Related Observation Info List
Get a list of RelatedObservationInfo objects.
GET /api/v3/relatedobservationinfos/?format=api&offset=200
{ "count": 1153, "next": "https://api.catalogue.ceda.ac.uk/api/v3/relatedobservationinfos/?format=api&limit=100&offset=300", "previous": "https://api.catalogue.ceda.ac.uk/api/v3/relatedobservationinfos/?format=api&limit=100&offset=100", "results": [ { "ob_id": 222, "relationType": "IsNewVersionOf", "subjectObservation": { "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." }, "objectObservation": { "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": 223, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 26860, "uuid": "b177c691ce9143729e16faadbdebced8", "short_code": "ob", "title": "CRU CY 4.02: Climatic Research Unit (CRU) year-by-year variation of selected climate variables by country (CY) version 4.02 (Jan. 1901 - Dec. 2017)", "abstract": "The Climatic Research Unit (CRU) Country (CY) data version 4.02 dataset consists of ten climate variables for country averages at a monthly, seasonal and annual frequency; including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and potential evapotranspiration. This version uses the updated set of country definitions, please see the appropriate Release Notes.\r\n\r\nThis dataset was produced in 2018 by CRU at the University of East Anglia and extends the CRU CY4.01 data to include 2017. CRU CY4.02 is a full release, differing only in methodology from the existing current version 3 release, v3.26. Both are released concurrently to support comparative evaluations between these two versions, however, this will be the last release of version 3. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nSpatial averages are calculated using area-weighted means. CRU CY4.02 is derived directly from the CRU TS4.02 dataset. CRU CY version 4.02 spans the period 1901-2017 for 289 countries.\r\n\r\nTo understand the CRU CY4.02 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS4.02. It is therefore recommended that all users read the Harris et al, 2020 paper and the CRU TS4.02 release notes listed in the online documentation on this record.\r\n\r\nCRU CY data are available for download to all CEDA users." }, "objectObservation": { "ob_id": 25065, "uuid": "d4e823f0172947c5ae6e6b265656c273", "short_code": "ob", "title": "CRU CY4.01: Climatic Research Unit (CRU) year-by-year variation of selected climate variables by country (CY) version 4.01 (Jan. 1901 - Dec. 2016)", "abstract": "The Climatic Research Unit (CRU) Country (CY) data version 4.01 dataset consists of ten climate variables for country averages at a monthly, seasonal and annual frequency; including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and potential evapotranspiration. This version uses the updated set of country definitions, please see the appropriate Release Notes.\r\n\r\nThis dataset was produced in 2017 by CRU at the University of East Anglia and extends the CRU CY4.00 data to include 2016. CRU CY4.01 is a full release, differing only in methodology from the existing current version 3 release, v3.25. Both are released concurrently to support comparative evaluations between these two versions, however, this will be the last release of version 3. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nSpatial averages are calculated using area-weighted means. CRU CY4.01 is derived directly from the CRU TS4.01 dataset. CRU CY version 4.01 spans the period 1901-2016 for 289 countries.\r\n\r\nTo understand the CRU CY4.01 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS4.01. It is therefore recommended that all users read the Harris et al, 2020 paper and the CRU TS4.01 release notes listed in the online documentation on this record.\r\n\r\nCRU CY data are available for download to all CEDA users." } }, { "ob_id": 224, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 26858, "uuid": "b2f81914257c4188b181a4d8b0a46bff", "short_code": "ob", "title": "CRU TS4.02: Climatic Research Unit (CRU) Time-Series (TS) version 4.02 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2017)", "abstract": "The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.02 data are month-by-month variations in climate over the period 1901-2017, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia.\r\n\r\nThe CRU TS4.02 variables are cloud cover, diurnal temperature range, frost day frequency, potential evapotranspiration (PET), precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period January 1901 - December 2017.\r\n\r\nThe CRU TS4.02 data were produced using angular-distance weighting (ADW) interpolation. All version 3 releases used triangulation routines in IDL. Please see the release notes for full details of this version update. CRU TS4.02 is a full release, differing only in methodology from the parallel release, v3.26. Both are released concurrently to support comparative evaluations between these two versions, however, this will be the last release of version 3. \r\n\r\nThe CRU TS4.02 data are monthly gridded fields based on monthly observational data calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and NetCDF data files both contain monthly mean values for the various parameters. The NetCDF versions contain an additional integer variable, ’stn’, which provides, for each datum in the main variable, a count (between 0 and 8) of the number of stations used in that interpolation. The missing value code for 'stn' is -999.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies." }, "objectObservation": { "ob_id": 25066, "uuid": "58a8802721c94c66ae45c3baa4d814d0", "short_code": "ob", "title": "CRU TS4.01: Climatic Research Unit (CRU) Time-Series (TS) version 4.01 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2016)", "abstract": "The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.01 data are month-by-month variations in climate over the period 1901-2016, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia.\r\n\r\nThe CRU TS4.01 variables are cloud cover, diurnal temperature range, frost day frequency, potential evapotranspiration (PET), precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period January 1901 - December 2016.\r\n\r\nThe CRU TS4.01 data were produced using angular-distance weighting (ADW) interpolation. All version 3 releases used triangulation routines in IDL. Please see the release notes for full details of this version update. CRU TS4.01 is a full release, differing only in methodology from the parallel release, v3.25. Both are released concurrently to support comparative evaluations between these two versions, however, this will be the last release of version 3.\r\n\r\nThe CRU TS4.01 data are monthly gridded fields based on monthly observational data calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and NetCDF data files both contain monthly mean values for the various parameters. The NetCDF versions contain an additional integer variable, ’stn’, which provides, for each datum in the main variable, a count (between 0 and 8) of the number of stations used in that interpolation. The missing value code for 'stn' is -999.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies." } }, { "ob_id": 225, "relationType": "IsPartOf", "subjectObservation": { "ob_id": 26437, "uuid": "a39add95a8dc49709f6e984c020c8dbc", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v201901", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2017. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." }, "objectObservation": { "ob_id": 1241, "uuid": "1bb479d3b1e38c339adb9c82c15579d8", "short_code": "ob", "title": "MIDAS: UK Daily Temperature Data", "abstract": "The UK daily temperature data describe maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements are recorded by observation stations across the UK and transmitted within NCM or DLY3208 or AWSDLY messages. The data span from 1853 to present." } }, { "ob_id": 226, "relationType": "IsPartOf", "subjectObservation": { "ob_id": 26892, "uuid": "0049795739e44310a4982e26d8e26748", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v201901", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1889 to 2017. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection." }, "objectObservation": { "ob_id": 1244, "uuid": "954d743d1c07d1dd034c131935db54e0", "short_code": "ob", "title": "MIDAS: UK Daily Weather Observation Data", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations across the UK and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1880 to present." } }, { "ob_id": 227, "relationType": "IsPartOf", "subjectObservation": { "ob_id": 26894, "uuid": "7aaa582fb00246b794dc85950f1be265", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v201901", "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2017.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset." }, "objectObservation": { "ob_id": 1251, "uuid": "bbd6916225e7475514e17fdbf11141c1", "short_code": "ob", "title": "MIDAS UK Hourly Rainfall Data", "abstract": "The UK hourly rainfall data describes the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also conatins precipitation amounts, however precipitation measured over 24 hours will not be stored. The data is collected by observation stations across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW, SSER and WAHRAIN. The data spans from 1915 to present." } }, { "ob_id": 228, "relationType": "IsPartOf", "subjectObservation": { "ob_id": 26896, "uuid": "c58c1af69b9745fda4cdf487a9547185", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v201901", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2017.\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data." }, "objectObservation": { "ob_id": 1214, "uuid": "916ac4bbc46f7685ae9a5e10451bae7c", "short_code": "ob", "title": "MIDAS: UK Hourly Weather Observation Data", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations across the UK and transmitted within SYNOP, METAR, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to present.\r\n\r\nThis dataset also contains data from a selection of overseas sites:\r\nSRC_ID STATION STATUS LAST DATA\r\n1580 GUTERSLOH CLOSED 28/10/2013 13:00\r\n1582 BRUGGEN CLOSED 29/09/2001 05:00\r\n1584 LAARBRUCH CLOSED 14/05/1999 23:00\r\n1585 GIBRALTAR, NORTH FRONT OPEN 03/02/2020 09:00\r\n1588 AKROTIRI, CYPRUS OPEN 03/02/2020 09:00\r\n1603 ASCENSION ISLAND AIRFIELD OPEN 02/02/2020 21:00\r\n1605 BOTTOMS WOOD, ST HELENA OPEN 03/02/2020 09:00\r\n1608 PORT STANLEY, FALKLAND IS CLOSED 31/12/1980 23:00\r\n1609 MOUNT PLEASANT, FALKLAND IS OPEN 03/02/2020 09:00\r\n56810 MOUNT OLYMPUS OPEN 16/04/2019 09:00\r\n61737 MOUNT KENT, FALKLAND ISLANDS OPEN 03/02/2020 09:00\r\n61743 MOUNT BYRON, FALKLAND ISLANDS OPEN 03/02/2020 09:00\r\n61744 MOUNT ALICE, FALKLAND ISLANDS OPEN 02/02/2020 05:00" } }, { "ob_id": 229, "relationType": "IsPartOf", "subjectObservation": { "ob_id": 26899, "uuid": "11c15f2640f541d4847dafe9be1bb90a", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v201901", "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2017. For further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, "objectObservation": { "ob_id": 1184, "uuid": "a1f65a362c26c9fa667d98c431a1ad38", "short_code": "ob", "title": "MIDAS: UK Mean Wind Data", "abstract": "The UK mean wind data describes the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data is collected by observation stations across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to present." } }, { "ob_id": 230, "relationType": "IsPartOf", "subjectObservation": { "ob_id": 26901, "uuid": "a7ba08d073eb40a9aab5e312f371d007", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v201901", "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2017.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, "objectObservation": { "ob_id": 1225, "uuid": "8dc05f6ecc6065a5d10fc7b8829589ec", "short_code": "ob", "title": "MIDAS: UK Soil Temperature Data", "abstract": "The UK soil temperature data describes daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements are recorded by observation stations across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to present." } }, { "ob_id": 231, "relationType": "IsNewVersionOf", "subjectObservation": { "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." }, "objectObservation": { "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": 232, "relationType": "IsNewVersionOf", "subjectObservation": { "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)" }, "objectObservation": { "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": 233, "relationType": "IsNewVersionOf", "subjectObservation": { "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." }, "objectObservation": { "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": 234, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27092, "uuid": "8d4360b5c6cd48eb967286da31b33567", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE Product, Version 04.4", "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. \r\n\r\nThe v04.4 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 2018-06-30 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" }, "objectObservation": { "ob_id": 26234, "uuid": "f77cbcfbb6214448aebaa2119d829692", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Active' Product, Version 04.2", "abstract": "The Soil Moisture CCI 'Active' dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) CCI project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. 'Passive' and 'Combined' products have also been created. The 'Passive' product is a fusion of radiometer data acquired by the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2, and SMOS satellite instruments. The 'Combined Product' is then a blended product based on the former two data sets.\r\n\r\nThe v04.2 Active product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2016-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). 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": 235, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27108, "uuid": "bac3632d641642988c4abf55c587eed0", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE Product, Version 04.4", "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 merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v04.4 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 2018-06-30. 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" }, "objectObservation": { "ob_id": 26239, "uuid": "a4f9546935a644d3b3260b7f6a0a183f", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Passive' Product, Version 04.2", "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 v04.2 Passive product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). 