphate, biological measurements including phytoplankton pigments, bacteria, picoplankton and larger phytoplankton abundance." }, { "ob_id": 5111, "uuid": "4cb65b399494b300e2bf647f828a20c3", "short_code": "ob", "title": "SOLAS-Rhamble: Roscoff experiment Micrometeorological parameters, ozone and particle fluxes", "abstract": "The overall aim of the UK Surface Ocean / Lower Atmosphere Study (UK SOLAS) is to advance understanding of environmentally significant interactions between the atmosphere and ocean, focusing on material exchanges that involve ocean productivity, atmospheric composition and climate. The knowledge obtained will improve the predictability of climate change and give insights into the distribution and fate of persistent pollutants. The dataset contains biological and chemical measurements such as: major nutrients and trace metal concentrations in aerosol and rain samples, chemical analyses of inorganic micro-nutrients, dissolved and particulate trace metal and carbon analyses, dissolved nitrogen and organic phosphate, biological measurements including phytoplankton pigments, bacteria, picoplankton and larger phytoplankton abundance." }, { "ob_id": 5104, "uuid": "71cdcf18af78758c41025f709554dda8", "short_code": "ob", "title": "SOLAS-Rhamble: Roscoff experiment Ozone measurements", "abstract": "The overall aim of the UK Surface Ocean / Lower Atmosphere Study (UK SOLAS) is to advance understanding of environmentally significant interactions between the atmosphere and ocean, focusing on material exchanges that involve ocean productivity, atmospheric composition and climate. The knowledge obtained will improve the predictability of climate change and give insights into the distribution and fate of persistent pollutants. The dataset contains biological and chemical measurements such as: major nutrients and trace metal concentrations in aerosol and rain samples, chemical analyses of inorganic micro-nutrients, dissolved and particulate trace metal and carbon analyses, dissolved nitrogen and organic phosphate, biological measurements including phytoplankton pigments, bacteria, picoplankton and larger phytoplankton abundance." }, { "ob_id": 5071, "uuid": "5c5da0f5148e85f906fd4dbf0b169a86", "short_code": "ob", "title": "SOLAS-Rhamble: Roscoff Experiment University of Leeds Laser Induced Fluorescence", "abstract": "The overall aim of the UK Surface Ocean / Lower Atmosphere Study (UK SOLAS) is to advance understanding of environmentally significant interactions between the atmosphere and ocean, focusing on material exchanges that involve ocean productivity, atmospheric composition and climate. The knowledge obtained will improve the predictability of climate change and give insights into the distribution and fate of persistent pollutants. The dataset contains biological and chemical measurements such as: major nutrients and trace metal concentrations in aerosol and rain samples, chemical analyses of inorganic micro-nutrients, dissolved and particulate trace metal and carbon analyses, dissolved nitrogen and organic phosphate, biological measurements including phytoplankton pigments, bacteria, picoplankton and larger phytoplankton abundance." }, { "ob_id": 5107, "uuid": "ca301ffd2207907dd45660492d13b250", "short_code": "ob", "title": "SOLAS-Rhamble: Roscoff Experiment Longpath DOAS from Leeds", "abstract": "The overall aim of the UK Surface Ocean / Lower Atmosphere Study (UK SOLAS) is to advance understanding of environmentally significant interactions between the atmosphere and ocean, focusing on material exchanges that involve ocean productivity, atmospheric composition and climate. The knowledge obtained will improve the predictability of climate change and give insights into the distribution and fate of persistent pollutants. The dataset contains biological and chemical measurements such as: major nutrients and trace metal concentrations in aerosol and rain samples, chemical analyses of inorganic micro-nutrients, dissolved and particulate trace metal and carbon analyses, dissolved nitrogen and organic phosphate, biological measurements including phytoplankton pigments, bacteria, picoplankton and larger phytoplankton abundance." }, { "ob_id": 5097, "uuid": "b8de63f50e61dfcd4cf5249aa233fb76", "short_code": "ob", "title": "SOLAS-Rhamble: Roscoff experiment NOxy measurements", "abstract": "The overall aim of the UK Surface Ocean / Lower Atmosphere Study (UK SOLAS) is to advance understanding of environmentally significant interactions between the atmosphere and ocean, focusing on material exchanges that involve ocean productivity, atmospheric composition and climate. The knowledge obtained will improve the predictability of climate change and give insights into the distribution and fate of persistent pollutants. The dataset contains biological and chemical measurements such as: major nutrients and trace metal concentrations in aerosol and rain samples, chemical analyses of inorganic micro-nutrients, dissolved and particulate trace metal and carbon analyses, dissolved nitrogen and organic phosphate, biological measurements including phytoplankton pigments, bacteria, picoplankton and larger phytoplankton abundance." } ], "identifier_set": [ 8635 ], "responsiblepartyinfo_set": [ 52097, 52098, 52099, 52100, 52105, 52106, 52108, 52101, 52103, 52102, 52104, 55031, 52107, 52109, 52110, 52111 ], "onlineresource_set": [ 8119, 8120, 8121 ], "project_set": [ 5099 ] }, { "ob_id": 13607, "uuid": "a2d86deca5264e38bce22b8c96f01d99", "short_code": "coll", "title": "UK SOLAS Reactive halogens in the marine boundary layer (RHaMBLe) campaign at Cape Verde (2007)", "abstract": "The UK SOLAS Reactive halogens in the marine boundary layer (RHaMBLe) campaign aimed at quantifying marine halogen cycling and investigating its spatial variability. The aim was also to determine the effects of marine halogen cycling on atmospheric oxidative chemistry.\r\n\r\nFieldwork has provided observations at the SOLAS Cape Verde Observatory in May 2007.\r\n\r\nMeasurements included trace molecules and radicals, aerosol characteristics and distribution (Leeds FAGE, filter packs, mist chambers).\r\n\r\n", "keywords": "Rhamble, SOLAS, Cape Verde, aerosols", "publicationState": "published", "dataPublishedTime": "2006-12-10T03:17:16", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 71 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1142, "name": "NDGO0005" } ], "member": [ { "ob_id": 13974, "uuid": "dc4cccdd3d18437f8ccd2fd212719c0d", "short_code": "ob", "title": "SOLAS-RHAMBLE: OH and HO2 measurements at Cape Verde Observatory", "abstract": "Data from observations made at the The Cape Verde Atmospheric Observatory (16.848N, 24.871W) 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. 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. The dataset contains mixing ratio measurements of OH and HO2 from University of Leeds during the SOLAS-RHAMBLE intensive measurement campaign.\r\n" }, { "ob_id": 13980, "uuid": "4de51ed6c5d043c28da6719908dc535a", "short_code": "ob", "title": "SOLAS-RHAMBLE: Mist Chamber measurements at Cape Verde Observatory", "abstract": "Data from observations made at the The Cape Verde Atmospheric Observatory (16.848N, 24.871W) 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. 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. The dataset contains mixing ratios of Acetic acid, Formic acid, HCl, Nitric acid, Ammonia gas and Nitrous acid gas from the University of Virginia Tandem mist chambers during the SOLAS-RHAMBLE intensive campaign.\r\n" }, { "ob_id": 13976, "uuid": "986f60f495f147909226fb7141ea4ffa", "short_code": "ob", "title": "SOLAS-RHAMBLE: Filter pack aerosol measurements at Cape Verde Observatory", "abstract": "Data from observations made at the The Cape Verde Atmospheric Observatory (16.848N, 24.871W) 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. 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. The dataset contains 47 mm diameter filter packs measurements from the University of New Hampshire, collected during the SOLAS-RHAMBLE intensive measurement campaign.\r\n" } ], "identifier_set": [ 8636 ], "responsiblepartyinfo_set": [ 52112, 52113, 52114, 52115, 52119, 52121, 52123, 52117, 52116, 52125, 52127, 55033, 52128 ], "onlineresource_set": [ 8124, 8122, 8123 ], "project_set": [ 5099 ] }, { "ob_id": 13702, "uuid": "bfbd5ec825fa422f9a858b14ae7b2a0d", "short_code": "coll", "title": "VolcanEESM (Volcanic Emissions for Earth System Models): Volcanic sulphur dioxide (SO2) emissions database from 1850 to present", "abstract": "The VolcanEESM database was a combination of all global volcanic emissions of SO2 (amount and location) collated from the available literature. Currently, the database is available for the period 1850-2015, but this is expected to be updated yearly with additional information. \r\n\r\nThe database includes no information about the size, mass, distribution or optical depth of resulting aerosol. As such the database is model agnostic and it is up to each modeling group to make decisions about how to implement the emission file in their prognostic stratospheric aerosol scheme. \r\n\r\nRevisions to databases, such as VolcanEESM, are part of the scientific process. Thus, the database is freely available for others to use and report back any errors or comments they may have to the database's curators. ", "keywords": "Volcano, SO2, sulphur dioxide, volcanic eruptions, Earth System Models, VolcanEESM", "publicationState": "published", "dataPublishedTime": "2016-02-03T16:09:13", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 13 ], "discoveryKeywords": [ { "ob_id": 1142, "name": "NDGO0005" }, { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 13703, "uuid": "a8a7e52b299a46c9b09d8e56b283d385", "short_code": "ob", "title": "VolcanEESM: Global volcanic sulphur dioxide (SO2) emissions database from 1850 to present - Version 1.0", "abstract": "This dataset is associated with the VolcanEESM project led by the project team at the University of Leeds. The project was funded by NCAR/UCAR Atmospheric Chemistry and Modeling Visiting Scientist Program, NCAS, University of Leeds. \r\n\r\nThe global volcanic sulphur dioxide (SO2) emissions database is a combination of available information from the wider literature with as many observations of the amount and location of SO2 emitted by each volcanic eruption as possible. The database includes no information about the size, mass, distribution or optical depth of resulting aerosol. As such the database is model agnostic and it is up to each modeling group to make decisions about how to implement the emission file in their prognostic stratospheric aerosol scheme. \r\n\r\nThe dataset is divided into two parts based on the availability of satellite data. For the pre-satellite era, the necessary information about the emissions was gathered from the latest ice core records of sulphate deposition in combination historical accounts available in the wider literature (see references included in the database for specific citation for each record). In the satellite era, volcanic emissions were primarily derived from remotely sensed observations. \r\n\r\nFor the period 1850 CE to 1979 the dataset combined the most recent volcanic sulfate deposition datasets from ice cores with volcanological and, where applicable, petrological estimates of the SO2 mass emitted as well as historical records of large-magnitude volcanic eruptions. In detail, for the majority of eruptions between 1850 CE to 1979 , there are few direct measurement of SO2 emissions or quantitative observations of the plume height and very few measurements of the aerosol optical depth (AOD). \r\n\r\nParameters in the database include: \r\nDay_of_Emission: The 24 hour period in which the emission is thought to have occurred. (Ordered by the variable Eruption_Number starting with the first eruption in the database.)\r\n\r\nEruption: Field that contains the Volcano_Number (Which uniquely identifies each volcano in the Global Volcanism Program Database), Volcano_Name (official name from the Global Volcanism Program Database), Notes_and_References (list of notes about the observed parameters and references used to derive each entry). ( Ordered by the variable Eruption_Number starting with the first eruption in the database.)\r\n\r\nLatitude: Latitude of each emission from -90 to +90 (Ordered by the variable Eruption_Number starting with the first eruption in the database.)\r\n\r\nLongitude: Longitude of each emission degrees East (Ordered by the variable Eruption_Number starting with the first eruption in the database.)\r\n\r\nVEI: Volcanic Explosively Index of each emission based on Global Volcanism Program Database (Ordered by the variable Eruption_Number starting with the first eruption in the database.)\r\n\r\nTotal_Emission_of_SO2_Tg: Total emission of SO2 in teragram for the specific database entry (Ordered by the variable Eruption_Number starting with the first eruption in the database.)\r\n\r\nMaximum_Injection_Height_km: Maximum height of each emission in kilometers above sea level. (Ordered by the variable Eruption_Number starting with the first eruption in the database.)\r\n\r\nMinimum_Injection_Height_km: Minimum height of each emission in kilometers above sea level. (Ordered by the variable Eruption_Number starting with the first eruption in the database.)\r\n\r\nMonth_of_Emission: The month in which the emission is thought to have occurred. (Ordered by the variable Eruption_Number starting with the first eruption in the database.)\r\n\r\nYear_of_Emission: The Year in which the emission is thought to have occurred. (Ordered by the variable Eruption_Number starting with the first eruption in the database.)\r\n" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 52503, 52366, 52367, 52369, 52370, 105427, 105451, 105379, 52368 ], "onlineresource_set": [], "project_set": [ 13700 ] }, { "ob_id": 13749, "uuid": "9c8c86ed78ae4836a336d45cbb6a757c", "short_code": "coll", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes Project: Vegetation and Meteorological Observations at the Sodankyla Site", "abstract": "Vegetation and meteorological observations (snow and radiation) were collected by various ground instruments in an area of forest near Sodankyla (Finalnd) during measurement campaigns in March 2011. This data is made available through the BADC. An open area and five 20 m × 20 m forest plots were selected for shortwave and longwave radiation measurements and canopy characterization.\r\n\r\nThe Arctic Research Centre of the Finnish Meteorological Institute at Sodankylä (67°22'N, 26°38'E) has continuous weather observations dating back to 1908 and is a major centre for meteorological and remote sensing field studies. The surrounding area includes forests of Norway Spruce (Picea abies) and Scots Pine (Pinus sylvestris), extensive mires and numerous lakes that are frozen and snow-covered in winter.\r\n\r\nThis was a NERC funded project.", "keywords": "NERC, snow, sodankyla", "publicationState": "published", "dataPublishedTime": "2013-11-05T20:15:19", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1142, "name": "NDGO0005" } ], "member": [ { "ob_id": 14295, "uuid": "d852835cb64a47129dc92d6b533da623", "short_code": "ob", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes: Sodankyla Hemispherical Photography 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 hemispherical photography data collected at Sodankyla 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." }, { "ob_id": 14283, "uuid": "69f6e93f5f074580861dfdb4c3385dbe", "short_code": "ob", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes: Sodankyla 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 Sodankyla 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." }, { "ob_id": 14292, "uuid": "f3c7e70b155f4bad85432cf52c2b563c", "short_code": "ob", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes: Sodankyla Above and Below-Canopy Radiation 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 radiation data collected at Abisko site in March 2011. \r\n\r\nAbove-canopy radiation:\r\nAn open area was selected at each study site (“plot O”) for measurements assumed to be representative of incoming radiation above the nearby forest canopy. A Delta-T Devices BF3 sunshine sensor and a Kipp & Zonen CGR3 pyrgeometer were connected to a Campbell Scientific CR1000 data logger recording 5-minute averages of measurements made every 5 seconds. The BF3 measures total and diffuse incoming shortwave radiation, and the CGR3 measures thermal longwave radiation.\r\nBelow-canopy radiation:\r\n\r\nIn the forest plots, two arrays of ten Kipp & Zonen CM3 shortwave pyranometers and four Kipp & Zonen CGR3 longwave pyrgeometers were connected to AM16/32B multiplexers and Campbell Scientific CR1000 data loggers recording 5-minute averages of measurements made every 5 seconds. One array was set up in a “continuity plot” C for the entire duration of each field campaign, while the other array was moved between four “roving plots” R1 to R4, providing at least 5 complete days of data at each plot. All radiometers were placed on small plywood platforms on the snow surface and were levelled and cleared of snow every morning. Radiometer positions were recorded using differential GPS at Abisko and averages of repeated handheld GPS measurements at Sodankylä.\r\nThis was a NERC funded project." }, { "ob_id": 14289, "uuid": "07636e99b00f472bb230a2beec6a4e1b", "short_code": "ob", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes: Sodankyla 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." }, { "ob_id": 14286, "uuid": "02f968aadaad48c7a4a48b772db41a0f", "short_code": "ob", "title": "Snow-Vegetation-Atmosphere Interactions over Heterogeneous Landscapes: Sodankyla 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 Sodankyla 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." } ], "identifier_set": [ 8683 ], "responsiblepartyinfo_set": [ 52616, 52617, 52618, 52626, 52621, 52623, 52625, 52620, 52619, 54896, 52622, 52624 ], "onlineresource_set": [ 8267, 8254, 8253, 8275 ], "project_set": [] }, { "ob_id": 13771, "uuid": "57116a45a09847a68395c75362436e05", "short_code": "coll", "title": "Hourly climate data from 23 stations on Kilimanjaro (East Africa) over three years - Version 1.0", "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\nTemperature and relative humidity (RH) data were collected hourly from 23 stations located on Mount Kilimanjaro between September 2012 to September 2015. \r\n\r\n", "keywords": "temperature, relative humidity, Kilimanjaro, mountain", "publicationState": "citable", "dataPublishedTime": "2016-02-08T12:14:53", "doiPublishedTime": "2016-02-09T16:48:04", "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1142, "name": "NDGO0005" } ], "member": [ { "ob_id": 13773, "uuid": "bf8d6babeb904fbbaff7e279f9c0db02", "short_code": "ob", "title": "Temperature 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\nTemperature measurements were taken at hourly intervals at 23 stations on Mount Kilimanjaro between September 2012 and September 2015. Specific station locations (elevation and lat/long) are stated in the data and are ordered in a transect across the mountain from South-West over the top to North-East. \r\n\r\nTwo of the stations have both ground level and air level sensors (hence there are 25 readings not 23). \r\n\r\nAdditional information about station locations and missing data can be found in a PDF on the CEDA archive. " }, { "ob_id": 13772, "uuid": "e8a3561149c0448fa34bd64f072d69f1", "short_code": "ob", "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. Specific station locations (elevation and lat/long) are stated in the data and are ordered in a transect across the mountain from South-West over the top to North-East. \r\n\r\nTwo of the stations have both ground level and air level sensors (hence there are 25 readings not 23). \r\n\r\nAdditional information about station locations and missing data can be found in a PDF on the CEDA archive. " } ], "identifier_set": [ 8774, 8689 ], "responsiblepartyinfo_set": [ 52724, 52726, 52730, 52731, 52732, 52727, 52728, 52729, 52725 ], "onlineresource_set": [ 8675 ], "project_set": [ 12135 ] }, { "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", "keywords": "NERC, RM2010, sulphur, tree rings, Italy, UK", "publicationState": "published", "dataPublishedTime": "2015-12-16T20:14:30", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1142, "name": "NDGO0005" } ], "member": [ { "ob_id": 13801, "uuid": "672e6e5d9aae4eac805175a80e40b535", "short_code": "ob", "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." } ], "identifier_set": [ 8690 ], "responsiblepartyinfo_set": [ 52806, 52807, 52808, 52810, 52811, 52809, 52858, 52859, 53622 ], "onlineresource_set": [ 8324 ], "project_set": [ 12274 ] }, { "ob_id": 14135, "uuid": "61e6e242d5334cf0949e2c3e969b96d1", "short_code": "coll", "title": "Centre for Ecology and Hydrology: Long-term monitoring of PAN (peroxyacetyl nitrate) in eastern Scotland 1993-1999", "abstract": "Hourly measurement data for PAN (peroxyacetyl nitrate) mixing ratios in the atmosphere at a rural site at Bush Estate, Penicuik EH26 0QB (CEH Edinburgh), 15 km south of Edinburgh, from 1993 to 1999 in ppt (parts per trillion). Measurements were made using a gas chromatograph with electron capture detector. \r\n\r\nAnnual average concentrations were between 0.1 and 0.15 nl l-1, with episodes up to 3 nl l-1 in long-range transported polluted air. PAN concentrations were approximately log-normally distributed. The concentrations measured are the result of a balance between photochemical production rates and removal by thermal decomposition and dry deposition. \r\n\r\nThere was a pronounced seasonal maximum in PAN concentrations in late spring, and a strong diurnal cycle only in April-June, with a maximum at 1700 h. Individual episodes, with concentrations up to 3 nl l-1, could be traced over distances of ca. 1000 km, with rapid changes in concentration as the prevailing winds advected polluted air masses across the site.", "keywords": "CEH, PAN, Chemistry", "publicationState": "published", "dataPublishedTime": "2016-02-22T15:55:47", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 132 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 14136, "uuid": "5e650bc4a1b846d88b08b464d6df9b35", "short_code": "ob", "title": "Centre of Ecology and Hydrology (CEH): Long-term PAN measurements from eastern Scotland (1993-1999)", "abstract": "Hourly measurement data for PAN (peroxyacetyl nitrate) mixing ratios in the atmosphere at a rural site at Bush Estate, Penicuik EH26 0QB (CEH Edinburgh), 15 km south of Edinburgh, from 1993 to 1999 in ppt (parts in 10^12). Measurements were made using a gas chromatograph with electron capture detector. \r\n\r\nAnnual average concentrations were between 0.1 and 0.15 nl l-1, with episodes up to 3 nl l-1 in long-range transported polluted air. PAN concentrations were approximately log-normally distributed. The concentrations measured are the result of a balance between photochemical production rates and removal by thermal decomposition and dry deposition. \r\n\r\nThere was a pronounced seasonal maximum in PAN concentrations in late spring, and a strong diurnal cycle only in April-June, with a maximum at 1700 h. Individual episodes, with concentrations up to 3 nl l-1, could be traced over distances of ca. 1000 km, with rapid changes in concentration as the prevailing winds advected polluted air masses across the site." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 54213, 54214, 54212, 54221, 54220, 54219, 54225, 54211, 54218, 54222, 54215 ], "onlineresource_set": [ 8561 ], "project_set": [ 14133 ] }, { "ob_id": 14148, "uuid": "5806da02ef934a7c83d959bed50c2252", "short_code": "coll", "title": "ESA Ozone Climate Change Initiative (Ozone CCI) Dataset Collection", "abstract": "Datasets of ozone products produced by the ozone project within the ESA Climate Change Initiative (CCI). The project focuses on developing, delivering and characterizing a number of ozone ECV data products generated from European nadir, limb and occultation satellite sensors.\r\n\r\nThree main product lines have been developed:\r\n\r\nTotal ozone from nadir UV backscatter sensors:\r\nA time-series covering the period from 1995 until present generated by merging total ozone measurements from the GOME, SCIAMACHY, GOME-2 and OMI instruments. All European sensors are processed using the state-of-the-art direct-fitting algorithm developed for GOME (GDP5). \r\n\r\nOzone profiles from nadir UV backscatter sensors:\r\nA merged ozone profile data set from GOME, SCIAMACHY, OMI and GOME-2 instruments generated for a minimum of two contiguous years. Best elements from existing retrieval codes are combined in a single CCI algorithm applied to all sensors.\r\n\r\nOzone profiles from limb and occultation sensors:\r\nA merged ozone profile data set covering at least two contiguous years created from all limb/occultation sensors onboard of ENVISAT (GOMOS, MIPAS, SCIAMACHY) as well as from the Third Party Missions OSIRIS, SMR and ACE/FTS.", "keywords": "ESA, Ozone, CCI, ECV", "publicationState": "published", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 95 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 14159, "uuid": "1f9f3e03137c48a086d008ba7b5cd48b", "short_code": "ob", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): Merged Level 3 Limb Ozone Semi-Monthly Mean Profiles, Version 2", "abstract": "This dataset consists of a gridded composite of limb ozone profile data, combining data from a range of instruments. \r\n\r\nThe Merged Semi-Monthly Mean (MSMM) dataset is created using measurements from limb sensors participating in Ozone_cci project, for years 2007-2008.\r\n\r\nFirst, the ozone profiles from individual instruments are averaged in 10° x 20° latitude-longitude zones over half-month time intervals, and then merged.\r\nThe merged semi-monthly mean ozone profiles are structured into yearly netcdf files with self-explanatory names. For example, the file “ESACCI-OZONE-L3-LP-SMM-2008-fv0002.nc” contains the semi-monthly mean ozone profiles for January 2008. In addition to the variables of the merged data, the profiles from individual instruments with their uncertainty parameters are also included (for the altitude range 250-1 hPa used in data merging)." }, { "ob_id": 14158, "uuid": "00a0da5d759d4d69ae866a23b84011be", "short_code": "ob", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): Merged Level 3 Limb Ozone Monthly Zonal Mean (MZM) Profiles, Version 2", "abstract": "This dataset consists of a gridded composite of limb ozone profile data, combining data from a range of instruments. \r\n\r\nThe data are zonal mean time series (10° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean. \r\n\r\nThe merged monthly zonal mean data (MMZM) include merged ozone profiles in 10° latitude zones for each month, on the ozone-CCI pressure grid from 250 hPa to 1 hPa, and the parameters which characterize the uncertainty of the merged profiles. In Phase I of the ESA CCI Programme, the dataset has been created for 2 years, 2007 and 2008.\r\n\r\nThe merged monthly zonal mean data are structured into monthly netcdf files with self-explanatory names. For example, the file “ESACCI-OZONE-L3-LP-MERGED-MZM-200801-fv0002.nc” contains merged monthly zonal mean data for January 2008. In addition to the variables of the merged data, the profiles from individual instruments with their uncertainty parameters are also included (for the altitude range 250-1 hPa used in data merging)." }, { "ob_id": 33001, "uuid": "e0329fa69dfa49d0903e132dca1c4890", "short_code": "ob", "title": "ESA Ozone Climate Change Initiative (Ozone_cci): MErged GRIdded Dataset of Ozone Profiles (MEGRIDOP), v0001", "abstract": "This dataset comprises the MErged GRIdded Dataset of Ozone Profiles (MEGRIDOP) in the stratosphere with a resolved longitudinal structure, which is derived from data by six limb and occultation satellite instruments: GOMOS, SCIAMACHY and MIPAS on Envisat, OSIRIS on Odin, OMPS on Suomi-NPP, and MLS on Aura. The merged dataset was generated as a contribution to the European Space Agency Climate Change Initiative Ozone project (Ozone_cci). The period of this merged time series of ozone profiles is from late 2001 until the end of 2022.\r\n\r\nThe monthly mean gridded ozone profiles and deseasonalised anomalies are provided in the altitude range from 10 to 50 km in bins of 10 degree latitude x 20 degree longitude. \r\n\r\nFor more details please see the associated readme file and Sofieva, V. F., Szeląg, M., Tamminen, J., Kyrölä, E., Degenstein, D., Roth, C., Zawada, D., Rozanov, A., Arosio, C., Burrows, J. P., Weber, M., Laeng, A., Stiller, G. P., von Clarmann, T., Froidevaux, L., Livesey, N., van Roozendael, M. and Retscher, C.: Measurement report: regional trends of stratospheric ozone evaluated using the MErged GRIdded Dataset of Ozone Profiles (MEGRIDOP), Atmos. Chem. Phys., 21(9), 6707–6720, doi:10.5194/acp-21-6707-2021, 2021" }, { "ob_id": 14152, "uuid": "b431fbecf73c4442ad5d7bcf80929b03", "short_code": "ob", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): GOMOS Level 3 Limb Ozone Monthly Zonal Mean (MZM) Profiles, Version 1", "abstract": "This dataset comprises gridded limb ozone monthly zonal mean profiles from the GOMOS instrument. \r\n\r\nThe data are zonal mean time series (10° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean.\r\n\r\nThe monthly zonal mean (MZM) data set provides ozone profiles averaged in 10° latitude zones from 90°S to 90°N, for each month. The monthly zonal mean data are structured into yearly netcdf files, for each instrument separately. The filename indicates the instrument and the year. For example, the file “ESACCI-OZONE-L3-LP-GOMOS_ENVISAT-MZM-2008.nc” contains monthly zonal mean data for GOMOS in 2008." }, { "ob_id": 14156, "uuid": "add104f4c4454b629dbc7648efaa1b50", "short_code": "ob", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): ODIN/SMR (544.6 GHz) Level 3 Limb Ozone Monthly Zonal Mean (MZM) Profiles, Version 1", "abstract": "This dataset comprises gridded limb ozone monthly zonal mean profiles from the ODIN/SMR (544.6 GHz) instrument. \r\n\r\nThe data are zonal mean time series (10° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean.\r\n\r\nThe monthly zonal mean (MZM) data set provides ozone profiles averaged in 10° latitude zones from 90°S to 90°N, for each month. The monthly zonal mean data are structured into yearly netcdf files, for each instrument separately. The filename indicates the instrument and the year. For example, the file “ESACCI-OZONE-L3-LP-MZM-SMR_ODIN-544_6_GHz-2008-fv0001.nc” contains monthly zonal mean data for ODIN/SMR at 544.6GHz in 2008." }, { "ob_id": 14149, "uuid": "0d2260ad4e2c42b6b14fe5b3308f5eaa", "short_code": "ob", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): Level 3 Total Ozone Merged Data Product, version 01", "abstract": "This dataset is a monthly mean gridded total ozone data record (level 3) produced by the ESA Ozone Climate Change Initiative project (Ozone CCI). The dataset is a prototype of a merged harmonised ozone data record combining ozone data from the GOME instrument on ERS-2, the SCIAMACHY instrument on ENVISAT and the GOME-2 instrument on METOP-A, and covers the period between April 1996 to June 2011." }, { "ob_id": 33000, "uuid": "8220babd91534bb3b83b87141c4ccc14", "short_code": "ob", "title": "ESA Ozone Climate Change Initiative (Ozone_cci): Merged SAGE II, Ozone_cci and OMPS-LP dataset of ozone profiles, v0002", "abstract": "The merged SAGE-CCI-OMPS+ dataset of ozone profiles is created using the data from several satellite instruments: SAGE II on ERBS; GOMOS, SCIAMACHY and MIPAS on Envisat; OSIRIS on Odin; ACE-FTS on SCISAT; OMPS on Suomi-NPP; POAM III on SPOT 4 and SAGE III on ISS. The merged dataset is created in the framework of European Space Agency Climate Change Initiative (Ozone_cci) with the aim of analyzing stratospheric ozone trends. For the merged dataset, we used the latest versions of the original ozone datasets. The long-term SAGE-CCI-OMPS+ dataset is created by computation and merging of deseasonalized anomalies from individual instruments. The detailed description of the dataset can be found in (Sofieva et al., 2017) and (Sofieva et al., 2023).\r\n\r\nThe merged SAGE-CCI-OMPS+ dataset consists of deseasonalized anomalies of ozone and ozone concentrations in 10 degree latitude bands from 90S to 90N and from 10 to 50 km in steps of 1 km covering the period from October 1984 to December 2021." }, { "ob_id": 14155, "uuid": "fe651dbef5d44248bef70906f4b3d12b", "short_code": "ob", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): ODIN/SMR Level 3 Limb Ozone Monthly Zonal Mean (MZM) Profiles, Version 1", "abstract": "This dataset comprises gridded limb ozone monthly zonal mean profiles from the ODIN/SMR instrument. \r\n\r\nThe data are zonal mean time series (10° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean.\r\n\r\nThe monthly zonal mean (MZM) data set provides ozone profiles averaged in 10° latitude zones from 90°S to 90°N, for each month. The monthly zonal mean data are structured into yearly netcdf files, for each instrument separately. The filename indicates the instrument and the year. For example, the file “ESACCI-OZONE-L3-LP-SMR_ODIN-MZM-2008-fv0001.nc” contains monthly zonal mean data for ODIN/SMR in 2008." }, { "ob_id": 14150, "uuid": "4eb4e801424a47f7b77434291921f889", "short_code": "ob", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): Level 3 Nadir Ozone Profile Merged Data Product, version 2", "abstract": "This dataset contains Level 3 nadir profile ozone data from the ESA Ozone Climate Change Initiative (CCI) project. The Level 3 data are monthly averages on a regular 3D grid derived from level 2 ozone profiles. In this version 2 of the dataset, data are available for 1997 and 2007 and 2008 only, and use data from the GOME instrument on ERS (1997) and the GOME-2 instrument on METOP-A (2007, 2008)." }, { "ob_id": 14154, "uuid": "f428fffb26cf4cd5b97dfb6381cb16bb", "short_code": "ob", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): OSIRIS Level 3 Limb Ozone Monthly Zonal Mean (MZM) Profiles, Version 1", "abstract": "This dataset comprises gridded limb ozone monthly zonal mean profiles from the OSIRIS instrument on the ODIN satellite. \r\n\r\nThe data are zonal mean time series (10° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean.\r\n\r\nThe monthly zonal mean (MZM) data set provides ozone profiles averaged in 10° latitude zones from 90°S to 90°N, for each month. The monthly zonal mean data are structured into yearly netcdf files, for each instrument separately. The filename indicates the instrument and the year. For example, the file “ESACCI-OZONE-L3-LP-OSIRIS_ODIN-MZM-2008-fv0001.nc” contains monthly zonal mean data for OSIRIS in 2008." }, { "ob_id": 14151, "uuid": "cb54bd70826842a9acf658ebabe4a104", "short_code": "ob", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): SCIAMACHY Level 3 Limb Ozone Monthly Zonal Mean (MZM) Profiles, Version 1", "abstract": "This dataset comprises gridded limb ozone monthly zonal mean profiles from the SCIAMACHY instrument on ENVISAT. \r\n\r\nThe data are zonal mean time series (10° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean.\r\n\r\nThe monthly zonal mean (MZM) data set provides ozone profiles averaged in 10° latitude zones from 90°S to 90°N, for each month. The monthly zonal mean data are structured into yearly netcdf files, for each instrument separately. The filename indicates the instrument and the year. For example, the file “ESACCI-OZONE-L3-LP-SCIAMACHY_ENVISAT-MZM-2008-fv0001.nc” contains monthly zonal mean data for SCIAMACHY in 2008." }, { "ob_id": 14153, "uuid": "4e106bb70a6b42d8a5a86c4635c855b9", "short_code": "ob", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): MIPAS Level 3 Limb Ozone Monthly Zonal Mean (MZM) Profiles, Version 1", "abstract": "This dataset comprises gridded limb ozone monthly zonal mean profiles from the MIPAS instrument on the ENVISAT satellite. \r\n\r\nThe data are zonal mean time series (10° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean.\r\n\r\nThe monthly zonal mean (MZM) data set provides ozone profiles averaged in 10° latitude zones from 90°S to 90°N, for each month. The monthly zonal mean data are structured into yearly netcdf files, for each instrument separately. The filename indicates the instrument and the year. For example, the file \"ESACCI-OZONE-L3-LP-MIPAS_ENVISAT-MZM-2008-fv0001.nc“ contains monthly zonal mean data for MIPAS in 2008." }, { "ob_id": 14157, "uuid": "ccbeb356a88847058159049678fe5c35", "short_code": "ob", "title": "ESA Ozone Climate Change Initiative (Ozone CCI): ACE Level 3 Limb Ozone Monthly Zonal Mean (MZM) Profiles, Version 1", "abstract": "This dataset comprises gridded limb ozone monthly zonal mean profiles from the ACE FTS instrument on the SCISAT satellite. \r\n\r\nThe data are zonal mean time series (10° latitude bin) and include uncertainty/variability of the Monthly Zonal Mean.\r\n\r\nThe monthly zonal mean (MZM) data set provides ozone profiles averaged in 10° latitude zones from 90°S to 90°N, for each month. The monthly zonal mean data are structured into yearly netcdf files, for each instrument separately. The filename indicates the instrument and the year. For example, the file “ESACCI-OZONE-L3-LP-ACE_FTS_SCISAT-MZM-2008-fv0001.nc” contains monthly zonal mean data for ACE in 2008." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 54337, 54339, 54340, 54518, 105400, 105428, 105452, 54341, 54338 ], "onlineresource_set": [ 8647, 8671, 14999, 8646 ], "project_set": [ 14147 ] }, { "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)", "keywords": "HiTemp, BUCL, UHI, temperature, dew point, relative humidity, pressure, solar radiation, precipitation, wind", "publicationState": "published", "dataPublishedTime": "2016-02-23T12:00:00", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1142, "name": "NDGO0005" } ], "member": [ { "ob_id": 13919, "uuid": "4aba1697ab3041148f1e5191679411dc", "short_code": "ob", "title": "HiTemp: High Density Temperature measurements within the Urban Birmingham Conurbation.", "abstract": "Temperature data from a high density network of meteorological sensors installed within the Birmingham conurbation: low-cost, battery-powered WiFi Aginova Sentinel Micro air temperature sensors were operated at 73 stations 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)" }, { "ob_id": 14311, "uuid": "eb7dfdc88df846398022862aedabf832", "short_code": "ob", "title": "HiTemp: High Density Meteorological measurements within the Urban Birmingham Conurbation.", "abstract": "Meteorological data from a high density network of meteorological sensors installed within the Birmingham conurbation: including 25 Vaisala WXT520 weather transmitters installed at sites within the Birmingham conurbation Each sensor measured temperature, precipitation, relative humidity, wind speed and direction, pressure, solar radiation and quality flags. \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)" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 55579, 55580, 55581, 55583, 55584, 55585, 55778, 55582, 55775, 55779, 55776, 55576, 55777 ], "onlineresource_set": [ 8732, 8731 ], "project_set": [ 13923 ] }, { "ob_id": 14316, "uuid": "394464f9c39445d3b6445d8e305841d7", "short_code": "coll", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland Ice Sheet CCI) Dataset Collection", "abstract": "The Greenland Ice Sheet CCI project aims to maximize the impact of ESA satellite data on climate research, by analysing data from ESA Earth Observation missions such as ERS, Envisat, CryoSat, GRACE and the new Sentinel series of satellites. Over the last decade, the Greenland Ice Sheet has shown rapid change, characterized by rapid thinning along the margins, accelerating outlet glaciers, and overall increasing mass loss. The state of the Greenland Ice Sheet is of global importance, and has consequently been included in the ESA CCI Programme as a monitored Essential Climate Variable (ECV).\r\n\r\nThe project is producing data products of the following five parameters, which are important in characterizing the Greenland Ice Sheet as an Essential Climate Variable: Surface Elevation Change (SEC) gridded data from radar altimetry; Ice Velocity (IV) gridded data from synthetic aperture radar interferometry and feature tracking; Calving Front Location (CFL) time series of marine-terminating glaciers; Grounding Line Location (GLL) time series of marine-terminating glaciers; Gravimetry Mass Balance (GMB) maps and time series.", "keywords": "Greenland, CCI, Ice Sheet", "publicationState": "published", "dataPublishedTime": "2016-04-11T16:18:32", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 14264, "uuid": "7ae7e43347d34308960c19313367e59c", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Ice Velocity Map 2015, v1.0", "abstract": "This dataset is part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project, and provides components of the ice velocity and the magnitude of the velocity for the Greenland Ice Sheet.\r\n\r\nThe dataset is derived from Interferometric Wide Swath SAR data from the Sentinel-1 satellite, acquired in the period from the 1st November 2014 to the 1st December 2015. The ocean mask is based on the GIMP Ocean mask (Version 2.0; Howat et al. 2014), but calving fronts of marine terminating glaciers have been updated using Landsat-8 data acquired from May to August 2015." }, { "ob_id": 14266, "uuid": "5c500e31c1be490498f6eab13ecb7dd1", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity data for the Greenland Margin from ERS-2 for winter 1995-1996 (April 2016 release)", "abstract": "This dataset contains ice velocities for the Greenland margin for winter 1995-1996. This dataset has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThis dataset consists of ice velocity maps which have been generated from SAR data from the ERS-2 satellite for winter 1995-1996. The data is supplied on a 500m polar stereographic grid. The ice velocity product contain the horizontal components, vN and vE, of the total velocity vector, which is derived from radar measurements assuming surface parallel flow. The used digital elevation model of the surface is also supplied. The North and East velocities at any grid points are given in a local geographic north-east coordinates system (and not in the used grid map projection system)." }, { "ob_id": 26782, "uuid": "ff4bfe39b7fe42fc993341d3cebdabb5", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Gravimetric Mass Balance from GRACE data (CSR RL06), derived by DTU Space, v1.5", "abstract": "This dataset provides the Gravitational Mass Balance (GMB) product derived from gravimetry data from the GRACE satellite instrument, by DTU Space. The data consists of two products: a mass change time series for the entire Greenland Ice Sheet and different drainage basins for the period April 2002 to June 2016; and mass trend grids for different 5-year periods between 2003 and 2016. This version (1.5) is derived from GRACE monthly solutions from the CSR RL06 product.\r\n\r\nThe mass change time series contains the mass change (with respect to a chosen reference month) for all of the Greenland Ice Sheet and each individual drainage basin. For each month (defined by a decimal year) a mass change in Gt and its associated error (also in Gt) is provided. The mass trend grid product is given in units of mm water equivalent per year.\r\n\r\nMass balance is an important variable to understand glacial thinning and ablation rates to enable mapping glacier area change. The time series allows the longer term comparison of trends whereas the mass trend grids provide a yearly snapshot which can be further analysed and compared across the data set. \r\n\r\nBasin definitions and further data descriptions can be found in the Algorithm Theoretical Baseline Document (ST-DTU-ESA-GISCCI-ATBD-001_v3.1.pdf) and Product Specification Document (ST-DTU-ESA-GISCCI-PSD_v2.2.pdf) which are provided on the Greenland Ice Sheet CCI project website. \r\n\r\nCitation: \r\nBarletta, V. R., Sørensen, L. S., and Forsberg, R.: Scatter of mass changes estimates at basin scale for Greenland and Antarctica, The Cryosphere, 7, 1411-1432, doi:10.5194/tc-7-1411-2013, 2013." }, { "ob_id": 43866, "uuid": "bf5f4731e8bd456082e2e43f97f4430e", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Gravimetric Mass Balance from GRACE data, derived by DTU Space, v3.0", "abstract": "This dataset provides a Gravimetric Mass Balance (GMB) product for the Greenland Ice Sheet (GIS), generated by DTU Space, based on monthly snapshots of the Earth’s gravity field provided by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on satellite mission (GRACE-FO). The product relies on monthly gravity field solutions (L2) of release 06 generated at the Center for Space Research (University of Texas at Austin) and spans the period from April 2002 through May 2024.\r\n\r\nThe GMB product covers the full GRACE mission period (April 2002 - June 2017) and is extended by means of GRACE-FO data starting from June 2018, thus including 200 monthly solutions. The mass change estimation is based on inversion method developed at DTU Space.\r\n\r\nTwo different types of products are available. First, the gridded mass trends product is comprised of ice mass change trends for cells of equal area with 44 km resolution covering the whole GIS and different drainage basins. Second, the mass change time series product provides time series of integrated mass changes for 8 drainage basins and the entire GIS over different 5-year periods between 2002 and 2024. Basin definitions and further data descriptions can be found in the Algorithm Theoretical Baseline Document and the Product Specification Document which are provided on the project website. \r\n\r\nReference:\r\nBarletta, V. R., Sørensen, L. S., and Forsberg, R. (2013) 'Scatter of mass changes estimates at basin scale for Greenland and Antarctica', The Cryosphere, 7, 1411-1432, doi:10.5194/tc-7-1411-2013." }, { "ob_id": 19868, "uuid": "82e4ede59fe746ba810009d9a30e0153", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Ice Velocity Map Winter 2014-2015, v1.0", "abstract": "This dataset provides an ice velocity map for the whole Greenland ice-sheet for the winter of 2014-2015, derived from Sentinel-1 SAR data, as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E). The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid; the vertical displacement (z), derived from a digital elevation model, is also provided. Please note that previous versions of this product provided the horizontal velocities as true East and North velocities." }, { "ob_id": 27057, "uuid": "8889dfe3de45406e815bce13ae8a0c92", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Calving Front Locations, v3.0", "abstract": "The data set provides calving front locations of 28 major outlet glaciers of the Greenland Ice Sheet, produced as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. \r\n\r\nThe Calving Front Location (CFL) of outlet glaciers from ice sheets is a basic parameter for ice dynamic modelling, for computing the mass fluxes at the calving gate, and for mapping glacier area change. \r\n\r\nThe calving front location has been derived by manual delineation using SAR (Synthetic Aperture Radar) data from the ERS-1/2, Envisat and Sentinel-1 satellites and satellite imagery from LANDSAT 5,7,8. The digitized calving fronts are stored in ESRI vector shape-file format and include metadata information on the sensor and processing steps in the corresponding attribute table.\r\n\r\nThe product was generated by ENVEO (Environmental Earth Observation Information Technology GmbH)" }, { "ob_id": 26667, "uuid": "88d02eb5a6c14952aa88028894d8a69c", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Optical ice velocity of the Døcker Smith Glacier between 2016-05-08 and 2016-05-18, generated using Sentinel-2 data, v1.0", "abstract": "This dataset contains an optical ice velocity time series for the Døcker Smith Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2016-05-08 and 2016-05-18. It is part of the ESA Greenland Ice Sheet CCI project.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG 3413:Latitude of true scale 70N, Reference Longitude 45E) with 50m grid spacing. The horizontal velocity is provided in true meters per day, towards EASTING (x) and NORTHING (y) direction of the grid. \r\n\r\nThe product was generated by S[&]T Norway." }, { "ob_id": 26635, "uuid": "925e3f0e807243e2936cc492f5207af6", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Kangerlussuaq Glacier for 2015-2017 from Sentinel-1, v1.1", "abstract": "This dataset contains a time series of ice velocity maps for the Kangerlussuag Glacier in Greenland derived from Sentinel-1 SAR (Synthetic Aperture Radar) data acquired between January 2015 and March 2017. This dataset has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 26631, "uuid": "e3dbdc32f7b6476e949d52d8d3990205", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Zachariae Glacier for 2015-2017 from Sentinel-1 data, v1.1", "abstract": "This dataset contains a time series of ice velocities for the Zachariae glacier in Greenland, derived from Sentinel-1 SAR (Synthetic Aperture Radar) data acquired between January 2015 and March 2017. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 26638, "uuid": "5c9935b8b8854baeb7a256446293c03b", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Hagen Glacier for 2015-2017 from Sentinel-1 data, v1.1", "abstract": "This dataset contains a time series of ice velocities for the Hagen glacier in Greenland derived from Sentinel-1 SAR (Synthetic Aperture Radar) data acquired between January 2015 and March 2017. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 19863, "uuid": "dcda86e1d52f44aaafcffb77b47ba1bb", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Jakobshavn Isbrae glacier, 2002-2010, v1.1 (June 2016 release)", "abstract": "This dataset contains a time series of ice velocities for the Jakobshavn Isbrae Glacier in Greenland between 2002-2010, which has been produced as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThis dataset consists of a time series of Ice velocity maps which have been generated from Image Swath mode images from the ASAR instrument on the ENVISAT satellite, with a 35 day repeat cycle. The data are supplied on a 500m polar stereographic grid. \r\n\r\nPlease note - this product was released on the Greenland Ice Sheets download page in June 2016, but an earlier product (also accidentally labelled v1.1) was available through the CCI Open Data Portal and the CEDA archive until 29th November 2016. Please now use the later v1.1 product." }, { "ob_id": 39550, "uuid": "dde78ab3388a4452b43ffe3e69e91fce", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Mass flow rate ice discharge (MFID) for Greenland from CCI IV, CCI SEC, and BedMachine v1.0", "abstract": "Mass flow rate ice discharge (MFID) for Greenland ice sheet sectors. This data set is part of the ESA Greenland Ice sheet CCI project. \r\n\r\nIt provides the following CSV files: \r\n- Mass flow rate ice discharge. Units are Gt yr^{-1}.\r\n- Mass flow rate ice discharge uncertainty. Units are Gt yr^{-1}.\r\n- Coverage for each sector at each timestamp. Unitless [0 to 1].\r\n\r\nIce discharge is calculated from the CCI Ice Velocity (IV) product, the CCI Surface Elevation Change (SEC) product (where it overlaps with the ice discharge gates), and ice thickness from BedMachine. Ice discharge gates are placed 10 km upstream from all marine terminating glacier termini that have baseline velocities of more than 150 m/yr. Results are summed by Zwally et al. (2012) sectors.\r\n\r\nThe methods, including description of \"coverage\", are described in Mankoff et al. 2020." }, { "ob_id": 26645, "uuid": "24dc5d5429434ccdb349db04a1a3233d", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Ice Velocity Map, Winter 2016-2017, v1.0", "abstract": "This dataset provides an ice velocity map for the whole Greenland ice-sheet for the winter of 2016-2017, derived from Sentinel-1 SAR data acquired from 23/12/2016 to 27/02/2017, as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. \r\n\r\nIn total approximately 1800 S-1A & S-1B scenes are used to derive the surface velocity applying feature tracking techniques. The ice velocity map is provided at 500m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity is provided in true meters per day, towards EASTING(vx) and NORTHING(vy) direction of the grid, and the vertical displacement (vz), derived from a digital elevation model is also provided. The product was generated by ENVEO (Earth Observation Information Technology GmbH)." }, { "ob_id": 19857, "uuid": "7bb9375151cf44e7993664c10d8d3da5", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity Time Series of the Storstroemmen Glacier for 2015-2016 from Sentinel-1 data, v1.0", "abstract": "This dataset contains a time series of ice velocities for the Storstromemmen glacier in Greenland, derived from Sentinel-1 SAR data acquired between 26/1/2015 and 8/6/2016. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 26655, "uuid": "27fc79c6e65f4302a18ec9788605c246", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Hagen glacier from ERS-1, ERS-2 and Envisat data for 1991-2010, v1.1", "abstract": "This dataset contains a time series of ice velocities for the Hagen glacier in Greenland, derived from intensity-tracking of ERS-1, ERS-2 and Envisat data acquired between 26/08/1991 and 7/5/2010. It provides components of the ice velocity and the magnitude of the velocity, and has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E) with 500m grid spacing. Image pairs with a repeat cycle of 6 to 35 days are used. The horizontal velocity is provided in true meters per day, towards EASTING(x) and NORTHING(y) direction of the grid, and the vertical displacement (z), derived from a digital elevation model, is also provided.\r\n\r\nThe product was generated by GEUS (Geological Survey of Denmark and Greenland)." }, { "ob_id": 26636, "uuid": "e1c0c34e0cc942898b3626efd1dcc095", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Jakobshavn Glacier for 2014-2017 from Sentinel-1 data, v1.1", "abstract": "This dataset contains a time series of ice velocities for the Jakobshavn glacier in Greenland, generated from Sentinel-1 SAR (Synthetic Aperture Radar) data acquired from October 2014 and March 2017. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 41959, "uuid": "89c654c2e4a74ce5a494b69753d8291e", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Mass flow rate ice discharge (MFID) for Greenland from CCI IV, CCI SEC, and BedMachine v2.0", "abstract": "Mass flow rate ice discharge (MFID) for Greenland ice sheet sectors. This data set is part of the ESA Greenland Ice sheet CCI project. \r\n\r\nIt provides the following CSV files: \r\n- Mass flow rate ice discharge. Units are Gt yr^{-1}.\r\n- Mass flow rate ice discharge uncertainty. Units are Gt yr^{-1}.\r\n- Coverage for each sector at each timestamp. Unitless [0 to 1].\r\n\r\nIce discharge is calculated from the CCI Ice Velocity (IV) product, the CCI Surface Elevation Change (SEC) product (where it overlaps with the ice discharge gates), and ice thickness from BedMachine. Ice discharge gates are placed 10 km upstream from all marine terminating glacier termini that have baseline velocities of more than 150 m/yr. Results are summed by Zwally et al. (2012) sectors.\r\n\r\nThe methods, including description of \"coverage\", are described in Mankoff et al. 2020." }, { "ob_id": 20115, "uuid": "0c724d2a018c48cab18e1a14f0fee6df", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Gravimetric Mass Balance from GRACE data, derived by TU Dresden, v1.0", "abstract": "This dataset provides the Gravitational Mass Balance (GMB) product derived from the GRACE satellite instrument, by TU Dresden. The data consists of two products, a mass change time series for the Greenland Ice Sheet and individual basins, and mass trend grids for 5-year periods. \r\n\r\nThe mass change time series contains the mass change (with respect to a chosen reference month) for all of the Greenland Ice Sheet and each individual drainage basin. For each month (defined by a decimal year) a mass change in Gt and its associated error (also in Gt) is provided. The mass trend grid product is given in units of mm water equivalent per year.\r\n\r\nMass balance is an important variable to understand glacial thinning and ablation rates to enable mapping glacier area change. The time series allows the longer term comparison of trends whereas the mass trend grids provide a yearly snapshot which can be further analysed and compared across the data set." }, { "ob_id": 26640, "uuid": "8d475d7d92894765ad1ddda16de0e610", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Upernavik glacier from ERS-1, ERS-2, Envisat and PALSAR data for 1992-2010, v1.2", "abstract": "This dataset contains a time series of ice velocities for the Upernavik glacier in Greenland, derived from intensity-tracking of ERS-1, ERS-2 and Envisat and PALSAR data aquired between 02/01/1992 and 22/08/2010. The data provides components of the ice velocity and the magnitude of the velocity, and has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E) with 500m grid spacing. The image pairs used have a repeat cycle between 1 and 35 days. The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NOTHING(y) directions of the grid, and the vertical displacement (z), derived from a digital elevation model, is also provided. \r\n\r\nThe product was generated by GEUS (Geological Survey of Denmark and Greenland)." }, { "ob_id": 19856, "uuid": "2587d4a63a1f4928880008d7d7770552", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Gravimetric Mass Balance from GRACE data, derived by DTU-Space, v1.0", "abstract": "This dataset provides the Gravitational Mass Balance (GMB) product derived from the GRACE satellite instrument, by DTU-Space. The data consists of two products, a mass change time series for the Greenland Ice Sheet and individual basins, and mass trend grids for 5-year periods. \r\n\r\nThe mass change time series contains the mass change (with respect to a chosen reference month) for all of the Greenland Ice Sheet and each individual drainage basin. For each month (defined by a decimal year) a mass change in Gt and its associated error (also in Gt) is provided. The mass trend grid product is given in units of mm water equivalent per year.\r\n\r\nMass balance is an important variable to understand glacial thinning and ablation rates to enable mapping glacier area change. The time series allows the longer term comparison of trends whereas the mass trend grids provide a yearly snapshot which can be further analysed and compared across the data set." }, { "ob_id": 26632, "uuid": "ef5c6596cae548c6aea9dea181c7624c", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Upernavik Glacier for 2014-2017 from Sentinel-1 data, v1.1", "abstract": "This dataset contains a time series of ice velocities for the Upernavik Glacier in Greenland, derived from Sentinel-1 SAR (Synthetic Aperture Radar) data acquired between October 2014 and March 2017. This dataset has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 20108, "uuid": "e4f39152bc50466f8887bd2a343cac93", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity data for the Greenland Northern Drainage basin from ERS-1 for winter 1991-1992, v1.1 (June 2016 release)", "abstract": "This dataset contains ice velocities for the Greenland Northern Drainage Basin for winter 1991-1992, which have been produced as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. The data has been derived from intensity-tracking of ERS-1 Ice phase (3 days repeat) data aquired between 29th December 1991 and 22nd March 1992.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E). The horizontal velocity is provided in true meters per day, towards EASTING(x) and NORTHING(y) direction of the grid, and the vertical displacement (z), derived from a digital elevation\r\nmodel, is also provided. (Please note that in earlier versions of this product the horizontal velocities were provided as true East and North velocities).\r\n\r\n Both a single NetCDF file (including all measurements and annotation), and separate geotiff files with the velocity components are provided. The product was generated by DTU Space - Microwaves and Remote Sensing.\r\n\r\nPlease note - this product was released on the Greenland Ice Sheets download page in June 2016, but an earlier product (also accidentally labelled v1.1) was available through the CCI Open Data Portal and the CEDA archive until 29th November 2016. Please now use this later v1.1 product." }, { "ob_id": 19864, "uuid": "ec38bfab8ae64c8a8b9a8072c2765b9a", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity Time series for the Upernavik region, 1992-2010, v1.1 (June 2016 release)", "abstract": "This dataset contains a time series of ice velocities for the Upernavik region in Greenland between 1992-2010, and has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe data consists of an ice velocity time series derived from intensity-tracking of ERS-1/2, ASAR and PALSAR data acquired between 02-01-1992 and 22-08-2010. It provides components of the ice velocity and the magnitude of the velocity.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E). The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NOTHING(y) directions of the grid, and the vertical displacement (z), derived from a digital elevation model, is also provided. Please note that the previous versions of this product provided the horizontal velocities as true East and North velocities.\r\n\r\nBoth a single NetCDF file (including all measurements and annotation), and separate geotiff files with the velocity components are provided. The product was generated by GEUS. For further information please see the Product User Guide (v2.0).\r\n\r\nPlease note - this product was released on the Greenland Ice Sheets download page in June 2016, but an earlier product (also accidentally labelled v1.1) was available through the CCI Open Data Portal and the CEDA archive until 29th November 2016. Please now use the later v1.1 product." }, { "ob_id": 26634, "uuid": "81332b9a10f14bda8a1a83b6463bb6de", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Petermann Glacier for 2015-2017 from Sentinel-1 data, v1.1", "abstract": "This dataset contains a time series of ice velocities for the Petermann Glacier in Greenland, derived from Sentinel-1 SAR (Synthetic Aperture Radar) data acquired between 22/1/2015-19/3/2017. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 26650, "uuid": "0470e96f2d8245549ef2ba81842cdfd8", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Surface Elevation Change grid from SARAL-AltiKa for 2013-2017, v0.1", "abstract": "This data set is part of the ESA Greenland Ice sheet CCI project. The data set provides surface elevation changes (SEC) for the Greenland Ice sheet derived from SARAL-AltiKa for 2013-2017.\r\n \r\nThis new experimental product of surface elevation change is based on data from the AltiKa-instrument onboard the France (CNES)/Indian (ISRO) SARAL satellite. The AktiKa altimeter utilizes Ka-band radar signals, which have less penetration in the upper snow. However, the surface slope and roughness has an imprint in the derived signal and the new product is only available for the flatter central parts of the Greenland ice sheet.\r\n\r\nThe corresponding SEC grid from Cryosat-2 is included for comparison. The algorithm used to devive the product is described in the paper “Implications of changing scattering properties on the Greenland ice sheet volume change from Cryosat-2 altimetry” by S.B. Simonsen and L.S. Sørensen, Remote Sensing of the Environment, 190,pp.207-216, doi:10.1016/j.rse.2016.12.012. The approach used here corresponds to Least Squares Method (LSM) 5 described in the paper, in which the slope within each grid cell is accounted for by subtraction of the GIMP DEM; the data are corrected for both backscatter and leading edge width; and the LSM is solved at 1 km grid resolution (2 km search radius) and averaged in the post-processing to 5 km grid resolution and with a correlation length of 20 km." }, { "ob_id": 14263, "uuid": "f558dea21c664d51b407fe59fe321e2c", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Grounding Line Locations, v1.1", "abstract": "This dataset contains grounding lines for 5 North Greenland glaciers, derived from SAR Interferometery data from the ERS-1 and -2 satellites. Data was produced as part of the ESA Greenland Ice Sheets Climate Change Initiative (CCI) project by ENVEO, Austria.\r\n\r\nThe grounding line separates the floating part of a glacier from the grounded part. Processes at the grounding lines of floating marine termini of glaciers and ice streams are important for understanding the response of the ice masses to changing boundary conditions and for establishing realistic scenarios for the response to climate change. The grounding line location product is derived from InSAR data by mapping the tidal flexure and is generated for a selection of the few glaciers in Greenland, which have a floating tongue. In general, the true location of the grounding line is unknown, and therefore validation is difficult for this product. \r\n\r\nRemote sensing observations do not provide direct measurement on the transition from floating to grounding ice (the grounding line). The satellite data deliver observations on ice surface features (e.g. tidal deformation by InSAR, spatial changes in texture and shading in optical images) that are indirect indicators for estimating the position of the grounding line. Due to the plasticity of ice these indicators spread out over a zone upstream and downstream of the grounding line, the tidal flexure zone (also called grounding zone)." }, { "ob_id": 26656, "uuid": "17767027aa484505b7b732aee6619c74", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Helheim glacier from ERS-1, ERS-2 and Envisat data for 1996-2010, v1.1", "abstract": "This dataset contains a time series of ice velocities for the Helheim glacier in Greenland derived from intensity-tracking of ERS-1, ERS-2 and Envisat data acquired between 29/05/1996 and 26/2/2010. It provides components of the ice velocity and the magnitude of the velocity and has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E) with 500m grid spacing. The image pairs have a repeat cycle of 35 days. The horizontal velocity is provided in true meters per day, towards EASTING(x) and NORTHING(y) direction of the grid, and the vertical displacement (z), derived from a digital elevation model, is also provided.\r\n\r\nThe product was generated by GEUS (Geological Survey of Denmark and Greenland)." }, { "ob_id": 26664, "uuid": "94f3670150de4bac90773806e26646f2", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Optical ice velocity of the Petermann Glacier between 2017-05-01 and 2017-09-14, generated using Sentinel-2 data, v1.1", "abstract": "This dataset contains optical ice velocity time series and seasonal product of the Petermann Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2017-05-01 and 2017-09-14. It has been produced as part of the ESA Greenland Ice sheet CCI project.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG 3413:Latitude of true scale 70N, Reference Longitude 45E) with 50m grid spacing. The horizontal velocity is provided in true meters per day, towards EASTING (x) and NORTHING (y) direction of the grid.\r\n\r\nThe data have been produced by S[&]T Norway." }, { "ob_id": 19870, "uuid": "369f9e483e0d4646a144d37f4f88f9fe", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Ice Velocity Map Winter 2015-2016, v1.0", "abstract": "This dataset provides an ice velocity map for the whole Greenland ice-sheet for the winter of 2015-2016, derived from Sentinel-1 SAR data, as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. \r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E). The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid; the vertical displacement (z), derived from a digital elevation model, is also provided. Please note that previous versions of this product provided the horizontal velocities as true East and North velocities." }, { "ob_id": 26660, "uuid": "f31e8e988c4144bebe13892b53d08e42", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Optical ice velocity of the 79Fjord Glacier between 2017-06-25 and 2017-08-10, generated using Sentinel-2 data, v1.1", "abstract": "This dataset contains optical ice velocity time series and seasonal product of the 79Fjord Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2017-06-25 and 2017-08-10. It has been produced as part of the ESA Greenland Ice Sheet CCI project.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG 3413:Latitude of true scale 70N, Reference Longitude 45E) with 50m grid spacing. The horizontal velocity is provided in true meters per day, towards EASTING (x) and NORTHING (y) direction of the grid. \r\n\r\nThe data have been produced by S[&]T Norway" }, { "ob_id": 26661, "uuid": "84faf575c8e841a3a16476b05cbd657d", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Optical ice velocity of the Upernavik Glacier between 2017-07-15 and 2017-08-14, generated using Sentinel-2 data, v1.1", "abstract": "This dataset contains optical ice velocity time series and seasonal product of the Upernavik Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2017-07-15 and 2017-08-14. It has been produced as part of the ESA Greenland Ice sheet CCI project. \r\n\r\nThe data are provided on a polar stereographic grid (EPSG 3413:Latitude of true scale 70N, Reference Longitude 45E) with 50m grid spacing. The horizontal velocity is provided in true meters per day, towards EASTING (x) and NORTHING (y) direction of the grid.\r\n\r\nThe product was generated by S[&]T Norway." }, { "ob_id": 26815, "uuid": "8381d3f3998143fd9b53c7086b7061e3", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series of the Storstrommen glacier from ERS-1, ERS-2 and Envisat data for 1991-2010, v1.1", "abstract": "This dataset contains a time series of ice velocities for the Storstrommen glacier in Greenland, derived from intensity-tracking of ERS-1, ERS-2 and Envisat data acquired between 06/10/1991 and 20/03/2010. It provides components of the ice velocity and the magnitude of the velocity, and has been produced as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E) with 500m grid spacing. Image pairs with a repeat cycle of 6 to 35 days are used. The horizontal velocity is provided in true meters per day, towards EASTING(x) and NORTHING(y) direction of the grid, and the vertical displacement (z), derived from a digital elevation model, is also provided.\r\n\r\nThe product was generated by GEUS (Geological Survey of Denmark and Greenland)." }, { "ob_id": 26637, "uuid": "0e289294f2c141bca545cd9d7fcb62d0", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Helheim Glacier for 2015-2017 from Sentinel-1 data, v1.1", "abstract": "This dataset contains a time series of ice velocities for the Helheim Glacier in Greenland derived from Sentinel-1 SAR (Synthetic Aperture Radar) data acquired between between June 2015 and March 2017. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 14265, "uuid": "378bd099a9b74c498e2975a1e156dd12", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Jakobshaven region for 2002-2010, v1.1 (April 2016 release)", "abstract": "This dataset contains a time series of ice velocities for the Jakobshavn glacier in Greenland between 2002 and 2010. This dataset has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThis dataset consists of a time series of ice velocity maps which have been generated from IS mode images from the ASAR instrument on the ENVISAT satellite, with a 35 day repeat cycle, and are supplied on a 500m polar stereographic grid. The ice velocity product contain the horizontal components, vN and vE, of the total velocity vector, which is derived from radar measurements assuming surface parallel flow. The used digital elevation model of the surface is also supplied. The North and East velocities at any grid points are given in a local geographic north-east coordinates system (and not in the used grid map projection system)." }, { "ob_id": 14262, "uuid": "70eae17a47e64c8597defcb0ed155dea", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Calving Front Locations, v1.1", "abstract": "The data set provides calving front locations of major outlet glaciers of the Greenland Ice Sheet from SAR data from various sensors, produced as part of the ESA Greenland Ice Sheets Climate Change Initiative (CCI) project. Version 1.1 of the dataset has been updated to include information from Sentinel 1 data.\r\n\r\nThe Calving Front Location (CFL) of outlet glaciers from ice sheets is a basic parameter for ice dynamic modelling, for computing the mass fluxes at the calving gate, and for mapping glacier area change. From the ice velocity at the calving front and the time sequence of Calving Front Locations the iceberg calving rate can be computed which is of relevance for estimating the export of ice mass to the ocean.\r\n\r\nThe calving front location has been derived by manual delineation based on SAR or optical satellite data. The CFL product is a collection of ESRI shapefile in latitude and longitude, on WGS84 projection. The basic data are vector line files (not polygons)." }, { "ob_id": 14275, "uuid": "73816cb40a584e609aca2eac02bb910e", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity data for the Greenland Northern Drainage Basins from ERS-1 for winter 1991 - 1992, v1.1 (April 2016 release)", "abstract": "This dataset contains ice velocities for the Greenland northern drainage basin for 1991-1992.This dataset has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThis dataset consists of ice velocity maps which have been generated from SAR data from the ERS-1 satellite, for winter 1991-1992. The data is supplied on a 500m polar stereographic grid. The ice velocity product contain the horizontal components, vN and vE, of the total velocity vector, which is derived from radar measurements assuming surface parallel flow. The used digital elevation model of the surface is also supplied. The North and East velocities at any grid points are given in a local geographic north-east coordinates system (and not in the used grid map projection system)." }, { "ob_id": 26828, "uuid": "723067f77b8b43609079d721e3b4a3c7", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Kangerlussuaq glacier from ERS-1, ERS-2, Envisat for 1992-2008, v1.0", "abstract": "This dataset contains a time series of ice velocities for the Kangerlussuaq glacier in Greenland, derived from intensity-tracking of ERS-1, ERS-2 and Envisat data aquired between 02/01/1992 and 17/12/2008. The data provides components of the ice velocity and the magnitude of the velocity, and has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E) with 500m grid spacing. The image pairs used have a repeat cycle between 3 and 35 days. The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NOTHING(y) directions of the grid, and the vertical displacement (z), derived from a digital elevation model, is also provided. \r\n\r\nThe product was generated by GEUS (Geological Survey of Denmark and Greenland)." }, { "ob_id": 19858, "uuid": "bf6bfa8a6ae74b27b6e5497ea3d45307", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity Time Series of the Zachariae Isstroem for 2015-2016 from Sentinel-1 data, v1.0", "abstract": "This dataset contains a time series of ice velocities for the Zachariae Isstroem glacier in Greenland, derived from Sentinel-1 SAR data acquired between 25/1/2015 and 8/6/2016. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 19877, "uuid": "84b5cf8380894d719b61deac5abf3bae", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity data for the Greenland Margin from the PALSAR instrument for 2006-2011, v1.1 (June 2016 version)", "abstract": "This dataset contains a time series of ice velocities for the Greenland margin from the PALSAR instrument on the ALOS satellite. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. \r\n\r\nThis dataset consists of a time series of ice velocity with yearly sampling, derived from intensity tracking of PALSAR data acquired between 20-12-2016 and 17-03-2011. It provides components of the ice velocity and the magnitude of the velocity.\r\n\r\n The data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E). The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid; the vertical displacement (z), derived from a digital elevation model, is also provided. Please note that the previous versions of this product provided the horizontal velocities as true East and North velocities.\r\n\r\nBoth a single NetCDF file (including all measurements and annotation), and separate geotiff files with the velocity components are provided. The product was generated by GEUS. For further details, please consult the Product User Guide (v2.0)\r\n\r\nPlease note - this product was released on the Greenland Ice Sheets download page in June 2016, but an earlier product (also accidentally labelled v1.1) was available through the CCI Open Data Portal and the CEDA archive until 29th November 2016. Please now use the later v1.1 product." }, { "ob_id": 19985, "uuid": "a9f4876560234ded84ac87eb9d4853c6", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Surface Elevation Change from Cryosat-2, v2.0", "abstract": "This data set is part of the ESA Greenland Ice sheet CCI project. The data set provides surface elevation changes (SEC) for the Greenland Ice sheet derived from Cryosat 2 satellite radar altimetry, for the time period between 2010 and 2015.\r\n \r\nThe surface elevation change data are provided as 2-year means (2011-2012, 2012-2013, 2013-2014 and 2014-2015), and a five-year mean is also provided (2011-2015), along with their associated errors. Data are provided in both NetCDF and gridded ASCII format, as well as png plots.\r\n\r\nThe algorithm used to devive the product is described in the paper “Implications of changing scattering properties on the Greenland ice sheet volume change from Cryosat-2 altimetry” by S.B. Simonsen and L.S. Sørensen, which has been submitted to Remote Sensing of the Environment." }, { "ob_id": 14326, "uuid": "8650e1ec31144253a31e948c53fa2cca", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity data for the Greenland Margin from the PALSAR instrument for winters 2006-2011 (April 2016 release)", "abstract": "This dataset contains ice velocities for the Greenland margin for winter 1995-1996. This dataset has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThis dataset consists of ice velocity maps which have been generated from PALSAR data on the ALOS satellite for the winters between 2006-2011. The data is supplied on a 500m polar stereographic grid. The ice velocity product contain the horizontal components, vN and vE, of the total velocity vector, which is derived from radar measurements assuming surface parallel flow. The used digital elevation model of the surface is also supplied. The North and East velocities at any grid points are given in a local geographic north-east coordinates system (and not in the used grid map projection system)." }, { "ob_id": 19865, "uuid": "e3a4bd4d857742c2922993722253f52b", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity Time Series of the Hagen Brae for 2015-2016 from Sentinel-1 data, v1.0", "abstract": "This dataset contains a time series of ice velocities for the Hagen Brae glacier in Greenland derived from Sentinel-1 SAR data acquired between 22/1/2015 and 1/6/2016. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 19859, "uuid": "3566cdffebf04ce784ad0fdcf094834a", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity Time Series of 79-Fjord Glacier for 2015-2016 from Sentinel-1 data, v1.0", "abstract": "This dataset contains a time series of ice velocities for the 79-Fjord Glacier in Greenland, derived from Sentinel-1 SAR data acquired between 25/1/2015 and 8/6/2016. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 26639, "uuid": "41e2300068b44fa190f24272dc08dcd0", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the 79-Fjord Glacier for 2015-2017 from Sentinel-1 data, v1.1", "abstract": "This dataset contains a time series of ice velocities for the 79-Fjord Glacier in Greenland, derived from Sentinel-1 SAR (Synthetic Aperture Radar) data acquired between January 2015 and March 2017. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 26642, "uuid": "41e9783d4caa447b99f653c065805579", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Surface Elevation Change from Cryosat-2, v2.2", "abstract": "This data set is part of the ESA Greenland Ice sheet CCI project. The data set provides surface elevation changes (SEC) for the Greenland Ice sheet derived from Cryosat 2 satellite radar altimetry, for the time period between 2010 and 2017.\r\n \r\nThe surface elevation change data are provided as 2-year means (2011-2012, 2012-2013, 2013-2014, 2014-2015, 2015-2016, and 2016-2017), and five-year means are also provided (2011-2015, 2012-2016, 2013-2017), along with their associated errors. Data are provided in both NetCDF and gridded ASCII format, as well as png plots.\r\n\r\nThe algorithm used to devive the product is described in the paper “Implications of changing scattering properties on the Greenland ice sheet volume change from Cryosat-2 altimetry” by S.B. Simonsen and L.S. Sørensen, Remote Sensing of the Environment, 190,pp.207-216, doi:10.1016/j.rse.2016.12.012" }, { "ob_id": 39549, "uuid": "35a3e7e5ad2946859ac31c36605486f0", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Machine Learning Generated Greenland Calving Front Locations v1.0", "abstract": "Calving Front locations for Upernavik A,E,F, Humboldt and Hagen glaciers in Greenland, generated by a deep learning based model using Sentinel-2 imagery.\r\n\r\nThe calving front location is generated by a deep learning based model using Sentinel-2 imagery acquired from 2019-2020. The digitized calving fronts are stored in geoJSON vector file format and include metadata information on the sensor and processing steps in the corresponding attribute table.