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": 236, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27110, "uuid": "a341b3dcb0d8416498acc70dd14faa6e", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED Product, Version 04.4", "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 directly merging Level 2 scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. \r\n\r\nThe v04.4 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 2018-06-30. 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" }, "objectObservation": { "ob_id": 26242, "uuid": "0869e3b34fa4465a911e2588396ff1ec", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): 'Combined' Product, Version 04.2", "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 satellite instruments. \r\n\r\nThe v04.2 Combined product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2016-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. 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": 237, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27113, "uuid": "dff5410043ee4d2094cdf3b9b5284a63", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the ACTIVE, PASSIVE and COMBINED products, Version 04.4", "abstract": "These ancillary datasets were used in the production of the ACTIVE, PASSIVE and COMBINED soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v04.4 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" }, "objectObservation": { "ob_id": 26247, "uuid": "55bff4add65d489e86c195edbae8f970", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 04.2", "abstract": "These ancillary datasets were used in the production of the \"Active\", \"Passive\" and \"Combined\" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v04.2 Soil Moisture CCI data.\r\n\r\nThe \"Active\" \"Passive\" and \"Combined\" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" } }, { "ob_id": 238, "relationType": "IsPartOf", "subjectObservation": { "ob_id": 27164, "uuid": "1e040656ae0a4646acafbef6144b10f2", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v201901", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2017.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, "objectObservation": { "ob_id": 1234, "uuid": "b4c028814a666a651f52f2b37a97c7c7", "short_code": "ob", "title": "MIDAS: Global Radiation Observations", "abstract": "The global radiation observation data contain hourly and daily radiation amounts, including those no longer being reported. The measurements of global solar irradiation amount, diffuse solar irradiation amount, direct irradiation amount, irradiation balance amount, and global horizontal illumination are recorded by observation stations worldwide and transmitted within SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data span from 1947 to present." } }, { "ob_id": 239, "relationType": "IsVariantFormOf", "subjectObservation": { "ob_id": 26438, "uuid": "ec54d5e5288a4ebb8c7ad2a1ef6aec42", "short_code": "ob", "title": "MIDAS Open: UK daily rainfall data, v201901", "abstract": "The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2017. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection." }, "objectObservation": { "ob_id": 1195, "uuid": "c732716511d3442f05cdeccbe99b8f90", "short_code": "ob", "title": "MIDAS: UK Daily Rainfall Data", "abstract": "The UK daily rainfall data describe the rainfall accumulation and precipitation amount over a 24 hour period. The data are collected by observation stations across the UK and transmitted within the following message types: WADRAIN, NCM, AWSDLY, DLY3208, SSER and WAMRAIN. The data spans from 1853 to present." } }, { "ob_id": 240, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 26437, "uuid": "a39add95a8dc49709f6e984c020c8dbc", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v201901", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2017. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." }, "objectObservation": { "ob_id": 26901, "uuid": "a7ba08d073eb40a9aab5e312f371d007", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v201901", "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2017.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." } }, { "ob_id": 241, "relationType": "IsSupplementTo", "subjectObservation": { "ob_id": 26437, "uuid": "a39add95a8dc49709f6e984c020c8dbc", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v201901", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2017. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." }, "objectObservation": { "ob_id": 26901, "uuid": "a7ba08d073eb40a9aab5e312f371d007", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v201901", "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2017.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." } }, { "ob_id": 242, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 20094, "uuid": "b2670fb9d6e14733b303865c85c2065d", "short_code": "ob", "title": "EUSTACE / E-OBS: Gridded European surface air temperature based on homogenised land station records since 1950", "abstract": "This dataset consists of an infilled analysis of European surface air temperature which has been based on homogenised meteorological land station records since 1950. The original homogenised station records are also available as a separate dataset. This dataset is a version of the ECA&D (European Climate Assessment & Dataset) E-OBS dataset, produced with funding from the EU Horizon2020 EUSTACE (EU Surface Temperature for All Corners of Earth) project and contract C3S_311a_Lot4 with the Copernicus Climate Change Service. \r\n\r\nThe data is available directly from the ECA&D website and is referenced here to form part of the EUSTACE collection of data. The EUSTACE version of the product is E-OBSv19.0eHOM and future versions of the gridded dataset using homogenised temperature data will be produced operationally from E-OBSv20.0e onward. \r\n\r\nData is available for non-commercial purposes under the ECA&D terms and conditions (see https://www.ecad.eu//documents/ECAD_datapolicy.pdf).\r\n\r\nThe EU EUSTACE project has received funding by the European Union's Horizon 2020 research and innovation programme under grant agreement no 640171 and contract C3S_311a_Lot4 with the Copernicus Climate Change Service." }, "objectObservation": { "ob_id": 20092, "uuid": "81784e3642bd465aa69c7fd40ffe1b1b", "short_code": "ob", "title": "EUSTACE / ECA&D: European land station daily air temperature measurements, homogenised", "abstract": "This dataset consists of homogenised time series of daily temperature observations for meteorological stations throughout Europe and the Mediterranean. The version of the dataset described here is a homogenised version of the ECA&D (European Climate Assessment & Dataset) daily dataset, produced with funding from the EU Horizon2020 EUSTACE (EU Surface Temperature for All Corners of Earth) project. \r\n\r\nThe data is available directly from the ECA&D website and is referenced here to form part of the EUSTACE collection of data. The EUSTACE version of the product is that labelled 'Homogenized ECA Dataset'. This dataset will continue to be updated by the ECA&D project beyond the end of EUSTACE.\r\n\r\nData is available for non-commercial purposes under the ECA&D terms and conditions (see https://www.ecad.eu//documents/ECAD_datapolicy.pdf).\r\n\r\nTo cite this dataset please use Squintu, AA, van der Schrier, G, Brugnara, Y, Klein Tank, A. \r\nHomogenization of daily temperature series in the European Climate Assessment & Dataset. /Int J Climatol/. 2019; 39: 1243– 1261. https://doi.org/10.1002/joc.5874\r\n\r\nThe EU EUSTACE project has received funding by the European Union's Horizon 2020 research and innovation programme under grant agreement no 640171." } }, { "ob_id": 243, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27405, "uuid": "004a2953edbc4c2e9b89bda0e2009e55", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Along-Track Scanning Radiometer (ATSR) Level 3 Collated (L3C) Climate Data Record, version 2.0", "abstract": "This v2.0 SST_cci Along-Track Scanning Radiometer (ATSR) Level 3 Collated (L3C) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the ATSR series of satellite instruments. It covers the period 11/1991 - 04/2012. This L3C product provides these SST data on a 0.05 regular latitude-longitude grid and collated to include all orbits for a day (separated into daytime and nighttime files).\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST CCI accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nData are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ ." }, "objectObservation": { "ob_id": 20087, "uuid": "b8285969426a4e00b7481434291ad603", "short_code": "ob", "title": "EUSTACE / CCI: Global clear-sky sea surface temperature from the (A)ATSR series at 0.25 degrees with estimates of uncertainty components, v1.2, 1991-2012", "abstract": "This dataset consists of Sea Surface Temperature data with uncertainty estimates, from the Along Track Scanning Radiometer series of satellite instruments (ATSR-1, ATSR-2 and AATSR). It forms part of the collection of datasets from the EUSTACE (EU Surface Temperature for All Corners of Earth) project, which is producing publically available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques.\r\n\r\nThe Sea Surface Temperature data provided here were retrieved in the context of the European Space Agency's (ESA's) Climate Change Initiative (CCI) Sea Surface Temperature (SST) project, and comprise a Level 3c gridded product, on a 0.25 degree grid. This v1.2 product was provided for input into the EUSTACE project. It is provided here for traceability; more recent CCI data is available from the SST CCI catalogue pages." } }, { "ob_id": 245, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27478, "uuid": "6448e7c92d4e48188533432f6b26fe22", "short_code": "ob", "title": "Global predicted sea-surface iodide concentrations v0.0.1", "abstract": "This dataset contains global spatially predicted sea-surface iodide concentrations at a monthly resolution for the year 1970. It was developed as part of the NERC project Iodide in the ocean:distribution and impact on iodine flux and ozone loss (NE/N009983/1), which aimed to quantify the dominant controls on the sea surface iodide distribution and improve parameterisation of the sea-to-air iodine flux and of ozone deposition.\r\n\r\nThis dataset is the output used in the published paper 'A machine learning based global sea-surface iodide distribution' ( https://doi.org/10.5194/essd-2019-40) \r\n\r\nThe main ensemble prediction (\"Ensemble_Monthly_mean \") is provided in a NetCDF file as a single variable (1). A second file (2) is provided which includes all of the predictions and the standard deviation on the prediction.\r\n(1) predicted_iodide_0.125x0.125_Ns_Just_Ensemble.nc\r\n(2) predicted_iodide_0.125x0.125_Ns_All_Ensemble_members.nc\r\n\r\nFor ease of use, this output has been re-gridded to various commonly used atmosphere and ocean model resolutions (see table SI table A5 in paper). These re-gridded files are included in the folder titled \"regridded_data\".\r\n\r\nAdditionally, a further file (3) is provided including the prediction made included data from the Skagerak dataset. As stated in the paper referenced above, it is recommended to use the use the core files (1,2) or their re-gridded equivalents.\r\n\r\n(3) predicted_iodide_0.125x0.125_All_Ensemble_members.nc\r\n\r\nAs new observations are made, this global data product will be updated through a \"living data\" model. The dataset versions follow semantic versioning (https://semver.org/) This dataset contains the first publicly released version v0.0.1 and supersedes the pre-review dataset named v0.0.0, Please refer to the paper referenced above for the current version number and information on this.\r\n\r\nUpdates for v0.0.1 vs. v0.0.0\r\n- Additional files included of the core data re-gridded for 0.5x0.5 degree and 0.25x0.25 degree horizontal resolution.\r\n- Minor updates were applied to all metadata in NetCDF files.\r\n- Updates were made to coordinate grids used for regriding files from 1x1 degree to 4x5 degree." }, "objectObservation": { "ob_id": 27020, "uuid": "02c6f4eea9914e5c8a8390dd09e5709a", "short_code": "ob", "title": "Global predicted sea-surface iodide concentrations v0.0.0", "abstract": "This dataset contains global spatially predicted sea-surface iodide concentrations at a monthly resolution. This dataset was developed as part of the NERC project Iodide in the ocean:distribution and impact on iodine flux and ozone loss (NE/N009983/1), which aimed to quantify the dominant controls on the sea surface iodide distribution and improve parameterisation of the sea-to-air iodine flux and of ozone deposition.\r\n\r\nThe main ensemble prediction (\"Ensemble Monthly mean \") is provided in a NetCDF (1) file as a single variable. A second file (2) is provided which includes all of the predictions and the standard deviation on the prediction.\r\n\r\n(1) predicted_iodide_0.125x0.125_Ns_Just_Ensemble.nc\r\n\r\n(2) predicted_iodide_0.125x0.125_Ns_All_Ensemble_members.nc\r\n\r\nThis is the output of the paper 'A machine learning based global sea-surface iodide distribution' (see related documentation). For ease of use, this output has been re-gridded to various commonly used atmosphere and ocean model resolutions (see table SI table A5 in paper). These re-gridded files are included in the folder titled \"regridded_data\".\r\n\r\nAdditionally, a file (3) is provided including the prediction made included data from the Skagerak dataset. As stated in the paper referenced above, it is recommended to use the use the core files (1,2) or their re-gridded equivalents.\r\n\r\n(3) predicted_iodide_0.125x0.125_All_Ensemble_members.nc\r\n\r\nAs new observations are made, we will update the global dataset through a \"living data\" model. The dataset versions archived here follow semantic versioning (https://semver.org/) The pre-review dataset is achieved in the folder named v0.0.0, with the with publically released versions numbered starting from v1.0.0. Please refer to the referenced paper (see related documentation) for the current version number and information on this." } }, { "ob_id": 246, "relationType": "IsNewVersionOf", "subjectObservation": { "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." }, "objectObservation": { "ob_id": 11070, "uuid": "9faba9794e07f15e9145cb312606f8c3", "short_code": "ob", "title": "Met Office Unified Model (UM) Operational Output: Global data", "abstract": "Data from the operational NWP (Numerical Weather Prediction) output from the Met Office Unified Model. These data are from both the Global and the North Atlantic European (NAE) part of the model. The NAE model runs on a grid centred around the UK. Analyses and intermediate forecast steps are stored to give an hourly time resolution for 6 hours following each analysis time-step. This archive only holds data to January 2012. A new NWP archive is being populated with data from January 2012." } }, { "ob_id": 247, "relationType": "IsNewVersionOf", "subjectObservation": { "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." }, "objectObservation": { "ob_id": 13540, "uuid": "687ad123093743c7b291795cf2a7d3a7", "short_code": "ob", "title": "Met Office Unified Model (UM) Operational Output: North Atlantic European (NAE) data", "abstract": "Data from the operational NWP (Numerical Weather Prediction) output from the Met Office Unified Model. These data are from both the Global and the North Atlantic European (NAE) part of the model. The NAE model runs on a grid centred around the UK. Analyses and intermediate forecast steps are stored to give an hourly time resolution for 6 hours following each analysis time-step. This archive only holds data to January 2012. A new NWP archive is being populated with data from January 2012.\r\n\r\nThe Met Office's North Atlantic and European model (NAE) model had 70 levels with a 12 km resolution." } }, { "ob_id": 248, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27492, "uuid": "d6768285fdc8408bbb9b02bb0f317774", "short_code": "ob", "title": "CRU CY 4.03: Climatic Research Unit year-by-year variation of selected climate variables by country version 4.03 (Jan. 1901 - Dec. 2018)", "abstract": "The Climatic Research Unit (CRU) Country (CY) data version 4.03 dataset consists of ten climate variables for country averages at a monthly, seasonal and annual frequency; including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and potential evapotranspiration. This version uses the updated set of country definitions, please see the appropriate Release Notes.\r\n\r\nThis dataset was produced in 2019 by CRU at the University of East Anglia and extends the CRU CY4.02 data to include 2018. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nSpatial averages are calculated using area-weighted means. CRU CY4.03 is derived directly from the CRU time series (TS) 4.03 dataset. CRU CY version 4.03 spans the period 1901-2018 for 292 countries.\r\n\r\nTo understand the CRU CY4.03 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS4.03. It is therefore recommended that all users read the Harris et al, 2020 paper and the CRU TS4.03 release notes listed in the online documentation on this record.\r\n\r\nCRU CY data are available for download to all CEDA users." }, "objectObservation": { "ob_id": 26860, "uuid": "b177c691ce9143729e16faadbdebced8", "short_code": "ob", "title": "CRU CY 4.02: Climatic Research Unit (CRU) year-by-year variation of selected climate variables by country (CY) version 4.02 (Jan. 1901 - Dec. 2017)", "abstract": "The Climatic Research Unit (CRU) Country (CY) data version 4.02 dataset consists of ten climate variables for country averages at a monthly, seasonal and annual frequency; including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and potential evapotranspiration. This version uses the updated set of country definitions, please see the appropriate Release Notes.\r\n\r\nThis dataset was produced in 2018 by CRU at the University of East Anglia and extends the CRU CY4.01 data to include 2017. CRU CY4.02 is a full release, differing only in methodology from the existing current version 3 release, v3.26. Both are released concurrently to support comparative evaluations between these two versions, however, this will be the last release of version 3. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nSpatial averages are calculated using area-weighted means. CRU CY4.02 is derived directly from the CRU TS4.02 dataset. CRU CY version 4.02 spans the period 1901-2017 for 289 countries.\r\n\r\nTo understand the CRU CY4.02 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS4.02. It is therefore recommended that all users read the Harris et al, 2020 paper and the CRU TS4.02 release notes listed in the online documentation on this record.\r\n\r\nCRU CY data are available for download to all CEDA users." } }, { "ob_id": 249, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27493, "uuid": "10d3e3640f004c578403419aac167d82", "short_code": "ob", "title": "CRU TS4.03: Climatic Research Unit (CRU) Time-Series (TS) version 4.03 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2018)", "abstract": "The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.03 data are month-by-month variations in climate over the period 1901-2018, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia.\r\n\r\nThe CRU TS4.03 variables are cloud cover, diurnal temperature range, frost day frequency, potential evapotranspiration (PET), precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period January 1901 - December 2018.\r\n\r\nThe CRU TS4.03 data were produced using angular-distance weighting (ADW) interpolation. All version 4 releases used triangulation routines in IDL. Please see the release notes for full details of this version update. \r\n\r\nThe CRU TS4.03 data are monthly gridded fields based on monthly observational data calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and NetCDF data files both contain monthly mean values for the various parameters. The NetCDF versions contain an additional integer variable, ’stn’, which provides, for each datum in the main variable, a count (between 0 and 8) of the number of stations used in that interpolation. The missing value code for 'stn' is -999.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies." }, "objectObservation": { "ob_id": 26858, "uuid": "b2f81914257c4188b181a4d8b0a46bff", "short_code": "ob", "title": "CRU TS4.02: Climatic Research Unit (CRU) Time-Series (TS) version 4.02 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2017)", "abstract": "The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.02 data are month-by-month variations in climate over the period 1901-2017, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia.\r\n\r\nThe CRU TS4.02 variables are cloud cover, diurnal temperature range, frost day frequency, potential evapotranspiration (PET), precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period January 1901 - December 2017.\r\n\r\nThe CRU TS4.02 data were produced using angular-distance weighting (ADW) interpolation. All version 3 releases used triangulation routines in IDL. Please see the release notes for full details of this version update. CRU TS4.02 is a full release, differing only in methodology from the parallel release, v3.26. Both are released concurrently to support comparative evaluations between these two versions, however, this will be the last release of version 3. \r\n\r\nThe CRU TS4.02 data are monthly gridded fields based on monthly observational data calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and NetCDF data files both contain monthly mean values for the various parameters. The NetCDF versions contain an additional integer variable, ’stn’, which provides, for each datum in the main variable, a count (between 0 and 8) of the number of stations used in that interpolation. The missing value code for 'stn' is -999.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies." } }, { "ob_id": 250, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27491, "uuid": "7f785c0e80aa4df2b39d068ce7351bbb", "short_code": "ob", "title": "CRU JRA v2.0: A forcings dataset of gridded land surface blend of Climatic Research Unit (CRU) and Japanese reanalysis (JRA) data; Jan.1901 - Dec.2018.", "abstract": "The CRU JRA V2.0 dataset is a 6-hourly, land surface, gridded time series of ten meteorological variables produced by the Climatic Research Unit (CRU) at the University of East Anglia (UEA), and is intended to be used to drive models. The variables are provided on a 0.5 deg latitude x 0.5 deg longitude grid, the grid is near global but excludes Antarctica (this is same as the CRU TS grid, though the set of variables is different) . The data are available at a 6 hourly time-step from January 1901 to December 2018.\r\n\r\nThe dataset is constructed by combining data from the Japanese Reanalysis data (JRA) produced by the Japanese Meteorological Agency (JMA) and adjusted where possible to align with the CRU TS 4.03 data (see the Process section and the ReadMe file for full details).\r\n\r\nThe CRU JRA data consists of the following ten meteorological variables: 2-metre temperature, 2-metre maximum and minimum temperature, total precipitation, specific humidity, downward solar radiation flux, downward long wave radiation flux, pressure and the zonal and meridional components of wind speed (see the ReadMe file for further details).\r\n\r\nThe CRU JRA dataset is intended to be a replacement of the CRU NCEP forcing dataset. The CRU JRA dataset follows the style of Nicolas Viovy's original CRU NCEP dataset rather than that which is available from UCAR. A link to the CRU NCEP documentation for comparison is provided in the documentation section. \r\n\r\nIf this dataset is used in addition to citing the dataset as per the data citation string users must also cite the following:\r\n\r\nHarris, I., Jones, P.D., Osborn, T.J. and Lister, D.H. (2014), Updated\r\nhigh-resolution grids of monthly climatic observations - the CRU TS3.10\r\nDataset. International Journal of Climatology 34, 623-642.\r\n\r\nKobayashi, S., et. al., The JRA-55 Reanalysis: General Specifications and\r\nBasic Characteristics. J. Met. Soc. Jap., 93(1), 5-48\r\nhttps://dx.doi.org/10.2151/jmsj.2015-001" }, "objectObservation": { "ob_id": 26978, "uuid": "13f3635174794bb98cf8ac4b0ee8f4ed", "short_code": "ob", "title": "CRU JRA v1.1: A forcings dataset of gridded land surface blend of Climatic Research Unit (CRU) and Japanese reanalysis (JRA) data; Jan.1901 - Dec.2017.", "abstract": "The CRU JRA V1.1 dataset is a 6-hourly, land surface, gridded time series of ten meteorological variables produced by the Climatic Research Unit (CRU) at the University of East Anglia (UEA), and is intended to be used to drive models. The variables are provided on a 0.5 deg latitude x 0.5 deg longitude grid, the grid is near global but excludes Antarctica (this is same as the CRU TS grid, though the set of variables is different) . The data are available at a 6 hourly time-step from January 1901 to December 2017.\r\n\r\nThe dataset is constructed by combining data from the Japanese Reanalysis data (JRA) produced by the Japanese Meteorological Agency (JMA) and adjusted where possible to align with the CRU TS 3.26 data (see the Process section and the ReadMe file for full details).\r\n\r\nThe CRU JRA data consists of the following ten meteorological variables: 2-metre temperature, 2-metre maximum and minimum temperature, total precipitation, specific humidity, downward solar radiation flux, downward long wave radiation flux, pressure and the zonal and meridional components of wind speed (see the ReadMe file for further details).\r\n\r\nThe CRU JRA dataset is intended to be a replacement of the CRUNCEP forcing dataset. The CRU JRA dataset follows the style of Nicolas Viovy's original CRUNCEP dataset rather than that which is available from UCAR. A link to the CRU NCEP documentation for comparison is provided in the documentation section. \r\n\r\nIf this dataset is used in addition to citing the dataset as per the data citation string users must also cite the following:\r\n\r\nHarris, I., Jones, P.D., Osborn, T.J. and Lister, D.H. (2014), Updated\r\nhigh-resolution grids of monthly climatic observations - the CRU TS3.10\r\nDataset. International Journal of Climatology 34, 623-642.\r\n\r\nKobayashi, S., et. al., The JRA-55 Reanalysis: General Specifications and\r\nBasic Characteristics. J. Met. Soc. Jap., 93(1), 5-48\r\nhttps://dx.doi.org/10.2151/jmsj.2015-001" } }, { "ob_id": 251, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27519, "uuid": "2282b4aeb9f24bc3a1e0961e4d545427", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Along-Track Scanning Radiometer (ATSR) Level 3 Uncollated (L3U) Climate Data Record, version 2.1", "abstract": "This v2.1 SST_cci Along-Track Scanning Radiometer (ATSR) Level 3 Uncollated (L3U) Climate Data Record consists of stable, low-bias sea surface temperature (SST) data from the ATSR series of satellite instruments. It covers the period between 11/1991 and 04/2012. The L3U products provide these SST data on a 0.05 regular latitude-longitude grid with with a single orbit per file.\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST_cci accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nThis CDR Version 2.1 product supercedes the CDR v2.0 and the Long Term product v1.1. Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ .\r\n\r\nWhen citing this dataset please also cite the associated data paper: Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x" }, "objectObservation": { "ob_id": 26425, "uuid": "a78d998cc9714e0bbd4276c0bdd87703", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Along-Track Scanning Radiometer (ATSR) Level 3 Uncollated (L3U) Climate Data Record, version 2.0", "abstract": "This v2.0 SST_cci Along-Track Scanning Radiometer (ATSR) Level 3 Uncollated (L3U) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the Along Track Scanning Radiometer (ATSR) series of satellite instruments. It covers the period between 11/1991 and 04/2012. This Level 3 Uncollated (L3U) product provides these SST data on a 0.05 regular latitude-longitude grid with a single orbit per file.\r\n \r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST_cci accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research. \r\n\r\nThis CDR Version 2.0 product is a later version of the Long Term product v1.1. Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ ." } }, { "ob_id": 252, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27522, "uuid": "5db2099606b94e63879d841c87e654ae", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Along-Track Scanning Radiometer (ATSR) Level 3 Collated (L3C) Climate Data Record, version 2.1", "abstract": "This v2.1 SST_cci Along-Track Scanning Radiometer (ATSR) Level 3 Collated (L3C) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the ATSR series of satellite instruments. It covers the period between 11/1991 and 04/2012. This L3C product provides these SST data on a 0.05 regular latitude-longitude grid and collated to include all orbits for a day (separated into daytime and nighttime files).\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST_cci accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nThis CDR Version 2.1 product supercedes the CDR v2.0 product. Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ .\r\n\r\nWhen citing this dataset please also cite the associated data paper: Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x" }, "objectObservation": { "ob_id": 27405, "uuid": "004a2953edbc4c2e9b89bda0e2009e55", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Along-Track Scanning Radiometer (ATSR) Level 3 Collated (L3C) Climate Data Record, version 2.0", "abstract": "This v2.0 SST_cci Along-Track Scanning Radiometer (ATSR) Level 3 Collated (L3C) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the ATSR series of satellite instruments. It covers the period 11/1991 - 04/2012. This L3C product provides these SST data on a 0.05 regular latitude-longitude grid and collated to include all orbits for a day (separated into daytime and nighttime files).\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST CCI accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nData are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ ." } }, { "ob_id": 253, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27524, "uuid": "916b93aaf1474ce793171a33ca4c5026", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Along-Track Scanning Radiometer (ATSR) Level 2 Preprocessed (L2P) Climate Data Record, version 2.1", "abstract": "This v2.1 SST_cci Along-Track Scanning Radiometer (ATSR) Level 2 Preprocessed (L2P) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the ATSR series of satellite instruments. It covers the period between 11/1991 and 04/2012. This L2P product provides these SST data on the original satellite swath with a single orbit of data per file.\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST_cci accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SST's to a quality suitable for climate research.\r\n\r\nThis CDR Version 2.1 product supercedes the CDR Version 2.0 product. Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ .\r\n\r\nWhen citing this dataset please also cite the associated data paper: Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x" }, "objectObservation": { "ob_id": 26431, "uuid": "cfe46deca7324763b8989adaa2607f20", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Along-Track Scanning Radiometer (ATSR) Level 2 Preprocessed (L2P) Climate Data Record, version 2.0", "abstract": "This v2.0 SST_cci Along-Track Scanning Radiometer (ATSR) Level 2 Preprocessed (L2P) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the ATSR series of satellite instruments. It covers the period between 11/1991 - 04/2012. This L2P product provides these SST data on the original satellite swath with a single orbit of data per file.\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project (ESA SST_cci). The data products from SST_cci accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nData are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ ." } }, { "ob_id": 254, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27526, "uuid": "373638ed9c434e78b521cbe01ace5ef7", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Advanced Very High Resolution Radiometer (AVHRR) Level 2 Preprocessed (L2P) Climate Data Record, version 2.1", "abstract": "This v2.1 SST_cci Advanced Very High Resolution Radiometer (AVHRR) Level 2 Preprocessed (L2P) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the AVHRR series of satellite instruments. It covers the period between 08/1981 and 12/2016. This L2P product provides these SST data on the original satellite swath with a single orbit of data per file.\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST_cci accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nThis CDR Version 2.1 product supercedes the CDR Version 2.0 product. Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ .\r\n\r\nWhen citing this dataset please also cite the associated data paper: Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x" }, "objectObservation": { "ob_id": 26427, "uuid": "60476148c74148cb8cac1e47c501a178", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Advanced Very High Resolution Radiometer (AVHRR) Level 2 Preprocessed (L2P) Climate Data Record, version 2.0", "abstract": "This v2.0 SST_cci Advanced Very High Resolution Radiometer (AVHRR) Level 2 Preprocessed (L2P) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the AVHRR series of satellite instruments. It covers the period between 08/1981 and 12/2016. This L2P product provides these SST data on the original satellite swath with a single orbit of data per file.\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST CCI accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nData are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/" } }, { "ob_id": 255, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27528, "uuid": "42f7230ab55641cdac1bba84eabd446a", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Advanced Very High Resolution Radiometer (AVHRR) Level 3 Uncollated (L3U) Climate Data Record, version 2.1", "abstract": "This v2.1 SST_cci Advanced Very High Resolution Radiometer (AVHRR) level 3 uncollated data (L3U) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the AVHRR series of satellite instruments. It covers the period between 08/1981 and 12/2016. This L3U product provides these SST data on a 0.05 regular latitude-longitude grid with with a single orbit per file.\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST_cci accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nThis CDR Version 2.1 product supercedes the CDR Version 2.0 product. Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ .\r\n\r\nWhen citing this dataset please also cite the associated data paper: Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x" }, "objectObservation": { "ob_id": 27515, "uuid": "79dd8e867b5a4bc28527118aae306095", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Advanced Very High Resolution Radiometer (AVHRR) Level 3 Uncollated (L3U) Climate Data Record version 2.0", "abstract": "This v2.0 SST_cci Advanced Very High Resolution Radiometer (AVHRR) level 3 uncollated data (L3U) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the AVHRR series of satellite instruments. It covers the period between 08/1981 - 12/2016. This Level 3 Uncollated (L3U) product provides these SST data on a 0.05 regular latitude-longitude grid with a single orbit per file. \r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST CCI accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nData are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ ." } }, { "ob_id": 256, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27530, "uuid": "7db4459605da4665b6ab9a7102fb4875", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Advanced Very High Resolution Radiometer (AVHRR) Level 3 Collated (L3C) Climate Data Record, version 2.1", "abstract": "This v2.1 SST_cci Advanced Very High Resolution Radiometer (AVHRR) Level 3 Collated (L3C) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the AVHRR series of satellite instruments. It covers the period between 08/1981 and 12/2016. This L3C product provides these SST data on a 0.05 regular latitude-longitude grid and collated to include all orbits for a day (separated into daytime and nighttime files).\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST_cci accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nThis CDR Version 2.1 product supercedes the CDR Version 2.0 product. Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ .\r\n\r\nWhen citing this dataset please also cite the associated data paper: Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x" }, "objectObservation": { "ob_id": 27517, "uuid": "13b5cf97be4446428d3396723864e121", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Advanced Very High Resolution Radiometer (AVHRR) Level 3 Collated (L3C) Climate Data Record, version 2.0", "abstract": "This v2.0 SST_cci Advanced Very High Resolution Radiometer (AVHRR) Level 3 Collated (L3C) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the AVHRR series of satellite instruments. It covers the period 08/1981 - 12/2016. This L3C product provides these SST data on a 0.05 regular latitude-longitude grid and collated to include all orbits for a day (separated into daytime and nighttime files).\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST CCI accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nData are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ ." } }, { "ob_id": 257, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27532, "uuid": "62c0f97b1eac4e0197a674870afe1ee6", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Level 4 Analysis Climate Data Record, version 2.1", "abstract": "This v2.1 SST_cci Level 4 Analysis Climate Data Record (CDR) provides a globally-complete daily analysis of sea surface temperature (SST) on a 0.05 degree regular latitude - longitude grid. It combines data from both the Advanced Very High Resolution Radiometer (AVHRR ) and Along Track Scanning Radiometer (ATSR) SST_cci Climate Data Records, using a data assimilation method to provide SSTs where there were no measurements. These data cover the period between 09/1981 and 12/2016.\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST_cci accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nThe CDR Version 2.1 product supercedes the CDR Version 2.0 product. Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/\r\n\r\nWhen citing this dataset please also cite the associated data paper: Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x" }, "objectObservation": { "ob_id": 27447, "uuid": "aced40d7cb964f23a0fd3e85772f2d48", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Level 4 Analysis Climate Data Record, version 2.0", "abstract": "This v2.0 SST_cci Level 4 Analysis Climate Data Record (CDR) provides a globally-complete daily analysis of sea surface temperature (SST) on a 0.05 degree regular latitude-longitude grid. It combines the orbit data from the Advanced High Resolution Radiometer (AVHRR) and Along Track Scanning Radiometer (ATSR) SST_cci Climate Data Records, using a data assimilation method to provide SSTs where there were no measurements. These data cover the period between 09/1981 and 12/2016.\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST CCI accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nData are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ ." } }, { "ob_id": 258, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27447, "uuid": "aced40d7cb964f23a0fd3e85772f2d48", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Level 4 Analysis Climate Data Record, version 2.0", "abstract": "This v2.0 SST_cci Level 4 Analysis Climate Data Record (CDR) provides a globally-complete daily analysis of sea surface temperature (SST) on a 0.05 degree regular latitude-longitude grid. It combines the orbit data from the Advanced High Resolution Radiometer (AVHRR) and Along Track Scanning Radiometer (ATSR) SST_cci Climate Data Records, using a data assimilation method to provide SSTs where there were no measurements. These data cover the period between 09/1981 and 12/2016.\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST CCI accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nData are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ ." }, "objectObservation": { "ob_id": 13928, "uuid": "c65ce27928f34ebd92224c451c2a8bed", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI): Analysis long term product version 1.1", "abstract": "The ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI) dataset accurately maps the surface temperature of the global oceans over the period 1991 to 2010, using observations from many satellites. The data provides an independently quantified SST to a quality suitable for climate research.\r\n\r\nThe ESA SST CCI Analysis Long Term Product consists of daily, spatially complete fields of sea surface temperature (SST), obtained by combining the orbit data from the AVHRR and ATSR ESA SST CCI Long Term Products, using optimal interpolation to provide SSTs where there were no measurements. These data cover the period between 09/1991 and 12/2010.\r\n\r\nThe Version 1.1 data is an update of the Version 1.0 dataset.\r\n\r\nVersion 1.0 of this dataset is cited in: Merchant, C. J., Embury, O., Roberts-Jones, J., Fiedler, E., Bulgin, C. E., Corlett, G. K., Good, S., McLaren, A., Rayner, N., Morak-Bozzo, S. and Donlon, C. (2014), Sea surface temperature datasets for climate applications from Phase 1 of the European Space Agency Climate Change Initiative (SST CCI). Geoscience Data Journal. doi: 10.1002/gdj3.20" } }, { "ob_id": 259, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 26427, "uuid": "60476148c74148cb8cac1e47c501a178", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Advanced Very High Resolution Radiometer (AVHRR) Level 2 Preprocessed (L2P) Climate Data Record, version 2.0", "abstract": "This v2.0 SST_cci Advanced Very High Resolution Radiometer (AVHRR) Level 2 Preprocessed (L2P) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the AVHRR series of satellite instruments. It covers the period between 08/1981 and 12/2016. This L2P product provides these SST data on the original satellite swath with a single orbit of data per file.\r\n\r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST CCI accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.\r\n\r\nData are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/" }, "objectObservation": { "ob_id": 11011, "uuid": "da85154480423eda8e8022d499abcc06", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI): Advanced Very High Resolution Radiometer (AVHRR) level 2 pre-processed (L2P) long term product version 1.0", "abstract": "The ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI) dataset accurately maps the surface temperature of the global oceans over the period 1991 to 2010, using observations from many satellites. The data provides an independently quantified SST to a quality suitable for climate research.\r\n\r\nThe ESA SST CCI AVHRR (Advanced Very High Resolution Radiometer) Long Term Product consists of stable, low-bias sea surface temperature (SST) data covering the period 08/1991 - 12/2010. The L2P data product provide these SST observations in the satellite swath.\r\n\r\nThis dataset is cited in: Merchant, C. J., Embury, O., Roberts-Jones, J., Fiedler, E., Bulgin, C. E., Corlett, G. K., Good, S., McLaren, A., Rayner, N., Morak-Bozzo, S. and Donlon, C. (2014), Sea surface temperature datasets for climate applications from Phase 1 of the European Space Agency Climate Change Initiative (SST CCI). Geoscience Data Journal. doi: 10.1002/gdj3.20" } }, { "ob_id": 260, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 26425, "uuid": "a78d998cc9714e0bbd4276c0bdd87703", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): Along-Track Scanning Radiometer (ATSR) Level 3 Uncollated (L3U) Climate Data Record, version 2.0", "abstract": "This v2.0 SST_cci Along-Track Scanning Radiometer (ATSR) Level 3 Uncollated (L3U) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the Along Track Scanning Radiometer (ATSR) series of satellite instruments. It covers the period between 11/1991 and 04/2012. This Level 3 Uncollated (L3U) product provides these SST data on a 0.05 regular latitude-longitude grid with a single orbit per file.