\r\n\r\nThe CCI Calving Front Locations (CFL) v1.0 release contains one primary dataset, the calving front locations, and auxiliary files to describe the file product: locations.png and glaciers.geojson for visualizing the glaciers, README and DESCRIPTION text files about the product structure, and a visual example of what a calving front looks like. The Greenland CCI Calving Front Locations (CFL) v1.0 product is an experimental product using deep learning to automatically derive calving front locations for selected glaciers based on Sentinel-2 imagery at the end of the summer season.\r\n\r\nThe product was generated by S[&]T Norway and ENVEO." }, { "ob_id": 14299, "uuid": "a7b87a912c494c03b4d2fa5ab8479d1c", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Surface Elevation Change 1992-2014, v1.2", "abstract": "This data set is part of the ESA Greenland Ice sheet CCI project. The data set provides surface elevation changes (SEC) for the Greenland Ice sheet derived from satellite (ERS‐1, ERS‐2, Envisat and Cryosat) radar altimetry. The ice mask is based on the GEUS/GST land/ice/ocean mask provided as part of national mapping projects, and based on 1980’s aerial photography. The data from ERS and Envisat are based on a 5‐year running average, using combined algorithms of repeat‐track (RT), along‐track (AT) or cross‐over (XO) algorithms, and include propagated error estimates. \r\n\r\nIt is important to note that different processing algorithms were applied to the ERS‐1, ERS‐2, Envisat and CryoSat data; for details see the Product User Guide (PUG), available on the CCI website and in the documentation section here. For ERS‐1, the radar data were processed using a cross‐over algorithm (XO) only. For ERS‐2 data and Envisat data in repeat mode, a combination of RT and XO algorithms was applied, followed by filtering. For across‐mission (i.e. ERS‐2‐Envisat) combinations, and for Envisat operating in a drifting orbit, an AT and XO combination was applied (the difference between RT and AT algorithms is that AT use reference tracks and searches for data in the vicinity of this track). For CryoSat data a binning/gridding and plane fit method has been applied, following by weak filtering (0.05 degree resolution)." }, { "ob_id": 19862, "uuid": "a21a03c1697f4d3f9bf3b2509d91b636", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity Time Series of the Helheim Glacier for 2015-2016 from Sentinel-1 data, v1.0", "abstract": "This dataset contains a time series of ice velocities for the Helheim Glacier in Greenland derived from Sentinel-1 SAR data acquired between between 17/1/2015 and 11/6/2016. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 26666, "uuid": "aae643e1a7614c24b6b604dea82cad93", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Optical ice velocity of the Kangerlussuaq Glacier between 2017-07-21 and 2017-08-20, generated using Sentinel-2 data, v1.1", "abstract": "This dataset contains optical ice velocity time series and seasonal product of the Kangerlussuaq Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2017-07-21 and 2017-08-20. It has been produced as part of the ESA Greenland Ice sheet CCI project. \r\n\r\nThe data are provided on a polar stereographic grid (EPSG 3413:Latitude of true scale 70N, Reference Longitude 45E) with 50m grid spacing. The horizontal velocity is provided in true meters per day, towards EASTING (x) and NORTHING (y) direction of the grid.\r\n\r\nThe data have been produced by S[&]T Norway." }, { "ob_id": 19855, "uuid": "fba8969ef8224c4cac3cbaca149aef8f", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Calving Front Locations, v2.0", "abstract": "The data set provides calving front locations of 28 major outlet glaciers of the Greenland Ice Sheet using ERS and ENVISAT and Sentinel-1 SAR data. A selected number of the glaciers have been sampled seasonally, whilst the rest are sampled annually.\r\n\r\nThe Calving Front Location (CFL) of outlet glaciers from ice sheets is a basic parameter for ice dynamic modelling, for computing the mass fluxes at the calving gate, and for mapping glacier area change. From the ice velocity at the calving front and the time sequence of Calving Front Locations the iceberg calving rate can be computed which is of relevance for estimating the export of ice mass to the ocean.\r\n\r\nThe CFL product is a collection of ESRI shapefile in latitude and longitude, WGS84 projection." }, { "ob_id": 14298, "uuid": "ad51086ffcc348debd392559b3205f11", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity data for the Upernavik region for 1992 - 2010, v1.1 (April 2016 release)", "abstract": "This dataset contains a time series of ice velocities for the Upernavik glacier in Greenland between 1992 and 2010. This dataset has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThis dataset consists of a time series of Ice velocity maps which have been generated from SAR data from the ERS-1 and ERS-2, ENVISAT and the ALOS satellites. The data are supplied on a 500m polar stereographic grid. The ice velocity product contain the horizontal components, vN and vE, of the total velocity vector, which is derived from radar measurements assuming surface parallel flow. The used digital elevation model of the surface is also supplied. The North and East velocities at any grid points are given in a local geographic north-east coordinates system (and not in the used grid map projection system)." }, { "ob_id": 26780, "uuid": "5970b33c92ef444793fb6d7e54d1230e", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Gravimetric Mass Balance from GRACE data (CSR RL06), derived by TU Dresden, v1.3", "abstract": "This dataset provides the Gravitational Mass Balance (GMB) product derived from gravimetry data from the GRACE satellite instrument, by TU Dresden. The data consists of two products: a mass change time series for the entire Greenland Ice Sheet and different drainage basins for the period April 2002 to August 2016; and mass trend grids for different 5-year periods between 2003 and 2016. This version (1.3) is derived from GRACE monthly solutions from the CSR RL06 product.\r\n\r\nThe mass change time series contains the mass change (with respect to a chosen reference month) for all of the Greenland Ice Sheet and each individual drainage basin. For each month (defined by a decimal year) a mass change in Gt and its associated error (also in Gt) is provided. The mass trend grid product is given in units of mm water equivalent per year.\r\n\r\nMass balance is an important variable to understand glacial thinning and ablation rates to enable mapping glacier area change. The time series allows the longer term comparison of trends whereas the mass trend grids provide a yearly snapshot which can be further analysed and compared across the data set. \r\n\r\nBasin definitions and further data descriptions can be found in the Algorithm Theoretical Baseline Document (ST-DTU-ESA-GISCCI-ATBD-001_v3.1.pdf) and Product Specification Document (ST-DTU-ESA-GISCCI-PSD_v2.2.pdf) which are provided on the Greenland Ice Sheet CCI project website. This GMB product has been produced by TU Dresden for comparison with the existing GMB product derived by DTU Space.\r\n\r\nPlease cite the dataset as follows: Groh, A., & Horwath, M. (2016). The method of tailored sensitivity kernels for GRACE mass change estimates. Geophysical Research Abstracts, 18, EGU2016-12065" }, { "ob_id": 37276, "uuid": "48cd535e93574c8da8e80b91e06c7d51", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Gravimetric Mass Balance from GRACE data, derived by DTU Space, v2.2", "abstract": "This dataset provides a Gravimetric Mass Balance (GMB) product for the Greenland Ice Sheet (GIS), generated by DTU Space, based on monthly snapshots of the Earth’s gravity field provided by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on satellite mission (GRACE-FO). The product relies on monthly gravity field solutions (L2) of release 06 generated at the Center for Space Research (University of Texas at Austin) and spans the period from April 2002 through August 2021.\r\n\r\nThe GMB product covers the full GRACE mission period (April 2002 - June 2017) and is extended by means of GRACE-FO data starting from June 2018, thus including 200 monthly solutions. The mass change estimation is based on inversion method developed at DTU Space.\r\n\r\nTwo different types of products are available. First, the gridded mass trends product is comprised of ice mass change trends for cells of equal area with 50 km resolution covering the whole GIS. Second, the mass change time series product provides time series of integrated mass changes for 8 drainage basins and the entire GIS.\r\n\r\nReference:\r\nBarletta, V. R., Sørensen, L. S., and Forsberg, R. (2013) 'Scatter of mass changes estimates at basin scale for Greenland and Antarctica', The Cryosphere, 7, 1411-1432, doi:10.5194/tc-7-1411-2013.\"," }, { "ob_id": 26659, "uuid": "ada968fd392d49fbbb07ac84eeb23ac6", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Optical ice velocity of the Zachariae Glacier between 2017-06-25 and 2017-08-10, generated using Sentinel-2 data, v1.1", "abstract": "This dataset contains an optical ice velocity time series and seasonal product of the Zachariae Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2017-06-25 and 2017-08-10. It has been produced as part of the ESA Greenland Ice Sheet CCI project.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG 3413:Latitude of true scale 70N, Reference Longitude 45E) with 50m grid spacing. The horizontal velocity is provided in true meters per day, towards EASTING (x) and NORTHING (y) direction of the grid. \r\n\r\nThe product was generated by S[&]T Norway." }, { "ob_id": 19986, "uuid": "d58ffcfd861a4f03bad97f77c505814b", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity Time Series of the Jakobshavn Isbrae for 2014-2016 from Sentinel-1 data, v1.0", "abstract": "This dataset contains a time series of ice velocities for the Jakobshavn Isbrae glacier in Greenland, generated from Sentinel-1 SAR data acquired from 11/10/2014 and 02/06/2016. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 26784, "uuid": "35ea8189e75e4b6f95e7c86812080ecb", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Gravimetric Mass Balance from GRACE data, derived by DTU Space, v1.4", "abstract": "This dataset provides the Gravitational Mass Balance (GMB) product derived from gravimetry data from the GRACE satellite instrument, by DTU Space. The data consists of two products: a mass change time series for the entire Greenland Ice Sheet and different drainage basins for the period April 2002 to June 2017; and mass trend grids for different 5-year periods between 2003 and 2017. This version (1.4) is derived from GRACE monthly solutions provided by TU Graz (ITSG-Grace 2016), apart from August 2016 time series which is computed using the CRS-R05 solution.\r\n\r\nThe mass change time series contains the mass change (with respect to a chosen reference month) for all of the Greenland Ice Sheet and each individual drainage basin. For each month (defined by a decimal year) a mass change in Gt and its associated error (also in Gt) is provided. The mass trend grid product is given in units of mm water equivalent per year.\r\n\r\nMass balance is an important variable to understand glacial thinning and ablation rates to enable mapping glacier area change. The time series allows the longer term comparison of trends whereas the mass trend grids provide a yearly snapshot which can be further analysed and compared across the data set. \r\n\r\nBasin definitions and further data descriptions can be found in the Algorithm Theoretical Baseline Document (ST-DTU-ESA-GISCCI-ATBD-001_v3.1.pdf) and Product Specification Document (ST-DTU-ESA-GISCCI-PSD_v2.2.pdf) which are provided on the Greenland Ice Sheet CCI project website. \r\n\r\nCitation: \r\nBarletta, V. R., Sørensen, L. S., and Forsberg, R.: Scatter of mass changes estimates at basin scale for Greenland and Antarctica, The Cryosphere, 7, 1411-1432, doi:10.5194/tc-7-1411-2013, 2013." }, { "ob_id": 19878, "uuid": "0b23b3c771db4fff8958196432d978cb", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity data for the Greenland Margin from ERS-2 for winter 1995-1996, v1.1 (June 2016 release)", "abstract": "This dataset contains ice velocities for the Greenland margin for winter 1995-1996, which have been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. The data were derived from intensity-tracking of ERS-2 data acquired between 03-09-1995 and 29-03-1996. It provides components of the ice velocity and the magnitude of the velocity.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E). The horizontal velocity is provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid; the vertical displacement (z), derived from a digital elevation model, is also provided. Please note that previous versions of this product provided the horizontal velocities as true East and North velocities.\r\n\r\nBoth a single NetCDF file (including all measurements and annotation), and separate geotiff files with the velocity components are provided. The product was generated by DTU Space - Microwaves and Remote Sensing. For further information please see the product user guide.\r\n\r\nPlease note - this product was released on the Greenland Ice Sheets download page in June 2016, but an earlier product (also accidentally labelled v1.1) was available through the CCI Open Data Portal and the CEDA archive until 29th November 2016. Please now use the later v1.1 product." }, { "ob_id": 19987, "uuid": "7687e5d628f1496cbe6c2622642842b2", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity Time Series of the Kangerlussuaq Glacier for 2015-2016 from Sentinel-1, v1.0", "abstract": "This dataset contains a time series of ice velocity maps for the Kangerlussuag Glacier in Greenland derived from Sentinel-1 SAR data acquired between January 2015 and June 2016. This dataset has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 26665, "uuid": "1e3fcdc14e2246c69fc54f0e1fe7a6ca", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Optical ice velocity of the Helheim Glacier between 2017-05-01 and 2017-08-29, generated using Sentinel-2 data, v1.1", "abstract": "This dataset contains optical ice velocity time series and seasonal product of the Helheim Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2017-05-01 and 2017-08-29. It has been produced as part of the ESA Greenland Ice sheet CCI project. \r\n\r\nThe data are provided on a polar stereographic grid (EPSG 3413:Latitude of true scale 70N, Reference Longitude 45E) with 50m grid spacing. The horizontal velocity is provided in true meters per day, towards EASTING (x) and NORTHING (y) direction of the grid.\r\n\r\nThe data have been produced by S[&]T Norway." }, { "ob_id": 26658, "uuid": "22254b5608ab430fa360d0ff7e71c34e", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Petermann glacier from ERS-1, ERS-2 and Envisat data for 1991-2010, v1.1", "abstract": "This dataset contains a time series of ice velocities for the Petermann glacier in Greenland derived from intensity-tracking of ERS-1, ERS-2 and Envisat data acquired between 16/08/1991 and 01/06/2010. It provides components of the ice velocity and the magnitude of the velocity and has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E) with 500m grid spacing. Image pairs with a repeat cycle of 1 to 35 days are used. The horizontal velocity is provided in true meters per day, towards EASTING(x) and NORTHING(y) direction of the grid, and the vertical displacement (z), derived from a digital elevation model, is also provided.\r\n\r\nThe product was generated by GEUS (Geological Survey of Denmark and Greenland)." }, { "ob_id": 26662, "uuid": "e7fa45e785a64481960c3b140038c948", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Optical ice velocity of the Hagen Glacier between 2017-06-30 and 2017-08-14, generated using Sentinel-2 data, v1.1", "abstract": "This dataset contains optical ice velocity time series and seasonal product of the Hagen Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2017-06-30 and 2017-08-14. It has been produced as part of the ESA Greenland Ice sheet CCI project. \r\n\r\nThe data are provided on a polar stereographic grid (EPSG 3413:Latitude of true scale 70N, Reference Longitude 45E) with 50m grid spacing. The horizontal velocity is provided in true meters per day, towards EASTING (x) and NORTHING (y) direction of the grid.\r\n\r\nThe data have been produced by S[&]T Norway." }, { "ob_id": 26657, "uuid": "2457272c747f4d6ca33cb40833bd9cc2", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Zachariae and 79Fjord area from ERS-1, ERS-2 and Envisat data for 1991-2011, v1.1", "abstract": "This dataset contains a time series of ice velocities for the Zachariae and 79Fjord area in Greenland derived from intensity-tracking of ERS-1, ERS-2 and Envisat data acquired between 01/08/1991 and 07/02/2011. It provides components of the ice velocity and the magnitude of the velocity and has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E) with 500m grid spacing. The image pairs have a repeat cycle between 1 and 35 days. The horizontal velocity is provided in true meters per day, towards EASTING(x) and NORTHING(y) direction of the grid, and the vertical displacement (z), derived from a digital elevation model, is also provided.\r\n\r\nThe product was generated by GEUS (Geological Survey of Denmark and Greenland)." }, { "ob_id": 26633, "uuid": "1dd4c30a78d84e628cd8097bae3148fd", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Storstroemmen Glacier for 2015-2017 from Sentinel-1 data, v1.1", "abstract": "This dataset contains a time series of ice velocities for the Storstromemmen glacier in Greenland, derived from Sentinel-1 SAR (Synthetic Aperture Radar) data acquired between 24/1/2015 and 22/03/2017. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 19869, "uuid": "9bdeb99d91a743fe84623264587ad043", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Ice Velocity Map Winter 2013-2014, v1.0", "abstract": "This dataset provides an ice velocity map for the whole Greenland ice-sheet for the winter of 2013-2014, derived from RADARSAT-2 data, as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. The ice velocity data were derived from intensity-tracking of RADARSAT-2 data aquired between 21/1/2014 and 02/04/2014. \r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E). The horizontal velocity is provided in true meters per day, towards the Eastings and Northings direction of the grid; the vertical displacement, derived from a digital elevation model, is also provided. Both a single NetCDF file (including all measurements and annotation), and separate geotiff files with the velocity components are provided. This product was generated by DTU Space - Microwaves and Remote Sensing." }, { "ob_id": 19854, "uuid": "2d43e43de3484810ae24cfdc13eab263", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Grounding Line Locations v1.2", "abstract": "This dataset contains grounding lines for 5 North Greenland glaciers, derived from generated from ERS -1/-2 SAR Tandem and 3 days data sets. This addition includes the grounding line for the Petermann glacier from Sentinel-1A. Data was produced as part of the ESA Greenland Ice Sheets Climate Change Initiative (CCI) project by ENVEO, Austria. \r\n\r\nThe grounding line is the separation point between the floating and grounded parts of the glacier. Processes at the grounding lines of floating marine termini of glaciers and ice streams are important for understanding the response of the ice masses to changing boundary conditions and for establishing realistic scenarios for the response to climate change. The grounding line location product is derived from InSAR data by mapping the tidal flexure and is generated for a selection of the few glaciers in Greenland, which have a floating tongue. In general, the true location of the grounding line is unknown, and therefore validation is difficult for this product.\r\n\r\nRemote sensing observations do not provide direct measurement on the transition from floating to grounding ice (the grounding line). The satellite data deliver observations on ice surface features (e.g. tidal deformation by InSAR, spatial changes in texture and shading in optical images) that are indirect indicators for estimating the position of the grounding line. Due to the plasticity of ice these indicators spread out over a zone upstream and downstream of the grounding line, the tidal flexure zone (also called grounding zone)." }, { "ob_id": 26778, "uuid": "b017235a8e544d6fbad21387ebfbf0d8", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Gravimetric Mass Balance from GRACE data, derived by TU Dresden, v1.2", "abstract": "This dataset provides the Gravitational Mass Balance (GMB) product derived from gravimetry data from the GRACE satellite instrument, by TU Dresden. The data consists of two products: a mass change time series for the entire Greenland Ice Sheet and different drainage basins for the period April 2002 to August 2016; and mass trend grids for different 5-year periods between 2003 and 2016. This version (1.2) is derived from GRACE monthly solutions provided by TU Graz (ITSG-Grace 2016)\r\n\r\nThe mass change time series contains the mass change (with respect to a chosen reference month) for all of the Greenland Ice Sheet and each individual drainage basin. For each month (defined by a decimal year) a mass change in Gt and its associated error (also in Gt) is provided. The mass trend grid product is given in units of mm water equivalent per year.\r\n\r\nMass balance is an important variable to understand glacial thinning and ablation rates to enable mapping glacier area change. The time series allows the longer term comparison of trends whereas the mass trend grids provide a yearly snapshot which can be further analysed and compared across the data set. \r\n\r\nBasin definitions and further data descriptions can be found in the Algorithm Theoretical Baseline Document (ST-DTU-ESA-GISCCI-ATBD-001_v3.1.pdf) and Product Specification Document (ST-DTU-ESA-GISCCI-PSD_v2.2.pdf) which are provided on the Greenland Ice Sheet CCI project website. This GMB product has been produced by TU Dresden for comparison with the existing GMB product derived by DTU Space.\r\n\r\nPlease cite the dataset as follows: Groh, A., & Horwath, M. (2016). The method of tailored sensitivity kernels for GRACE mass change estimates. Geophysical Research Abstracts, 18, EGU2016-12065" }, { "ob_id": 26647, "uuid": "302f379334e84664bd3409d08eca6565", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Ice Velocity Map, Winter 2015-2016, v1.2", "abstract": "This dataset provides an ice velocity map for the whole Greenland ice-sheet for the winter of 2015-2016, derived from Sentinel-1 SAR data acquired from 01/10/2015 to 31/10/2016, as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. \r\n\r\nThe ice velocity map is provided at 500m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity is provided in true meters per day, towards EASTING(vx) and NORTHING(vy) direction of the grid, and the vertical displacement (vz), derived from a digital elevation model is also provided. The product was generated by ENVEO (Earth Observation Information Technology GmbH)." }, { "ob_id": 26641, "uuid": "a0d9764a3068439b997c42928ef739d2", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Jakobshavn glacier from ERS-1, ERS2 and ENVISAT data for 1992-2010, v1.2", "abstract": "This dataset contains time series of ice velocities for the Jakobshavn Glacier in Greenland, which have been derived from intensity-tracking of ERS-1, ERS-2 and Envisat data acquired between between 1992 and 2010. It provides components of the ice velocity and the magnitude of the ice velocity and has been produced as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nThe dataset contains two time series: 'Greenland_Jakobshavn_TimeSeries_2002_2010' contains an older version of the time series kept for completeness and also to ensure the best temporal coverage. It is based on data from the ASAR instrument on ENVISAT, acquired between 10/11/2002 and 23/09/2010 and contains 47 maps of ice velocity. \r\n\r\nThe second time series 'greenland_jakobshavn_timeseries_1992_2010' contains the latest version of the time serives based on ERS-1, ERS-2 and Envisat data acquired between 27/01/1992 and 13/06/2010 and contains 120 maps.\r\n\r\nThe data is provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E) with 500m grid spacing. The image pairs have a repeat cycle between 1 and 35 days.\r\nThe horizontal velocity is provided in true meters per day, towards EASTING(x) and NORTHING(y) direction of the grid, and the vertical displacement (z), derived from a digital elevation model, is also provided.\r\n\r\nThe product was generated by GEUS (Geological Survey of Denmark and Greenland) and ENVEO (Earth Observation Information Technology GmbH)." }, { "ob_id": 26668, "uuid": "2e54b40f184b44c797db36e192d2b679", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity time series for the Jakobshavn Glacier from COSMO-SkyMed for 2012-2014, v1.0", "abstract": "This dataset contains ice velocity time series of then Jakobshavn glacier in Greenland, derived from intensity-tracking of COSMO-SkyMed data acquired between 2/6/2012 and 25/12/2014. The ice velocity data is derived using 4-day COSMO-SkyMed offset-tracking pairs. It has been produced as part of the ESA Greenland Ice sheet CCI project. \r\n\r\nThe data are provided on a polar stereographic grid (EPSG3413: Latitude of true scale 70N, Reference Longitude 45E) with 250m grid spacing. Image pairs with a repeat cycle of 4 days have been used.\r\nThe horizontal velocity is provided in true meters per day, towards EASTING(x) and NORTHING(y) direction of the grid, and the vertical displacement (z), derived from a digital elevation model, is also provided.\r\n\r\nThe product was generated by DTU Space. For further details, please consult the document:\r\nT. Nagler, et al., Product User Guide (PUG) for the Greenland_Ice_Sheet_cci project of ESA's Climate Change Initiative, version 2.0." }, { "ob_id": 19860, "uuid": "b989a4bf8d534973918470118c0d96fe", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity Time Series of the Petermann Glacier for 2015-2016 from Sentinel-1 data, v1.0", "abstract": "This dataset contains a time series of ice velocities for the Petermann Glacier in Greenland, derived from Sentinel-1 SAR data acquired between 23/1/2015-10/6/2016. It has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 19866, "uuid": "ea4fefb0e791495fb80d6f571f055a6b", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Ice Velocity Time Series of the Upernavik Isstroem for 2014-2016 from Sentinel-1 data, v1.0", "abstract": "This dataset contains a time series of ice velocities for the Upernavik Isstroem glacier in Greenland, derived from Sentinel-1 SAR data acquired between October 2014 and June 2016. This dataset has been produced by the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project.\r\n\r\nData files are delivered in NetCDF format at 250m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity components are provided in true meters per day, towards the EASTING(x) and NORTHING(y) directions of the grid." }, { "ob_id": 26644, "uuid": "ea7a4cbe7b83450bb7a00bf3761c40d7", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Grounding Line Locations from SAR Interferometry, v1.3", "abstract": "This dataset contains grounding lines for 5 North Greenland glaciers, derived from generated from ERS -1/-2 and Sentinel-1 SAR (Synthetic Aperture Radar) interferometry. This version of the dataset (v1.3) has been extended with grounding lines for 2017. Data was produced as part of the ESA Greenland Ice Sheets Climate Change Initiative (CCI) project by ENVEO, Austria. \r\n\r\nThe grounding line is the separation point between the floating and grounded parts of the glacier. Processes at the grounding lines of floating marine termini of glaciers and ice streams are important for understanding the response of the ice masses to changing boundary conditions and for establishing realistic scenarios for the response to climate change. The grounding line location product is derived from InSAR data by mapping the tidal flexure and is generated for a selection of the few glaciers in Greenland, which have a floating tongue. In general, the true location of the grounding line is unknown, and therefore validation is difficult for this product.\r\n\r\nRemote sensing observations do not provide direct measurement on the transition from floating to grounding ice (the grounding line). The satellite data deliver observations on ice surface features (e.g. tidal deformation by InSAR, spatial changes in texture and shading in optical images) that are indirect indicators for estimating the position of the grounding line. Due to the plasticity of ice these indicators spread out over a zone upstream and downstream of the grounding line, the tidal flexure zone (also called grounding zone)." }, { "ob_id": 26648, "uuid": "eaed9fba86c44e9c854dfbdec9d16b99", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Ice Velocity Map, Winter 2017-2018, v1.0", "abstract": "This dataset provides an ice velocity map for the whole Greenland ice-sheet for the winter of 2017-2018, derived from Sentinel-1 SAR data acquired from 28/12/2017 to 28/02/2018, as part of the ESA Greenland Ice Sheet Climate Change Initiative (CCI) project. \r\n\r\nIn total approximately 1900 S-1A & S-1B scenes are used to derive the surface velocity applying feature tracking techniques. The ice velocity map is provided at 500m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity is provided in true meters per day, towards EASTING(vx) and NORTHING(vy) direction of the grid, and the vertical displacement (vz),\r\nderived from a digital elevation model, is also provided. The product was generated by ENVEO (Earth Observation Information Technology GmbH)." }, { "ob_id": 26663, "uuid": "cfe3102659f34d33b123b2a0043e4068", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Optical ice velocity of the Jakobshavn Glacier between 2017-06-03 and 2017-09-08, generated using Sentinel-2 data, v1.1", "abstract": "This dataset contains optical ice velocity time series and seasonal product of the Jakobshavn Glacier in Greenland, derived from intensity-tracking of Sentinel-2 data acquired between 2017-06-03 and 2017-09-08. It has been produced as part of the ESA Greenland Ice sheet CCI project. \r\n\r\nThe data are provided on a polar stereographic grid (EPSG 3413:Latitude of true scale 70N, Reference Longitude 45E) with 50m grid spacing. The horizontal velocity is provided in true meters per day, towards EASTING (x) and NORTHING (y) direction of the grid.\r\n\r\nThe data have been produced by S[&]T Norway." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 55593, 55592, 55589, 105401, 105409, 105429, 105453, 55591, 55590 ], "onlineresource_set": [ 8733, 9263 ], "project_set": [ 14317 ] }, { "ob_id": 14346, "uuid": "6ac7dd15c35b416d83dbebc1713c7909", "short_code": "coll", "title": "Polluted Troposphere TORCH2: Tropospheric ORganic CHemistry Experiment (TORCH2) Ground-based Atmospheric Components Measurements Collection from the Weybourne Atmospheric Observatory, Norfolk", "abstract": "The Polluted Troposphere Programme was a 5-year NERC thematic research programme which was centred upon the study of polluted boundary layer air and its transport to the free troposphere. The programme focussed on the regional scale, defined as intermediate between urban and hemispheric.\r\n\r\nThis dataset collection contains measurements of O3, CO, NO, NO2, C2-C8 hydrocarbons, C1-C4 oxygenated hydrocarbons, PAN, Peroxides (Organic and Inorganic), Organic nitrates, OH and HO2 radicals, Sum of RO2 + HO2 radicals, OH chemical lifetime, Photolysis frequencies (e.g. j(O1D), j(NO2), j (HCHO), Aerosol number and size distribution, Aerosol composition, Local meteorology, and 5 and 10 day back trajectories. Many of the instruments are also part of the Universities Facility for Atmospheric Measurement (UFAM).\r\n \r\nTORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast. \r\n\r\nThe goals were to provide both a detailed data set on organic composition in the polluted atmosphere, and to develop theoretical and modelling tools which may be used in defining future air quality policy. \r\n\r\nThis collection also includes data collected as part of the NERC Polluted Troposphere \"Advanced GC-MS technology for observing OVOCs and NMHCs in the polluted troposphere\" project.\r\n\r\n\r\n", "keywords": "Polluted Troposphere, TORCH2, Chemistry, Meteorology", "publicationState": "published", "dataPublishedTime": "2007-12-10T02:41:25", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1142, "name": "NDGO0005" } ], "member": [ { "ob_id": 3232, "uuid": "354fcb89720ad5278a216e02b086c043", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of East Anglia Peroxyacetylnitrate (PAN) measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains peroxyacetylnitrate (PAN) measurements from a GC- ECD." }, { "ob_id": 3235, "uuid": "8455dff040b64d6e70b8ff897f2a8c60", "short_code": "ob", "title": "Polluted Troposphere TORCH2: Univeristy of York: Dual Column Gas Chromatograph-Flame Ionization Detector 1 (DC-GC-FID1) NMHC, O-VOC and DMS measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains NMHC, O-VOC and DMS measurement by dual channel PTV-GC-FID." }, { "ob_id": 3186, "uuid": "0ddb1dcc05def74fa5e9e9c2c21f21b3", "short_code": "ob", "title": "Polluted Troposphere TORCH2: Vertical wind profile data from the Universities' Facility for Atmospheric Measurement's (UFAM) 1290mhz Degreane Mobile Wind Profiler deployed at the Weybourne Atmospheric Observatory", "abstract": "The University of Wales, Aberystwyth, 1290mhz mobile wind profiler - now referred to as the University of Manchester mobile wind profiler, was operated at the Weybourne Atmospheric Observatory during the 2nd field campaign of the Tropospheric ORganic CHemistry Experiment (TORCH) Project. The TORCH project was part of the Natural Environmental Research Council's (NERC) Polluted Troposphere research programme. The field campaign ran from 22nd April to 28th May 2004, during which period the mobile wind profiler obtained vertical profiles of the horizontal and vertical wind components. For each signal beam profiles of the signal to noise (SNR) ratio and spectral widths were also taken. The data consist of files in the netCDF binary format and plots in PNG format. Data are available to all BADC registered users under the Government Open Data licence." }, { "ob_id": 3189, "uuid": "6c89394eb0a8a3c00fdf33489cec9d4d", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of Leeds OH and H2O Fluorecence Assay Gas Expansion (FAGE) measurments at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains OH and HO2 measurement by the Fluorecence Assay Gas Expansion (FAGE) at Weybourne Atmospheric Observatory" }, { "ob_id": 14332, "uuid": "56d4701433134da7bcd4795f0b0520d7", "short_code": "ob", "title": "Polluted Troposphere TORCH2: Univeristy of Leicester filter radiometer j(NO2) measurements at Writtle College, UK", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains j(NO2) measurements from a filter radiometer." }, { "ob_id": 3204, "uuid": "0fba03e97504faac0c7bde95b91ec366", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of Leicester filter radiometer j(O1D)-a measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains filter radiometer j(O1D)-a measurements." }, { "ob_id": 14328, "uuid": "8a575ae6a7fc42348315cab8d5754ad6", "short_code": "ob", "title": "Polluted Troposphere TORCH2: ECMWF trajectories", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains ECMWF trajectories." }, { "ob_id": 3238, "uuid": "a9955ad7782cfefe492c4e2a8c6f7f98", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of York Dual Column GC-fid 2 NMHC, O-VOC and DMS measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains NMHC, O-VOC and DMS measurement by dual channel PTV-GC-FID." }, { "ob_id": 3226, "uuid": "0da7902e61d08e14590026030be155f5", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of East Anglia condensation nuclei counter measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains condensation nuclei counter measurements." }, { "ob_id": 14330, "uuid": "7826da5f1ac14003b38e6cfb50f9969d", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of East Anglia O3 measurements at Weybourne Atmospheric Observatory, UK", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains O3 measurements from a 49C Analyser." }, { "ob_id": 3220, "uuid": "6b72f314409e6d0b0d56f01242f599e0", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of East Anglia Gas Chromatography Negative Ion Chemical Ionisation Mass Spectrometry nitrate measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains gas chromatography negative ion chemical ionisation mass spectrometry nitrate measurements." }, { "ob_id": 3223, "uuid": "86fd4d4d8ad5c0b91ed9add50715a5aa", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of East Anglia Formaldehyde (HCHO) measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains formaldehyde (HCHO) measurements." }, { "ob_id": 3207, "uuid": "54e4b2dd1c7e0f609d48dedfa43e1536", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of Leicester PEroxy measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains peroxy measurements from a PEroxy Radical Chemical Amplification." }, { "ob_id": 3247, "uuid": "55e55d33eca08e3d82f2982c1672ea8f", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of Leicester CH3CHO, CH3COCH3, H202, HNO3, HONO, NO2, O1D and PAN Spectral Radiometer measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains measurements of CH3CHO, CH3COCH3, H202, HNO3, HONO, NO2, O1D and PAN from a Spectral Radiometer." }, { "ob_id": 14334, "uuid": "6ea9a78aa6c14ae1ac24ad697876875c", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of Bristol butane and benzene measurements at Weybourne Atmospheric Observatory, UK", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains butane and benzene measurements from a MADS-GCMS.\r\n\r\nThese data were also collected as part of the Polluted Troposphere: Advanced GC-MS technology for observing OVOCs and NMHCs in the polluted troposphere project." }, { "ob_id": 3216, "uuid": "760635e10997481e00e22ae5a1fbb112", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of East Anglia CO measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains CO measurements from a aerolaser." }, { "ob_id": 3213, "uuid": "1cef5485d0ef7b6809e28bdbf7fe1924", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of Manchester/UFAM Condensation Particle Counter measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains condensation particle counter measurements." }, { "ob_id": 3198, "uuid": "61294eb32798afe5e42ce6160363c4c0", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of Leeds O3 measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis datasets contains O3 measurements using TEI49C UV ozone analyser." }, { "ob_id": 3195, "uuid": "9d827059c54b8e33dd6f7d438267f9f0", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of Leeds OH lifetime measurments at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains OH Lifetime measurement Weybourne Atmospheric Observatory." }, { "ob_id": 3241, "uuid": "2de7e7241a62535eb07fb663900a8dd1", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of York Dual Column GC-fid 3 NMHC, O-VOC and DMS measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains NMHC, O-VOC and DMS measurements by dual channel PTV-GC-FID." }, { "ob_id": 3192, "uuid": "b0111895307656d831edd429226d2d9b", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of Leeds Wind, Relative humidity and temperature measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains temperature, relative humidity, wind speed and wind direction measurements taken using Campbell Scientific basic weather station." }, { "ob_id": 3210, "uuid": "a043fe4fc3a2256914f9aa0acbecb74d", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of Manchester/UFAM at Sulphate, Nitrate, Ammonium and organic matter measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains sulphate, nitrate, ammonium and organic matter measurements from a aerosol mass spectrometer." }, { "ob_id": 3229, "uuid": "eb00f1550bb17c715df4109149a8070e", "short_code": "ob", "title": "Polluted Troposphere TORCH2: University of East Anglia NOx, O3 and NOy measurements at Weybourne Atmospheric Observatory", "abstract": "Tropospheric ORganic CHemistry Experiment (TORCH) was a Natural Environment Research Council (NERC) Polluted Troposphere Research Programme project (Round 1 - NER/T/S/2002/00145. Duration 2002 - 2005) led by A. Lewis, University of York. TORCH 2 took place in April and May 2004 at Weybourne Atmospheric Observatory, on the north Norfolk coast.