\r\n \r\nThe dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST_cci accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research. \r\n\r\nThis CDR Version 2.0 product is a later version of the Long Term product v1.1. Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ ." }, "objectObservation": { "ob_id": 11016, "uuid": "5a807d9ebb2d67b5472624e9639253a9", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI): Along-Track Scanning Radiometer (ATSR) level 3 uncollated data (L3U) long-term product version 1.1", "abstract": "The ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI) dataset accurately maps the surface temperature of the global oceans over the period 1991 to 2010 using observations from many satellites. The data provides an independently quantified SST to a quality suitable for climate research. \r\nThe ESA SST CCI ATSR (Along-Track Scanning Radiometer) Long Term Product version 1.1 consists of stable, low-bias sea surface temperature (SST) data covering the period 08/1991 - 04/2012. The L3U data product provides these SST data regridded onto a global longitude-latitude grid.\r\n\r\nThe version 1.1 data is an update to the version 1.0 dataset.\r\n\r\nThis dataset is cited in: Merchant, C. J., Embury, O., Roberts-Jones, J., Fiedler, E., Bulgin, C. E., Corlett, G. K., Good, S., McLaren, A., Rayner, N., Morak-Bozzo, S. and Donlon, C. (2014), Sea surface temperature datasets for climate applications from Phase 1 of the European Space Agency Climate Change Initiative (SST CCI). Geoscience Data Journal. doi: 10.1002/gdj3.20" } }, { "ob_id": 261, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 11016, "uuid": "5a807d9ebb2d67b5472624e9639253a9", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI): Along-Track Scanning Radiometer (ATSR) level 3 uncollated data (L3U) long-term product version 1.1", "abstract": "The ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI) dataset accurately maps the surface temperature of the global oceans over the period 1991 to 2010 using observations from many satellites. The data provides an independently quantified SST to a quality suitable for climate research. \r\nThe ESA SST CCI ATSR (Along-Track Scanning Radiometer) Long Term Product version 1.1 consists of stable, low-bias sea surface temperature (SST) data covering the period 08/1991 - 04/2012. The L3U data product provides these SST data regridded onto a global longitude-latitude grid.\r\n\r\nThe version 1.1 data is an update to the version 1.0 dataset.\r\n\r\nThis dataset is cited in: Merchant, C. J., Embury, O., Roberts-Jones, J., Fiedler, E., Bulgin, C. E., Corlett, G. K., Good, S., McLaren, A., Rayner, N., Morak-Bozzo, S. and Donlon, C. (2014), Sea surface temperature datasets for climate applications from Phase 1 of the European Space Agency Climate Change Initiative (SST CCI). Geoscience Data Journal. doi: 10.1002/gdj3.20" }, "objectObservation": { "ob_id": 11014, "uuid": "2608443849391d2513d903482a19f206", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI): Along-Track Scanning Radiometer (ATSR) level 3 uncollated data (L3U) long-term product version 1.0", "abstract": "The ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI) dataset accurately maps the surface temperature of the global oceans over the period 1991 to 2010 using observations from many satellites. The data provides an independently quantified SST to a quality suitable for climate research. \r\nThe ESA SST CCI ATSR (Along-Track Scanning Radiometer) Long Term Product Version 1.0 consists of stable, low-bias sea surface temperature (SST) data covering the period 08/1991 - 12/2010. The L3U data product provides these SST data regridded onto a global longitude-latitude grid.\r\n\r\nPlease note, the version 1.0 data described here has now been superseded by the version 1.1 data product as described in Merchant, C. J., Embury, O., Roberts-Jones, J., Fiedler, E., Bulgin, C. E., Corlett, G. K., Good, S., McLaren, A., Rayner, N., Morak-Bozzo, S. and Donlon, C. (2014), Sea surface temperature datasets for climate applications from Phase 1 of the European Space Agency Climate Change Initiative (SST CCI). Geoscience Data Journal. doi: 10.1002/gdj3.20" } }, { "ob_id": 262, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 13928, "uuid": "c65ce27928f34ebd92224c451c2a8bed", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI): Analysis long term product version 1.1", "abstract": "The ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI) dataset accurately maps the surface temperature of the global oceans over the period 1991 to 2010, using observations from many satellites. The data provides an independently quantified SST to a quality suitable for climate research.\r\n\r\nThe ESA SST CCI Analysis Long Term Product consists of daily, spatially complete fields of sea surface temperature (SST), obtained by combining the orbit data from the AVHRR and ATSR ESA SST CCI Long Term Products, using optimal interpolation to provide SSTs where there were no measurements. These data cover the period between 09/1991 and 12/2010.\r\n\r\nThe Version 1.1 data is an update of the Version 1.0 dataset.\r\n\r\nVersion 1.0 of this dataset is cited in: Merchant, C. J., Embury, O., Roberts-Jones, J., Fiedler, E., Bulgin, C. E., Corlett, G. K., Good, S., McLaren, A., Rayner, N., Morak-Bozzo, S. and Donlon, C. (2014), Sea surface temperature datasets for climate applications from Phase 1 of the European Space Agency Climate Change Initiative (SST CCI). Geoscience Data Journal. doi: 10.1002/gdj3.20" }, "objectObservation": { "ob_id": 11006, "uuid": "916986a220e6bad55411d9407ade347c", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI): Analysis long term product version 1.0", "abstract": "The ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI) dataset accurately maps the surface temperature of the global oceans over the period 1991 to 2010, using observations from many satellites. The data provides an independently quantified SST to a quality suitable for climate research.\r\n\r\nThe ESA SST CCI Analysis Long Term Product consists of daily, spatially complete fields of sea surface temperature (SST), obtained by combining the orbit data from the AVHRR and ATSR ESA SST CCI Long Term Products, using optimal interpolation to provide SSTs where there were no measurements. These data cover the period between 09/1991 and 12/2010.\r\n\r\nThis dataset is cited in: Merchant, C. J., Embury, O., Roberts-Jones, J., Fiedler, E., Bulgin, C. E., Corlett, G. K., Good, S., McLaren, A., Rayner, N., Morak-Bozzo, S. and Donlon, C. (2014), Sea surface temperature datasets for climate applications from Phase 1 of the European Space Agency Climate Change Initiative (SST CCI). Geoscience Data Journal. doi: 10.1002/gdj3.20\r\n\r\nPlease note that this dataset has now been superseded by the version 1.1 product, available from http://catalogue.ceda.ac.uk/uuid/c65ce27928f34ebd92224c451c2a8bed" } }, { "ob_id": 265, "relationType": "HasMetadata", "subjectObservation": { "ob_id": 27790, "uuid": "9604cf11798b4af3a9dfe573617571d2", "short_code": "ob", "title": "IPCC AR5 Seasonal temperature and precipitation extremes in IPCC regions for CMIP5", "abstract": "Projected regional average change in seasonal and annual temperature and precipitation extremes for the IPCC SREX regions for CMIP5. The data were produced in 2013 by the Intergovernmental Panel on Climate Change (IPCC) Working Group II (WGII) Chapter 14 supplementary material (SM) author team for the IPCC Fifth Assessment Report (AR5). \r\n\r\nRegional average seasonal and annual temperature and precipitation extremes for the periods 2016-2035, 2046-2065 and 2081-2100 for CMIP5 General Circulation Model (GCM) projections are compared to a baseline of 1986-2005 from each model's historical simulation. The temperature and precipitation data are based on the difference between the projected periods and the historical baseline for which the 25th, 50th and 75th percentiles, and the lowest and highest responses among the 32 models which are expressed for temperature as degrees Celsius change and for precipitation as a per cent change. The temperature responses are averaged over the boreal winter and summer seasons; December, January, February (DJF) and June, July and August (JJA) respectively. The precipitation responses are averaged over half year periods, boreal winter (BW); October, November, December, January, February and March (ONDJFM) and boreal summer (BS); April, May, June, July, August and September (AMJJAS). \r\n\r\nRegional averages are based on the SREX regions defined by the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (IPCC, 2012: also known as \"SREX\"). Added to the SREX regions are additional regions containing the two polar regions, the Caribbean, Indian Ocean and Pacific Island States. The data are further categorised by the land and sea mask for each SREX region." }, "objectObservation": { "ob_id": 27811, "uuid": "a3b6d7f93e5c4ea986f3622eeee2b96f", "short_code": "ob", "title": "IPCC AR5 reference regions", "abstract": "The boundaries of a set of regions which are defined in Chapter 14 of the Working Group 1 (WGI) contribution to the 2013 Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and in the AR5 Annex I Atlas of Global and Regional Climate Projections. The regions are used for the calculation of IPCC regional climate statistics.\r\n\r\nThe regions used to calculate regional climate statistics in AR5 are the 26 SREX regions defined by the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (IPCC, 2012: also known as \"SREX\"). For AR5 an additional 7 regions containing the two polar regions, the Caribbean, Indian Ocean and Pacific Island States have been added. In total there are 33 region boundaries and of these, 4 (the Arctic, Antarctic, South Asia and South-East Asia) are used twice for land-only and sea-only analysis, giving a total of 37 IPCC analysis regions.\r\n\r\nEach of the 33 regions is provided with a name and a label. The label is set to the three letter code used in the SREX report for the 26 SREX regions. The 7 additional reference regions are also given three letter short names.\r\n\r\nThe 26 SREX regions are: Alaska/NW Canada (ALA), Eastern Canada/Greenland/Iceland (CGI), Western North America (WNA), Central North America (CNA), Eastern North America (ENA), Central America/Mexico (CAM), Amazon (AMZ), NE Brazil (NEB), West Coast South America (WSA), South- Eastern South America (SSA), Northern Europe (NEU), Central Europe (CEU), Southern Europe/the Mediterranean (MED), Sahara (SAH), Western Africa (WAF), Eastern Africa (EAF), Southern Africa (SAF), Northern Asia (NAS), Western Asia (WAS), Central Asia (CAS), Tibetan Plateau (TIB), Eastern Asia (EAS), Southern Asia (SAS), Southeast Asia (SEA), Northern Australia (NAS) and Southern Australia/New Zealand (SAU).\r\n\r\nThe non-SREX reference regions are: Antarctica (ANT), Arctic (ARC), Caribbean (CAR), Western Indian Ocean (WIO), Northern Tropical Pacific (NTP), Equatorial Tropical Pacific (ETP) and Southern Tropical Pacific (STP). \r\n\r\nThe region definitions have a subtlety regarding the treatment of land and sea areas which needs to be handled with care. The climate models use a range of methods for dealing with coastal boundaries. The archived data includes a field giving the proportion of each model grid cell which is land or sea. A model grid cell is considered land if more that 50% of the cell is land. The mean for a given region is then defined in terms of the grid points (which are the cell centres) which are within the specified reference boundaries. The spatial area covered by these grid cells will then differ from model to model. The reference boundaries thus provide a starting point for defining the regional means: the means are not a simple average of these areas. The distinction is not expected to be substantial, but anyone wanting to reproduce exactly the same numbers will need to follow all steps carefully." } }, { "ob_id": 266, "relationType": "HasMetadata", "subjectObservation": { "ob_id": 26598, "uuid": "9d0f61dc7a1b4017b22d88f9d38ab398", "short_code": "ob", "title": "IPCC AR5 Seasonal Mean Temperature and Precipitation in IPCC Regions for CMIP3 and CMIP5", "abstract": "Projected regional average change in seasonal and annual mean temperature and precipitation for the IPCC SREX regions for CMIP5 and CMIP3. The data were produced in 2014 by the Intergovernmental Panel on Climate Change (IPCC) Working Group II (WGII) Chapter 21 author team for the IPCC Fifth Assessment Report (AR5). \r\n\r\nRegional average seasonal and annual mean temperature and precipitation for the period 2071-2100 are compared to a baseline of 1961-1990 for CMIP5 and CMIP3 General Circulation Model (GCM) projections.\r\nThe data compare the range of projections from 35 Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble under four Representative Concentration Pathway (RCP) scenarios compared with GCM projections from 22 CMIP3 ensemble under three Special Report on Emission Scenarios (SRES) scenarios. \r\n\r\nRegional averages are based on SREX regions defined by the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (IPCC, 2012: also known as \"SREX\")." }, "objectObservation": { "ob_id": 27811, "uuid": "a3b6d7f93e5c4ea986f3622eeee2b96f", "short_code": "ob", "title": "IPCC AR5 reference regions", "abstract": "The boundaries of a set of regions which are defined in Chapter 14 of the Working Group 1 (WGI) contribution to the 2013 Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and in the AR5 Annex I Atlas of Global and Regional Climate Projections. The regions are used for the calculation of IPCC regional climate statistics.\r\n\r\nThe regions used to calculate regional climate statistics in AR5 are the 26 SREX regions defined by the IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (IPCC, 2012: also known as \"SREX\"). For AR5 an additional 7 regions containing the two polar regions, the Caribbean, Indian Ocean and Pacific Island States have been added. In total there are 33 region boundaries and of these, 4 (the Arctic, Antarctic, South Asia and South-East Asia) are used twice for land-only and sea-only analysis, giving a total of 37 IPCC analysis regions.\r\n\r\nEach of the 33 regions is provided with a name and a label. The label is set to the three letter code used in the SREX report for the 26 SREX regions. The 7 additional reference regions are also given three letter short names.