\r\n\r\nThis dataset contains NOx, O3 and NOy measurements from the uea-cranox instrument." } ], "identifier_set": [ 8964, 8970, 10410 ], "responsiblepartyinfo_set": [ 55680, 55681, 55682, 55683, 55684, 55687, 55686, 55685, 55728, 55726, 55721, 55724, 55716, 55727, 55731, 55690, 55715, 55688, 55730, 55723, 55732, 55722, 55718, 55719, 55729, 55720, 55689 ], "onlineresource_set": [ 8741, 8740, 8742, 8743 ], "project_set": [ 14345, 12035 ] }, { "ob_id": 14367, "uuid": "5e789087d4e847308a39b3fe5b26e281", "short_code": "coll", "title": "ESA Sea Ice Climate Change Initiative (Sea Ice CCI) Dataset Collection", "abstract": "Collection of datasets from the ESA Sea Ice Climate Change Initiative (CCI) project. The Sea Ice CCI is developing improved and validated timeseries of ice concentration for the Arctic and Antarctic and ice thickness datasets for the Arctic to support climate research and monitoring. Since sea ice is a sensitive climate indicator with large seasonal and regional variability, the climate research community require long-term and regular observations of the key ice parameters in both Arctic and Antarctic.", "keywords": "ESA, Sea Ice, CCI, ECV", "publicationState": "published", "dataPublishedTime": "2016-03-08T16:48:48", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 95 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 14369, "uuid": "206cb2ee5d964760824dfe23b90a1cda", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea Ice CCI): Northern Hemisphere Sea Ice Concentration (SIC) from the SSMI instrument, Version 1.11", "abstract": "This data set is part of the ESA Sea Ice Climate Change Initiative (CCI) project. The dataset provides sea ice concentration for the Arctic region, derived from the SSMI satellite instrument.\r\n\r\nIt consists of daily gridded SIC fields based on Passive Microwave Radiometer measurements from the SSMI instrument with a 25km grid spacing, along with the total standard error (uncertainty) and quality control flags. It has been built upon the algorithms and processing software originally developed at the EUMETSAT OSI SAF for their SIC dataset.\r\n\r\nPlease note, in the sea ice concentration data set - on purpose - no weather filter has been applied to eliminate weather-induced spurious ice in the open ocean along the ice edge in order to avoid discarding regions with a real sea ice cover. Users are advised to read the product user guide and the publication by Ivanova et al. [2015] (see documentation section). \r\n\r\nA second sea ice dataset has also been produced from the AMSR-E instrument, and these should be regarded as individual datasets and not combined without further investigations about the compatibility.\r\n\r\n\r\n\r\n" }, { "ob_id": 41402, "uuid": "67b003a864cd4e9ebeccd29fbdf4447e", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from the CryoSat-2 satellite on a monthly grid (L3C), v3.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the SH polar region, derived from the SIRAL (SAR Interferometer Radar ALtimeter) instrument on the CryoSat-2 satellite at Level 3C (L3C). This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data gridded on a Lambeth Azimuthal Equal Area grid for the period November 2010 to April 2020. Note, the southern hemisphere sea ice thickness dataset is an experimental climate data record, as the algorithm does not properly considers the impact of the complex snow morphology in the freeboard retrieval. Sea ice thickness is provided for all months but needs to be considered biased high in areas with high snow depth and during the southern summer months. Please consult the Product User Guide (PUG) for more information." }, { "ob_id": 41406, "uuid": "92eb2ba942074bec804af6a8b5436bee", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from Envisat on the satellite swath (L2P), v3.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the northern hemisphere polar region, derived from the RA-2 (Radar Altimeter -2) instrument on the Envisat satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data for the winter months of October to April annually on the satellite measurement grid (Level 2P) at the full sensor resolution for the period October 2002 to March 2012." }, { "ob_id": 43948, "uuid": "e74c6b7eb76645ed8b1b88ecb3d6dcc8", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Sea Ice: drift-aware sea-ice thickness for the Southern Hemisphere from Envisat, v1.0", "abstract": "This dataset provides daily drift-aware sea ice freeboard and thickness maps, using satellite altimetry data from Envisat, covering the entire Antarctic sea ice domain. Daily files are provided during austral summer seasons (October to April).\r\n\r\nNeglecting sea ice drift when generating monthly sea ice thickness maps from satellite altimetry will cause blurring of the spatial distribution of ice thickness. We therefore suggest synergizing sea ice freeboard and thickness information from satellite altimetry with sea ice drift estimates from passive microwave satellite sensors. With our approach, we successively advect individual parcels of satellite altimeter measurements daily over a time span of one month to obtain drift-aware sea ice freeboard and thickness maps. Because of the drift correction, we can also determine sea ice that was overflown by the satellite multiple times. This allows to estimate growth rates and changes in the sea ice thickness distribution due to deformation and thermodynamic ice growth between satellite overflights. With the estimation of sea ice growth, measurements can be corrected for the time offset between the acquisition day and the target day, the day to which all measurements within a month are projected.\r\n\r\nNORCE, METNO" }, { "ob_id": 14373, "uuid": "a8fb73c6610a46128181053b3c1c7333", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea Ice CCI): Southern Hemisphere Sea Ice Concentration (SIC) from the AMSR-E instrument, Version 1.11", "abstract": "This data set is part of the ESA Sea Ice Climate Change Initiative (CCI) project. The dataset provides sea ice concentration for the Antarctic region, derived from the AMSR-E satellite instrument.\r\n\r\nIt consists of daily gridded SIC fields based on Passive Microwave Radiometer measurements from the AMSR-E instrument with a 25km grid spacing, along with the total standard error (uncertainty) and quality control flags. It has been built upon the algorithms and processing software originally developed at the EUMETSAT OSI SAF for their SIC dataset.\r\n\r\nPlease note, in the sea ice concentration data set - on purpose - no weather filter has been applied to eliminate weather-induced spurious ice in the open ocean along the ice edge in order to avoid discarding regions with a real sea ice cover. Users are advised to read the product user guide and the publication by Ivanova et al. [2015] (see documentation section). \r\n\r\nA second sea ice dataset has also been produced from the SSM/I instrument, and these should be regarded as individual datasets and not combined without further investigations about the compatibility.\r\nThe project team warns potential users that the AMSR-E SIC time-series is less mature than the SSM/I one, and that the former should be used with extra care, possibly after visual inspection or comparison to other data sources (such as the SSM/I time series during the overlap period)\r\n\r\n\r\n" }, { "ob_id": 41401, "uuid": "83b11005a3d7472eb57df4f90933c462", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from the Envisat satellite on a monthly grid (L3C), v3.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the northern hemisphere polar region, derived from the RA-2 (Radar Altimeter -2) instrument on the ENVISAT satellite at Level 3C (L3C). This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly gridded sea ice thickness data on a Lambeth Azimuthal Equal Area grid for the period October 2002 to March 2012. Data is only available for the NH winter months, October - April." }, { "ob_id": 41404, "uuid": "ab6a05baacce4c848d137a0bc9921e6e", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from the Envisat satellite on a monthly grid (L3C), v3.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the southern hemisphere polar region, derived from the RA-2 (Radar Altimeter -2) instrument on the Envisat satellite at Level 3C (L3C). This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly gridded sea ice thickness data on a Lambeth Azimuthal Equal Area Projection for the period October 2002 to March 2012. Note, the southern hemisphere sea ice thickness dataset is an experimental climate data record, as the algorithm does not properly consider the impact of the complex snow morphology in the freeboard retrieval. Sea ice thickness is provided for all months but needs to be considered biased high in areas with high snow depth and during the southern summer months. Please consult the Product User Guide (PUG) for more information." }, { "ob_id": 14371, "uuid": "0bf2a301eeba46dfa16668b716d02ab5", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea Ice CCI): Northern Hemisphere Sea Ice Concentration (SIC) from the AMSR-E instrument, Version 1.11", "abstract": "This data set is part of the ESA Sea Ice Climate Change Initiative (CCI) project. The dataset provides sea ice concentration for the Arctic region, derived from the AMSR-E satellite instrument.\r\n\r\nIt consists of daily gridded SIC fields based on Passive Microwave Radiometer measurements from the AMSR-E instrument with a 25km grid spacing, along with the total standard error (uncertainty) and quality control flags. It has been built upon the algorithms and processing software originally developed at the EUMETSAT OSI SAF for their SIC dataset.\r\n\r\nPlease note, in the sea ice concentration data set - on purpose - no weather filter has been applied to eliminate weather-induced spurious ice in the open ocean along the ice edge in order to avoid discarding regions with a real sea ice cover. Users are advised to read the product user guide and the publication by Ivanova et al. [2015] (see documentation section). \r\n\r\nA second sea ice dataset has also been produced from the SSM/I instrument, and these should be regarded as individual datasets and not combined without further investigations about the compatibility.\r\nThe project team warns potential users that the AMSR-E SIC time-series is less mature than the SSM/I one, and that the former should be used with extra care, possibly after visual inspection or comparison to other data sources (such as the SSM/I time series during the overlap period). \r\n\r\n\r\n" }, { "ob_id": 44279, "uuid": "26b398778ac441f889e5b873c73a6343", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from Sentinel-3B on the satellite swath (L2P), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the northern hemisphere polar region, derived from the SRAL (Synthetic aperture Radar Altimeter) instrument on the from the Sentinel-3B satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data for the months October to April annually on the satellite measurement grid (Level 2P) at the full sensor resolution for the period November 2018 to April 2024." }, { "ob_id": 20367, "uuid": "8a45e78c4657438997617c726337dffc", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Sea Ice Concentration Climate Data Record from the AMSR-E and AMSR-2 instruments at 50 km grid spacing, version 2.0", "abstract": "The dataset provides a Climate Data Record of Sea Ice Concentration (SIC) for the polar regions, derived from medium resolution passive microwave satellite data (AMSR-E and AMSR-2). It is processed with an algorithm using coarse resolution (6 GHz and 37 GHz) imaging channels, and has been gridded at 50km grid spacing.\r\n\r\nThis product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea_Ice_CCI project. The EUMETSAT OSI SAF contributed with access and re-use of part of its processing software and facilities.\r\n\r\nA SIC CDR at 25km grid spacing is also available (doi: 10.5285/c61bfe88-873b-44d8-9b0e-6a0ee884ad95) and a 12.5km product is in preparation." }, { "ob_id": 43483, "uuid": "8978580336864f6d8282656d58771b32", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Nimbus-5 ESMR Sea Ice Concentration, version 1.1", "abstract": "This dataset provides Sea Ice Concentration (SIC) for the polar regions, derived from the Nimbus-5 Electrical Scanning Microwave Radiometer (ESMR), which operated between 1972 and 1977. It is processed with an algorithm using the single channel ESMR data (19.35 GHz), and has been gridded at 25 km grid spacing. This is the second version of the product, v1.1.\r\n\r\nThis product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project." }, { "ob_id": 25870, "uuid": "fbfae06e787b4fefb4b03cba2fd04bc3", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from CryoSat-2 on the satellite swath (L2P), v2.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the SH polar region, derived from the SIRAL (SAR Interferometer Radar ALtimeter) instrument on the CryoSat-2 satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data on the satellite measurement grid (Level 2P) at the full sensor resolution for the period November 2010 to April 2017. Note, the southern hemisphere sea ice thickness dataset is an experimental climate data record, as the algorithm does not properly considers the impact of the complex snow morphology in the freeboard retrieval. Sea ice thickness is provided for all months but needs to be considered biased high in areas with high snow depth and during the southern summer months. Please consult the Product User Guide (PUG) for more information." }, { "ob_id": 41407, "uuid": "861ad3c7f3a34ebd8be6f618a92bd8e3", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from CryoSat-2 on the satellite swath (L2P), v3.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the SH polar region, derived from the SIRAL (SAR Interferometer Radar ALtimeter) instrument on the CryoSat-2 satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data on the satellite measurement grid (Level 2P) at the full sensor resolution for the period November 2010 to April 2020. Note, the southern hemisphere sea ice thickness dataset is an experimental climate data record, as the algorithm does not properly consider the impact of the complex snow morphology in the freeboard retrieval. Sea ice thickness is provided for all months but needs to be considered biased high in areas with high snow depth and during the southern summer months. Please consult the Product User Guide (PUG) for more information." }, { "ob_id": 20365, "uuid": "bc3f8a3cf94c4d0180a60b7e2bfd9c5b", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Sea Ice Concentration Climate Data Record from the AMSR-E and AMSR-2 instruments at 25km grid spacing, version 2.0", "abstract": "The dataset provides a Climate Data Record of Sea Ice Concentration (SIC) for the polar regions, derived from medium resolution passive microwave satellite data (AMSR-E and AMSR-2). It is processed with an algorithm using medium resolution (19 GHz and 37 GHz) imaging channels, and has been gridded at 25km grid spacing.\r\n\r\nThis product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project. The EUMETSAT OSI SAF contributed with access and re-use of part of its processing software and facilities.\r\n\r\nA SIC CDR at 50 km grid spacing is also available (doi:10.5285/70f611b0-ba82-48e6-9190-a62cf9f925f2) and a 12.5km product is in preparation." }, { "ob_id": 44283, "uuid": "f4631b76dbae432ead809836805944d7", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from Envisat on a monthly grid (L3C), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the southern hemisphere polar region, derived from the RA-2 (Radar Altimeter -2) instrument on the Envisat satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly sea ice thickness data annually on the satellite measurement grid (Level 3C) at the full sensor resolution for the period October 2002 to March 2012." }, { "ob_id": 25873, "uuid": "5b6033bfb7f241e89132a83fdc3d5364", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from CryoSat-2 on the satellite swath (L2P), v2.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the NH polar region, derived from the SIRAL (SAR Interferometer Radar ALtimeter) instrument on the CryoSat-2 satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data for the months October to April annually on the satellite measurement grid (Level 2P) at the full sensor resolution for the period November 2010 to April 2017." }, { "ob_id": 44287, "uuid": "f4d89a6e59724ecbb7a4b8d4a8df622d", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from Sentinel-3A on a monthly grid (L3C), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the Southern Hemisphere polar region, derived from the SRAL (Synthetic aperture Radar Altimeter) instrument on the Sentinel -3A satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly sea ice thickness data on the satellite measurement grid (Level 3C) at the full sensor resolution for the period October 2016 to April 2024." }, { "ob_id": 25867, "uuid": "f4c34f4f0f1d4d0da06d771f6972f180", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from the Envisat satellite on a monthly grid (L3C), v2.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the northern hemisphere polar region, derived from the RA-2 (Radar Altimeter -2) instrument on the ENVISAT satellite at Level 3C (L3C). This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly gridded sea ice thickness data on a Lambeth Azimuthal Equal Area grid for the period October 2002 to March 2012. Data is only available for the NH winter months, October - April." }, { "ob_id": 41400, "uuid": "45b5b1e556da448089e2b57452f277f5", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from the CryoSat-2 satellite on a monthly grid (L3C), v3.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the Northern Hemisphere polar region, derived from the SIRAL (SAR Interferometer Radar ALtimeter) instrument on the CryoSat-2 satellite at Level 3C (L3C). This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly gridded sea ice thickness data on a Lambeth Azimuthal Equal Area grid for the period November 2010 to April 2020. Data are only available for the NH winter months, October - April." }, { "ob_id": 25866, "uuid": "54e2ee0803764b4e84c906da3f16d81b", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from Envisat on the satellite swath (L2P), v2.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the northern hemisphere polar region, derived from the RA-2 (Radar Altimeter -2) instrument on the Envisat satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data for the winter months of October to April annually on the satellite measurement grid (Level 2P) at the full sensor resolution for the period October 2002 to March 2012." }, { "ob_id": 25869, "uuid": "550d938da3184d0ca44a06a4c0c14ffa", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from Envisat on the satellite swath (L2P), v2.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the southern hemisphere polar region, derived from the RA-2 (Radar Altimeter -2) instrument on the Envisat satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data on the satellite measurement grid (Level 2P) at the full sensor resolution for the period October 2002 to March 2012. Note, the southern hemisphere sea ice thickness dataset is an experimental climate data record, as the algorithm does not properly considers the impact of the complex snow morphology in the freeboard retrieval. Sea ice thickness is provided for all months but needs to be considered biased high in areas with high snow depth and during the southern summer months. Please consult the Product User Guide (PUG) for more information." }, { "ob_id": 25057, "uuid": "f17f146a31b14dfd960cde0874236ee5", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Sea Ice Concentration Climate Data Record from the AMSR-E and AMSR-2 instruments at 25km grid spacing, version 2.1", "abstract": "The dataset provides a Climate Data Record of Sea Ice Concentration (SIC) for the polar regions, derived from medium resolution passive microwave satellite data from the Advanced Microwave Scanning Radiometer series (AMSR-E and AMSR-2). It is processed with an algorithm using medium resolution (19 GHz and 37 GHz) imaging channels, and has been gridded at 25km grid spacing. This version of the product is v2.1, which is an extension of the v2.0 Sea_Ice_cci data and has identical data until 2015-12-25.\r\n\r\nThis product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project. The EUMETSAT OSI SAF contributed with access and re-use of part of its processing software and facilities.\r\n\r\nA SIC CDR at 50 km grid spacing is also available." }, { "ob_id": 44278, "uuid": "fe7025b9938346dc99f31a61ad7d4e01", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from Sentinel-3A on the satellite swath (L2P), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the Southern Hemisphere polar region, derived from the SRAL (Synthetic aperture Radar Altimeter) instrument on the Sentinel-3A satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data on the satellite measurement grid (Level 2P) at the full sensor resolution for the period October 2016 to April 2024." }, { "ob_id": 25872, "uuid": "ff79d140824f42dd92b204b4f1e9e7c2", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from the CryoSat-2 satellite on a monthly grid (L3C), v2.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the Northern Hemisphere polar region, derived from the SIRAL (SAR Interferometer Radar ALtimeter) instrument on the CryoSat-2 satellite at Level 3C (L3C). This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly gridded sea ice thickness data on a Lambeth Azimuthal Equal Area grid for the period November 2010 to April 2017. Data are only available for the NH winter months, October - April." }, { "ob_id": 14375, "uuid": "ffea041274fd4f2b929ff7a826395742", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern Hemisphere Sea Ice Concentration (SIC) from the SSMI instrument, Version 1.11", "abstract": "This data set is part of the ESA Sea Ice Climate Change Initiative (CCI) project. The dataset provides sea ice concentration (SIC) for the Antarctic region, derived from the SSMI satellite instrument. \r\n\r\n It consists of daily gridded SIC fields based on Passive Microwave Radiometer measurements from the SSMI instrument with a 25km grid spacing, along with the total standard error (uncertainty) and quality control flags. It has been built upon the algorithms and processing software originally developed at the EUMETSAT OSI SAF for their SIC dataset.\r\n\r\nPlease note, in the sea ice concentration data set - on purpose - no weather filter has been applied to eliminate weather-induced spurious ice in the open ocean along the ice edge in order to avoid discarding regions with a real sea ice cover. Users are advised to read the product user guide and the publication by Ivanova et al. [2015] (see documentation section). \r\n\r\nA second sea ice dataset has also been produced from the AMSR-E instrument, and these should be regarded as individual datasets and not combined without further investigations about the compatibility.\r\n\r\n\r\n\r\n" }, { "ob_id": 25871, "uuid": "48fc3d1e8ada405c8486ada522dae9e8", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from the CryoSat-2 satellite on a monthly grid (L3C), v2.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the SH polar region, derived from the SIRAL (SAR Interferometer Radar ALtimeter) instrument on the CryoSat-2 satellite at Level 3C (L3C). This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data gridded on a Lambeth Azimuthal Equal Area grid for the period November 2010 to April 2017. Note, the southern hemisphere sea ice thickness dataset is an experimental climate data record, as the algorithm does not properly considers the impact of the complex snow morphology in the freeboard retrieval. Sea ice thickness is provided for all months but needs to be considered biased high in areas with high snow depth and during the southern summer months. Please consult the Product User Guide (PUG) for more information." }, { "ob_id": 39465, "uuid": "34a15b96f1134d9e95b9e486d74e49cf", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Nimbus-5 ESMR Sea Ice Concentration, version 1.0", "abstract": "This dataset provides Sea Ice Concentration (SIC) for the polar regions, derived from the Nimbus-5 Electrical Scanning Microwave Radiometer (ESMR), which operated between 1972 and 1977. It is processed with an algorithm using the single channel ESMR data (19.35 GHz), and has been gridded at 25 km grid spacing. This is the first version of the product, v1.0.\r\n\r\nThis product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project." }, { "ob_id": 44289, "uuid": "db0aee3dbdc54ab0981bca2e632f3be3", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from Sentinel-3B on a monthly grid (L3C), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the Southern Hemisphere polar region, derived from the SRAL (Synthetic aperture Radar Altimeter) instrument on the Sentinel -3B satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly sea ice thickness data on the satellite measurement grid (Level 3C) at the full sensor resolution for the period November 2018 to April 2024." }, { "ob_id": 25058, "uuid": "5f75fcb0c58740d99b07953797bc041e", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Sea Ice Concentration Climate Data Record from the AMSR-E and AMSR-2 instruments at 50km grid spacing, version 2.1", "abstract": "The dataset provides a Climate Data Record of Sea Ice Concentration (SIC) for the polar regions, derived from medium resolution passive microwave satellite data from the Advanced Microwave Scanning Radiometer series (AMSR-E and AMSR-2). It is processed with an algorithm using coarse resolution (6 GHz and 37 GHz) imaging channels, and has been gridded at 50km grid spacing. This version of the product is v2.1, which is an extension of the version 2.0 Sea_Ice_cci dataset and has identical data until 2015-12-25.\r\n\r\nThis product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea_Ice_CCI project. The EUMETSAT OSI SAF contributed with access and re-use of part of its processing software and facilities.\r\n\r\nA SIC CDR at 25km grid spacing is also available." }, { "ob_id": 44281, "uuid": "dfc03980decc4e50b111d5981358930e", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from ERS-2 on a monthly grid (L3C), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the northern hemisphere polar region, derived from the RA (Radar Altimeter) instrument on the ERS-2 satellite (European Remote-sensing Satellite - 2). This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly sea ice thickness data for the months October to April annually on the satellite measurement grid (Level 3C) at the full sensor resolution for the period October 1995 to April 2003." }, { "ob_id": 41408, "uuid": "af96a1ec493f49caa39dc912d15f2b17", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from Envisat on the satellite swath (L2P), v3.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the southern hemisphere polar region, derived from the RA-2 (Radar Altimeter -2) instrument on the Envisat satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data on the satellite measurement grid (Level 2P) at the full sensor resolution for the period October 2002 to March 2012. Note, the southern hemisphere sea ice thickness dataset is an experimental climate data record, as the algorithm does not properly considers the impact of the complex snow morphology in the freeboard retrieval. Sea ice thickness is provided for all months but needs to be considered biased high in areas with high snow depth and during the southern summer months. Please consult the Product User Guide (PUG) for more information." }, { "ob_id": 44280, "uuid": "b8359626272e4f7ba9e2e821b5eab032", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from Sentinel-3B on the satellite swath (L2P), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the southern hemisphere polar region, derived from the SRAL (Synthetic aperture Radar Altimeter) instrument on the from the Sentinel-3B satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data on the satellite measurement grid (Level 2P) at the full sensor resolution for the period November 2018 to April 2024." }, { "ob_id": 44274, "uuid": "1ba530ada3bc4d61a2141e6fa68315f1", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from Envisat on the satellite swath (L2P), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the southern hemisphere polar region, derived from the RA-2 (Radar Altimeter -2) instrument on the Envisat satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data on the satellite measurement grid (Level 2P) at the full sensor resolution for the period October 2002 to March 2012. Note, the southern hemisphere sea ice thickness dataset is an experimental climate data record, as the algorithm does not properly considers the impact of the complex snow morphology in the freeboard retrieval. Sea ice thickness is provided for all months but needs to be considered biased high in areas with high snow depth and during the southern summer months. Please consult the Product User Guide (PUG) for more information." }, { "ob_id": 44285, "uuid": "5cd23b8adfe149e59f218e9b1c9364b3", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from CryoSat-2 on a monthly grid (L3C), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the southern hemisphere polar region, derived from the SIRAL (SAR Interferometer Radar Altimeter) instrument on the CryoSat-2 satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly sea ice thickness data annually on the satellite measurement grid (Level 3C) at the full sensor resolution for the period November 2010 to April 2024." }, { "ob_id": 44288, "uuid": "e33393b68592473cab41701219c74fd7", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from Sentinel-3B on a monthly grid (L3C), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the Northern Hemisphere polar region, derived from the SRAL (Synthetic aperture Radar Altimeter) instrument on the Sentinel -3B satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly sea ice thickness data for the winter months of October to March annually on the satellite measurement grid (Level 3C) at the full sensor resolution for the period November 2018 to April 2024." }, { "ob_id": 44277, "uuid": "1ac5ba6a41d34007bd64bd83b91dc09b", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from Sentinel-3A on the satellite swath (L2P), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the Northern Hemisphere polar region, derived from the SRAL (Synthetic aperture Radar Altimeter) instrument on the Sentinel-3A satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data for the months October to April annually on the satellite measurement grid (Level 2P) at the full sensor resolution for the period October 2016 to April 2024." }, { "ob_id": 44286, "uuid": "87623591b26042a2aa1bac231f657923", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from Sentinel-3A on a monthly grid (L3C), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the Northern Hemisphere polar region, derived from the SRAL (Synthetic aperture Radar Altimeter) instrument on the Sentinel -3A satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly sea ice thickness data for the winter months of October to March annually on the satellite measurement grid (Level 3C) at the full sensor resolution for the period October 2016 to April 2024." }, { "ob_id": 44270, "uuid": "17c6b09a5466406c800c2978f17b8372", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from ERS-2 on the satellite swath (L2P), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the northern hemisphere polar region, derived from the RA (Radar Altimeter) instrument on the ERS-2 satellite (European Remote-sensing Satellite - 2). This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data for the months October to April annually on the satellite measurement grid (Level 2P) at the full sensor resolution for the period October 1995 to April 2003." }, { "ob_id": 44273, "uuid": "5e58f03c4d664b2b9e4e16f2d12e0c4f", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from Envisat on the satellite swath (L2P), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the northern hemisphere polar region, derived from the RA-2 (Radar Altimeter -2) instrument on the Envisat satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data for the winter months of October to April annually on the satellite measurement grid (Level 2P) at the full sensor resolution for the period October 2002 to March 2012." }, { "ob_id": 44275, "uuid": "5487186f657644f798a1e6828d8bed3c", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from CryoSat-2 on the satellite swath (L2P), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the northern hemisphere polar region, derived from the SIRAL (SAR Interferometer Radar Altimeter) instrument on the CryoSat-2 satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data for the months October to April annually on the satellite measurement grid (Level 2P) at the full sensor resolution for the period October 2010 to April 2024." }, { "ob_id": 44284, "uuid": "887ebbe3aa4345f3bbcbe2dd1834d955", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from CryoSat-2 on a monthly grid (L3C), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the northern hemisphere polar region, derived from the SIRAL (SAR Interferometer Radar Altimeter) instrument on the CryoSat-2 satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly sea ice thickness data for the winter months of October to March annually on the satellite measurement grid (Level 3C) at the full sensor resolution for the period October 2010 to April 2024." }, { "ob_id": 44276, "uuid": "edfda165965749cbb8ba7c2e0d30a6b4", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from CryoSat-2 on the satellite swath (L2P), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the southern hemisphere polar region, derived from the SIRAL (SAR Interferometer Radar Altimeter) instrument on the CryoSat-2 satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data on the satellite measurement grid (Level 2P) at the full sensor resolution for the period November 2010 to April 2024. Note, the southern hemisphere sea ice thickness dataset is an experimental climate data record, as the algorithm does not properly consider the impact of the complex snow morphology in the freeboard retrieval. Sea ice thickness is provided for all months but needs to be considered biased high in areas with high snow depth and during the southern summer months. Please consult the Product User Guide (PUG) for more information." }, { "ob_id": 25868, "uuid": "b1f1ac03077b4aa784c5a413a2210bf5", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Southern hemisphere sea ice thickness from the Envisat satellite on a monthly grid (L3C), v2.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the southern hemisphere polar region, derived from the RA-2 (Radar Altimeter -2) instrument on the Envisat satellite at Level 3C (L3C). This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly gridded sea ice thickness data on a Lambeth Azimuthal Equal Area Projection for the period October 2002 to March 2012. Note, the southern hemisphere sea ice thickness dataset is an experimental climate data record, as the algorithm does not properly considers the impact of the complex snow morphology in the freeboard retrieval. Sea ice thickness is provided for all months but needs to be considered biased high in areas with high snow depth and during the southern summer months. Please consult the Product User Guide (PUG) for more information." }, { "ob_id": 41405, "uuid": "c6504378f78c4ecd9f839b0434023eff", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from CryoSat-2 on the satellite swath (L2P), v3.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the NH polar region, derived from the SIRAL (SAR Interferometer Radar ALtimeter) instrument on the CryoSat-2 satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides daily sea ice thickness data for the months October to April annually on the satellite measurement grid (Level 2P) at the full sensor resolution for the period November 2010 to April 2020." }, { "ob_id": 44282, "uuid": "a0120f31bcd94f8da74ddfebe658773d", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Northern hemisphere sea ice thickness from Envisat on a monthly grid (L3C), v4.0", "abstract": "This dataset provides a Climate Data Record of Sea Ice Thickness for the northern hemisphere polar region, derived from the RA-2 (Radar Altimeter -2) instrument on the Envisat satellite. This product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project.\r\n\r\nIt provides monthly sea ice thickness data for the winter months of October to March annually on the satellite measurement grid (Level 3C) at the full sensor resolution for the period October 2002 to March 2012." }, { "ob_id": 43947, "uuid": "97791d46330b42838af744301c74a9fb", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Drift-aware sea-ice thickness for the Northern Hemisphere from Envisat, v1.0", "abstract": "This dataset provides daily drift-aware sea ice freeboard and thickness maps, using satellite altimetry data from Envisat, covering the entire Arctic sea ice domain. Daily files are provided during boreal winter seasons (October to April).\r\n\r\nNeglecting sea ice drift when generating monthly sea ice thickness maps from satellite altimetry will cause blurring of the spatial distribution of ice thickness. This dataset synergizes sea ice freeboard and thickness information from satellite altimetry with sea ice drift estimates from passive microwave satellite sensors. Individual parcels of satellite altimeter measurements are advected daily over a time span of one month to obtain drift-aware sea ice freeboard and thickness maps. Because of the drift correction, this allows the determination of sea ice that was overflown by the satellite multiple times, and therefore the estimation of growth rates and changes in the sea ice thickness distribution due to deformation and thermodynamic ice growth between satellite overflights. With the estimation of sea ice growth, measurements can be corrected for the time offset between the acquisition day and the target day, the day to which all measurements within a month are projected.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme, as part of the ESA CCI Sea Ice project." }, { "ob_id": 43890, "uuid": "c7cd8115391340638bdd9adb0fbf28e9", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Drift-aware sea-ice thickness for the Northern Hemisphere from CryoSat-2, v1.0", "abstract": "This dataset provides daily drift-aware sea ice freeboard and thickness maps, using satellite altimetry data from CryoSat-2, covering the entire Arctic sea ice domain. Daily files are provided during boreal winter seasons (October to April).\r\n\r\nNeglecting sea ice drift when generating monthly sea ice thickness maps from satellite altimetry will cause blurring of the spatial distribution of ice thickness. This dataset synergizes sea ice freeboard and thickness information from satellite altimetry with sea ice drift estimates from passive microwave satellite sensors. Individual parcels of satellite altimeter measurements are advected daily over a time span of one month to obtain drift-aware sea ice freeboard and thickness maps. Because of the drift correction, this allows the determination of sea ice that was overflown by the satellite multiple times, and therefore the estimation of growth rates and changes in the sea ice thickness distribution due to deformation and thermodynamic ice growth between satellite overflights. With the estimation of sea ice growth, measurements can be corrected for the time offset between the acquisition day and the target day, the day to which all measurements within a month are projected.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme, as part of the ESA CCI Sea Ice project." }, { "ob_id": 39793, "uuid": "eade27004395466aaa006135e1b2ad1a", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): High(er) Resolution Sea Ice Concentration Climate Data Record Version 3 (SSM/I and SSMIS)", "abstract": "This climate data record of sea ice concentration (SIC) is obtained using passive microwave satellite data from the Special Sensor Microwave Imager (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS) over the polar regions (Arctic and Antarctic). The processing chain features: 1) dynamic tuning of tie-points and algorithms, 2) correction of atmospheric noise using a Radiative Transfer Model, 3) computation of per-pixel uncertainties, 4) an optimal hybrid sea ice concentration algorithm, and 5) pan-sharpening of the SIC fields using the near-90 GHz imagery channels. This dataset was generated by the ESA Climate Change Initiative (CCI+) Sea Ice Phase 1 project. This dataset is an enhanced-resolution version of the EUMETSAT Ocean and Sea Ice Satellite Application Facility Global Sea Ice Concentration Climate Data Record (OSI SAF OSI-450-a CDR) over the period 1991-2020." }, { "ob_id": 43946, "uuid": "eb8191228ff84aa285cd02cb66553ab0", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Sea Ice: drift-aware sea-ice thickness for the Southern Hemisphere from CryoSat-2, v1.0", "abstract": "This dataset provides daily drift-aware sea ice freeboard and thickness maps, using satellite altimetry data from CryoSat-2, covering the entire Antarctic sea ice domain. Daily files are provided during austral summer seasons (October to April).