\r\n\r\nThe 26 SREX regions are: Alaska/NW Canada (ALA), Eastern Canada/Greenland/Iceland (CGI), Western North America (WNA), Central North America (CNA), Eastern North America (ENA), Central America/Mexico (CAM), Amazon (AMZ), NE Brazil (NEB), West Coast South America (WSA), South- Eastern South America (SSA), Northern Europe (NEU), Central Europe (CEU), Southern Europe/the Mediterranean (MED), Sahara (SAH), Western Africa (WAF), Eastern Africa (EAF), Southern Africa (SAF), Northern Asia (NAS), Western Asia (WAS), Central Asia (CAS), Tibetan Plateau (TIB), Eastern Asia (EAS), Southern Asia (SAS), Southeast Asia (SEA), Northern Australia (NAS) and Southern Australia/New Zealand (SAU).\r\n\r\nThe non-SREX reference regions are: Antarctica (ANT), Arctic (ARC), Caribbean (CAR), Western Indian Ocean (WIO), Northern Tropical Pacific (NTP), Equatorial Tropical Pacific (ETP) and Southern Tropical Pacific (STP). \r\n\r\nThe region definitions have a subtlety regarding the treatment of land and sea areas which needs to be handled with care. The climate models use a range of methods for dealing with coastal boundaries. The archived data includes a field giving the proportion of each model grid cell which is land or sea. A model grid cell is considered land if more that 50% of the cell is land. The mean for a given region is then defined in terms of the grid points (which are the cell centres) which are within the specified reference boundaries. The spatial area covered by these grid cells will then differ from model to model. The reference boundaries thus provide a starting point for defining the regional means: the means are not a simple average of these areas. The distinction is not expected to be substantial, but anyone wanting to reproduce exactly the same numbers will need to follow all steps carefully." } }, { "ob_id": 267, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27815, "uuid": "b37382e8c1e74b849831a5fa13afdcae", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v201908", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2018. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." }, "objectObservation": { "ob_id": 26437, "uuid": "a39add95a8dc49709f6e984c020c8dbc", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v201901", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2017. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." } }, { "ob_id": 268, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27816, "uuid": "6ad6792f44c84c228651b01d182d9d73", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v201908", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1889 to 2018. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection." }, "objectObservation": { "ob_id": 26892, "uuid": "0049795739e44310a4982e26d8e26748", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v201901", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1889 to 2017. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection." } }, { "ob_id": 269, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27817, "uuid": "cb47cc464c5a41de8c718d117437b4e6", "short_code": "ob", "title": "MIDAS Open: UK daily rainfall data, v201908", "abstract": "The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2018. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection." }, "objectObservation": { "ob_id": 26438, "uuid": "ec54d5e5288a4ebb8c7ad2a1ef6aec42", "short_code": "ob", "title": "MIDAS Open: UK daily rainfall data, v201901", "abstract": "The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2017. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection." } }, { "ob_id": 270, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27818, "uuid": "6c441aea187b44819b9e929e575b0d7e", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v201908", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2018.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data." }, "objectObservation": { "ob_id": 26896, "uuid": "c58c1af69b9745fda4cdf487a9547185", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v201901", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2017.\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data." } }, { "ob_id": 271, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27819, "uuid": "d6bbe115245042dc93ee68caa253d60b", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v201908", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2018.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, "objectObservation": { "ob_id": 27164, "uuid": "1e040656ae0a4646acafbef6144b10f2", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v201901", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2017.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." } }, { "ob_id": 272, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27820, "uuid": "ddcfd8bb1ff44cd2855e81838b40b17c", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v201908", "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2018.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nFor further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, "objectObservation": { "ob_id": 26899, "uuid": "11c15f2640f541d4847dafe9be1bb90a", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v201901", "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2017. For further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." } }, { "ob_id": 273, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27821, "uuid": "9972bc173ef94068b2070d4b26f849a7", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v201908", "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2018.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, "objectObservation": { "ob_id": 26901, "uuid": "a7ba08d073eb40a9aab5e312f371d007", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v201901", "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2017.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." } }, { "ob_id": 274, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27822, "uuid": "a58b9c8a724e4ec795a40a74455462b7", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v201908", "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2018.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset." }, "objectObservation": { "ob_id": 26894, "uuid": "7aaa582fb00246b794dc85950f1be265", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v201901", "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. 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A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset." } }, { "ob_id": 275, "relationType": "IsPartOf", "subjectObservation": { "ob_id": 27815, "uuid": "b37382e8c1e74b849831a5fa13afdcae", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v201908", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2018. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." }, "objectObservation": { "ob_id": 1241, "uuid": "1bb479d3b1e38c339adb9c82c15579d8", "short_code": "ob", "title": "MIDAS: UK Daily Temperature Data", "abstract": "The UK daily temperature data describe maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements are recorded by observation stations across the UK and transmitted within NCM or DLY3208 or AWSDLY messages. 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Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. 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Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. 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The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." } }, { "ob_id": 278, "relationType": "IsPartOf", "subjectObservation": { "ob_id": 27816, "uuid": "6ad6792f44c84c228651b01d182d9d73", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v201908", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1889 to 2018. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. 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The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2018. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection." }, "objectObservation": { "ob_id": 1195, "uuid": "c732716511d3442f05cdeccbe99b8f90", "short_code": "ob", "title": "MIDAS: UK Daily Rainfall Data", "abstract": "The UK daily rainfall data describe the rainfall accumulation and precipitation amount over a 24 hour period. The data are collected by observation stations across the UK and transmitted within the following message types: WADRAIN, NCM, AWSDLY, DLY3208, SSER and WAMRAIN. The data spans from 1853 to present." } }, { "ob_id": 280, "relationType": "IsPartOf", "subjectObservation": { "ob_id": 27818, "uuid": "6c441aea187b44819b9e929e575b0d7e", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v201908", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2018.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data." }, "objectObservation": { "ob_id": 1214, "uuid": "916ac4bbc46f7685ae9a5e10451bae7c", "short_code": "ob", "title": "MIDAS: UK Hourly Weather Observation Data", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations across the UK and transmitted within SYNOP, METAR, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to present.\r\n\r\nThis dataset also contains data from a selection of overseas sites:\r\nSRC_ID STATION STATUS LAST DATA\r\n1580 GUTERSLOH CLOSED 28/10/2013 13:00\r\n1582 BRUGGEN CLOSED 29/09/2001 05:00\r\n1584 LAARBRUCH CLOSED 14/05/1999 23:00\r\n1585 GIBRALTAR, NORTH FRONT OPEN 03/02/2020 09:00\r\n1588 AKROTIRI, CYPRUS OPEN 03/02/2020 09:00\r\n1603 ASCENSION ISLAND AIRFIELD OPEN 02/02/2020 21:00\r\n1605 BOTTOMS WOOD, ST HELENA OPEN 03/02/2020 09:00\r\n1608 PORT STANLEY, FALKLAND IS CLOSED 31/12/1980 23:00\r\n1609 MOUNT PLEASANT, FALKLAND IS OPEN 03/02/2020 09:00\r\n56810 MOUNT OLYMPUS OPEN 16/04/2019 09:00\r\n61737 MOUNT KENT, FALKLAND ISLANDS OPEN 03/02/2020 09:00\r\n61743 MOUNT BYRON, FALKLAND ISLANDS OPEN 03/02/2020 09:00\r\n61744 MOUNT ALICE, FALKLAND ISLANDS OPEN 02/02/2020 05:00" } }, { "ob_id": 281, "relationType": "IsPartOf", "subjectObservation": { "ob_id": 27819, "uuid": "d6bbe115245042dc93ee68caa253d60b", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v201908", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2018.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, "objectObservation": { "ob_id": 1234, "uuid": "b4c028814a666a651f52f2b37a97c7c7", "short_code": "ob", "title": "MIDAS: Global Radiation Observations", "abstract": "The global radiation observation data contain hourly and daily radiation amounts, including those no longer being reported. The measurements of global solar irradiation amount, diffuse solar irradiation amount, direct irradiation amount, irradiation balance amount, and global horizontal illumination are recorded by observation stations worldwide and transmitted within SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data span from 1947 to present." } }, { "ob_id": 282, "relationType": "IsPartOf", "subjectObservation": { "ob_id": 27820, "uuid": "ddcfd8bb1ff44cd2855e81838b40b17c", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v201908", "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2018.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nFor further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, "objectObservation": { "ob_id": 1184, "uuid": "a1f65a362c26c9fa667d98c431a1ad38", "short_code": "ob", "title": "MIDAS: UK Mean Wind Data", "abstract": "The UK mean wind data describes the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data is collected by observation stations across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to present." } }, { "ob_id": 283, "relationType": "IsPartOf", "subjectObservation": { "ob_id": 27821, "uuid": "9972bc173ef94068b2070d4b26f849a7", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v201908", "abstract": "The UK soil temperature data contain daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to 2018.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nAt many stations temperatures below the surface are measured at various depths. The depths used today are 5, 10, 20, 30 and 100cm, although measurements are not necessarily made at all these depths at a station and exceptionally measurements may be made at other depths. When imperial units were in general use, typically before 1961, the normal depths of measurement were 4, 8, 12, 24 and 48 inches.\r\n\r\nLiquid-in-glass soil thermometers at a depth of 20 cm or less are unsheathed and have a bend in the stem between the bulb and the lowest graduation. At greater depths the thermometer is suspended in a steel tube and has its bulb encased in wax.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, "objectObservation": { "ob_id": 1225, "uuid": "8dc05f6ecc6065a5d10fc7b8829589ec", "short_code": "ob", "title": "MIDAS: UK Soil Temperature Data", "abstract": "The UK soil temperature data describes daily and hourly values of soil temperatures at depths of 5, 10, 20, 30, 50, and 100 centimetres. The measurements are recorded by observation stations across the UK and transmitted within NCM or DLY3208 messages. The data spans from 1900 to present." } }, { "ob_id": 284, "relationType": "IsPartOf", "subjectObservation": { "ob_id": 27822, "uuid": "a58b9c8a724e4ec795a40a74455462b7", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v201908", "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2018.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset." }, "objectObservation": { "ob_id": 1251, "uuid": "bbd6916225e7475514e17fdbf11141c1", "short_code": "ob", "title": "MIDAS UK Hourly Rainfall Data", "abstract": "The UK hourly rainfall data describes the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also conatins precipitation amounts, however precipitation measured over 24 hours will not be stored. The data is collected by observation stations across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW, SSER and WAHRAIN. The data spans from 1915 to present." } }, { "ob_id": 285, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27797, "uuid": "3200894e4add4049b31f8df132c0d664", "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 4.0", "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 4.0 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 4.0 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." }, "objectObservation": { "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": 286, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27798, "uuid": "fa199424852d49f4ba85afddd850eae6", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global chlorophyll-a data products gridded on a sinusoidal projection, Version 4.0", "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 4.0 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." }, "objectObservation": { "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": 287, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27799, "uuid": "8fd7c9c728104c209fd88604c2022f26", "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 4.0", "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 4.0 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." }, "objectObservation": { "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": 288, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27800, "uuid": "846a55c8a91b43bba6f3b97aa3e776e2", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global remote sensing reflectance gridded on a sinusoidal projection, Version 4.0", "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 4.0 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 versions of the data are now available." }, "objectObservation": { "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": 289, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27801, "uuid": "b0b9fb9cd7434323b65bbe1dae0a2e94", "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 4.0", "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 4.0 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 versions of the data are now available." }, "objectObservation": { "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": 290, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27802, "uuid": "6f891faf986349f792043ebac64f7938", "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 4.0", "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 4.0 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 4.0 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." }, "objectObservation": { "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": 291, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27803, "uuid": "eef36ac7c892491aa862097e79827f68", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global chlorophyll-a data products gridded on a geographic projection, Version 4.0", "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 4.0 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." }, "objectObservation": { "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": 292, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27804, "uuid": "b9269d708e3e413fba6fbf7cb3419b3a", "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 4.0", "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 4.0 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." }, "objectObservation": { "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": 293, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27805, "uuid": "f56fe5c95e374c1fbaa73dcca8144787", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global remote sensing reflectance gridded on a geographic projection, Version 4.0", "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 4.0 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 versions of the data are now available." }, "objectObservation": { "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": 294, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27806, "uuid": "175105e9c36b49d7b98ebf43579c5cdd", "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 4.0", "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 4.0 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." }, "objectObservation": { "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": 295, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 28137, "uuid": "d134335808894b2bb249e9f222e2eca8", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.0.1.0 (1862-2018)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The data sets cover the UK at 1km x 1km resolution. These 1km x 1km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 26863, "uuid": "2a62652a4fe6412693123dd6328f6dc8", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.0.0.0 (1862-2017)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The data sets cover the UK at 1km x 1km resolution. These 1km x 1km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1862 to 2017, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." } }, { "ob_id": 296, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 28138, "uuid": "8929d37209c24f44ba33a5e11910c363", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 12km grid over the UK, v1.0.1.0 (1862-2018)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The data set at 12 km resolution is derived from the associated 1km x 1km resolution to allow for comparison to data from climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 26871, "uuid": "dc2ef1e4f10144f29591c21051d99d39", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 12km grid over the UK, v1.0.0.0 (1862-2017)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The data set at 12 km resolution is derived from the associated 1km x 1km resolution to allow for comparison to data from climate projections. The dataset spans the period from 1862 to 2017, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." } }, { "ob_id": 297, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 28139, "uuid": "e84aabcd886c41c488b4bd84558ab974", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 25km grid over the UK, v1.0.1.0 (1862-2018)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The data set at 25 km resolution is derived from the associated 1km x 1km resolution to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". 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The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 26877, "uuid": "a2fb07be9622439fa191f0e596f5e4f9", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 60km grid over the UK, v1.0.0.0 (1862-2017)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The data set at 60 km resolution is derived from the associated 1km x 1km resolution to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1862 to 2017, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." } }, { "ob_id": 299, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 28141, "uuid": "e4d28cddec7b4e1ab50eae189070f7dc", "short_code": "ob", "title": "HadUK-Grid Climate Observations by Administrative Regions over the UK, v1.0.1.0 (1862-2018)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. These data at 1km resolution have been averaged across a set of discrete geographies defining UK administrative regions consistent with data from UKCP18 climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 26880, "uuid": "373c4edbcbdd41c3be6c6de6abb5afeb", "short_code": "ob", "title": "HadUK-Grid Climate Observations by Administrative Regions over the UK, v1.0.0.0 (1862-2017)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. These data at 1km resolution have been averaged across a set of discrete geographies defining UK administrative regions consistent with data from UKCP18 climate projections. The dataset spans the period from 1862 to 2017, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." } }, { "ob_id": 300, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 28142, "uuid": "131fd45e37d74bcc82d9a6e12fc1d366", "short_code": "ob", "title": "HadUK-Grid Climate Observations by UK river basins, v1.0.1.0 (1862-2018)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. These data at 1km resolution have been averaged across a set of discrete geographies defining UK river basins consistent with data from UKCP18 climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 26883, "uuid": "607a713e4a0e4a229dac1b23fd6d41a6", "short_code": "ob", "title": "HadUK-Grid Climate Observations by UK river basins, v1.0.0.0 (1862-2017)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. These data at 1km resolution have been averaged across a set of discrete geographies defining UK river basins consistent with data from UKCP18 climate projections. The dataset spans the period from 1862 to 2017, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." } }, { "ob_id": 301, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 28143, "uuid": "1715a1c03e544f47a3e803324f0bf4ca", "short_code": "ob", "title": "HadUK-Grid Climate Observations by UK countries, v1.0.1.0 (1862-2018)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. These data at 1km resolution have been averaged across a set of discrete geographies defining UK countries consistent with data from UKCP18 climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 26886, "uuid": "5c4d012e7fb84bcf87a9dfb481eb657b", "short_code": "ob", "title": "HadUK-Grid Climate Observations by UK countries, v1.0.0.0 (1862-2017)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. These data at 1km resolution have been averaged across a set of discrete geographies defining UK countries consistent with data from UKCP18 climate projections. The dataset spans the period from 1862 to 2017, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." } }, { "ob_id": 302, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 27607, "uuid": "dd63f6f7239f4c1da830950c6e58cfdd", "short_code": "ob", "title": "FIDUCEO: Sea and Lake Surface Temperature Climate Data Record, V2.11, 2006 -2016", "abstract": "The FIDelity and Uncertainty in Climate data records from Earth Observations (FIDUCEO) project Sea and Lake Surface Temperature Climate Data Record core retrieved quantity is the skin (radiometric) temperature of the Earth’s water surfaces (sea and large lakes). This is provided as a best estimate, plus an ensemble of 10 perturbations capturing known uncertainties. The CDR contains grid-cell instantaneous averagesof retrieved surface temperature over ice-free oceans and 300 large lakes.\r\n\r\n\r\nThe FIDUCEO Surface Temperature CDR differs from the ESA Sea Surface Temperature Climate Change Initiative CDRs ; which were generated using in the using the same cloud detection and SST retrieval methodology in the following points:\r\n\r\n- The calibration of the brightness temperatures used is revised for the FIDUCEO ST CDR. The first step in this has been multi-sensor harmonisation to obtain baseline calibration coefficients (Giering et al., 2019). For specific ST application, these coefficients were adjusted such that SSTs had lower bias, using a method of cross-referencing to matched drifting buoys (Merchant et al., 2019)\r\n- Perturbations to the obtained ST and quality level determination are provided for an ensemble of 10 members, for the purpose of propagating uncertainty in ST in complex (large scale, non-linear) applications.\r\n- The FIDUCEO ST CDR includes retrievals over the world’s 300 largest lakes, unlike the SST-only product. (Lakes, including much smaller lakes,are addressed in other CDRs requiring significantly different methodsto cope with the difficulties of small target water bodies.)\r\n\r\nFull documentation including product user guide, tutorials, the scientific basis and relevant publications are available in the documentation." }, "objectObservation": { "ob_id": 27601, "uuid": "631e1f22d1754b78b5a64a3d66f4ce73", "short_code": "ob", "title": "FIDUCEO: Fundamental Climate Data Record of recalibrated brightness temperatures for the Advanced Very-High-Resolution Radiometer (AVHRR) with ten member ensemble of perturbed level1 data, 2006 - 2016, v1.0", "abstract": "This Fundamental Climate Data Record (FDCR) ensemble product contains both recalibrated AVHRR/3 MetOp-A Radiance/Brightness Temperature data with associated metrologically traceable uncertainties in the FIDUCEO FCDR format. It also contains files containing an Ensemble dataset consisting of perturbations to the associated FIDUCEO FCDR radiances and brightness temperatures. By applying the 10 perturbations to the baseline FCDR radiances and brightness temperatures a user is able to generate 10 sets of new measurements whose variance capture the associated underlying uncertainty distributions contained in the Easy FCDR itself. \r\n\r\nThe FIDelity and Uncertainty in Climate data records from Earth Observations (FIDUCEO) project AVHRR FCDR improves on existing AVHRR level-1B: in the infrared the calibration has been improved with a measurement function approach such that the data is of better quality (noise has been reduced, outliers have been filtered) the metrologically traceable uncertainties have been derived together with their associated effects, cross-channel correlations and long-term correlation structures have now been calculated from the processed data and are being understood and used to improve data quality and consistency. For the Ensemble product the sensors have been calibrated against the Advanced Along-Track Scanning Radiometer (AATSR) sensor with additional corrections to calibration parameters which make the data better able to derive sea surface temperature estimates that are consistent with theInternational Comprehensive Ocean-Atmosphere Data Set (ICOADS) drifting buoy network. Because the Ensemble has been tuned for Sea Surface Temperature retrieval it should only be used over ocean scenes." } }, { "ob_id": 303, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 27270, "uuid": "061fc7fd1ca940e7ad685daf146db08f", "short_code": "ob", "title": "University of Bath: King Edward Point Skiymet meteor radar data (2016-2020)", "abstract": "The University of Bath's meteor radar located at the King Edward Point Magnetic Observatory (KEP, 54.2820 S, 36.4930 W) on South Georgia island in the South Atlantic , is an all-sky VHF (Very High Frequency) meteor radar commercially produced Skiymet system. It has been operational since 2016 providing meteor detection and derived wind data in support of the NERC funded South Georgia Wave (SG-WEX) and DRAGON-WEX: The Drake Passage and Southern Ocean Wave Experiments (see linked Project records for further details).\r\n\r\nThe radar detects radio scatter from the ionised trails of individual meteors drifting with the winds of the upper mesosphere, mesopause and lower thermosphere. A low-gain transmitter antenna is used to provide broad illumination of the sky. An array of five receiver antennas act as an interferometer to determine the azimuth and zenith angles of individual meteor echoes. Doppler measurements from each meteor determine the radial drift velocity and the meteor is assumed to be a passive tracer of atmospheric flow. The radar typically detects of order a few thousand meteors per day. These observations can be used to determine zonal and meridional winds in the mesosphere, mesopause and lower thermosphere at heights of about 80 – 100 km and with height and time resolutions of ~ 3 km and 2 hours.\r\n\r\nThe radar produces daily “meteor position data” data files (mpd files) recording the details of each individual meteor echo. In normal operation a few thousand individual meteors are detected per day. See parameter list for details of available data.