\r\n\r\nNeglecting sea ice drift when generating monthly sea ice thickness maps from satellite altimetry will cause blurring of the spatial distribution of ice thickness. We therefore suggest synergizing sea ice freeboard and thickness information from satellite altimetry with sea ice drift estimates from passive microwave satellite sensors. With our approach, we successively advect individual parcels of satellite altimeter measurements daily over a time span of one month to obtain drift-aware sea ice freeboard and thickness maps. Because of the drift correction, we can also determine sea ice that was overflown by the satellite multiple times. This allows to estimate growth rates and changes in the sea ice thickness distribution due to deformation and thermodynamic ice growth between satellite overflights. With the estimation of sea ice growth, measurements can be corrected for the time offset between the acquisition day and the target day, the day to which all measurements within a month are projected.\r\n\r\nNORCE, METNO" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 55757, 55760, 55758, 55781, 105403, 105431, 105455, 55761, 55756 ], "onlineresource_set": [ 8797, 8798 ], "project_set": [ 14368 ] }, { "ob_id": 14430, "uuid": "c19b0914521144ab8c18c91d586c6847", "short_code": "coll", "title": "ESA Land Cover Climate Change Initiative (Land Cover CCI) Dataset Collection", "abstract": "The Land Cover CCI has generated a number of data products as part of its Climate Data Research Package. These consist of: \r\n\r\n- A new time series of consistent global LC maps at 300 m spatial resolution on an annual basis from 1992 to 2015;\r\n- 1 user tool for sub-setting, re-projecting and re-sampling the products in a way which is suitable to each climate model.\r\n- The full archive of AVHRR HRPT 1 km surface reflectance 7-day composites from 1992 to 1999;\r\n- The full archive of MERIS surface reflectance 7-day composites from 2003 to 2011 (300 m and 1 km resolution);\r\n- A PROBA-V 1 km time series of surface reflectance 7-day composites from mid March 2014 to end 2015;\r\n- 1 static map of open water bodies including ENVISAT ASAR data;\r\n- 3 global land surface seasonality products characterizing the vegetation greenness, the snow and the burned areas dynamics.\r\n\r\nIn the context of the CCI Open Data portal, a subset of these data products are held within the CEDA archive. \r\n\r\nThe complete set of data products are available from the CCI Landcover team via their portal at: http://maps.elie.ucl.ac.be/CCI/viewer/", "keywords": "ESA, Land Cover, CCI, ECV", "publicationState": "published", "dataPublishedTime": "2016-03-09T16:29:40", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 111 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 27640, "uuid": "b382ebe6679d44b8b0e68ea4ef4b701c", "short_code": "ob", "title": "ESA Land Cover Climate Change Initiative (Land_Cover_cci): Global Land Cover Maps, Version 2.0.7", "abstract": "As part of the ESA Land Cover Climate Change Initiative (CCI) project a new set of Global Land Cover Maps have been produced. These maps are available at 300m spatial resolution for each year between 1992 and 2015.\r\n\r\nEach pixel value corresponds to the classification of a land cover class defined based on the UN Land Cover Classification System (LCCS). The reliability of the classifications made are documented by the four quality flags (decribed further in the Product User Guide) that accompany these maps. Data are provided in both NetCDF and GeoTiff format.\r\n\r\nFurther Land Cover CCI products, user tools and a product viewer are available at: http://maps.elie.ucl.ac.be/CCI/viewer/index.php . Maps for the 2016-2020 time period have been produced in the context of the Copernicus Climate Change service, and can be downloaded from the Copernicus Climate Data Store (CDS)." }, { "ob_id": 19847, "uuid": "7c114fc6e2884c1f9ca107e7a502fdbf", "short_code": "ob", "title": "ESA Land Cover Climate Change Initiative (Land_Cover_cci): Land Surface Seasonality Products", "abstract": "This dataset consists of Land Surface Seasonality products produced as part of the ESA Land Cover Climate Change Initiative (CCI) project. The products are Vegetation Greenness (NDVI), Snow Occurrence and Burned Area Occurrence. \r\n\r\nOn a per pixel basis, these climatological variables reflect, along the year, the average trajectory and the inter-annual variability of a land surface feature over the 1999-2012 period. They are built from existing long-term global datasets with high temporal frequency and moderate spatial resolution (500m-1km). They result from a compilation of 14 years of 7-day instantaneous observations into 1 temporarily aggregated profile depicting, along the year, the reference behaviour for the vegetation greenness, the snow and the BA at global scale. These products are referred to as condition products in the product user guide." }, { "ob_id": 14549, "uuid": "7e139108035142a9a1ddd96abcdfff36", "short_code": "ob", "title": "ESA Land Cover Climate Change Initiative (Land_Cover_cci): Water Bodies Map, v4.0", "abstract": "As part of the ESA Land Cover Climate Change Initiative (CCI) project a static map of open water bodies at 150 m spatial resolution at the equator has been produced. \r\n\r\nThe CCI WB v4.0 is composed of two layers:\r\n\r\n1. A static map of open water bodies at 150 m spatial resolution resulting from a compilation and editions of land/water classifications: the Envisat ASAR water bodies indicator, a sub-dataset from the Global Forest Change 2000 - 2012 and the Global Inland Water product.\r\n\r\nThis product is delivered at 150 m as a stand-alone product but it is consistent with class \"Water Bodies\" of the annual MRLC (Medium Resolution Land Cover) Maps. The product was resampled to 300 m using an average algorithm. Legend : 1-Land, 2-Water\r\n\r\n2. A static map with the distinction between ocean and inland water is now available at 150 m spatial resolution. It is fully consistent with the CCI WB-Map v4.0. Legend: 0-Ocean, 1-Land.\r\n\r\nTo cite the CCI WB-Map v4.0, please refer to : Lamarche, C.; Santoro, M.; Bontemps, S.; D’Andrimont, R.; Radoux, J.; Giustarini, L.; Brockmann, C.; Wevers, J.; Defourny, P.; Arino, O. Compilation and Validation of SAR and Optical Data Products for a Complete and Global Map of Inland/Ocean Water Tailored to the Climate Modeling Community. Remote Sens. 2017, 9, 36. https://doi.org/10.3390/rs9010036" }, { "ob_id": 37340, "uuid": "26a0f46c95ee4c29b5c650b129aab788", "short_code": "ob", "title": "ESA Land Cover Climate Change Initiative (Land_Cover_cci): Global Plant Functional Types (PFT) Dataset, v2.0.8", "abstract": "This dataset contains Global Plant Functional Types (PFT) data, from the ESA Medium Resolution Land Cover (MRLC) Climate Change Initiative project. The data provides yearly data, and initially covers the time period from 1992 to 2020. It is anticipated that the dataset will be updated annually going forward.\r\n\r\nThe PFT v2.0.8 global dataset has 14 layers, each describing the percentage cover (0-100%) of a plant functional type at a spatial resolution of 300 m: broadleaved evergreen trees, broadleaved deciduous trees, needleleaved evergreen trees, needleleaved deciduous trees, broadleaved evergreen shrubs, broadleaved deciduous shrubs, needleleaved evergreen shrubs, needleleaved deciduous shrubs, natural grasses, herbaceous cropland (i.e., managed grasses), built, water, bare areas, and snow and ice.\r\n\r\n\"Plant Functional Types” (PFTs) refer to globally representative and similarly behaving plant types. PFTs can be related to physiognomy and phenology, climate (which defines the geographical ranges in which a plant type can grow and reproduce under natural conditions, and physiological activity (e.g., C3/C4 photosynthetic pathways).\r\n\r\nAll terrestrial zones of the Earth between the parallels 90°N and 90°S are covered. The PFT dataset has a regular latitude-longitude grid with a grid spacing of 0.002777777777778°, corresponding to ~300 m at the equator and ~200 m in the midlatitudes. The Coordinate Reference System used for the global land cover database is a geographic coordinate system (GCS) based on the World Geodetic System 84 (WGS84) reference ellipsoid.\r\n\r\nThe plant functional type (PFT) distribution was created by combining auxiliary data products with the CCI MRLC map series. The LC classification provides the broad characteristics of the 300 m pixel, including the expected vegetation form(s) (tree, shrub, grass) and/or abiotic land type(s) (water, bare area, snow and ice, built-up) in the pixel. For some classes, the class legend specifies an expected range for the fractional covers of the contributing PFTs and broadly differentiates between natural and cultivated vegetation. We used a quantitative, globally consistent method that fuses the 300-metre MRLC product with a suite of existing high-resolution datasets to develop spatially explicit annual maps of PFT fractional composition at 300 metres. The new PFT product exhibits intraclass spatial variability in PFT fractional cover at the 300-metre pixel level and is complementary to the MRLC maps since the derived PFT fractions maintain consistency with the original LC class legend. \r\n\r\nThis dataset was generated to reduce the cross-walking component of uncertainty by adding spatial variability to the PFT composition within a LC class. This work moved beyond fine-tuning the cross-walking approach for specific LC classes or regions and, instead, separately quantifies the PFT fractional composition for each 300 m pixel globally. The result is a dataset representing the cover fractions of 14 PFTs at 300 m for each year within the time range, consistent with the CCI MRLC LC maps for the corresponding year.\r\n\r\nThis study was carried out with the continued support of the European Space Agency Climate Change Initiative under the contract ESA/No.4000126564 Land_Cover_cci." }, { "ob_id": 44300, "uuid": "313854aedcb04a5eb56f711401a87396", "short_code": "ob", "title": "ESA Land Cover Climate Change Initiative (Land_Cover_cci): Global Plant Functional Types (PFT) Dataset, v2.0.81", "abstract": "This dataset contains Global Plant Functional Types (PFT) data, from the ESA Medium Resolution Land Cover (MRLC) Climate Change Initiative project. The data provides yearly data, and initially covers the time period from 1992 to 2020. It is anticipated that the dataset will be updated annually going forward.\r\n\r\nThis version of the data is v2.0.81, which corrects an issue found with a file in v2.0.8.\r\n\r\nThe PFT v2.0.81 global dataset has 14 layers, each describing the percentage cover (0-100%) of a plant functional type at a spatial resolution of 300 m: broadleaved evergreen trees, broadleaved deciduous trees, needleleaved evergreen trees, needleleaved deciduous trees, broadleaved evergreen shrubs, broadleaved deciduous shrubs, needleleaved evergreen shrubs, needleleaved deciduous shrubs, natural grasses, herbaceous cropland (i.e., managed grasses), built, water, bare areas, and snow and ice.\r\n\r\n\"Plant Functional Types” (PFTs) refer to globally representative and similarly behaving plant types. PFTs can be related to physiognomy and phenology, climate (which defines the geographical ranges in which a plant type can grow and reproduce under natural conditions, and physiological activity (e.g., C3/C4 photosynthetic pathways).\r\n\r\nAll terrestrial zones of the Earth between the parallels 90°N and 90°S are covered. The PFT dataset has a regular latitude-longitude grid with a grid spacing of 0.002777777777778°, corresponding to ~300 m at the equator and ~200 m in the midlatitudes. The Coordinate Reference System used for the global land cover database is a geographic coordinate system (GCS) based on the World Geodetic System 84 (WGS84) reference ellipsoid.\r\n\r\nThe plant functional type (PFT) distribution was created by combining auxiliary data products with the CCI MRLC map series. The LC classification provides the broad characteristics of the 300 m pixel, including the expected vegetation form(s) (tree, shrub, grass) and/or abiotic land type(s) (water, bare area, snow and ice, built-up) in the pixel. For some classes, the class legend specifies an expected range for the fractional covers of the contributing PFTs and broadly differentiates between natural and cultivated vegetation. We used a quantitative, globally consistent method that fuses the 300-metre MRLC product with a suite of existing high-resolution datasets to develop spatially explicit annual maps of PFT fractional composition at 300 metres. The new PFT product exhibits intraclass spatial variability in PFT fractional cover at the 300-metre pixel level and is complementary to the MRLC maps since the derived PFT fractions maintain consistency with the original LC class legend. \r\n\r\nThis dataset was generated to reduce the cross-walking component of uncertainty by adding spatial variability to the PFT composition within a LC class. This work moved beyond fine-tuning the cross-walking approach for specific LC classes or regions and, instead, separately quantifies the PFT fractional composition for each 300 m pixel globally. The result is a dataset representing the cover fractions of 14 PFTs at 300 m for each year within the time range, consistent with the CCI MRLC LC maps for the corresponding year.\r\n\r\nThis study was carried out with the continued support of the European Space Agency Climate Change Initiative under the contract ESA/No.4000126564 Land_Cover_cci." }, { "ob_id": 14427, "uuid": "4761751d7c844e228ec2f5fe11b2e3b0", "short_code": "ob", "title": "ESA Land Cover Climate Change Initiative (Land_Cover_cci): Global Land Cover Maps, Version 1.6.1", "abstract": "As part of the ESA Land Cover Climate Change Initiative (CCI) project a set of Global Land Cover Maps have been produced. These are available at 300m spatial resolution for three epochs centred on the year 2010 (2008-2012), 2005 (2003-2007) and 2000 (1998-2002), where each epoch covers a 5-year period.\r\n\r\nEach pixel value corresponds to the label of a land cover class defined using UN-LCCS classifiers. For each epoch, the land cover map is delivered along with 4 quality flags which document the reliability of the classification. These are described further in the Product User Guides.\r\n\r\nFurther Land Cover CCI products, user tools and a product viewer are available at: http://maps.elie.ucl.ac.be/CCI/viewer/index.php" }, { "ob_id": 19849, "uuid": "e80f28ccb0504c32b403eee654a8a5b3", "short_code": "ob", "title": "ESA Land Cover Climate Change Initiative (Land_Cover_cci): MERIS Surface Reflectance", "abstract": "This dataset consists of time series of surface reflectance from the MERIS instrument on the ENVISAT satellite, produced as part of the ESA Land Cover Climate Change Initiative (CCI) project. \r\n\r\nThe time series are a temporal syntheses obtained over a 7-day compositing period, and encompass 13 of the 15 MERIS spectral channels (not including bands 11 and 15). The spatial resolution is 300m for the Full Resolution (FR) data and 1000m for the Reduced Resolution (RR) data.\r\n\r\nGiven the amount and size of the MERIS surface reflectance archive (10 To), the Land Cover CCI team make the data available on request, through your own disks. Please contact contact@esa-landcover-cci.org" } ], "identifier_set": [], "responsiblepartyinfo_set": [ 55994, 55997, 55999, 56000, 105402, 105430, 105454, 55996, 55995 ], "onlineresource_set": [ 8919, 8918, 8917 ], "project_set": [ 14431 ] }, { "ob_id": 14450, "uuid": "2c2d7affc1b74e2ea7c7d3c74abd5354", "short_code": "coll", "title": "UTLS Night-Time Chemistry of the Upper Troposphere and Lower Stratosphere: NO3 and NO2 measurements", "abstract": "NERC-UTLS Ozone Thematic Program, 'Night-Time Chemistry of the Upper Troposphere and Lower Stratosphere' project measuring sunrise NO3 and sunset NO2 column densities above Aberystwyth, Mid-Wales.", "keywords": "UTLS, Night time, Chemistry", "publicationState": "published", "dataPublishedTime": "2000-12-10T02:34:39", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 42 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 14457, "uuid": "87fa7b8754e24d5ebf3a5ab894536aa3", "short_code": "ob", "title": "UTLS Night-Time Chemistry of the Upper Troposphere and Lower Stratosphere NO2 measurements", "abstract": "NERC-UTLS Ozone Thematic Program, 'Night-Time Chemistry of the Upper Troposphere and Lower Stratosphere' project measuring sunrise NO3 and sunset NO2 column densities above Aberystwyth.\r\n\r\nThis dataset contains column density and profiles of NO2." }, { "ob_id": 14451, "uuid": "c4e198e4e85a4a3985abea6d8f4785d9", "short_code": "ob", "title": "UTLS Night-Time Chemistry of the Upper Troposphere and Lower Stratosphere NO3 measurements", "abstract": "NERC-UTLS Ozone Thematic Program, 'Night-Time Chemistry of the Upper Troposphere and Lower Stratosphere' project measuring sunrise NO3 and sunset NO2 column densities above Aberystwyth.\r\n\r\nThis dataset contains column density and profiles of NO3." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 56059, 56061, 56062, 56063, 56066, 56070, 56060, 56064, 56067, 56068, 56069, 56071 ], "onlineresource_set": [ 8977 ], "project_set": [ 14448 ] }, { "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.", "keywords": "methane, IASI, optimal estimation, retrieval, assimilation, averaging kernels", "publicationState": "preview", "dataPublishedTime": null, "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 130 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 29992, "uuid": "f717a8ea622f495397f4e76f777349d1", "short_code": "ob", "title": "STFC RAL methane retrievals from IASI on board MetOp-A, version 2.0", "abstract": "This 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 (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 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 United Kingdom Research and Innnovation (UKRI) Science and Technology Facilities Council (STFC) Remote Sensing Group (RSG) at the Rutherford Appleton Laboratory (RAL).\r\n\r\nThis is version 2.0 of the dataset." }, { "ob_id": 13804, "uuid": "510b22c6d12e4635b604c172b583167e", "short_code": "ob", "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." }, { "ob_id": 33460, "uuid": "4bbcb1722f2842c1b0a5ebc19160a863", "short_code": "ob", "title": "STFC RAL methane retrievals from IASI on board MetOp-B, version 2.0", "abstract": "This Infrared Atmospheric Sounding Interferometer (IASI) methane dataset contains height-resolved and column-averaged volume mixing ratios of atmospheric methane (CH4) retrieved from the IASI instrument on the MetOp-B satellite. It 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. This dataset was produced by Version 2.0 of the Rutherford Appleton Laboratory's (RAL's) IASI optimal estimation scheme to retrieve methane, which takes as input temperature and water vapour profiles and surface spectral emissivity pre-retrieved by RAL's Infrared and Microwave Scheme applied to IASI, MHS and AMSU-A on MetOp-B. 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\nDevelopment of the Version 2.0 scheme and its application to MetOp-A (2007-2017, http://dx.doi.org/10.5285/f717a8ea622f495397f4e76f777349d1) was funded by the National Centre for Earth Observation (NCEO) under the UK Natural Environment Research Council (NERC) with additional funding from EUMETSAT. Adaptation to MetOp-B and production of the IASI MetOp-B methane dataset 01/2018-03/2021 were funded by NCEO and ESA Contract No. 4000129987/20/I-DT Methane+.\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)." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 56201, 56137, 56139, 56140, 56141, 56143, 105456, 56138, 56142, 56204, 56202, 56200, 56203, 56199, 56205, 164405 ], "onlineresource_set": [ 36931 ], "project_set": [ 8594 ] }, { "ob_id": 14515, "uuid": "99b29b4bfeae470599fb96243e90cde3", "short_code": "coll", "title": "EUCLEIA: European Climate and weather Events: Interpretation and Attribution", "abstract": "Data for EUCLEIA consists of the following simulations that have been produced with HadGEM3-A (N216 L85):\r\n\r\n- two 15 member multi-decadal stochastic physics ensemble simulations (ALL and NAT) spanning the period 1960 – 2013 which form the basis for model evaluation assessments including forecast reliability and modelled statistics of extreme events.\r\n- two corresponding large ensemble simulations (ALL and NAT) spanning the period 2014 – 2015 to be used for attribution studies.\r\n\r\nALL simulations include historical natural and anthropogenic climate forcings which include GHGs, ozone, aerosols and land use. NAT simulations include only historical natural forcings with GHG, aerosol and land use forcings fixed to 1850 levels. The aerosol prescription is essentially the same as for the HadGEM2-ES historical simulations for CMIP5 with post-2005 values being taken from the RCP4.5 scenario. Sea surface temperature (SST) and sea ice (SIC) lower boundary conditions are derived from the HadISST observational dataset which for the NAT simulations have the multi-model mean of a set of coupled model estimates of the anthropogenic contribution removed. Within each set of simulations ensemble members differ only through the operation of the stochastic physics scheme. The multi-decadal simulations share initialisation from ERA-40 reanalysis at 0000Z Dec 1st 1959. Large ensemble simulations are initialised from the atmospheric state of the corresponding multi-decadal experiment at 0000Z Dec 1st 2013.", "keywords": "eucleia, event, attribution, extreme, validation", "publicationState": "published", "dataPublishedTime": "2016-04-27T23:00:00", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 162 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 14473, "uuid": "cb7aa79352b34910920fef729e5f75b8", "short_code": "ob", "title": "EUCLEIA short historical natural-only forcings experiment (2014 – 2015), a numerical simulation data produced by the UK Met Office using HadGEM3-A.", "abstract": "The data provided here are the numerical simulation data for the historical natural-only forcings-only short experiment (2014 – 2015 inclusive) as a test case for the upgraded Met Office HadGEM3-A based operational event attribution system for EUCLEIA (European Climate and weather Events: Interpretation and Attribution).\r\nImprovements include higher horizontal and vertical resolution (N216 L85) and the latest dynamical core (ENDGame) and land surface model (JULES). External forcings are restricted to just historical natural variability of solar irradiance and volcanic aerosol optical depth. SST and SIC lower boundary conditions are provided from the HadISST observational dataset minus an estimate of the anthropogenic contribution derived from CMIP5 coupled model simulations. The experiment comprises a 15 member stochastic physics ensemble using kinetic energy backscatter and randomly perturbed physics schemes. Ensemble members are initialised from dumps taken from 0000Z December 1st 2013 at the end of the corresponding multi-decadal validation experiment." }, { "ob_id": 14472, "uuid": "3de3d8ff18d64a9f8d245af7e9852a68", "short_code": "ob", "title": "EUCLEIA short historical forcings experiment (2014 – 2015), a numerical simulation data produced by the UK Met Office using HadGEM3-A.", "abstract": "The data provided here are the numerical simulation data for the historical forcings-only short experiment (2014 – 2015 inclusive) as a test case for the upgraded Met Office HadGEM3-A based operational event attribution system for EUCLEIA (European Climate and weather Events: Interpretation and Attribution).\r\nImprovements include higher horizontal and vertical resolution (N216 L85) and the latest dynamical core (ENDGame) and land surface model (JULES). External forcings are historical natural variability of solar irradiance and volcanic aerosol optical depth as well as historical anthropogenic prescriptions of GHGs, ozone, aerosols and land use change. SST and SIC lower boundary conditions are provided from the HadISST observational dataset. The experiment comprises a 15 member stochastic physics ensemble using kinetic energy backscatter and randomly perturbed physics schemes. Ensemble members are initialised from dumps taken from 0000Z December 1st 2013 at the end of the corresponding multi-decadal validation experiment." }, { "ob_id": 14470, "uuid": "95541c4741a84b0483d6b1c812a912de", "short_code": "ob", "title": "EUCLEIA multi-decadal historical forcings (1960 – 2013), a numerical simulation data produced by the UK Met Office using HadGEM3-A.", "abstract": "The data provided here are the numerical simulation data for the multi-decadal experiment (1960 – 2013 inclusive) for the validation of the upgraded Met Office HadGEM3-A based operational event attribution system for EUCLEIA (European Climate and weather Events: Interpretation and Attribution). Improvements include higher horizontal and vertical resolution (N216 L85) and the latest dynamical core (ENDGame) and land surface model (JULES). External forcings are historical natural variability of solar irradiance and volcanic aerosol optical depth as well as historical anthropogenic prescriptions of GHGs, ozone, aerosols and land use change. SST and SIC lower boundary conditions are provided from the HadISST observational dataset. The experiment comprises a 15 member stochastic physics ensemble using kinetic energy backscatter and randomly perturbed physics schemes. All ensemble members share identical initialisation of the atmospheric state from ERA-40 reanalysis at 0000Z December 1st 1959.\r\n\r\nAtmospheric data are provided at temporal output resolutions of 3-hourly, 6-hourly, daily and monthly; land data are provided at daily and monthly resolutions." }, { "ob_id": 14471, "uuid": "b1e2f38d1df048808625437764ca9578", "short_code": "ob", "title": "EUCLEIA multi-decadal historical natural-only forcings (1960 – 2013), a numerical simulation data produced by the UK Met Office using HadGEM3-A.", "abstract": "The data provided here are the numerical simulation data for the natural forcings-only version of the EUCLEIA multi-decadal experiment (1960 – 2013 inclusive) for the validation of the upgraded Met Office HadGEM3-A based operational event attribution system for EUCLEIA (European Climate and weather Events: Interpretation and Attribution). Improvements include higher horizontal and vertical resolution (N216 L85) and the latest dynamical core (ENDGame) and land surface model (JULES). External forcings are restricted to just historical natural variability of solar irradiance and volcanic aerosol optical depth. SST and SIC lower boundary conditions are provided from the HadISST observational dataset minus an estimate of the anthropogenic contribution derived from CMIP5 coupled model simulations. The experiment comprises a 15 member stochastic physics ensemble using kinetic energy backscatter and randomly perturbed physics schemes. All ensemble members share identical initialisation of the atmospheric state from ERA-40 reanalysis at 0000Z December 1st 1959.\r\n\r\nAtmospheric data are provided at temporal output resolutions of 3-hourly, 6-hourly, daily and monthly; land data are provided at daily and monthly resolutions." } ], "identifier_set": [ 8815 ], "responsiblepartyinfo_set": [ 56305, 56306, 56308, 71728, 71736, 71737, 71739, 71729, 56307, 148621 ], "onlineresource_set": [ 9039 ], "project_set": [ 14514 ] }, { "ob_id": 14567, "uuid": "4d6f884bf7cf46df8950b1b570fe8453", "short_code": "coll", "title": "NWP-Euro: Operational Numerical Weather Prediction (NWP) output from the European Atmospheric High Resolution Model; part of the Met Office Unified Model (UM)", "abstract": "This dataset collection contains model data from the Met Office Unified Model (UM) operational Numerical Weather Prediction (NWP) European high resolution model. This is a regional downscaled configuration of the Unified Model, covering a European domain, with hourly forecast data covering the period T+1 to T+54 hours. With a resolution of approximately 0.04 degrees it is able to produce selected hourly data covering the first 48 hours at surface level and at standard pressure levels four times a day. The model’s initial state is kept close to the real atmosphere by starting from a downscaled global starting condition.\r\n\r\nThis archive currently holds data from April 2016 onwards but data will be back populated for earlier years.", "keywords": "NWP, Met Office, UM, unified model, European atmospheric model, Europe", "publicationState": "published", "dataPublishedTime": "2016-05-24T10:41:27", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 69 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 14762, "uuid": "05170d042871409c8814bacc80a74a12", "short_code": "ob", "title": "NWP-Euro: Met Office European Atmospheric High Resolution Model data", "abstract": "This dataset contains model data from the Met Office Unified Model (UM) operational Numerical Weather Prediction (NWP) European high resolution model. This is a regional downscaled configuration of the Unified Model, covering a European domain, with hourly forecast data covering the period T+1 to T+54 hours. With a resolution of approximately 0.04 degrees it is able to produce selected hourly data covering the first 48 hours at surface level and at standard pressure levels four times a day. The model’s initial state is kept close to the real atmosphere by starting from a downscaled global starting condition.\r\n\r\nThis archive currently holds data from April 2016 onwards but data will be back populated for earlier years." } ], "identifier_set": [ 8827 ], "responsiblepartyinfo_set": [ 56486, 56487, 56484, 56483, 56482, 56481, 56488, 56485, 56494 ], "onlineresource_set": [ 9104 ], "project_set": [ 555 ] }, { "ob_id": 14570, "uuid": "e4ac04e7fa2541278ad4ad06fb4fd5f3", "short_code": "coll", "title": "NWP-Global: Operational Numerical Weather Prediction (NWP) output from the UK Met Office Global Atmospheric Unified Model (UM)", "abstract": "A global configuration of the Met Office Unified Model provides the most accurate short range deterministic forecast by any national meteorological service covering a six day period. With a resolution of approximately 0.234 x 0.153 degrees, it is able to produce selected hourly data covering the first 48 hours at surface level and at standard pressure levels twice a day. The model’s initial state is kept close to the real atmosphere using hybrid 4D-Var data assimilation.\r\n\r\nThis dataset collection contains model data from the Met Office Unified Model (UM) operational Global Numerical Weather Prediction (NWP) model. The archive currently holds data from April 2016 onwards but data will be back populated for earlier years.", "keywords": "NWP, Met Office, UM, unified model, Global atmospheric model, Global", "publicationState": "published", "dataPublishedTime": "2016-05-24T10:45:01", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 69 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 14763, "uuid": "86df725b793b4b4cb0ca0646686bd783", "short_code": "ob", "title": "NWP-Global: Met Office Global Atmospheric High Resolution Model data", "abstract": "A global configuration of the Met Office Unified Model provides the most accurate short range deterministic forecast by any national meteorological service covering a six day period. With a resolution of approximately 0.234 x 0.153 degrees, it is able to produce selected hourly data covering the first 48 hours at surface level and at standard pressure levels twice a day. The model’s initial state is kept close to the real atmosphere using hybrid 4D-Var data assimilation.\r\n\r\nThis dataset contains model data from the Met Office Unified Model (UM) operational Global Numerical Weather Prediction (NWP) model. The archive currently holds data from April 2016 onwards but data will be back populated for earlier years." } ], "identifier_set": [ 8828 ], "responsiblepartyinfo_set": [ 56495, 56496, 56497, 56498, 56499, 56501, 56502, 56500, 56503 ], "onlineresource_set": [ 9115 ], "project_set": [ 555 ] }, { "ob_id": 14571, "uuid": "78f23c539d304591b137cf986b69a525", "short_code": "coll", "title": "NWP-UKV: Operational Numerical Weather Prediction (NWP) output from the UK Met Office UK Atmospheric High Resolution Unified Model (UM)", "abstract": "This dataset collection contains model data from the Met Office Unified Model (UM) operational Numerical Weather Prediction (NWP) UK high resolution model. \r\n\r\nA post processed regional downscaled configuration of the Unified Model, covering the UK and Ireland, is used with hourly forecast data covering the period T+0 to T+120 hours. With a resolution of approximately 0.018 degrees it is able to produce hourly data at surface level and at standard pressure levels up to eight times a day. The model’s initial state is kept close to the real atmosphere using incremental 3D-Var data assimilation.\r\n\r\nThis archive currently holds data from April 2016 onwards but data will be back populated for earlier years.", "keywords": "NWP, Met Office, UM, unified model, UK atmospheric model, UKV", "publicationState": "published", "dataPublishedTime": "2016-05-24T10:43:37", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 69 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 14573, "uuid": "f47bc62786394626b665e23b658d385f", "short_code": "ob", "title": "NWP-UKV: Met Office UK Atmospheric High Resolution Model data", "abstract": "A global configuration provides the large-scale weather forecast and also supports the nested higher resolution regional models with boundary data. More detailed short-range forecasts are provided by these high-resolution models which are able to represent certain atmospheric processes more accurately, as well as having a more detailed representation of surface features such as coastlines and orography.\r\n\r\nThis dataset contains UK atmospheric high resolution data from the UK Met Office operational NWP (Numerical Weather Prediction) Unified Model (UM). \r\n\r\nA post-processed regional downscaled configuration of the Unified Model, covering the UK and Ireland, is used with hourly forecast data covering the period T+0 to T+120 hours is used. With a resolution of approximately 0.018 degrees are able to produce hourly data at surface level and at standard pressure levels up to eight times a day.\r\n\r\nThe model’s initial state is kept close to the real atmosphere using incremental 3D-Var data assimilation.\r\n\r\nThis archive currently holds data from April 2016 onwards.\r\n\r\nAn issue has been identified with the representation of the Transverse Mercator projection in the GRIB files in which some of the projection metadata values were set incorrectly. This error has been corrected in all data since 15th Jan 2020. The values that were corrected are as follows:\r\n\r\n\r\nUp to 15/01/2020: \r\n\r\nSource of Grid Definition: 12\r\nLatitude of True Origin: 49\r\nLongitude of True Origin: -2\r\n\r\nFrom 15/01/2020:\r\n\r\nSource of Grid Definition: 0\r\nLatitude of True Origin: 49.0e06\r\nLongitude of True Origin: -2.0e06" } ], "identifier_set": [ 8829 ], "responsiblepartyinfo_set": [ 56504, 56505, 56506, 56508, 56509, 56510, 56511, 56507, 56512 ], "onlineresource_set": [ 9116 ], "project_set": [ 555 ] }, { "ob_id": 15135, "uuid": "dec3e7638e7e491699480a5175fd56a5", "short_code": "coll", "title": "SeptEx: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for NCAS general FAAM flying (SeptEx, Winter 2010).", "keywords": "SeptEx, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2014-07-14T13:38:12", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 15401, "uuid": "7cd4930f8336428db0f07c40c4c05782", "short_code": "ob", "title": "FAAM B546 SeptEx flight, number 2: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 2 for NCAS general FAAM flying (SeptEx, Winter 2010) project." }, { "ob_id": 15700, "uuid": "d13cc8863ee94774acd658ca39cc22e1", "short_code": "ob", "title": "FAAM B689 NCAS flight, number 2: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 2 for NCAS general FAAM flying (SeptEx, Winter 2010) project." }, { "ob_id": 15393, "uuid": "9357e1a8c1594f1ebd961218d7e01d5c", "short_code": "ob", "title": "FAAM B547 SeptEx flight, number 3: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 3 for NCAS general FAAM flying (SeptEx, Winter 2010) project." }, { "ob_id": 16137, "uuid": "a2305f099b6b4220b7d5c8b1e4bc83ec", "short_code": "ob", "title": "FAAM B690 NCAS flight, number 3: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft during flight 3 for NCAS general FAAM flying (SeptEx, Winter 2010) project." }, { "ob_id": 15148, "uuid": "14a3222c6ad44e819cd02aa2f6eb5b99", "short_code": "ob", "title": "FAAM B550 SeptEx and RONOCO flight, number 7: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 7 for NCAS general FAAM flying (SeptEx, Winter 2010) and RONOCO: ROle of Nighttime chemistry in controlling the Oxidising Capacity of the AtmOsphere Consortium Project projects." }, { "ob_id": 16544, "uuid": "d66059cb68694cba8a3e487730c19edc", "short_code": "ob", "title": "FAAM B907 Oil and Gas flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for NCAS general FAAM flying (SeptEx, Winter 2010) (Oil and Gas) project." }, { "ob_id": 15282, "uuid": "e0aeded8757e4488866b10cef364fb26", "short_code": "ob", "title": "FAAM B554 SeptEx and CONSTRAIN flight, number 12: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 12 for NCAS general FAAM flying (SeptEx, Winter 2010) and CONSTRAIN - Cold Cloud Microphysical Parameterisation Studies projects." }, { "ob_id": 15290, "uuid": "b5f4ee578ccc45a58e79b57e17c03189", "short_code": "ob", "title": "FAAM B556 SeptEx and CONSTRAIN flight, number 14: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 14 for NCAS general FAAM flying (SeptEx, Winter 2010) and CONSTRAIN - Cold Cloud Microphysical Parameterisation Studies projects." }, { "ob_id": 20210, "uuid": "3c0eb3264d0a4e358a893060b855442d", "short_code": "ob", "title": "FAAM B985 VANAHEIM and Oil and Gas flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Volcanic and Atmospheric Near- to far-field Analysis of plumes Helping Interpretation and Modelling (VANAHEIM) and NCAS general FAAM flying (SeptEx, Winter 2010, Oil & Gas) projects." }, { "ob_id": 20181, "uuid": "2152d10278d8438cb7e7fce11036674e", "short_code": "ob", "title": "FAAM B955 Oil and Gas flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for NCAS general FAAM flying (SeptEx, Winter 2010, Oil & Gas) (Oil and Gas) project." }, { "ob_id": 15274, "uuid": "1c4577cb764f4b769b68c7398ee4da2a", "short_code": "ob", "title": "FAAM B552 SeptEx flight, number 10: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 10 for NCAS general FAAM flying (SeptEx, Winter 2010) project." }, { "ob_id": 15286, "uuid": "844fa23a49014a60bdcd6aaaf0cf333f", "short_code": "ob", "title": "FAAM B555 SeptEx and CONSTRAIN flight, number 13: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 13 for NCAS general FAAM flying (SeptEx, Winter 2010) and CONSTRAIN - Cold Cloud Microphysical Parameterisation Studies projects." }, { "ob_id": 16021, "uuid": "b431ca96ca5049a7a1440e8d0f42c9db", "short_code": "ob", "title": "FAAM B910 Oil and Gas flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for NCAS general FAAM flying (SeptEx, Winter 2010) (Oil and Gas) project." }, { "ob_id": 16802, "uuid": "3c7b2f5525d445d88ce42ed4078be8b9", "short_code": "ob", "title": "FAAM B459 EM25 and ADIENT flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for NCAS general FAAM flying (SeptEx, Winter 2010) (EM25) and ADIENT (Appraising the Direct Impacts of aErosol oN climaTe) project, Part of the APPRAISE (Aerosol Properties, PRocesses And Influences on the Earth's climate) Program." }, { "ob_id": 25506, "uuid": "688479502d914e94903dffd10716f424", "short_code": "ob", "title": "FAAM C065 NCAS-Training flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for NCAS general FAAM flying (SeptEx, Winter 2010, Oil & Gas) (NCAS-Training) project." }, { "ob_id": 15298, "uuid": "bb75f2cfe0ef4f39b95eccde865851ba", "short_code": "ob", "title": "FAAM B558 SeptEx flight, number 16: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft during flight 16 for NCAS general FAAM flying (SeptEx, Winter 2010) project." }, { "ob_id": 17348, "uuid": "50d63d561ccf4392831a3b0cd70f7dfe", "short_code": "ob", "title": "FAAM B460 EM25 and ADIENT flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for NCAS general FAAM flying (SeptEx, Winter 2010) (EM25) and ADIENT (Appraising the Direct Impacts of aErosol oN climaTe) project, Part of the APPRAISE (Aerosol Properties, PRocesses And Influences on the Earth's climate) Program." }, { "ob_id": 16129, "uuid": "129f881135d447e09ad1360d107b382a", "short_code": "ob", "title": "FAAM B691 NCAS flight, number 4: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft during flight 4 for NCAS general FAAM flying (SeptEx, Winter 2010) project." }, { "ob_id": 15302, "uuid": "13f6e26b3f9d4d128530986db69405eb", "short_code": "ob", "title": "FAAM B559 SeptEx and APPRAISE flight, number 17: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft during flight 17 for NCAS general FAAM flying (SeptEx, Winter 2010) and APPRAISE - Aerosol properties, processes and influences on the Earth's climate projects." }, { "ob_id": 16806, "uuid": "859c9fb18ad24752b5d17cda3b2916db", "short_code": "ob", "title": "FAAM B458 EM25 and ADIENT flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for NCAS general FAAM flying (SeptEx, Winter 2010) (EM25) and ADIENT (Appraising the Direct Impacts of aErosol oN climaTe) project, Part of the APPRAISE (Aerosol Properties, PRocesses And Influences on the Earth's climate) Program." }, { "ob_id": 15552, "uuid": "8661a3ecd94948e9903192588e3805b2", "short_code": "ob", "title": "FAAM B913 Oil and Gas flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for NCAS general FAAM flying (SeptEx, Winter 2010) (Oil and Gas) project." }, { "ob_id": 15258, "uuid": "8235866e243d4c16bb051d8ecbffdd5d", "short_code": "ob", "title": "FAAM B551 SeptEx and RONOCO flight, number 9: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 9 for NCAS general FAAM flying (SeptEx, Winter 2010) and RONOCO: ROle of Nighttime chemistry in controlling the Oxidising Capacity of the AtmOsphere Consortium Project projects." }, { "ob_id": 15696, "uuid": "b5529294eba84405b7055dd54703ed86", "short_code": "ob", "title": "FAAM B688 NCAS flight, number 1: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft during flight 1 for NCAS general FAAM flying (SeptEx, Winter 2010) project." }, { "ob_id": 16827, "uuid": "f8288e65eb5740949bd45eef99f5d301", "short_code": "ob", "title": "FAAM B457 EM25 and VISURB flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for NCAS general FAAM flying (SeptEx, Winter 2010) (EM25) and URBan VISibility in UK projects." }, { "ob_id": 18314, "uuid": "42ed1e3feeed4deeae91e80f9c25c1d9", "short_code": "ob", "title": "FAAM B727 NCAS flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for NCAS general FAAM flying (SeptEx, Winter 2010) project." }, { "ob_id": 16045, "uuid": "fdbed0fbf9984642ae8199db85215514", "short_code": "ob", "title": "FAAM B918 Oil and Gas flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for NCAS general FAAM flying (SeptEx, Winter 2010) (Oil and Gas) project." }, { "ob_id": 15294, "uuid": "5600815d029e46caa7ba8d282028a26c", "short_code": "ob", "title": "FAAM B557 SeptEx flight, number 15: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 15 for NCAS general FAAM flying (SeptEx, Winter 2010) project." }, { "ob_id": 16125, "uuid": "ff111fac1b7f4b4b8aab38998cfb2d59", "short_code": "ob", "title": "FAAM B693 NCAS flight, number 5: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft during flight 5 for NCAS general FAAM flying (SeptEx, Winter 2010) project." }, { "ob_id": 15134, "uuid": "3433d56a9f9940cb860966591744b32f", "short_code": "ob", "title": "FAAM B545 SeptEx flight, number 1: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 1 for NCAS general FAAM flying (SeptEx, Winter 2010) project." }, { "ob_id": 15278, "uuid": "9b8ad05a6a21475d98d0e5370c2fd665", "short_code": "ob", "title": "FAAM B553 SeptEx, APPRAISE and CONSTRAIN flight, number 11: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 11 for NCAS general FAAM flying (SeptEx, Winter 2010), APPRAISE - Aerosol properties, processes and influences on the Earth's climate and CONSTRAIN - Cold Cloud Microphysical Parameterisation Studies projects." }, { "ob_id": 16565, "uuid": "7f03d51730b74e1a8ecfdd4962654ad8", "short_code": "ob", "title": "FAAM B908 Oil and Gas flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for NCAS general FAAM flying (SeptEx, Winter 2010) (Oil and Gas) project." }, { "ob_id": 17352, "uuid": "c50cad6e39804148bbf6263fb5fb0195", "short_code": "ob", "title": "FAAM B461 EM25 and ADIENT flight, -: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft, - flight for NCAS general FAAM flying (SeptEx, Winter 2010) (EM25) and ADIENT (Appraising the Direct Impacts of aErosol oN climaTe) project, Part of the APPRAISE (Aerosol Properties, PRocesses And Influences on the Earth's climate) Program." }, { "ob_id": 15212, "uuid": "b9e61aeae7754738a06f208c409a47f4", "short_code": "ob", "title": "FAAM B548 SeptEx flight, number 5: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 5 for NCAS general FAAM flying (SeptEx, Winter 2010) project." }, { "ob_id": 15196, "uuid": "bbd1ede528c348a085271ee16f8b331f", "short_code": "ob", "title": "FAAM B549 SeptEx and RONOCO flight, number 6: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 6 for NCAS general FAAM flying (SeptEx, Winter 2010) and RONOCO: ROle of Nighttime chemistry in controlling the Oxidising Capacity of the AtmOsphere Consortium Project projects." }, { "ob_id": 18322, "uuid": "ec03e6fa3e28447d8aea2366122051b9", "short_code": "ob", "title": "FAAM B572 FENNEC and NCAS-Training flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) and NCAS general FAAM flying (SeptEx, Winter 2010) projects." }, { "ob_id": 15548, "uuid": "2c41dc58161b47bcbb0f15c3bfa607a2", "short_code": "ob", "title": "FAAM B912 Oil and Gas flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for NCAS general FAAM flying (SeptEx, Winter 2010) (Oil and Gas) project." }, { "ob_id": 17360, "uuid": "2caeafa5315e4420b51671f59b289eca", "short_code": "ob", "title": "FAAM B463 EM25 and ADIENT flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for NCAS general FAAM flying (SeptEx, Winter 2010) (EM25) and ADIENT (Appraising the Direct Impacts of aErosol oN climaTe) project, Part of the APPRAISE (Aerosol Properties, PRocesses And Influences on the Earth's climate) Program." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 58665, 58666, 58667, 58670, 58671, 58672, 58673, 58674, 58668, 58669 ], "onlineresource_set": [], "project_set": [ 12008 ] }, { "ob_id": 15217, "uuid": "2dd32d52baae4ef898c1f71309a10fe7", "short_code": "coll", "title": "CONSTRAIN: surface UV Raman lidar measurements from the Chilbolton Observatory and in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for CONSTRAIN - Cold Cloud Microphysical Parameterisation Studies.\r\n\r\nThe main issues are the pristine ice number concentration, snow evolution leading to surface precipitation, mixed-phase and cold cloud length scales. The main goals in order of priority are \r\n- to provide statistical datasets to act as a critical holistic test of three phase microphysics as RICO did for warm cloud microphysics (e.g. cold air outbreak). - to test whether the background aerosol concentration active as ice nuclei can be used to predict the pristine ice concentration in cases where there is limited ice multiplication. \r\n- to test detailed microphysical assumptions in model, which include capacitance, aggregation efficiency vs temperature (conversion rate from 'ice' to 'snow' categories), mass-dimension relations and area-dimension relations (these combine to give fall-speed). \r\n- To investigate small ice (sub 100 microns) concentration controversy.\r\n\r\nThe project aimed to conduct studies of water vapour, ice crystal habit, turbulence and radiative properties of contrail as it either spreads into cirrus or dissipates. Boundary conditions for LEM studies of contrail lifecycles were delivered and Measurements of radiative forcing from spreading contrail were taken for comparison to other cases. Case studies for testing later contrail cirrus parameterization in the Unified Model were also be considered.", "keywords": "CONSTRAIN, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2014-07-14T13:38:12", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 15270, "uuid": "058e5bc46bd248e384ee64cf7bc3bc35", "short_code": "ob", "title": "FAAM B498 CONSTRAIN flight, number 3: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 3 for CONSTRAIN - Cold Cloud Microphysical Parameterisation Studies project." }, { "ob_id": 15282, "uuid": "e0aeded8757e4488866b10cef364fb26", "short_code": "ob", "title": "FAAM B554 SeptEx and CONSTRAIN flight, number 12: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 12 for NCAS general FAAM flying (SeptEx, Winter 2010) and CONSTRAIN - Cold Cloud Microphysical Parameterisation Studies projects." }, { "ob_id": 15290, "uuid": "b5f4ee578ccc45a58e79b57e17c03189", "short_code": "ob", "title": "FAAM B556 SeptEx and CONSTRAIN flight, number 14: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 14 for NCAS general FAAM flying (SeptEx, Winter 2010) and CONSTRAIN - Cold Cloud Microphysical Parameterisation Studies projects." }, { "ob_id": 15286, "uuid": "844fa23a49014a60bdcd6aaaf0cf333f", "short_code": "ob", "title": "FAAM B555 SeptEx and CONSTRAIN flight, number 13: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 13 for NCAS general FAAM flying (SeptEx, Winter 2010) and CONSTRAIN - 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data on board the FAAM BAE-146 aircraft collected for ADIENT (Appraising the Direct Impacts of aErosol oN climaTe) project, Part of the APPRAISE (Aerosol Properties, PRocesses And Influences on the Earth's climate) Program and EUCAARI-LONGREX (European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions)." }, { "ob_id": 17560, "uuid": "4e447c9c7380402bb643ef9c6ba568ad", "short_code": "ob", "title": "FAAM B366 ADIENT and EUCAARI flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for ADIENT (Appraising the Direct Impacts of aErosol oN climaTe) project, Part of the APPRAISE (Aerosol Properties, PRocesses And Influences on the Earth's climate) Program and EUCAARI-LONGREX (European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions)." }, { "ob_id": 16519, "uuid": "acd621bb126e409091877237f37fc2ba", "short_code": "ob", "title": "FAAM B372 ADIENT and EUCAARI flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for ADIENT (Appraising the Direct Impacts of aErosol oN climaTe) project, Part of the APPRAISE (Aerosol Properties, PRocesses And Influences on the Earth's climate) Program and EUCAARI-LONGREX (European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions)." }, { "ob_id": 17573, "uuid": "f18650f53900461881ba484eb9054d17", "short_code": "ob", "title": "FAAM B363 ADIENT and EUCAARI flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for ADIENT (Appraising the Direct Impacts of aErosol oN climaTe) project, Part of the APPRAISE (Aerosol Properties, PRocesses And Influences on the Earth's climate) Program and EUCAARI-LONGREX (European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions)." }, { "ob_id": 16495, "uuid": "78a6c16dd9824937b3bf352dae1557d2", "short_code": "ob", "title": "FAAM B374 ADIENT and EUCAARI flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for ADIENT (Appraising the Direct Impacts of aErosol oN climaTe) project, Part of the APPRAISE (Aerosol Properties, PRocesses And Influences on the Earth's climate) Program and EUCAARI-LONGREX (European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions)." }, { "ob_id": 16499, "uuid": 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the Direct Impacts of aErosol oN climaTe) project, Part of the APPRAISE (Aerosol Properties, PRocesses And Influences on the Earth's climate) Program and EUCAARI-LONGREX (European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions)." }, { "ob_id": 16491, "uuid": "b8fe6cc2b3ae4cc5b9ac39a32feaf4c5", "short_code": "ob", "title": "FAAM B379 ADIENT and EUCAARI flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for ADIENT (Appraising the Direct Impacts of aErosol oN climaTe) project, Part of the APPRAISE (Aerosol Properties, PRocesses And Influences on the Earth's climate) Program and EUCAARI-LONGREX (European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions)." }, { "ob_id": 16487, "uuid": "e9708ca891a84f378b4f0afd44c6c2ad", "short_code": "ob", 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project." }, { "ob_id": 15602, "uuid": "233008b6250741299fe4349e1e448e73", "short_code": "ob", "title": "FAAM B856 MAGIC flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for MAGIC project." }, { "ob_id": 15590, "uuid": "4e2e5f028e9b47f5a12dc41c81dc6a68", "short_code": "ob", "title": "FAAM B855 MAGIC flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for MAGIC project." }, { "ob_id": 15598, "uuid": "7e45f483ea0a45dda6d7e2d704294af6", "short_code": "ob", "title": "FAAM B857 MAGIC flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 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measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for ISMAR Test flight: International Sub-Millimetre Airborne Radiometer project." }, { "ob_id": 18281, "uuid": "1da2efdec5384ebaa90b0b575a2e1da0", "short_code": "ob", "title": "FAAM B787 ISMAR and Instrument Test flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for ISMAR Test flight: International Sub-Millimetre Airborne Radiometer and FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects." }, { "ob_id": 17174, "uuid": "c5b0e9c754714e248656bba0ceb39608", "short_code": "ob", "title": "FAAM B878 STICCS and ISMAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for STICCS - Submillimetre Trial In Cirrus and Clear Skies and ISMAR Test flight: International Sub-Millimetre Airborne Radiometer projects." }, { "ob_id": 18193, "uuid": "745cf6f941bd4b7ead6dda8677bb66b3", "short_code": "ob", "title": "FAAM B849 ISMAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for ISMAR Test flight: International Sub-Millimetre Airborne Radiometer project." }, { "ob_id": 15564, "uuid": "876df6ef7ef3412aafafeb7aafcdd37f", "short_code": "ob", "title": "FAAM B916 ISMAR Test flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for ISMAR Test flight: International Sub-Millimetre Airborne Radiometer project." }, { "ob_id": 17651, "uuid": "6ba397d6c8854da19bcced8ea588c1f9", "short_code": "ob", "title": "FAAM B895 CIRCCREX and ISMAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Cirrus Coupled Cloud-Radiation Experiment (CIRCCREX) and ISMAR Test flight: International Sub-Millimetre Airborne Radiometer projects." }, { "ob_id": 16603, "uuid": "23406f61b8a84509b75516ab3f96576d", "short_code": "ob", "title": "FAAM B884 PIKNMIX and ISMAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events and ISMAR Test flight: International Sub-Millimetre Airborne Radiometer projects." }, { "ob_id": 20206, "uuid": "46ca2a2cc8ce497fbf06beaf31f67098", "short_code": "ob", "title": "FAAM B984 ISMAR and T-NAWDEX flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for ISMAR Test flight: International Sub-Millimetre Airborne Radiometer and T-NAWDEX (Pilot) - THORPEX - North Atlantic Waveguide and Downstream projects." }, { "ob_id": 16615, "uuid": "d96ab06db2ad4904a90d8640fee62c6d", "short_code": "ob", "title": "FAAM B889 COSMICS and ISMAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for COSMICS - Cold-air Outbreak and sub-Millimetre Ice Cloud Study and ISMAR Test flight: International Sub-Millimetre Airborne Radiometer projects." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 60133, 60134, 60135, 60138, 60139, 60140, 60141, 60142, 60136, 60137 ], "onlineresource_set": [], "project_set": [ 14837 ] }, { "ob_id": 15574, "uuid": "664832a9194f4246b2165142e1c69ecd", "short_code": "coll", "title": "SUMEX: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for SUMEX-14: Met Office Summer Campaign, 2014.", "keywords": "SUMEX, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2015-04-23T13:37:31", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 17145, 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aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for SUMEX-14: Met Office Summer Campaign, 2014 project." }, { "ob_id": 15573, "uuid": "193c9af2f0d94ce88fc6495aca777796", "short_code": "ob", "title": "FAAM B851 SUMEX flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for SUMEX-14: Met Office Summer Campaign, 2014 project." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 60171, 60172, 60173, 60176, 60177, 60178, 60179, 60180, 60174, 60175 ], "onlineresource_set": [], "project_set": [ 14850 ] }, { "ob_id": 15682, "uuid": "69835240982f4aee9f9038a6414e02c1", "short_code": "coll", "title": "FENNEC: surface meteorological and in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "Fennec -The Saharan Climate System was a NERC consortium project 2010-2012 lead by the University of Oxford and involving the Universities of Leeds, Reading, Sussex and the Met Office.\r\n\r\nThe aim of Fennec was to quantify and model boundary layer and aerosol processes over the Saharan 'heat low' region, the greatest dust region during summer. This is the most ambitious project ever to observe the Saharan climate system and the role of dust aerosols. This collection includes surface measurements from eight automatic weather station (AWS) installed across the Sahara - four of which were installed in remote locations in the central desert where no previous meteorological observations had previously existed - and an aircraft field campaign with the FAAM BAe-146.", "keywords": "FENNEC, FAAM, airborne, atmospheric measurments, AWS", "publicationState": "published", "dataPublishedTime": "2016-01-12T10:17:36", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 18 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 18531, "uuid": "6dd1f39e37b049d8901d79f31f4df3e3", "short_code": "ob", "title": "FAAM B603 FENNEC flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 16748, "uuid": "7fc13a733cc1467b84e0d564654244a0", "short_code": "ob", "title": "FAAM B699 FENNEC flight, number 1: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 1 for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 15886, "uuid": "2436839b5f874f65b954fc2f52190ffc", "short_code": "ob", "title": "FAAM B612 FENNEC flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 16374, "uuid": "37001e2dd16141a6af353c9608dbc5c8", "short_code": "ob", "title": "FAAM B710 FENNEC flight, number 12: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 12 for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 18067, "uuid": "ce21f2c4b3074fcead420829107adc74", "short_code": "ob", "title": "FAAM B614 FENNEC flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Fennec - 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The Saharan Climate System (FENNEC) project." }, { "ob_id": 18535, "uuid": "8ca073b24afd43318a0c8ef916189e77", "short_code": "ob", "title": "FAAM B608 FENNEC flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 15681, "uuid": "30d103ff6e2a4ee888c76005ba476803", "short_code": "ob", "title": "FAAM B698 FENNEC Transit flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 17368, "uuid": "3412fb734a6747e4a016e5225abe4ae4", "short_code": "ob", "title": "FAAM B704 FENNEC flight, number 6: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 6 for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 18502, "uuid": "8dbba4f1449147278e7f053bdc6bb6c8", "short_code": "ob", "title": "FAAM B604 FENNEC, LADUNEX and EUFAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC), EUFAR Lagrangian Dust Source Inversion Experiment and European Facility for Airborne Research in Environmental and Geo-sciences (EUFAR) projects." }, { "ob_id": 16196, "uuid": "042b44263eb0474184208d0848edb684", "short_code": "ob", "title": "FAAM B591 FENNEC Pilot flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 18519, "uuid": "77ec7d4621fb49c4b6618c80ff90aa72", "short_code": "ob", "title": "FAAM B600 FENNEC flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 17364, "uuid": "f0ce6114fb8e44b08b3b8e16eea76f2d", "short_code": "ob", "title": "FAAM B705 FENNEC flight, number 7: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 7 for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 16787, "uuid": "7a912abb43e54cbebaac5689d1178726", "short_code": "ob", "title": "FAAM B594 FENNEC Pilot flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 17372, "uuid": "a086e1e8d3c443c2b9190050709a1369", "short_code": "ob", "title": "FAAM B707 FENNEC flight, number 9: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 9 for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 24688, "uuid": "819bdb021a644a9fb0b31704479523db", "short_code": "ob", "title": "Fennec automatic weather station (AWS) data from the Saharan Desert between 2011-2013", "abstract": "Data were collected under the NERC funded project - Fennec -The Saharan Climate System. The project was lead by the University of Oxford and involved the Universities of Leeds, Reading, Sussex and the UK Met Office. Fennec investigated the Saharan climate system and the role of dust aerosols, involving a unique surface and aircraft field campaign with the FAAM BAe-146.\r\n\r\nVarious meteorological variables were collected at 3 min 20 second intervals, between 2011 and 2013 at 8 Automatic Weather Stations. Parameters include: 1m pressure, 3 min 20 sec mean 2m windspeed (sonic and cup anemometers), number of windspeeds sampled, variance of windspeed in sample, skew of windspeed in sample, 2m relative humidity, 2 temperature, soil temperature (2 depths), ground flux, shortwave radiation up and down, longwave radiation up and down. \r\n\r\nSpecific station locations are stated both in the data files and the CEDA platform record. One station had to be moved after the first year, hence there are 9 station locations listed.\r\n\r\nDue to harsh environmental conditions a number of the AWS stopped operating after deployment. Additional information regarding instrument issues and missing data can be found in a PDF on the CEDA archive. \r\n\r\n\r\n" }, { "ob_id": 15881, "uuid": "a239eede6d1e4e5bbfec8d64117c5c1d", "short_code": "ob", "title": "FAAM B613 FENNEC flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 17376, "uuid": "1a7af9eb8fde42669f115c8799a25738", "short_code": "ob", "title": "FAAM B706 FENNEC flight, number 8: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 8 for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 16810, "uuid": "ac19fa5bfeca4722ab96b4e9e7376cbf", "short_code": "ob", "title": "FAAM B592 FENNEC Pilot flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 18761, "uuid": "7134b25419dc4a3facc8682783ac0c91", "short_code": "ob", "title": "FAAM B588 FENNEC Test flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 16814, "uuid": "c0263a4dc8cd4f4aa99da0ca3b5be28c", "short_code": "ob", "title": "FAAM B593 FENNEC Pilot flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 15952, "uuid": "8ddc4a997185415db8096c499b446018", "short_code": "ob", "title": "FAAM B711 FENNEC Transit flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 18527, "uuid": "66eeb5969ae74766a80811a9ef9bc3e0", "short_code": "ob", "title": "FAAM B602 FENNEC flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 16037, "uuid": "f28789110bf7488fab63d380dd3d1c56", "short_code": "ob", "title": "FAAM B708 FENNEC flight, number 10: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 10 for Fennec - The Saharan Climate System (FENNEC) project." }, { "ob_id": 18789, "uuid": "fcb11b8a63ab4f2d9524f10d7ee85bb2", "short_code": "ob", "title": "FAAM B589 FENNEC Pilot flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC) project." }, { 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aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events project." }, { "ob_id": 18346, "uuid": "c0b508bd418d44a8ba7c23ae0ba28ba7", "short_code": "ob", "title": "FAAM B670 PIKNMIX flight, number 6: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 6 for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events project." }, { "ob_id": 17157, "uuid": "08df468297684b6097b0875d7c477467", "short_code": "ob", "title": "FAAM B876 PIKNMIX flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events project." }, { "ob_id": 18725, "uuid": "22cb9df7f814465aa1e98b9d212c856f", "short_code": "ob", "title": "FAAM B816 PIKNMIX flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events project." }, { "ob_id": 18330, "uuid": "7ff0c2730446488f90300b5780a752b5", "short_code": "ob", "title": "FAAM B673 PIKNMIX flight, number 9: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 9 for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events project." }, { "ob_id": 18358, "uuid": "e0402bb5c4714a6fba8718e3cbdac0a0", "short_code": "ob", "title": "FAAM B675 PIKNMIX flight, number 10: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 10 for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events project." }, { "ob_id": 27918, "uuid": "6a2bc7a1edc34650bd41e0f958cbd50a", "short_code": "ob", "title": "FAAM C153 PIKNMIX-F flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events (PIKNMIX-F) project." }, { "ob_id": 16603, "uuid": "23406f61b8a84509b75516ab3f96576d", "short_code": "ob", "title": "FAAM B884 PIKNMIX and ISMAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events and ISMAR Test flight: International Sub-Millimetre Airborne Radiometer projects." }, { "ob_id": 18717, "uuid": "f505edd50b794399974e80c52772a2b0", "short_code": "ob", "title": "FAAM B814 PIKNMIX flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events project." }, { "ob_id": 16578, "uuid": "550c45312c3b45c9adef7acbd5d4a2e4", "short_code": "ob", "title": "FAAM B882 PIKNMIX flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events project." }, { "ob_id": 27940, "uuid": "c3461c55e13942df9e3e217daeb4a909", "short_code": "ob", "title": "FAAM C164 PIKNMIX-F flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events (PIKNMIX-F) project." }, { "ob_id": 27920, "uuid": "ff1bef1f13744d76a228f138f2873afd", "short_code": "ob", "title": "FAAM C154 PIKNMIX-F flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events (PIKNMIX-F) project." }, { "ob_id": 17276, "uuid": "b8da54526b524f698bd6cfc0382f8f4a", "short_code": "ob", "title": "FAAM B664 PIKNMIX Test flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events project." }, { "ob_id": 27948, "uuid": "aee65288656346d286eb1247638c1ebf", "short_code": "ob", "title": "FAAM C168 PIKNMIX-F flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events (PIKNMIX-F) project." }, { "ob_id": 15810, "uuid": "25b04eac70b24a50a9c0d9a07a4a1ebf", "short_code": "ob", "title": "FAAM B667 PIKNMIX flight, number 3: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 3 for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events project." }, { "ob_id": 27938, "uuid": "9e859ab11d3642d688437088561f7cf2", "short_code": "ob", "title": "FAAM C163 PIKNMIX-F flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events (PIKNMIX-F) project." }, { "ob_id": 27926, "uuid": "2dd33547716548d9b0017c292d6156cd", "short_code": "ob", "title": "FAAM C157 PIKNMIX-F flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events (PIKNMIX-F) project." }, { "ob_id": 16200, "uuid": "b00e22fbd09d4285826948a43e1fd2e5", "short_code": "ob", "title": "FAAM B668 PIKNMIX flight, number 4: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 4 for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events project." }, { "ob_id": 18342, "uuid": "a188ceead9504b6e9eaed6dfd83374b8", "short_code": "ob", "title": "FAAM B671 PIKNMIX flight, number 7: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft during flight 7 for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events project." }, { "ob_id": 27936, "uuid": "b942c797723d41bc801d23dc916ce840", "short_code": "ob", "title": "FAAM C162 PIKNMIX-F flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events (PIKNMIX-F) project." }, { "ob_id": 27946, "uuid": "ec03a5624c3c42938a007ecbe69e5530", "short_code": "ob", "title": "FAAM C167 PIKNMIX-F flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events (PIKNMIX-F) project." }, { "ob_id": 27942, "uuid": "2b62ba1cfb08460980b2587b593d136f", "short_code": "ob", "title": "FAAM C165 PIKNMIX-F flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Met Office PIKNMIX campaigns: cloud pyhsics and radiation events (PIKNMIX-F) project." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 60983, 60984, 60985, 60988, 60989, 60990, 60991, 60992, 60986, 60987 ], "onlineresource_set": [], "project_set": [ 14844 ] }, { "ob_id": 15827, "uuid": "0816a24092be4d1395b9539f4c1deb0a", "short_code": "coll", "title": "AETIAQ: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for AETIAQ - Aviation Emissions and Their Impact on Air Quality .", "keywords": "AETIAQ, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2014-07-14T13:38:12", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 17827, "uuid": "343ee4edcb29498f88bb0ffc7445d53e", "short_code": "ob", "title": "FAAM B429 AETIAQ flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for AETIAQ - Aviation Emissions and Their Impact on Air Quality project." }, { "ob_id": 17823, "uuid": "87b1c80567854a1484ba53ff18ecc075", "short_code": "ob", "title": "FAAM B428 AETIAQ flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for AETIAQ - Aviation Emissions and Their Impact on Air Quality project. This flight was aborted due to technical issues and no data is available." }, { "ob_id": 15977, "uuid": "1a98825b246445dd828fe36b72d9696e", "short_code": "ob", "title": "FAAM B340 AETIAQ flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for AETIAQ - Aviation Emissions and Their Impact on Air Quality project." }, { "ob_id": 18047, "uuid": "7efc930546cc42e0a0334f94085e8736", "short_code": "ob", "title": "FAAM B328 AETIAQ flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for AETIAQ - Aviation Emissions and Their Impact on Air Quality project." }, { "ob_id": 17635, "uuid": "7631cf6779b0450ca58601e2e90078fe", "short_code": "ob", "title": "FAAM B342 AETIAQ flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for AETIAQ - Aviation Emissions and Their Impact on Air Quality project." }, { "ob_id": 15973, "uuid": "9cfea2c60f3c4a3f96b11074a0175b29", "short_code": "ob", "title": "FAAM B341 AETIAQ flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for AETIAQ - Aviation Emissions and Their Impact on Air Quality project." }, { "ob_id": 15826, "uuid": "2ab6c84ecb3544eaa26fcaaf588777b5", "short_code": "ob", "title": "FAAM B382 AETIAQ flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for AETIAQ - Aviation Emissions and Their Impact on Air Quality project." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 61063, 61064, 61065, 61068, 61069, 61070, 61071, 61072, 61066, 61067 ], "onlineresource_set": [], "project_set": [ 14406 ] }, { "ob_id": 15846, "uuid": "2ff89840a89840868acff801f8859451", "short_code": "coll", "title": "SAMBBA: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for South AMerican Biomass Burning Analysis (SAMBBA).\r\n\r\nSAMBBA project - a UK-Brasil Consortium funded by NERC. Biomass burning aerosols have a significant influence on climate – both directly as they scatter and absorb solar radiation – and indirectly as they influence cloud optical properties and lifetime through their ability to act as sites for cloud droplet formation. Biomass burning aerosols are a complex mixture of black carbon, organic carbon, and inorganic compounds, and are thus difficult to model accurately. While parameterisations have been developed in the climate version of the UM (e.g. HADGEM-2) that enable reasonable representation of the aerosol optical depth, significant uncertainties still exists in accurately determining the aerosol absorption (via the single scattering albedo) and the subsequent effects on radiation. These radiative effects have a significant impact on climate, which needs to be quantified over key regions such as Amazonia. Furthermore, BB aerosols have a direct impact on the performance of numerical weather prediction models. The effects of biomass burning aerosol upon cloud microphysical and optical properties play a significant role in assessing the radiative influence of clouds. These are also processes that are poorly quantified and hence provide fundamental uncertainties in weather forecasts and climate change scenarios. To improve quantification of these uncertainties, the microphysical and chemical properties of biomass burning aerosol and its precursors need to be determined yet these remain uncertain and are known to be modified during their lifetime in the atmosphere. Furthermore, it is important to assess the background state of the atmosphere in the region to understand the influence such large anthropogenic perturbations are having on the region. However, aerosol particles in the natural tropical atmosphere remain poorly understood.\r\n\r\nThe aim of the SAMBBA project was to investigate the properties of biomass burning aerosols over South America. The main biomass burning season occurs during Sept/Oct when deforestation fires and agricultural burning are prolific, particularly over central and south eastern parts of Brazil. These contribute to high loadings of biomass burning aerosol over much of South America with aerosol optical depths frequently exceeding 1 in many central parts of the continent. SAMBBA was a consortium of 7 university groups, the UK Met Office and a number of Brazilian partners, which delivered a suite of ground, aircraft and satellite measurements of Amazonian BBA and use this data to:\r\n\r\n-improve our knowledge of BB emissions;\r\n-challenge and improve the latest aerosol process models;\r\n-challenge and improve satellite retrievals;\r\n-test predictions of aerosol influences on regional climate and weather over Amazonia and the surrounding regions made using the next generation of climate and NWP models with extensive prognostic aerosol schemes; and\r\n-assess the impact of biomass burning on the Amazonian biosphere.", "keywords": "SAMBBA, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2014-07-14T13:38:13", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 16133, "uuid": "7d811241f5564ffc9cb797b3531d6318", "short_code": "ob", "title": "FAAM B731 SAMBBA flight, number 1: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 1 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17795, "uuid": "7e7783fcd44e4a3890f3bd67e89e585e", "short_code": "ob", "title": "FAAM B742 SAMBBA flight, number 12: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites on board the FAAM BAE-146 aircraft during flight 12 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17639, "uuid": "38435109ac5c4922946ad180e14efee0", "short_code": "ob", "title": "FAAM B729 SAMBBA Test flight, number 1: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft during flight 1 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17819, "uuid": "09c4253801434e51b29c8be73ff0f0c3", "short_code": "ob", "title": "FAAM B748 SAMBBA flight, number 18: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 18 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17811, "uuid": "dc37ef25d4ea40ff974499e232fee224", "short_code": "ob", "title": "FAAM B746 SAMBBA flight, number 16: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 16 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17967, "uuid": "48404016b4724379ae41b976511de29c", "short_code": "ob", "title": "FAAM B733 SAMBBA flight, number 3: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 3 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17946, "uuid": "2210e6c7bee94ffbb6e0fa08a17d066b", "short_code": "ob", "title": "FAAM B736 SAMBBA flight, number 6: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 6 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 15911, "uuid": "e1aa669451ac4bbd8631108fb3045fb1", "short_code": "ob", "title": "FAAM B730 SAMBBA Test flight, number 2: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft during flight 2 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 18543, "uuid": "b24491f2334140a08167a0a145ba05f7", "short_code": "ob", "title": "FAAM B750 SAMBBA flight, number 20: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 20 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 15845, "uuid": "8ab7c4fca8f34fc7826dec2716750dc5", "short_code": "ob", "title": "FAAM B738 SAMBBA flight, number 8: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 8 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17815, "uuid": "35208a20d8454d78a886ea2245e9e632", "short_code": "ob", "title": "FAAM B749 SAMBBA flight, number 19: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 19 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17963, "uuid": "ae2f39c12cd14a70887354074ef7c743", "short_code": "ob", "title": "FAAM B732 SAMBBA flight, number 2: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 2 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17799, "uuid": "521cc8020983423b8adf716dd9296b83", "short_code": "ob", "title": "FAAM B745 SAMBBA flight, number 15: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 15 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17942, "uuid": "cc90c99c5c4145559650bb41778154cb", "short_code": "ob", "title": "FAAM B735 SAMBBA flight, number 5: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 5 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17787, "uuid": "0b857ca8100f4fb881b5f39ccbcf9b1d", "short_code": "ob", "title": "FAAM B740 SAMBBA flight, number 10: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 10 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17803, "uuid": "4608d403f70b4c498b2be709073fd933", "short_code": "ob", "title": "FAAM B744 SAMBBA flight, number 14: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 14 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17938, "uuid": "0b64e9f8b5b14d9b942c868416077cf3", "short_code": "ob", "title": "FAAM B734 SAMBBA flight, number 4: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 4 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17783, "uuid": "9886b8c1ff4a4cb08a9deed700d78a00", "short_code": "ob", "title": "FAAM B741 SAMBBA flight, number 11: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 11 for South AMerican Biomass Burning Analysis (SAMBBA) project." }, { "ob_id": 17791, "uuid": 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BAE-146 aircraft collected for BUNCEFIELD SMOKE EXPERIMENT (Buncefield Smoke Experiment) project." }, { "ob_id": 18829, "uuid": "b24ec4a348be46c6ac90bf1400ed86e3", "short_code": "ob", "title": "FAAM B149 Buncefield Smoke Experiment flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for BUNCEFIELD SMOKE EXPERIMENT (Buncefield Smoke Experiment) project." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 67977, 67978, 67979, 67982, 67983, 67984, 67985, 67986, 67980, 67981 ], "onlineresource_set": [], "project_set": [ 14407 ] }, { "ob_id": 17959, "uuid": "072fb80085e94f39b26b7b3d6fe1c127", "short_code": "coll", "title": "ACEMED: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for ACEMED - Evaluation of CALIPSO's Aerosol Classification scheme over Eastern MEDiterranean.", "keywords": "ACEMED, EUFAR, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2014-07-14T13:38:13", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 18947, "uuid": "d966e1e2f5044cdeac47e553a5b7d1fe", "short_code": "ob", "title": "FAAM B644 ACEMED and EUFAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for ACEMED - Evaluation of CALIPSO's Aerosol Classification scheme over Eastern MEDiterranean and European Facility for Airborne Research in Environmental and Geo-sciences (EUFAR) projects." }, { "ob_id": 17958, "uuid": "f014fe1ff19f40d78c83223458d82aee", "short_code": "ob", "title": "FAAM B638 ACEMED and EUFAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for ACEMED - Evaluation of CALIPSO's Aerosol Classification scheme over Eastern MEDiterranean and European Facility for Airborne Research in Environmental and Geo-sciences (EUFAR) projects." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 68071, 68072, 68073, 68076, 68077, 68078, 68079, 68080, 68074, 68075 ], "onlineresource_set": [], "project_set": [ 14829 ] }, { "ob_id": 17972, "uuid": "3b70e9db60ba40d399e8805f4bc70ebd", "short_code": "coll", "title": "SONATA: In-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "This dataset collection contains in-situ airborne observations by the FAAM BAE-146 aircraft for School ON Aircraft Techniques for the studies of Atmospheric chemistry. (SONATA).", "keywords": "SONATA, EUFAR, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2014-07-14T13:38:13", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 17971, "uuid": "875b5a571e404e9681369ce3c8adb3bc", "short_code": "ob", "title": "FAAM B635 SONATA and EUFAR flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for School ON Aircraft Techniques for the studies of Atmospheric chemistry (SONATA) and European Facility for Airborne Research in Environmental and Geo-sciences (EUFAR) projects." }, { "ob_id": 17997, "uuid": "52857e2592404999b73a1316afbe348a", "short_code": "ob", "title": "FAAM B633 SONATA and EUFAR Transit flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for School ON Aircraft Techniques for the studies of Atmospheric chemistry (SONATA) and European Facility for Airborne Research in Environmental and Geo-sciences (EUFAR) projects." }, { "ob_id": 17976, "uuid": "afd8900efd46474fb839f5cb0aa46f70", "short_code": "ob", "title": "FAAM B634 SONATA and EUFAR flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for School ON Aircraft Techniques for the studies of Atmospheric chemistry (SONATA) and European Facility for Airborne Research in Environmental and Geo-sciences (EUFAR) projects." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 68125, 68123, 68124, 68128, 68129, 68130, 68131, 68132, 68126, 68127 ], "onlineresource_set": [], "project_set": [ 14848 ] }, { "ob_id": 17981, "uuid": "49304a80a55343aca2f147d0c60e5a65", "short_code": "coll", "title": "AEGEAN-GAME: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for AEGEAN-GAME - AEGEAN Pollution: Gaseous and Aerosol airborne Measurements project.", "keywords": "AEGEAN-GAME, EUFAR, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2014-07-14T13:38:13", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 18934, "uuid": "ff5f9a1fd5ad4456a38e44dcc5967017", "short_code": "ob", "title": "FAAM B641 AEGEAN-GAME and EUFAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for AEGEAN-GAME - AEGEAN Pollution: Gaseous and Aerosol airborne Measurements project and European Facility for Airborne Research in Environmental and Geo-sciences (EUFAR)." }, { "ob_id": 18930, "uuid": "f8cd1bbc7947471aa47e198cfd7fc705", "short_code": "ob", "title": "FAAM B640 AEGEAN-GAME and EUFAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for AEGEAN-GAME - AEGEAN Pollution: Gaseous and Aerosol airborne Measurements project and European Facility for Airborne Research in Environmental and Geo-sciences (EUFAR)." }, { "ob_id": 18005, "uuid": "375030073be04d24b6de8daa12267250", "short_code": "ob", "title": "FAAM B639 AEGEAN-GAME, EUFAR and FAAM-ESA flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for AEGEAN-GAME - AEGEAN Pollution: Gaseous and Aerosol airborne Measurements project, European Facility for Airborne Research in Environmental and Geo-sciences (EUFAR) and FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects." }, { "ob_id": 17985, "uuid": "040a778af56a402c8521e04d92e6d717", "short_code": "ob", "title": "FAAM B636 AEGEAN-GAME and EUFAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for AEGEAN-GAME - AEGEAN Pollution: Gaseous and Aerosol airborne Measurements project and European Facility for Airborne Research in Environmental and Geo-sciences (EUFAR)." }, { "ob_id": 17980, "uuid": "b81e2f0db35c4b32a9d641edd7e71706", "short_code": "ob", "title": "FAAM B637 AEGEAN-GAME and EUFAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for AEGEAN-GAME - AEGEAN Pollution: Gaseous and Aerosol airborne Measurements project and European Facility for Airborne Research in Environmental and Geo-sciences (EUFAR)." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 68161, 68162, 68163, 68166, 68167, 68168, 68169, 68170, 68164, 68165 ], "onlineresource_set": [], "project_set": [ 14830 ] }, { "ob_id": 18290, "uuid": "96410726603c455d8901ade773368c92", "short_code": "coll", "title": "SALSTICE: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for SALSTICE Semi-Arid Land Surface Temperature IASI Cal/val.", "keywords": "SALSTICE, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2015-03-23T20:34:07", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 18289, "uuid": "15d8da1b6e284a5a894180b6a3046fda", "short_code": "ob", "title": "FAAM B781 SALSTICE flight, number 9: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 9 for SALSTICE Semi-Arid Land Surface Temperature IASI Cal/val project." }, { "ob_id": 18450, "uuid": "392721e2caad4953958cddb807afde30", "short_code": "ob", "title": "FAAM B773 SALSTICE flight, number 1: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 1 for SALSTICE Semi-Arid Land Surface Temperature IASI Cal/val project." }, { "ob_id": 18466, "uuid": "930e0931fb1f457d9958160ee6adcc21", "short_code": "ob", "title": "FAAM B777 SALSTICE flight, number 5: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 5 for SALSTICE Semi-Arid Land Surface Temperature IASI Cal/val project." }, { "ob_id": 18458, "uuid": "f4bcecedc4ee49d889f2d2af734f6ca7", "short_code": "ob", "title": "FAAM B775 SALSTICE flight, number 3: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 3 for SALSTICE Semi-Arid Land Surface Temperature IASI Cal/val project." }, { "ob_id": 18410, "uuid": "b660c4108a8840f3a505e9a3a1d87dea", "short_code": "ob", "title": "FAAM B779 SALSTICE flight, number 9: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 9 for SALSTICE Semi-Arid Land Surface Temperature IASI Cal/val project." }, { "ob_id": 18406, "uuid": "37c23dcb9f0344b6a0619b255fea54f8", "short_code": "ob", "title": "FAAM B778 SALSTICE flight, number 6: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 6 for SALSTICE Semi-Arid Land Surface Temperature IASI Cal/val project." }, { "ob_id": 18294, "uuid": "0439f2f018ec405a815e51aeeaff635a", "short_code": "ob", "title": "FAAM B780 SALSTICE flight, number 8: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 8 for SALSTICE Semi-Arid Land Surface Temperature IASI Cal/val project." }, { "ob_id": 18302, "uuid": "94cf8e5d8a0d499da12a4dee778b399a", "short_code": "ob", "title": "FAAM B782 SALSTICE flight, number 10: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 10 for SALSTICE Semi-Arid Land Surface Temperature IASI Cal/val project." }, { "ob_id": 18454, "uuid": "e84713aedfe2496fb031026d97f78295", "short_code": "ob", "title": "FAAM B774 SALSTICE flight, number 2: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 2 for SALSTICE Semi-Arid Land Surface Temperature IASI Cal/val project." }, { "ob_id": 18462, "uuid": "cc4036d00f97456ba5ac7323ada261e8", "short_code": "ob", "title": "FAAM B776 SALSTICE flight, number 4: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft during flight 4 for SALSTICE Semi-Arid Land Surface Temperature IASI Cal/val project." }, { "ob_id": 18446, "uuid": "b1438e7b91384a6e966be4d8f4e88592", "short_code": "ob", "title": "FAAM B772 SALSTICE Test flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for SALSTICE Semi-Arid Land Surface Temperature IASI Cal/val project." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 69151, 69152, 69153, 69156, 69157, 69158, 69159, 69160, 69154, 69155 ], "onlineresource_set": [], "project_set": [ 14846 ] }, { "ob_id": 18503, "uuid": "a4d6edc8efdc4b8c952d86d92270ab65", "short_code": "coll", "title": "LADUNEX: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for EUFAR Lagrangian Dust Source Inversion Experiment (LADUNEX).", "keywords": "FENNEC, LADUNEX, EUFAR, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2014-07-14T13:38:13", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 18515, "uuid": "0ab5786cde484cc49c85f6dd3bd343b9", "short_code": "ob", "title": "FAAM B607 FENNEC, LADUNEX and EUFAR flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC), EUFAR Lagrangian Dust Source Inversion Experiment and European Facility for Airborne Research in Environmental and Geo-sciences (EUFAR) projects." }, { "ob_id": 18502, "uuid": "8dbba4f1449147278e7f053bdc6bb6c8", "short_code": "ob", "title": "FAAM B604 FENNEC, LADUNEX and EUFAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC), EUFAR Lagrangian Dust Source Inversion Experiment and European Facility for Airborne Research in Environmental and Geo-sciences (EUFAR) projects." }, { "ob_id": 18511, "uuid": "1f4555d2589841a8a4bbbf1fe42f54c8", "short_code": "ob", "title": "FAAM B606 FENNEC, LADUNEX and EUFAR flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for Fennec - The Saharan Climate System (FENNEC), EUFAR Lagrangian Dust Source Inversion Experiment and European Facility for Airborne Research in Environmental and Geo-sciences (EUFAR) projects." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 69833, 69834, 69835, 69838, 69839, 69840, 69841, 69842, 69836, 69837 ], "onlineresource_set": [], "project_set": [ 11988 ] }, { "ob_id": 18902, "uuid": "b6787e70e4104cf9ae95aec673699d47", "short_code": "coll", "title": "OMEGA: in-situ airborne observations by the FAAM BAE-146 aircraft", "abstract": "In-situ airborne observations by the FAAM BAE-146 aircraft for OMEGA (BAFFLES).", "keywords": "OMEGA, FAAM, airborne, atmospheric measurments", "publicationState": "published", "dataPublishedTime": "2014-07-14T13:38:13", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 8 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 18901, "uuid": "8a90b9434c524a36884c836ad1c5347f", "short_code": "ob", "title": "FAAM B649 OMEGA flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for OMEGA (BAFFLES) project." }, { "ob_id": 18955, "uuid": "313233ee19ff4bc5baed39be33fda948", "short_code": "ob", "title": "FAAM B646 OMEGA and DIAMET Test flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for OMEGA (BAFFLES) and DIAMET (Diabatic influences on mesoscale structures in extratropical storms) projects." }, { "ob_id": 18951, "uuid": "7e92c75474b7495f9dea8d39276ec760", "short_code": "ob", "title": "FAAM B645 OMEGA flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for OMEGA (BAFFLES) project." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 71159, 71160, 71161, 71164, 71165, 71166, 71167, 71168, 71162, 71163 ], "onlineresource_set": [], "project_set": [ 14417 ] }, { "ob_id": 19146, "uuid": "6ceb72ed91df42f69050a2a0fa18ea55", "short_code": "coll", "title": "RAPID Understanding uncertainty in simulations of THC-related rapid climate change:", "abstract": "The main tools that are used for making projections of climate change in the coming century resulting from greenhouse-gas and other emissions are detailed coupled three-dimensional models of the atmosphere and ocean. However, such models give widely different results for some important aspects of climate change, thus limiting our ability to make practically useful projections. One such aspect is changes that may happen in the Atlantic Ocean thermohaline circulation, often referred to as the Gulf Stream. This circulation transports a great deal of heat northwards. If it weakened, future warming in Europe in particular could be reduced or possibly reversed. The spread of model results basically reflects limitations in current understanding of how the large-scale climate system operates. The aim of this project was to identify which are the most important aspects of that uncertainty by making comparisons of the responses simulated by a range of climate models. The results were intended to help improve the models by focusing attention on the aspects which require further theoretical or observational study.\r\n\r\nThis dataset collection contains meteorology and ocean model outputs.\r\n\r\nRapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation.\r\n", "keywords": "RAPID, Climate change, Atlantic Ocean's Thermohaline Circulation", "publicationState": "published", "dataPublishedTime": "2008-12-10T02:40:23", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 23 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" }, { "ob_id": 1142, "name": "NDGO0005" } ], "member": [ { "ob_id": 6247, "uuid": "ae274369f993074ea4d31e8073b9155a", "short_code": "ob", "title": "HadGEM1 Control run experiment - afepb run", "abstract": "The HadGEM1 model is the Met Office Hadley centre global environment model version 1. This version of the model includes a detailed representation of the atmosphere, land surface, ocean, and cryosphere. This dataset includes a control run and a number of climate change experiments. Part of the UK Met Office Hadley Centre's contributions to the fourth assessment report of the IPCC (Intergovernmental Panel on Climate Change) was based on the HadGEM1 model. This dataset provides all the available data from the control integration (run with preindustrial levels of CO2 and other forcings) as well as output from a number of climate change experiments. The data is provided in the Met Office PP format, but tools are available to extract subsets in NetCDF and other formats." }, { "ob_id": 19151, "uuid": "89896f4ac3224d68a0afa279a96bc63a", "short_code": "ob", "title": "RAPID: FRUGAL meteorology and ocean model outputs", "abstract": "\"Improving our ability to predict rapid changes in the El Nino Southern Oscillation climatic phenomenon\" project, which was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 1 - NER/T/S/2002/00443 - Duration 1 Jan 2004 - 30 Sep 2007) led by Prof Alexander Tudhope of the University of Edinburgh, with co-investigators at the Scottish Universities Environment Research Centre, Bigelow Laboratory for Ocean Sciences, and the University of Reading. \r\n\r\nThis dataset collection contains meteorology and ocean model outputs from the FRUGAL model.\r\n\r\nThe objective was to use a combination of palaeoclimate reconstruction from annually-banded corals and the fully coupled HadCM3 atmosphere-ocean general circulation model to develop an understanding of the controls on variability in the strength and frequency of ENSO, and to improve our ability to predict the likelihood of future rapid changes in this important element of the climate system. To achieve this, we targeted three periods:0-2.5 ka: Representative of near-modern climate forcing; revealing the internal variability in the system.6-9 ka: a period of weak or absent ENSO, and different orbital forcing; a test of the model's ability to capture externally-forced change in ENSO.200-2100 AD: by using the palaeo periods to test and optimise model parameterisation, produce a new, improved, prediction of ENSO variability in a warming world.\r\n\r\nRapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation." }, { "ob_id": 19147, "uuid": "07b007d59e83414baae0bf54e0b31483", "short_code": "ob", "title": "RAPID: HADCM3 meteorology ans ocean model outputs", "abstract": "\"Improving our ability to predict rapid changes in the El Nino Southern Oscillation climatic phenomenon\" project, which was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 1 - NER/T/S/2002/00443 - Duration 1 Jan 2004 - 30 Sep 2007) led by Prof Alexander Tudhope of the University of Edinburgh, with co-investigators at the Scottish Universities Environment Research Centre, Bigelow Laboratory for Ocean Sciences, and the University of Reading. \r\n\r\nThis dataset collection contains meteorology and ocean model outputs from the Hadley Centre Coupled Model, version 3 (HadCM3) model.\r\n\r\nThe objective was to use a combination of palaeoclimate reconstruction from annually-banded corals and the fully coupled HadCM3 atmosphere-ocean general circulation model to develop an understanding of the controls on variability in the strength and frequency of ENSO, and to improve our ability to predict the likelihood of future rapid changes in this important element of the climate system. To achieve this, we targeted three periods:0-2.5 ka: Representative of near-modern climate forcing; revealing the internal variability in the system.6-9 ka: a period of weak or absent ENSO, and different orbital forcing; a test of the model's ability to capture externally-forced change in ENSO.200-2100 AD: by using the palaeo periods to test and optimise model parameterisation, produce a new, improved, prediction of ENSO variability in a warming world.\r\n\r\nRapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation." }, { "ob_id": 19159, "uuid": "8201bebead8e48c2ad0aa74eab3e0c7a", "short_code": "ob", "title": "RAPID: CHIME meteorology and ocean model outputs", "abstract": "\"Improving our ability to predict rapid changes in the El Nino Southern Oscillation climatic phenomenon\" project, which was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 1 - NER/T/S/2002/00443 - Duration 1 Jan 2004 - 30 Sep 2007) led by Prof Alexander Tudhope of the University of Edinburgh, with co-investigators at the Scottish Universities Environment Research Centre, Bigelow Laboratory for Ocean Sciences, and the University of Reading. \r\n\r\nThis dataset collection contains meteorology and ocean model outputs from the Coupled Hadley-Isopycnic Model Experiment (CHIME).\r\n\r\nThe objective was to use a combination of palaeoclimate reconstruction from annually-banded corals and the fully coupled HadCM3 atmosphere-ocean general circulation model to develop an understanding of the controls on variability in the strength and frequency of ENSO, and to improve our ability to predict the likelihood of future rapid changes in this important element of the climate system. To achieve this, we targeted three periods:0-2.5 ka: Representative of near-modern climate forcing; revealing the internal variability in the system.6-9 ka: a period of weak or absent ENSO, and different orbital forcing; a test of the model's ability to capture externally-forced change in ENSO.200-2100 AD: by using the palaeo periods to test and optimise model parameterisation, produce a new, improved, prediction of ENSO variability in a warming world.\r\n\r\nRapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation." }, { "ob_id": 19149, "uuid": "4f655cfbf48d43a2aa8367c629cf3de5", "short_code": "ob", "title": "RAPID: GENIE-1 EMIC meteorology and ocean model outputs", "abstract": "\"Improving our ability to predict rapid changes in the El Nino Southern Oscillation climatic phenomenon\" project, which was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 1 - NER/T/S/2002/00443 - Duration 1 Jan 2004 - 30 Sep 2007) led by Prof Alexander Tudhope of the University of Edinburgh, with co-investigators at the Scottish Universities Environment Research Centre, Bigelow Laboratory for Ocean Sciences, and the University of Reading. \r\n\r\nThis dataset collection contains meteorology and ocean model outputs from the GENIE-1 EMIC model.\r\n\r\nThe objective was to use a combination of palaeoclimate reconstruction from annually-banded corals and the fully coupled HadCM3 atmosphere-ocean general circulation model to develop an understanding of the controls on variability in the strength and frequency of ENSO, and to improve our ability to predict the likelihood of future rapid changes in this important element of the climate system. To achieve this, we targeted three periods:0-2.5 ka: Representative of near-modern climate forcing; revealing the internal variability in the system.6-9 ka: a period of weak or absent ENSO, and different orbital forcing; a test of the model's ability to capture externally-forced change in ENSO.200-2100 AD: by using the palaeo periods to test and optimise model parameterisation, produce a new, improved, prediction of ENSO variability in a warming world.\r\n\r\nRapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation." }, { "ob_id": 6740, "uuid": "98536d052df0cbff8a85725758fccf4d", "short_code": "ob", "title": "RAPID: ORCA025 model output (1987-2004)", "abstract": "The Assimilation in ocean and coupled models to determine the thermohaline circulation\" project was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 2 - NE/C509058/1 - Duration 1 Sep 2005 - 30 Sep 2009) led by Prof Keith Haines of the University of Reading, with co-investigators at the National Oceanography Centre. \r\n\r\nThis dataset collection contains Atlantic Ocean Thermohaline Circulation ORCA025 model output." }, { "ob_id": 19153, "uuid": "71f66f878ce445f7bf72a5891111e24d", "short_code": "ob", "title": "RAPID: FORTE meteorology and ocean model outputs", "abstract": "\"Improving our ability to predict rapid changes in the El Nino Southern Oscillation climatic phenomenon\" project, which was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 1 - NER/T/S/2002/00443 - Duration 1 Jan 2004 - 30 Sep 2007) led by Prof Alexander Tudhope of the University of Edinburgh, with co-investigators at the Scottish Universities Environment Research Centre, Bigelow Laboratory for Ocean Sciences, and the University of Reading. \r\n\r\nThis dataset collection contains meteorology and ocean model outputs from the FORTE model.\r\n\r\nThe objective was to use a combination of palaeoclimate reconstruction from annually-banded corals and the fully coupled HadCM3 atmosphere-ocean general circulation model to develop an understanding of the controls on variability in the strength and frequency of ENSO, and to improve our ability to predict the likelihood of future rapid changes in this important element of the climate system. To achieve this, we targeted three periods:0-2.5 ka: Representative of near-modern climate forcing; revealing the internal variability in the system.6-9 ka: a period of weak or absent ENSO, and different orbital forcing; a test of the model's ability to capture externally-forced change in ENSO.200-2100 AD: by using the palaeo periods to test and optimise model parameterisation, produce a new, improved, prediction of ENSO variability in a warming world.\r\n\r\nRapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation." }, { "ob_id": 19164, "uuid": "0291fc69526e4d8699737d7f67c60177", "short_code": "ob", "title": "RAPID: ORCA1 model output data (1958-2004)", "abstract": "The Assimilation in ocean and coupled models to determine the thermohaline circulation\" project was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 2 - NE/C509058/1 - Duration 1 Sep 2005 - 30 Sep 2009) led by Prof Keith Haines of the University of Reading, with co-investigators at the National Oceanography Centre. \r\n\r\nThis dataset collection contains Atlantic Ocean Thermohaline Circulation ORCA1 model data." }, { "ob_id": 19155, "uuid": "d4c6ac6309dd4728adc11023628e2294", "short_code": "ob", "title": "RAPID: FORTE2 meteorology and ocean model outputs", "abstract": "\"Improving our ability to predict rapid changes in the El Nino Southern Oscillation climatic phenomenon\" project, which was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 1 - NER/T/S/2002/00443 - Duration 1 Jan 2004 - 30 Sep 2007) led by Prof Alexander Tudhope of the University of Edinburgh, with co-investigators at the Scottish Universities Environment Research Centre, Bigelow Laboratory for Ocean Sciences, and the University of Reading. \r\n\r\nThis dataset collection contains meteorology and ocean model outputs from the FORTE2 model.\r\n\r\nThe objective was to use a combination of palaeoclimate reconstruction from annually-banded corals and the fully coupled HadCM3 atmosphere-ocean general circulation model to develop an understanding of the controls on variability in the strength and frequency of ENSO, and to improve our ability to predict the likelihood of future rapid changes in this important element of the climate system. To achieve this, we targeted three periods:0-2.5 ka: Representative of near-modern climate forcing; revealing the internal variability in the system.6-9 ka: a period of weak or absent ENSO, and different orbital forcing; a test of the model's ability to capture externally-forced change in ENSO.200-2100 AD: by using the palaeo periods to test and optimise model parameterisation, produce a new, improved, prediction of ENSO variability in a warming world.\r\n\r\nRapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation." }, { "ob_id": 19157, "uuid": "34e0ce3a92994050b4ab34bd05a0a0ab", "short_code": "ob", "title": "RAPID: FAMOUS meteorology and ocean model outputs", "abstract": "\"Improving our ability to predict rapid changes in the El Nino Southern Oscillation climatic phenomenon\" project, which was a Natural Environment Research Council (NERC) RAPID Climate Change Research Programme project (Round 1 - NER/T/S/2002/00443 - Duration 1 Jan 2004 - 30 Sep 2007) led by Prof Alexander Tudhope of the University of Edinburgh, with co-investigators at the Scottish Universities Environment Research Centre, Bigelow Laboratory for Ocean Sciences, and the University of Reading. \r\n\r\nThis dataset collection contains meteorology and ocean model outputs from FAMOUS model.\r\n\r\nThe objective was to use a combination of palaeoclimate reconstruction from annually-banded corals and the fully coupled HadCM3 atmosphere-ocean general circulation model to develop an understanding of the controls on variability in the strength and frequency of ENSO, and to improve our ability to predict the likelihood of future rapid changes in this important element of the climate system. To achieve this, we targeted three periods:0-2.5 ka: Representative of near-modern climate forcing; revealing the internal variability in the system.6-9 ka: a period of weak or absent ENSO, and different orbital forcing; a test of the model's ability to capture externally-forced change in ENSO.200-2100 AD: by using the palaeo periods to test and optimise model parameterisation, produce a new, improved, prediction of ENSO variability in a warming world.\r\n\r\nRapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation." } ], "identifier_set": [ 8969, 10444 ], "responsiblepartyinfo_set": [ 72017, 72019, 72020, 72021, 72022, 72023, 72024, 72018, 72025, 72459, 72037, 72026 ], "onlineresource_set": [ 15203, 15201, 15202 ], "project_set": [ 19145 ] }, { "ob_id": 19163, "uuid": "b02ac774670248c7b8a700851ff6fd69", "short_code": "coll", "title": "RAPID HadCM3", "abstract": "Rapid Climate Change (RAPID) was a £20 million, six-year (2001-2007) programme for the Natural Environment Research Council. The programme aimed to improve the ability to quantify the probability and magnitude of future rapid change in climate, with a main (but not exclusive) focus on the role of the Atlantic Ocean's Thermohaline Circulation.\r\n", "keywords": "RAPID, Climate change, Atlantic Ocean's Thermohaline Circulation", "publicationState": "published", "dataPublishedTime": "2008-12-10T02:40:23", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 23 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 4868, "uuid": "12fc103f80759ab4b8e94cb4e6056681", "short_code": "ob", "title": "HadCM3 Control run - 100 years run", "abstract": "Numerical model data from the Hadley Centre coupled model (HadCM3) Control Run. Please note that these data have now been superceeded by the data from the main BADC HadCM3 archive. The current dataset covers 100 years (2079 - 2178), and contains all atmospheric and oceanic fields derived from the HadCM3 model. A 1000 year dataset (1849-2849) of model data for selected parameters has also been retrieved from the Met Office and stored at the BADC." }, { "ob_id": 4862, "uuid": "948396dc867163e927c4553ac2332d52", "short_code": "ob", "title": "HadCM3 Control run - 1000 years run", "abstract": "Numerical model data from the Hadley Centre coupled model (HadCM3) Control Run. Please note that these data have now been superceeded by the data from the main BADC HadCM3 archive. The current dataset covers 100 years (2079 - 2178), and contains all atmospheric and oceanic fields derived from the HadCM3 model. A 1000 year dataset (1849-2849) of model data for selected parameters has also been retrieved from the Met Office and stored at the BADC." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 72087, 72091, 72090, 72088, 72092, 72093, 72094, 72089, 72466 ], "onlineresource_set": [ 15205, 15206, 15204 ], "project_set": [ 19162 ] }, { "ob_id": 19274, "uuid": "43b756af495440ef8ab460d16926263f", "short_code": "coll", "title": "Microphysics of Antarctic Clouds (MAC) project :in-situ airborne atmospheric measurements, model output and NAME dispersion footprints.", "abstract": "Microphysics of Antarctic Clouds (MAC) is an active NERC (Natural Environment Research Council) funded project (NE/K01305X/1). \r\n\r\nThis dataset collection contains NAME dispersion footprints model plots, model output and data in-situ observations from the British Antarctic Survey (BAS) Masin twin-otter aircraft. \r\n\r\nThe largest uncertainties in future climate predictions highlighted by the Intergovernmental Panel on Climate change (IPCC 2007) arise from our lack of knowledge of the interaction of clouds with solar and terrestrial radiation (Dufresene & Bony, 2008). In Antarctica clouds play a major role in determining the continent's ice sheet radiation budget, its surface mass balance and ozone climatology. However in spite of this there are few in situ measurements of cloud properties, aerosol numbers, Cloud Condensation Nuclei (CCN) or Ice Nuclei (IN) with the main focus being on remote sensing data sets (see the review by Bromwich et al 2012). As a result the skill in climate and forecast models at high latitudes is significantly poorer than at mid latitudes. In this project a more representative of the Antarctic continent's coastal region was used. It is in this coastal region that clouds will have the biggest impact on the climate as in the interior of the continent the total cloud cover is less (Lachlan-Cope 2010) and those clouds that exist are more tenuous. To achieve this flights were conducted from the Halley research station.", "keywords": "MAC, aircraft, CCN, cloud, Antartic, NAME dispersion footprints", "publicationState": "published", "dataPublishedTime": "2016-07-11T09:38:34", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1142, "name": "NDGO0005" }, { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 27053, "uuid": "5d1af7fc779346de86de4a6fcf750912", "short_code": "ob", "title": "Microphysics of Antarctic Clouds: Polar-optimised Weather Research and Forecasting (PWRF) model simulations for case study with BAS MASIN twin-otter flights 218 and 219", "abstract": "The NERC-funded Microphysics of Antarctic Clouds (MAC) project was centred on an aircraft campaign measuring clouds, aerosols, and boundary layer properties over the Weddell Sea, Antarctica. These data are simulations of the Polar-optimised Weather Research and Forecasting (PWRF) model for 5 configurations of the model's Morrison microphysics scheme, produced for a case study of two separate flights over the same region during the campaign (British Antarctic Survey MASIN twin-otter aircraft flights 218 an 219 on 27th November 2015). Each simulation contains data from two domains - a parent domain with 5km grid size and a nest with a 1km grid size.\r\n\r\nThe control simulation used default physics options in the PWRF model's Morrison microphysics scheme. For the no-threshold, 2xHM, 5xHM, 10xHM simulations, thresholds restricting Hallett-Mossop secondary ice production in the PWRF model's Morrison microphysics scheme were removed, and for the 2xHM, 5xHM, and 10xHM cases the corresponding ice multiplication factor was increased by a factor of 2, 5 or 10. \r\n\r\nIn all simulations, an approximation of the DeMott et al., 2010 (PNAS) parametrization used for primary ice nucleation. \r\n \r\nMethodology and further details can be found in Young et al., 2019 (Geophysical Research Letters): Radiative effects of secondary ice enhancement in coastal Antarctic clouds." }, { "ob_id": 19276, "uuid": "d29c23b800554d98bfd1f18e2e802c74", "short_code": "ob", "title": "Microphysics of Antarctic Clouds (MAC): NAME dispersion footprints model plots", "abstract": "Microphysics of Antarctic Clouds (MAC) is a active NERC (Natural Environment Research Council) funded project (NE/K01305X/1). \r\n\r\nThis dataset collection contains NAME dispersion footprints model plots. \r\n\r\nThe largest uncertainties in future climate predictions highlighted by the Intergovernmental Panel on Climate change (IPCC 2007) arise from our lack of knowledge of the interaction of clouds with solar and terrestrial radiation (Dufresene & Bony, 2008). In Antarctica clouds play a major role in determining the continent's ice sheet radiation budget, its surface mass balance and ozone climatology. However in spite of this there are few in situ measurements of cloud properties, aerosol numbers, Cloud Condensation Nuclei (CCN) or Ice Nuclei (IN) with the main focus being on remote sensing data sets (see the review by Bromwich et al 2012). As a result the skill in climate and forecast models at high latitudes is significantly poorer than at mid latitudes. In this project a more representative of the Antarctic continent's coastal region was used. It is in this coastal region that clouds will have the biggest impact on the climate as in the interior of the continent the total cloud cover is less (Lachlan-Cope 2010) and those clouds that exist are more tenuous. To achieve this flights were conducted from the Halley research station." }, { "ob_id": 27181, "uuid": "401e4c48509e41d09ad08235a5797f83", "short_code": "ob", "title": "BAS Twin-Otter flight 219 MAC flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAS Masin Twin-Otter aircraft.", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the British Antarctic Survey (BAS) Masin Twin-Otter aircraft collected for the Microphysics of Antarctic Clouds (MAC) project." }, { "ob_id": 27179, "uuid": "d9aaa1c2371147669e4ace0446dd9758", "short_code": "ob", "title": "BAS Twin-Otter flight 218 MAC flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAS Masin Twin-Otter aircraft.", "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the British Antarctic Survey (BAS) Masin Twin-Otter aircraft collected for the Microphysics of Antarctic Clouds (MAC) project." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 72812, 72814, 72815, 72816, 72817, 72818, 72820, 72813, 72821 ], "onlineresource_set": [], "project_set": [ 19273 ] }, { "ob_id": 19563, "uuid": "93fdb48b713b4dbc93a28d695771312d", "short_code": "coll", "title": "NERC Project: Are tropical uplands regional hotspots for methane and nitrous oxide?: in-situ ground based atmospheric flux measurements and model output", "abstract": "'Are tropical uplands regional hotspots for methane and nitrous oxide?' was a NERC (Natural Environment Research Council) funded project from 2010-2015 with the following grant references NE/H007849/1, NE/H006753/1 and NE/H006583/2.\r\n\r\nThis dataset collection contains in-situ ground based soil-atmosphere flux and soil condition measurements from 4 different ecosystems located in the Peruvian Andes over ~2.5 years between 2010-2013. The ecosystems included upper montane forest (Wayqecha), lower montane forest (San Pedro), premontane forest (Villa Carmen) and grassland sites. \r\n\r\nAt present, data are only available for 3 ecosystems; Wayqecha, San Pedro and Villa Carman. However, the grassland dataset will follow shortly along with some model output.", "keywords": "methane, nitrous oxide, Andes, Peru, tropical ecosystems, rainforest, greenhouse gases", "publicationState": "published", "dataPublishedTime": "2016-07-12T09:50:21", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 2 ], "discoveryKeywords": [ { "ob_id": 1142, "name": "NDGO0005" }, { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 26608, "uuid": "3d7412e881f74846b9f2e120e5083118", "short_code": "ob", "title": "Ground-based measurements of carbon dioxide, methane and nitrous oxide taken from Tres Cruces (montane grassland) in the Peruvian Andes (2010-2013)", "abstract": "The dataset contains concentrations of carbon dioxide, methane and nitrous oxide which were collected in discrete air samples between 5th January 2011 and 4th July 2013 by the University of Aberdeen Thermo TRACE Gas Chromatograph Ultra at Tres Cruces, a montane grassland ecosystem ground site, in the Peruvian Andes.\r\n\r\nData were collected for the NERC project: 'Are tropical uplands regional hotspots for methane and nitrous oxide?' (NERC grant awards: NE/H007849/1, NE/H006753/1 and NE/H006583/2)." }, { "ob_id": 19564, "uuid": "d323783d14b44400b5a7fb156023a65e", "short_code": "ob", "title": "Ground based measurements of carbon dioxide, methane and nitrous oxide taken from Wayqecha (upper montane forest) in the Peruvian Andes (2010-2013)", "abstract": "The dataset contains concentrations of carbon dioxide, methane and nitrous oxide which were collected in discrete air samples between 17th December 2010 and 5th July 2013 by the University of St Andrews Thermo TRACE Gas Chromatograph Ultra at Wayqecha, an upper montane forest ecosystem ground site, in the Peruvian Andes. \r\n\r\nData were collected tor the NERC project: 'Are tropical uplands regional hotspots for methane and nitrous oxide?' (NERC grant awards: NE/H007849/1, NE/H006753/1 and NE/H006583/2). \r\n\r\n" }, { "ob_id": 19607, "uuid": "0c22d4b33d0b4247b3d31112742a8206", "short_code": "ob", "title": "Ground based measurements of carbon dioxide, methane and nitrous oxide taken from San Pedro (lower montane forest) in the Peruvian Andes (2010-2013)", "abstract": "The dataset contains concentrations of carbon dioxide, methane and nitrous oxide which were collected in discrete air samples between 15th December 2010 and 6th July 2013 by the University of St Andrews Thermo TRACE Gas Chromatograph Ultra at San Pedro, a lower montane forest ecosystem ground site, in the Peruvian Andes. \r\n\r\nData were collected for the NERC project: 'Are tropical uplands regional hotspots for methane and nitrous oxide?' (NERC grant awards: NE/H007849/1, NE/H006753/1 and NE/H006583/2). \r\n" }, { "ob_id": 26600, "uuid": "39ff3d8b84b341b8af6be78aaaaa5cdb", "short_code": "ob", "title": "Ground based measurements of carbon dioxide and methane taken from Tres Cruces (montane grasslands) in the Peruvian Andes (seasonal campaigns)", "abstract": "The dataset contains concentrations of carbon dioxide and methane which were collected in discrete air samples during intensive seasonal campaigns in November 2011 and August 2012 by the University of St Andrews Thermo TRACE Gas Chromatograph Ultra at Tres Cruces, a montane grassland ecosystem ground site, in the Peruvian Andes.\r\n\r\nData were collected for the NERC project: 'Are tropical uplands regional hotspots for methane and nitrous oxide?' (NERC grant awards: NE/H007849/1, NE/H006753/1 and NE/H006583/2)." }, { "ob_id": 19608, "uuid": "5e532731b36246009dcafdff25e396f8", "short_code": "ob", "title": "Ground based measurements of carbon dioxide, methane and nitrous oxide taken from Villa Carmen (premontane forest) in the Peruvian Andes (2011-2013)", "abstract": "The dataset contains concentrations of carbon dioxide, methane and nitrous oxide which were collected in discrete air samples between 23rd July 2011 and 8th July 2013 by the University of St Andrews Thermo TRACE Gas Chromatograph Ultra at Villa Carmen, a premontane forest ecosystem ground site, in the Peruvian Andes. \r\n\r\nData were collected for the NERC project: 'Are tropical uplands regional hotspots for methane and nitrous oxide?' (NERC grant awards: NE/H007849/1, NE/H006753/1 and NE/H006583/2). \r\n\r\n\r\n\r\n" } ], "identifier_set": [ 8971 ], "responsiblepartyinfo_set": [ 74238, 74237, 74235, 74403, 74450, 105432, 105457, 105380, 74236, 74400, 74401, 74402, 74234 ], "onlineresource_set": [ 15407 ], "project_set": [ 19561 ] }, { "ob_id": 19727, "uuid": "68c71a0163c44270b2ca0e0f2e0d90f4", "short_code": "coll", "title": "AATSR Multimission land and sea surface data, version 3", "abstract": "Advanced Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR). \r\n\r\nThis dataset collection contains version 3 AATSR Multimission land and sea surface data. These data are identical to version 2.1.\r\n\r\nThe instrument uses thermal channels at 3.7, 10.8, and 12 microns wavelength; and reflected visible/near infra-red channels at 0.555, 0.659, 0.865, and 1.61 microns wavelength. Level 1b products contain gridded brightness temperature and reflectance. Level 2 products contain land and sea-surface temperature, and NDVI at a range of spatial resolutions. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files. The data were acquired by the European Space Agency's (ESA) Envisat satellite, and the NERC Earth Observation Data Centre (NEODC) mirrors the data for UK users.", "keywords": "AATSR, temperature, reflectance, satellite ", "publicationState": "published", "dataPublishedTime": "2014-07-04T11:11:44", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 114 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 8147, "uuid": "5c433d03503b6afea005488b582c72fd", "short_code": "ob", "title": "AATSR: L2P Product (AATSR L2P) sea surface temperature values, v2.1", "abstract": "Advanced Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR). \r\n\r\nThis dataset contains the Advanced Along-Track Scanning Radiometer (AATSR) on ESA ENVISAT satellite L2P product. These data are full resolution data with dual-view Sea Surface Temperature (SST) values. \r\n\r\nVersion 3.0 of this dataset is produced with the ARC L2P processor version 1.2, which replaces the ARC SST processor. The processor applies its own algorithm to generate SST data from the Level 1B Data. This method differs from that used to produce the Gridded Surface Temperature (GST) products. This product also includes the ATSR Saharan Dust index (ASDI) and the clear-sky probability estimated by the ARC cloud detection algorithm." }, { "ob_id": 8125, "uuid": "ebb0efd3bf06d7d0472503729201e624", "short_code": "ob", "title": "AATSR: Gridded Surface Temperature (GST) product (ATS_NR__2P), v2.1", "abstract": "Advanced Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Advanced Along-Track Scanning Radiometer (AATSR) on ESA ENVISAT satellite Gridded Surface Temperature (GST) product. These data are the Level 2 full spatial resolution (approximately 1 km by 1 km) geophysical product derived from Level 1B product and auxiliary data. \r\n\r\nThe contents of the pixel fields, which are a mixture of Top of Atmosphere (TOA) and surface brightness temperature/radiance, are switch-able depending on the surface type. The third reprocessing was done to implement updated algorithms, processors (the IPF Processor 6.05 from the IPF Processor 6.01), and auxiliary files." }, { "ob_id": 8089, "uuid": "008ad14a19d37cc23286a38ed7627522", "short_code": "ob", "title": "AATSR: Three Band Colour Composite Browse Product (ATS_AST_BP), v2.1", "abstract": "Advanced Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Advanced Along-Track Scanning Radiometer (AATSR) on ESA ENVISAT satellite Three Band Colour Composite Browse Product. These data are 3 band colour composite, quick-look images at coarse resolution. \r\n\r\nThis product has been derived from the Level 1B product and auxiliary data. The three bands are selected to best show the feature of the image, and it could vary between daylight time and night time. It also includes geolocation grid. The third reprocessing was done to implement updated algorithms, processors (the IPF Processor 6.05 from the IPF Processor 6.01), and auxiliary files." }, { "ob_id": 8161, "uuid": "931156948d9e417e1a271974d133f5b7", "short_code": "ob", "title": "AATSR: Level 2 University of Leicester Land Surface Temperature (LST) product (UOL_LST_2P), v2.1", "abstract": "Land Surface Temperature (LST) Level 2 data products (UOL_LST_2P) from the Advanced Along Track Scanning Radiometer (AATSR) produced by the University of Leicester. \r\n\r\nThe data consists of a Level 2 1km resolution AATSR-orbit based product at a pre-defined set of spatial and temporal resolutions. The product provide AATSR-derived land surface temperature data and its associated uncertainty, as wall as additional auxiliary information.\r\n\r\nLevel 2 products were produced under contract to the European Space Agency and constitute part of the official (A)ATSR multimission product from version 3 of that dataset. Funding from NERC and the National Centre for Earth Observation (NCEO) also helped in the development of this product and enabled the production of the derived Level 3 products. Both products are NetCDF formatted. For further information on the formats of each of the products please see their product user guides." }, { "ob_id": 8156, "uuid": "84b0200944d5eca9b57aa6370429f23c", "short_code": "ob", "title": "AATSR: Level 3 University of Leicester Land Surface Temperature (LST) product (UOL_LST_3P), v2.1", "abstract": "Land Surface Temperature (LST) Level 3 gridded data products (UOL_LST_3P) from the Advanced Along Track Scanning Radiometer (AATSR) produced by the University of Leicester. \r\n\r\nThe data consists of global gridded Level 3 product at a pre-defined set of spatial and temporal resolutions. The product provide AATSR-derived land surface temperature data and its associated uncertainty, as wall as additional auxiliary information.\r\n\r\nThe gridded level 3 product has been derived from the 1km Level-2 AATSR Version 3 LST product (UOL_LST_2P). The Level 3 gridded product was produced under funding from the National Centre for Earth Observation (NCEO)." }, { "ob_id": 8142, "uuid": "fcf76f049fc4ef9e263aafedc76259d5", "short_code": "ob", "title": "AATSR: L3U Product (AATSR L3U) sea surface temperature values, v2.1", "abstract": "Advanced Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Advanced Along-Track Scanning Radiometer (AATSR) sea surface temperature values on ESA ENVISAT satellite L3U product. These data are newly introduced product in the third reprocessing of (A)ATSR multimission data.\r\n\r\nIt is produced by the new ARC L2P processor version 1.2 that also produced the new L2P data. The L3U product is produced through averaging the L2P data onto a regular grid at 30 arcminute resolution. Hence, the L3U product is similar to the AST/METEO product." }, { "ob_id": 8074, "uuid": "514e5dfbef651f336862ae5ca0424e86", "short_code": "ob", "title": "AATSR: Sea Surface Temperature Meteo Product (ATS_MET_2P), v2.1", "abstract": "Advanced Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Advanced Along-Track Scanning Radiometer on ESA ENVISAT satellite (AATSR) Spatially Averaged Sea Surface Temperature Product for Meteo Users. These data are the Level 2 product designed for the use by meteorological offices derived from Level 2 AST product. \r\n\r\nThe product contains only the sea surface temperature with spatial resolution of 10 arc minutes. It also contains Average Brightness Temperature (ABT) fields, which includes brightness temperature and TOA sea record on the same spatial resolution. Like the AST product this product is derived from, all areas contains data, where the land pixels have empty data, and the coasts containing averages derived only from the sea pixels in the cell. The third reprocessing was done to implement the updated algorithms, processors (the IPF Processor 6.05 from the IPF Processor 6.01), and auxiliary files." }, { "ob_id": 8108, "uuid": "e05b507ee79b11cf8c12486ae9ac5404", "short_code": "ob", "title": "AATSR: Gridded Brightness Temperature/Reflectance (GBTR) product (ATS_TOA_1P), v2.1", "abstract": "Advanced Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Advanced Along-Track Scanning Radiometer on ESA ENVISAT satellite (AATSR) Gridded Brightness Temperature/Reflectance (GBTR) Product. These data are the Level 1B product that consists of Top of Atmosphere (TOA) radiance measurements and brightness temperatures at full resolution for both the nadir and forward views. \r\n\r\nThe product is calibrated for instrumental and atmospheric effects and re-sampled to a fixed grid aligned to the sub-satellite track. This product is derived from the Level 0 product and auxiliary data, and serves as the input data for all Level 2 products. The third reprocessing was done to implement the updated algorithms, processors (the IPF Processor 6.05 from the IPF Processor 6.01), and auxiliary files." }, { "ob_id": 8084, "uuid": "644af662c4b8c1d6492c1b4f9bf4bf51", "short_code": "ob", "title": "AATSR: Averaged Surface Temperature (AST) product (ATS_AR__2P), v2.1", "abstract": "Advanced Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains Advanced Along-Track Scanning Radiometer (AATSR) on ESA ENVISAT satellite Average Surface Temperature (AST) product. These data are the Level 2 spatially averaged geophysical product derived from Level 1B product and auxiliary data. \r\n\r\nThere are two types of averages provided: 10 arcminute cells and 30 arcminute cells. All cells are present regardless of the surface type. Hence, the sea (land) cells would also have the land (sea) records even though these would be empty. Cells containing coastlines will have both valid land and sea records; the land (sea) record only contains averages from the land (sea) pixels. The third reprocessing was done to implement the updated algorithms, processors (the IPF Processor 6.05 from the IPF Processor 6.01), and auxiliary files." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 74668, 74669, 74670, 74672, 74673, 74674, 74675, 74671 ], "onlineresource_set": [ 15459, 15454, 15449, 15445, 15452, 15446, 15447, 15448, 15451, 15453, 15456, 15455, 15458, 15457, 15460, 15461, 15462, 15463, 15464, 15465, 15466, 15467, 15468, 15469, 15470, 15471, 15450 ], "project_set": [ 19899 ] }, { "ob_id": 19728, "uuid": "960298f960b7487b9cc07d81aebbf04c", "short_code": "coll", "title": "ATSR-1 Multimission land and sea surface data, version 2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR). \r\n\r\nThis dataset collection contains version 2.1 ATSR Multimission land and sea surface data.\r\n\r\nThe instrument uses thermal channels at 3.7, 10.8, and 12 microns wavelength; and reflected visible/near infra-red channels at 0.555, 0.659, 0.865, and 1.61 microns wavelength. Level 1b products contain gridded brightness temperature and reflectance. Level 2 products contain land and sea-surface temperature, and NDVI at a range of spatial resolutions. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files. The data were acquired by the European Space Agency's (ESA) Envisat satellite, and the NERC Earth Observation Data Centre (NEODC) mirrors the data for UK users.", "keywords": "ATSR, temperature, reflectance, satellite ", "publicationState": "published", "dataPublishedTime": "2014-07-04T11:11:44", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 99 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 8080, "uuid": "a5e6869570913d7db9a8b79956f7f6e1", "short_code": "ob", "title": "ATSR-1: Sea Surface Temperature Meteo Product (AT1_MET_2P) v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) Spatially Averaged Sea Surface Temperature Product for Meteo Users. These data are the Level 2 product designed for the use by meteorological offices derived from Level 2 AST product.\r\n\r\nThe product contains only the sea surface temperature with spatial resolution of 10 arc minutes. It also contains the Average Brightness Temperature (ABT) fields, which includes brightness temperature and TOA sea record on the same spatial resolution. Like the AST product this product is derived from, all areas contains data, where the land pixels have empty data, and the coasts containing averages derived only from the sea pixels in the cell. The third reprocessing was done to implement the updated algorithms, processors, and auxiliary files." }, { "ob_id": 8100, "uuid": "26c2a8daa01d31297e7f6f5a52967f25", "short_code": "ob", "title": "ATSR-1: Average Surface Temperature (AST) product (AT1_AR__2P), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) Average Surface Temperature (AST) Product. These data are the Level 2 spatially averaged geophysical product derived from Level 1B product and auxiliary data. \r\n\r\nThere are two types of averages provided: 10 arcminute cells and 30 arcminute cells. All cells are present regardless of the surface type. Hence, the sea (land) cells would also have the land (sea) records even though these would be empty. Cells containing coastlines will have both valid land and sea records; the land (sea) record only contains averages from the land (sea) pixels. The third reprocessing was done to implement the updated algorithms, processors, and auxiliary files." }, { "ob_id": 8066, "uuid": "4da63d4bf3bd88eb939d6eea2cc1009d", "short_code": "ob", "title": "ATSR-1: Gridded Surface Temperature (GST) Product (AT1_NR__2P), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) Gridded Surface Temperature (GST) Product. These data are the Level 2 full spatial resolution (approximately 1 km by 1 km) geophysical product derived from Level 1B product and auxiliary data. \r\n\r\nThe contents of the pixel fields, which are a mixture of Top of Atmosphere (TOA) and surface brightness temperature/radiance, are switch-able depending on the surface type. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files." }, { "ob_id": 8152, "uuid": "f1814549468ddabed6177b1cf0d5f314", "short_code": "ob", "title": "ATSR-1: L2P Product (ATSR-1 L2P) sea surface temperature values, v2.1", "abstract": "Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) L2P sea surface temperature product. These data are full resolution data with dual-view Sea Surface Temperature (SST) values. Version 3.0 of this dataset have been produced with the ARC L2P processor version 1.2, which replaces the ARC SST processor. The processor applies its own algorithm to generate SST data from the Level 1B Data. This method differs from that used to produce the Gridded Surface Temperature (GST) products. This product also includes the ATSR Saharan Dust index (ASDI) and the clear-sky probability estimated by the ARC cloud detection algorithm." }, { "ob_id": 8060, "uuid": "9a41a2e3e0a9e52f24a8635d47cac381", "short_code": "ob", "title": "ATSR-1: Gridded Brightness Temperature/Reflectance (GBTR) product (AT1_TOA_1P), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) Gridded Brightness Temperature/Reflectance (GBTR) Product. These data are the Level 1B product that consists of Top of Atmosphere (TOA) radiance measurements and brightness temperatures at full resolution for both the nadir and forward views. \r\n\r\nThe product was calibrated for instrumental and atmospheric effects and re-sampled to a fixed grid aligned to the sub-satellite track. This product were derived from the Level 0 product and auxiliary data, and serves as the input data for all Level 2 products. The third reprocessing was done to implement the updated algorithms, processors, and auxiliary files." }, { "ob_id": 19744, "uuid": "289126a92b7a4b8a9ac69714263c1c1d", "short_code": "ob", "title": "ATSR-1: Multimission land and sea surface removal data, v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains version 2.1 ATSR Multimission land and sea surface removal data. These data were taken during calibration phase." }, { "ob_id": 8070, "uuid": "29645585678b0eedfdbcf568778b31b2", "short_code": "ob", "title": "ATSR-1: Three Band Colour Composite Browse Product (AT1_AST_BP) v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) Browse Product. These data are 3 band colour composite, quick-look images at coarse resolution. The browse product for the ATSR-1 and the ATSR-2 missions were introduced during the third reprocessing of data products. This product was derived from the Level 1B product and auxiliary data." }, { "ob_id": 8138, "uuid": "60e4d870ecc64359f804d1aee7ba373c", "short_code": "ob", "title": "ATSR-1: L3U Product (ATSR-1 L3U) sea surface temperature values, v2.1", "abstract": "Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) L3U product. These data were introduced product in the third reprocessing of (A)ATSR multimission data. These data were produced by the new ARC L2P processor version 1.2 that also produced the new L2P data. The L3U product was produced through averaging the L2P data onto a regular grid at 30 arcminute resolution. Hence, the L3U product is similar to the AST/METEO product." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 74676, 74677, 74678, 74680, 74681, 74682, 74683, 74679 ], "onlineresource_set": [ 15490, 15479, 15480, 15495, 15481, 15472, 15491, 15473, 15482, 15474, 15475, 15476, 15483, 15477, 15478, 15484, 15492, 15485, 15486, 15487, 15488, 15489, 15496, 15497, 15493, 15494, 15498 ], "project_set": [ 19905 ] }, { "ob_id": 19729, "uuid": "07caa9a158294700afe55166160b5139", "short_code": "coll", "title": "ATSR-1 Multimission land and sea surface data, version 3", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR). \r\n\r\nThis dataset collection contains version 3 ATSR Multimission land and sea surface data. These data are identical to version 2.1.\r\n\r\nThe instrument uses thermal channels at 3.7, 10.8, and 12 microns wavelength; and reflected visible/near infra-red channels at 0.555, 0.659, 0.865, and 1.61 microns wavelength. Level 1b products contain gridded brightness temperature and reflectance. Level 2 products contain land and sea-surface temperature, and NDVI at a range of spatial resolutions. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files. The data were acquired by the European Space Agency's (ESA) Envisat satellite, and the NERC Earth Observation Data Centre (NEODC) mirrors the data for UK users.", "keywords": "AATSR, temperature, reflectance, satellite ", "publicationState": "published", "dataPublishedTime": "2014-07-04T11:11:44", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 99 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 8080, "uuid": "a5e6869570913d7db9a8b79956f7f6e1", "short_code": "ob", "title": "ATSR-1: Sea Surface Temperature Meteo Product (AT1_MET_2P) v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) Spatially Averaged Sea Surface Temperature Product for Meteo Users. These data are the Level 2 product designed for the use by meteorological offices derived from Level 2 AST product.\r\n\r\nThe product contains only the sea surface temperature with spatial resolution of 10 arc minutes. It also contains the Average Brightness Temperature (ABT) fields, which includes brightness temperature and TOA sea record on the same spatial resolution. Like the AST product this product is derived from, all areas contains data, where the land pixels have empty data, and the coasts containing averages derived only from the sea pixels in the cell. The third reprocessing was done to implement the updated algorithms, processors, and auxiliary files." }, { "ob_id": 8100, "uuid": "26c2a8daa01d31297e7f6f5a52967f25", "short_code": "ob", "title": "ATSR-1: Average Surface Temperature (AST) product (AT1_AR__2P), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) Average Surface Temperature (AST) Product. These data are the Level 2 spatially averaged geophysical product derived from Level 1B product and auxiliary data. \r\n\r\nThere are two types of averages provided: 10 arcminute cells and 30 arcminute cells. All cells are present regardless of the surface type. Hence, the sea (land) cells would also have the land (sea) records even though these would be empty. Cells containing coastlines will have both valid land and sea records; the land (sea) record only contains averages from the land (sea) pixels. The third reprocessing was done to implement the updated algorithms, processors, and auxiliary files." }, { "ob_id": 8066, "uuid": "4da63d4bf3bd88eb939d6eea2cc1009d", "short_code": "ob", "title": "ATSR-1: Gridded Surface Temperature (GST) Product (AT1_NR__2P), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) Gridded Surface Temperature (GST) Product. These data are the Level 2 full spatial resolution (approximately 1 km by 1 km) geophysical product derived from Level 1B product and auxiliary data. \r\n\r\nThe contents of the pixel fields, which are a mixture of Top of Atmosphere (TOA) and surface brightness temperature/radiance, are switch-able depending on the surface type. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files." }, { "ob_id": 8152, "uuid": "f1814549468ddabed6177b1cf0d5f314", "short_code": "ob", "title": "ATSR-1: L2P Product (ATSR-1 L2P) sea surface temperature values, v2.1", "abstract": "Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) L2P sea surface temperature product. These data are full resolution data with dual-view Sea Surface Temperature (SST) values. Version 3.0 of this dataset have been produced with the ARC L2P processor version 1.2, which replaces the ARC SST processor. The processor applies its own algorithm to generate SST data from the Level 1B Data. This method differs from that used to produce the Gridded Surface Temperature (GST) products. This product also includes the ATSR Saharan Dust index (ASDI) and the clear-sky probability estimated by the ARC cloud detection algorithm." }, { "ob_id": 8060, "uuid": "9a41a2e3e0a9e52f24a8635d47cac381", "short_code": "ob", "title": "ATSR-1: Gridded Brightness Temperature/Reflectance (GBTR) product (AT1_TOA_1P), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) Gridded Brightness Temperature/Reflectance (GBTR) Product. These data are the Level 1B product that consists of Top of Atmosphere (TOA) radiance measurements and brightness temperatures at full resolution for both the nadir and forward views. \r\n\r\nThe product was calibrated for instrumental and atmospheric effects and re-sampled to a fixed grid aligned to the sub-satellite track. This product were derived from the Level 0 product and auxiliary data, and serves as the input data for all Level 2 products. The third reprocessing was done to implement the updated algorithms, processors, and auxiliary files." }, { "ob_id": 19744, "uuid": "289126a92b7a4b8a9ac69714263c1c1d", "short_code": "ob", "title": "ATSR-1: Multimission land and sea surface removal data, v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains version 2.1 ATSR Multimission land and sea surface removal data. These data were taken during calibration phase." }, { "ob_id": 8070, "uuid": "29645585678b0eedfdbcf568778b31b2", "short_code": "ob", "title": "ATSR-1: Three Band Colour Composite Browse Product (AT1_AST_BP) v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) Browse Product. These data are 3 band colour composite, quick-look images at coarse resolution. The browse product for the ATSR-1 and the ATSR-2 missions were introduced during the third reprocessing of data products. This product was derived from the Level 1B product and auxiliary data." }, { "ob_id": 8138, "uuid": "60e4d870ecc64359f804d1aee7ba373c", "short_code": "ob", "title": "ATSR-1: L3U Product (ATSR-1 L3U) sea surface temperature values, v2.1", "abstract": "Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-1 satellite (ATSR-1) L3U product. These data were introduced product in the third reprocessing of (A)ATSR multimission data. These data were produced by the new ARC L2P processor version 1.2 that also produced the new L2P data. The L3U product was produced through averaging the L2P data onto a regular grid at 30 arcminute resolution. Hence, the L3U product is similar to the AST/METEO product." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 74684, 74685, 74686, 74688, 74689, 74690, 74691, 74687 ], "onlineresource_set": [ 15510, 15500, 15502, 15501, 15505, 15506, 15507, 15508, 15509, 15511, 15512, 15513, 15514, 15515, 15516, 15517, 15518, 15519, 15520, 15521, 15522, 15523, 15524, 15525, 15503, 15504, 15499 ], "project_set": [ 19905 ] }, { "ob_id": 19730, "uuid": "ec976af94c3340b280c826252f4be842", "short_code": "coll", "title": "ATSR-2 Multimission land and sea surface product, version 2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR). \r\n\r\nThis dataset collection contains version 2.1 ATSR2 Multimission land and sea surface data.\r\n\r\nThe instrument uses thermal channels at 3.7, 10.8, and 12 microns wavelength; and reflected visible/near infra-red channels at 0.555, 0.659, 0.865, and 1.61 microns wavelength. Level 1b products contain gridded brightness temperature and reflectance. Level 2 products contain land and sea-surface temperature, and NDVI at a range of spatial resolutions. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files. The data were acquired by the European Space Agency's (ESA) Envisat satellite, and the NERC Earth Observation Data Centre (NEODC) mirrors the data for UK users.", "keywords": "AATSR, temperature, reflectance, satellite ", "publicationState": "published", "dataPublishedTime": "2014-07-04T11:11:44", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 99 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 8094, "uuid": "9347586615e04edf3f6d3b5f9b98b729", "short_code": "ob", "title": "ATSR-2: Average Surface Temperature (AST) Product (AT2_AR__2P), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) Average Surface Temperature (AST) Product. These data are the Level 2 spatially averaged geophysical product derived from Level 1B product and auxiliary data.\r\n\r\nThere are two types of averages provided: 10 arcminute cells and 30 arcminute cells. All cells are present regardless of the surface type. Hence, the sea (land) cells would also have the land (sea) records even though these would be empty. Cells containing coastlines will have both valid land and sea records; the land (sea) record only contains averages from the land (sea) pixels. The third reprocessing was done to implement the updated algorithms, processors, and auxiliary files." }, { "ob_id": 8104, "uuid": "6ee6eb0a4706d5020bcc1c441cd89f8f", "short_code": "ob", "title": "ATSR-2: Sea Surface Temperature Meteo Product (AT2_MET_2P), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) Spatially Averaged Sea Surface Temperature Product for Meteo Users. These data are the Level 2 product designed for the use by meteorological offices derived from Level 2 AST product. The product contains only the sea surface temperature with spatial resolution of 10 arc minutes. It also contains the Average Brightness Temperature (ABT) fields, which includes brightness temperature and TOA sea record on the same spatial resolution. Like the AST product this product is derived from, all areas contains data, where the land pixels have empty data, and the coasts containing averages derived only from the sea pixels in the cell. The third reprocessing was done to implement the updated algorithms, processors, and auxiliary files." }, { "ob_id": 8113, "uuid": "36473df8dd5b82309c06539a57210698", "short_code": "ob", "title": "ATSR-2: Gridded Surface Temperature (GST) Product (AT2_NR__2P), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) Gridded Surface Temperature (GST) Product. These data are the Level 2 full spatial resolution (approximately 1 km by 1 km) geophysical product derived from Level 1B product and auxiliary data. The contents of the pixel fields, which are a mixture of Top of Atmosphere (TOA) and surface brightness temperature/radiance, are switch-able depending on the surface type. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files." }, { "ob_id": 8121, "uuid": "3c3336df1dbad3ff98962734db843c2d", "short_code": "ob", "title": "ATSR-2: Gridded Brightness Temperature/Reflectance (GBTR) Product (AT2_TOA_1P), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) Gridded Brightness Temperature/Reflectance (GBTR) Product. These data are the Level 1B product that consists of Top of Atmosphere (TOA) radiance measurements and brightness temperatures at full resolution for both the nadir and forward views. The product was calibrated for instrumental and atmospheric effects and re-sampled to a fixed grid aligned to the sub-satellite track. This product were derived from the Level 0 product and auxiliary data, and serves as the input data for all Level 2 products. The third reprocessing was done to implement the updated algorithms, processors, and auxiliary files." }, { "ob_id": 19746, "uuid": "320fec47a9184273a08d268137036e8d", "short_code": "ob", "title": "ATSR-2: Multimission land and sea surface removal data, v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains version 2.1 ATSR-2 Multimission land and sea surface removal data. These data were taken during calibration phase.\r\n\r\n" }, { "ob_id": 8117, "uuid": "e91ec49fa67680b7fb0e090a2761db63", "short_code": "ob", "title": "ATSR-2: Three Band Colour Composite Browse Product (AT2_AST_BP), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThe Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) Browse Product. These data are 3 band colour composite, quick-look images at coarse resolution. The browse product for the ATSR-1 and the ATSR-2 missions were introduced during the third reprocessing of data products. This product was derived from the Level 1B product and auxiliary data." }, { "ob_id": 8134, "uuid": "97e5db7e92ded2f321405041a7d5513f", "short_code": "ob", "title": "ATSR-2: L2P Product (ATSR-2 L2P) sea surface temperature values, v2.1", "abstract": "Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) L2P product is a full resolution data with dual-view Sea Surface Temperature (SST) values. \r\n\r\nVersion 3.0 of this dataset were produced with the ARC L2P processor version 1.2, which replaces the ARC SST processor. The processor applies its own algorithm to generate SST data from the Level 1B Data. This method differs from that used to produce the Gridded Surface Temperature (GST) products. This product also includes the ATSR Saharan Dust index (ASDI) and the clear-sky probability estimated by the ARC cloud detection algorithm." }, { "ob_id": 8130, "uuid": "669b8fb96b189db46ddcdc7dd7f1cfd7", "short_code": "ob", "title": "ATSR-2: L3U Product (ATSR-2 L3U) sea surface temperature values, v2.1", "abstract": "Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) L3U product. These data were introduced product in the third reprocessing of (A)ATSR multimission data. These data were produced by the new ARC L2P processor version 1.2 that also produced the new L2P data. The L3U product was produced through averaging the L2P data onto a regular grid at 30 arcminute resolution. Hence, the L3U product is similar to the AST/METEO product." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 74692, 74693, 74694, 74696, 74697, 74698, 74699, 74695 ], "onlineresource_set": [ 15531, 15551, 15526, 15536, 15527, 15528, 15544, 15529, 15537, 15530, 15532, 15538, 15533, 15534, 15535, 15539, 15545, 15540, 15541, 15542, 15546, 15543, 15550, 15549, 15548, 15547, 15552 ], "project_set": [ 19910 ] }, { "ob_id": 19731, "uuid": "3b1c1cf972b24db3b26dfd592f751a77", "short_code": "coll", "title": "ATSR-2 Multimission land and sea surface data, version 3", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR). \r\n\r\nThis dataset collection contains version 3 ATSR2 Multimission land and sea surface data. These data are identical to version 2.1.\r\n\r\nThe instrument uses thermal channels at 3.7, 10.8, and 12 microns wavelength; and reflected visible/near infra-red channels at 0.555, 0.659, 0.865, and 1.61 microns wavelength. Level 1b products contain gridded brightness temperature and reflectance. Level 2 products contain land and sea-surface temperature, and NDVI at a range of spatial resolutions. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files. The data were acquired by the European Space Agency's (ESA) Envisat satellite, and the NERC Earth Observation Data Centre (NEODC) mirrors the data for UK users.", "keywords": "AATSR, temperature, reflectance, satellite ", "publicationState": "published", "dataPublishedTime": "2014-07-04T11:11:44", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 99 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 8094, "uuid": "9347586615e04edf3f6d3b5f9b98b729", "short_code": "ob", "title": "ATSR-2: Average Surface Temperature (AST) Product (AT2_AR__2P), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) Average Surface Temperature (AST) Product. These data are the Level 2 spatially averaged geophysical product derived from Level 1B product and auxiliary data.\r\n\r\nThere are two types of averages provided: 10 arcminute cells and 30 arcminute cells. All cells are present regardless of the surface type. Hence, the sea (land) cells would also have the land (sea) records even though these would be empty. Cells containing coastlines will have both valid land and sea records; the land (sea) record only contains averages from the land (sea) pixels. The third reprocessing was done to implement the updated algorithms, processors, and auxiliary files." }, { "ob_id": 8104, "uuid": "6ee6eb0a4706d5020bcc1c441cd89f8f", "short_code": "ob", "title": "ATSR-2: Sea Surface Temperature Meteo Product (AT2_MET_2P), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) Spatially Averaged Sea Surface Temperature Product for Meteo Users. These data are the Level 2 product designed for the use by meteorological offices derived from Level 2 AST product. The product contains only the sea surface temperature with spatial resolution of 10 arc minutes. It also contains the Average Brightness Temperature (ABT) fields, which includes brightness temperature and TOA sea record on the same spatial resolution. Like the AST product this product is derived from, all areas contains data, where the land pixels have empty data, and the coasts containing averages derived only from the sea pixels in the cell. The third reprocessing was done to implement the updated algorithms, processors, and auxiliary files." }, { "ob_id": 8113, "uuid": "36473df8dd5b82309c06539a57210698", "short_code": "ob", "title": "ATSR-2: Gridded Surface Temperature (GST) Product (AT2_NR__2P), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) Gridded Surface Temperature (GST) Product. These data are the Level 2 full spatial resolution (approximately 1 km by 1 km) geophysical product derived from Level 1B product and auxiliary data. The contents of the pixel fields, which are a mixture of Top of Atmosphere (TOA) and surface brightness temperature/radiance, are switch-able depending on the surface type. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files." }, { "ob_id": 8121, "uuid": "3c3336df1dbad3ff98962734db843c2d", "short_code": "ob", "title": "ATSR-2: Gridded Brightness Temperature/Reflectance (GBTR) Product (AT2_TOA_1P), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) Gridded Brightness Temperature/Reflectance (GBTR) Product. These data are the Level 1B product that consists of Top of Atmosphere (TOA) radiance measurements and brightness temperatures at full resolution for both the nadir and forward views. The product was calibrated for instrumental and atmospheric effects and re-sampled to a fixed grid aligned to the sub-satellite track. This product were derived from the Level 0 product and auxiliary data, and serves as the input data for all Level 2 products. The third reprocessing was done to implement the updated algorithms, processors, and auxiliary files." }, { "ob_id": 19746, "uuid": "320fec47a9184273a08d268137036e8d", "short_code": "ob", "title": "ATSR-2: Multimission land and sea surface removal data, v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains version 2.1 ATSR-2 Multimission land and sea surface removal data. These data were taken during calibration phase.\r\n\r\n" }, { "ob_id": 8117, "uuid": "e91ec49fa67680b7fb0e090a2761db63", "short_code": "ob", "title": "ATSR-2: Three Band Colour Composite Browse Product (AT2_AST_BP), v2.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThe Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) Browse Product. These data are 3 band colour composite, quick-look images at coarse resolution. The browse product for the ATSR-1 and the ATSR-2 missions were introduced during the third reprocessing of data products. This product was derived from the Level 1B product and auxiliary data." }, { "ob_id": 8134, "uuid": "97e5db7e92ded2f321405041a7d5513f", "short_code": "ob", "title": "ATSR-2: L2P Product (ATSR-2 L2P) sea surface temperature values, v2.1", "abstract": "Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) L2P product is a full resolution data with dual-view Sea Surface Temperature (SST) values. \r\n\r\nVersion 3.0 of this dataset were produced with the ARC L2P processor version 1.2, which replaces the ARC SST processor. The processor applies its own algorithm to generate SST data from the Level 1B Data. This method differs from that used to produce the Gridded Surface Temperature (GST) products. This product also includes the ATSR Saharan Dust index (ASDI) and the clear-sky probability estimated by the ARC cloud detection algorithm." }, { "ob_id": 8130, "uuid": "669b8fb96b189db46ddcdc7dd7f1cfd7", "short_code": "ob", "title": "ATSR-2: L3U Product (ATSR-2 L3U) sea surface temperature values, v2.1", "abstract": "Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains the Along-Track Scanning Radiometer on ESA ERS-2 satellite (ATSR-2) L3U product. These data were introduced product in the third reprocessing of (A)ATSR multimission data. These data were produced by the new ARC L2P processor version 1.2 that also produced the new L2P data. The L3U product was produced through averaging the L2P data onto a regular grid at 30 arcminute resolution. Hence, the L3U product is similar to the AST/METEO product." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 74700, 74701, 74702, 74704, 74705, 74706, 74707, 74703 ], "onlineresource_set": [ 15554, 15555, 15556, 15572, 15559, 15560, 15573, 15561, 15562, 15563, 15574, 15564, 15565, 15566, 15575, 15567, 15568, 15569, 15576, 15570, 15571, 15577, 15578, 15579, 15553, 15557, 15558 ], "project_set": [ 19910 ] }, { "ob_id": 19734, "uuid": "9a5ae4243c6c47efbd626135dfbe36a6", "short_code": "coll", "title": "AATSR Multimission land and sea surface data, version 1.1", "abstract": "Advanced Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset collection contains version 1.1 AATSR Multimission land and sea surface data.\r\n\r\nThe instrument uses thermal channels at 3.7, 10.8, and 12 microns wavelength; and reflected visible/near infra-red channels at 0.555, 0.659, 0.865, and 1.61 microns wavelength. Level 1b products contain gridded brightness temperature and reflectance. Level 2 products contain land and sea-surface temperature, and NDVI at a range of spatial resolutions. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files. The data were acquired by the European Space Agency's (ESA) Envisat satellite, and the NERC Earth Observation Data Centre (NEODC) mirrors the data for UK users.", "keywords": "AATSR, temperature, reflectance, satellite", "publicationState": "published", "dataPublishedTime": "2007-12-10T02:43:01", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 114 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 10917, "uuid": "84898c2eeb91b9e3a9cd29ddf938665b", "short_code": "ob", "title": "AATSR: Multimission land and sea surface data, v1.1", "abstract": "Advanced Along-Track Scanning Radiometer (AATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset contains version 1.1 AATSR Multimission land and sea surface temperature data.\r\n\r\nThe instrument uses thermal channels at 3.7, 10.8, and 12 microns wavelength; and reflected visible/near infra-red channels at 0.555, 0.659, 0.865, and 1.61 microns wavelength. Level 1b products contain gridded brightness temperature and reflectance. Level 2 products contain land and sea-surface temperature, and NDVI at a range of spatial resolutions. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files. The data were acquired by the European Space Agency's (ESA) Envisat satellite, and the NERC Earth Observation Data Centre (NEODC) mirrors the data for UK users." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 74712, 74713, 74714, 74715, 74708, 74710, 74711, 74709 ], "onlineresource_set": [ 15603, 15593, 15582, 15587, 15583, 15580, 15590, 15584, 15588, 15585, 15581, 15586, 15589, 15591, 15595, 15592, 15594, 15597, 15596, 15598, 15599, 15600, 15601, 15602 ], "project_set": [ 19899 ] }, { "ob_id": 19735, "uuid": "92d4f1fbca9347cda08d06eb0df7b0c3", "short_code": "coll", "title": "ATSR-1 Multimission land and sea surface data, version 1.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset collection contains version 1.1 ATSR-1 Multimission land and sea surface data.\r\n\r\nThe instrument uses thermal channels at 3.7, 10.8, and 12 microns wavelength; and reflected visible/near infra-red channels at 0.555, 0.659, 0.865, and 1.61 microns wavelength. Level 1b products contain gridded brightness temperature and reflectance. Level 2 products contain land and sea-surface temperature, and NDVI at a range of spatial resolutions. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files. The data were acquired by the European Space Agency's (ESA) Envisat satellite, and the NERC Earth Observation Data Centre (NEODC) mirrors the data for UK users.", "keywords": "ATSR, temperature, reflectance, satellite", "publicationState": "published", "dataPublishedTime": "2007-12-10T02:43:01", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 99 ], "discoveryKeywords": [ { "ob_id": 1138, "name": "NDGO0003" } ], "member": [ { "ob_id": 10926, "uuid": "a905a0c1a6522c9b1c8221703b0986e0", "short_code": "ob", "title": "ATSR-1: Multimission land and sea surface data, v1.1", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset collection contains version 1.1 ATSR Multimission land and sea surface temperature data.\r\n\r\nThe instrument uses thermal channels at 3.7, 10.8, and 12 microns wavelength; and reflected visible/near infra-red channels at 0.555, 0.659, 0.865, and 1.61 microns wavelength. Level 1b products contain gridded brightness temperature and reflectance. Level 2 products contain land and sea-surface temperature, and NDVI at a range of spatial resolutions. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files. The data were acquired by the European Space Agency's (ESA) Envisat satellite, and the NERC Earth Observation Data Centre (NEODC) mirrors the data for UK users." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 74716, 74717, 74718, 74719, 74721, 74722, 74723, 74720 ], "onlineresource_set": [ 15604, 15620, 15606, 15607, 15608, 15621, 15609, 15610, 15611, 15622, 15612, 15613, 15614, 15615, 15616, 15617, 15624, 15618, 15619, 15625, 15627, 15605, 15626, 15623 ], "project_set": [ 19905 ] }, { "ob_id": 19736, "uuid": "a664a77781a249e38cbef6caecfeb2f4", "short_code": "coll", "title": "ATSR-1 Multimission land and sea surface data, version 2.0", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset collection contains version 2.0 ATSR-1 Multimission land and sea surface data.\r\n\r\nThe instrument uses thermal channels at 3.7, 10.8, and 12 microns wavelength; and reflected visible/near infra-red channels at 0.555, 0.659, 0.865, and 1.61 microns wavelength. Level 1b products contain gridded brightness temperature and reflectance. Level 2 products contain land and sea-surface temperature, and NDVI at a range of spatial resolutions. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files. The data were acquired by the European Space Agency's (ESA) Envisat satellite, and the NERC Earth Observation Data Centre (NEODC) mirrors the data for UK users.", "keywords": "ATSR, temperature, reflectance, satellite", "publicationState": "published", "dataPublishedTime": "2007-12-10T02:43:01", "doiPublishedTime": null, "dontHarvestFromProjects": true, "imageDetails": [ 99 ], "discoveryKeywords": [], "member": [ { "ob_id": 19742, "uuid": "7913089bdbf447188f66697cbca9da1e", "short_code": "ob", "title": "ATSR-1: Multimission land and sea surface data, v2.0", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset collection contains version 2.0 ATSR Multimission land and sea surface temperature data.\r\n\r\nThe instrument uses thermal channels at 3.7, 10.8, and 12 microns wavelength; and reflected visible/near infra-red channels at 0.555, 0.659, 0.865, and 1.61 microns wavelength. Level 1b products contain gridded brightness temperature and reflectance. Level 2 products contain land and sea-surface temperature, and NDVI at a range of spatial resolutions. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files. The data were acquired by the European Space Agency's (ESA) Envisat satellite, and the NERC Earth Observation Data Centre (NEODC) mirrors the data for UK users." } ], "identifier_set": [], "responsiblepartyinfo_set": [ 74724, 74725, 74726, 74727, 74729, 74730, 74731, 74728 ], "onlineresource_set": [ 15638, 15641, 15651, 15640, 15633, 15628, 15636, 15630, 15634, 15631, 15632, 15642, 15635, 15639, 15637, 15643, 15644, 15645, 15646, 15647, 15648, 15649, 15650, 15629 ], "project_set": [ 19905 ] } ] }