\r\n\r\nRecordings are made for each individual meteor detected allowing measurements of zonal and meridional wind speeds in the mesosphere and lower thermosphere to be obtained. Meteor count rates vary diurnally and with season, but are usually up to a few thousand meteors per day." }, "objectObservation": { "ob_id": 28240, "uuid": "d1d6f63b4197452495b5d17a95977843", "short_code": "ob", "title": "SG-WEx: British Antarctic Survey Vaisala RS92 radiosonde data from King Edward Point (2015)", "abstract": "The British Antarctic Survey (BAS) operated a Vaisala RS92 radiosonde unit at King Edward Point, South Georgia Islands to support meteor radar data also recorded at the site during the South Georgia Wave Experiment (SG-WEx) project. The sonde ascents took place during two campaigns: January 2015 and June/July 2015 to measure gravity waves. The data are standard radiosonde measurements of temperature, humidity, wind speeds, direction and pressure along the ascent at 10s intervals. These balloon ascents typically continue until the balloon fails in the stratosphere. The highest ascent recorded in these data was around 32km. Some ascents also provide data for parts of the descending part of the flight until the instrumentation failed.\r\n\r\nThe King Edward Point Magnetic Observatory (KEP, 54.2820 S, 36.4930 W) is located on the South Georgia island in the South Atlantic." } }, { "ob_id": 304, "relationType": "IsSupplementTo", "subjectObservation": { "ob_id": 28240, "uuid": "d1d6f63b4197452495b5d17a95977843", "short_code": "ob", "title": "SG-WEx: British Antarctic Survey Vaisala RS92 radiosonde data from King Edward Point (2015)", "abstract": "The British Antarctic Survey (BAS) operated a Vaisala RS92 radiosonde unit at King Edward Point, South Georgia Islands to support meteor radar data also recorded at the site during the South Georgia Wave Experiment (SG-WEx) project. The sonde ascents took place during two campaigns: January 2015 and June/July 2015 to measure gravity waves. The data are standard radiosonde measurements of temperature, humidity, wind speeds, direction and pressure along the ascent at 10s intervals. These balloon ascents typically continue until the balloon fails in the stratosphere. The highest ascent recorded in these data was around 32km. Some ascents also provide data for parts of the descending part of the flight until the instrumentation failed.\r\n\r\nThe King Edward Point Magnetic Observatory (KEP, 54.2820 S, 36.4930 W) is located on the South Georgia island in the South Atlantic." }, "objectObservation": { "ob_id": 27270, "uuid": "061fc7fd1ca940e7ad685daf146db08f", "short_code": "ob", "title": "University of Bath: King Edward Point Skiymet meteor radar data (2016-2020)", "abstract": "The University of Bath's meteor radar located at the King Edward Point Magnetic Observatory (KEP, 54.2820 S, 36.4930 W) on South Georgia island in the South Atlantic , is an all-sky VHF (Very High Frequency) meteor radar commercially produced Skiymet system. It has been operational since 2016 providing meteor detection and derived wind data in support of the NERC funded South Georgia Wave (SG-WEX) and DRAGON-WEX: The Drake Passage and Southern Ocean Wave Experiments (see linked Project records for further details).\r\n\r\nThe radar detects radio scatter from the ionised trails of individual meteors drifting with the winds of the upper mesosphere, mesopause and lower thermosphere. A low-gain transmitter antenna is used to provide broad illumination of the sky. An array of five receiver antennas act as an interferometer to determine the azimuth and zenith angles of individual meteor echoes. Doppler measurements from each meteor determine the radial drift velocity and the meteor is assumed to be a passive tracer of atmospheric flow. The radar typically detects of order a few thousand meteors per day. These observations can be used to determine zonal and meridional winds in the mesosphere, mesopause and lower thermosphere at heights of about 80 – 100 km and with height and time resolutions of ~ 3 km and 2 hours.\r\n\r\nThe radar produces daily “meteor position data” data files (mpd files) recording the details of each individual meteor echo. In normal operation a few thousand individual meteors are detected per day. See parameter list for details of available data.\r\n\r\nRecordings are made for each individual meteor detected allowing measurements of zonal and meridional wind speeds in the mesosphere and lower thermosphere to be obtained. Meteor count rates vary diurnally and with season, but are usually up to a few thousand meteors per day." } }, { "ob_id": 305, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 27673, "uuid": "3a49f746dcdb4ff98e17919c84acbd20", "short_code": "ob", "title": "BITMAP: Tracks of western disturbances transiting Pakistan and north India from various CMIP5 midHolocene experiments", "abstract": "This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation). The dataset was produced utilising data derived from from various simulation output for the WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5) 'mid-Holocene' experiment. Similar datasets were produced using various model output from the WRCP CMIP5 'Historical', 'RCP45' and 'RCP85' experiments and the ECMWF ERA-Interim reanalysis model output, also available within the parent dataset collection.\r\n\r\nThe mid-Holocene period were designed to simulate the climate 6000 years ago, thus the representative date range for these data is circa 4025-4000 BC. Not all available CMIP5 mid-Holocene experiments were chosen for this dataset as the algorithm required 6-hourly output fields which were not available for all runs.\r\n\r\nWestern disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 500 hPa layer. This differs from those tracks from the ECMWF Era-Interim data which were carried out on the 450-300 hPa layer. See linked documentation for details of the algorithms used.\r\n\r\nBITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record." }, "objectObservation": { "ob_id": 22558, "uuid": "5c5963e796b747f7a75acca0394265d1", "short_code": "ob", "title": "WCRP CMIP5: Beijing Climate Center (BCC) bcc-csm1-1 model output for the midHolocene experiment", "abstract": "WCRP CMIP5: Beijing Climate Center (BCC) bcc-csm1-1 model output for the mid-Holocene (midHolocene) experiment. These data cover the following realms: atmos, land, landIce, ocean, ocnBgchem and seaIce; at the following frequencies: 6hr, day, fx, mon and monClim. The runs included the ensemble members: r0i0p0 and r1i1p1.\n\nThe WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5), was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the World Climate Research Program (WCRP) and provided input for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5)." } }, { "ob_id": 306, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 27673, "uuid": "3a49f746dcdb4ff98e17919c84acbd20", "short_code": "ob", "title": "BITMAP: Tracks of western disturbances transiting Pakistan and north India from various CMIP5 midHolocene experiments", "abstract": "This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation). The dataset was produced utilising data derived from from various simulation output for the WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5) 'mid-Holocene' experiment. Similar datasets were produced using various model output from the WRCP CMIP5 'Historical', 'RCP45' and 'RCP85' experiments and the ECMWF ERA-Interim reanalysis model output, also available within the parent dataset collection.\r\n\r\nThe mid-Holocene period were designed to simulate the climate 6000 years ago, thus the representative date range for these data is circa 4025-4000 BC. Not all available CMIP5 mid-Holocene experiments were chosen for this dataset as the algorithm required 6-hourly output fields which were not available for all runs.\r\n\r\nWestern disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 500 hPa layer. This differs from those tracks from the ECMWF Era-Interim data which were carried out on the 450-300 hPa layer. See linked documentation for details of the algorithms used.\r\n\r\nBITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record." }, "objectObservation": { "ob_id": 21158, "uuid": "2eed97ae6ee04fc7a8886ea88e608712", "short_code": "ob", "title": "WCRP CMIP5: The CSIRO-QCCCE team CSIRO-Mk3-6-0 model output for the midHolocene experiment", "abstract": "WCRP CMIP5: The CSIRO-QCCCE team CSIRO-Mk3-6-0 model output for the mid-Holocene (midHolocene) experiment. These data cover the following realms: aerosol, atmos, land, landIce, ocean and seaIce; at the following frequencies: 6hr, day, fx and mon. The runs included the ensemble members: r0i0p0 and r1i1p1.\n\nThe WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5), was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the World Climate Research Program (WCRP) and provided input for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5).\n\nThe CSIRO-QCCCE team consisted of the following agencies: The Commonwealth Scientific and Industrial Research Organisation (CSIRO, Australia) and Queensland Climate Change Centre of Excellence (QCCCE)." } }, { "ob_id": 307, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 27673, "uuid": "3a49f746dcdb4ff98e17919c84acbd20", "short_code": "ob", "title": "BITMAP: Tracks of western disturbances transiting Pakistan and north India from various CMIP5 midHolocene experiments", "abstract": "This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation). The dataset was produced utilising data derived from from various simulation output for the WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5) 'mid-Holocene' experiment. Similar datasets were produced using various model output from the WRCP CMIP5 'Historical', 'RCP45' and 'RCP85' experiments and the ECMWF ERA-Interim reanalysis model output, also available within the parent dataset collection.\r\n\r\nThe mid-Holocene period were designed to simulate the climate 6000 years ago, thus the representative date range for these data is circa 4025-4000 BC. Not all available CMIP5 mid-Holocene experiments were chosen for this dataset as the algorithm required 6-hourly output fields which were not available for all runs.\r\n\r\nWestern disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 500 hPa layer. This differs from those tracks from the ECMWF Era-Interim data which were carried out on the 450-300 hPa layer. See linked documentation for details of the algorithms used.\r\n\r\nBITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record." }, "objectObservation": { "ob_id": 23249, "uuid": "b8f0d443635a4cb49c6f8551b13650de", "short_code": "ob", "title": "WCRP CMIP5: The LASG-CESS team FGOALS-g2 model output for the midHolocene experiment", "abstract": "WCRP CMIP5: The LASG-CESS team FGOALS-g2 model output for the mid-Holocene (midHolocene) experiment. These data cover the following realms: atmos, land, landIce, ocean and seaIce; at the following frequencies: 6hr, day, fx and mon. The runs included the ensemble members: r0i0p0 and r1i1p1.\n\nThe WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5), was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the World Climate Research Program (WCRP) and provided input for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5).\n\nThe LASG-CESS team consisted of the following agencies: Institute of Atmospheric Physics (LASG) and Centre for Earth System Science (CESS)." } }, { "ob_id": 308, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 27673, "uuid": "3a49f746dcdb4ff98e17919c84acbd20", "short_code": "ob", "title": "BITMAP: Tracks of western disturbances transiting Pakistan and north India from various CMIP5 midHolocene experiments", "abstract": "This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation). The dataset was produced utilising data derived from from various simulation output for the WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5) 'mid-Holocene' experiment. Similar datasets were produced using various model output from the WRCP CMIP5 'Historical', 'RCP45' and 'RCP85' experiments and the ECMWF ERA-Interim reanalysis model output, also available within the parent dataset collection.\r\n\r\nThe mid-Holocene period were designed to simulate the climate 6000 years ago, thus the representative date range for these data is circa 4025-4000 BC. Not all available CMIP5 mid-Holocene experiments were chosen for this dataset as the algorithm required 6-hourly output fields which were not available for all runs.\r\n\r\nWestern disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 500 hPa layer. This differs from those tracks from the ECMWF Era-Interim data which were carried out on the 450-300 hPa layer. See linked documentation for details of the algorithms used.\r\n\r\nBITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record." }, "objectObservation": { "ob_id": 20717, "uuid": "3fc3b25ee29b4dc790d6a5992d7d6010", "short_code": "ob", "title": "WCRP CMIP5: Met Office Hadley Centre (MOHC) HadGEM2-CC model output for the midHolocene experiment", "abstract": "WCRP CMIP5: Met Office Hadley Centre (MOHC) HadGEM2-CC model output for the mid-Holocene (midHolocene) experiment. These data cover the following realms: aerosol, atmos, land, landIce, ocean, ocnBgchem and seaIce; at the following frequencies: 6hr, day, fx, mon and yr. The runs included the ensemble members: r0i0p0 and r1i1p1.\n\nThe WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5), was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the World Climate Research Program (WCRP) and provided input for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5)." } }, { "ob_id": 309, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 27673, "uuid": "3a49f746dcdb4ff98e17919c84acbd20", "short_code": "ob", "title": "BITMAP: Tracks of western disturbances transiting Pakistan and north India from various CMIP5 midHolocene experiments", "abstract": "This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation). The dataset was produced utilising data derived from from various simulation output for the WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5) 'mid-Holocene' experiment. Similar datasets were produced using various model output from the WRCP CMIP5 'Historical', 'RCP45' and 'RCP85' experiments and the ECMWF ERA-Interim reanalysis model output, also available within the parent dataset collection.\r\n\r\nThe mid-Holocene period were designed to simulate the climate 6000 years ago, thus the representative date range for these data is circa 4025-4000 BC. Not all available CMIP5 mid-Holocene experiments were chosen for this dataset as the algorithm required 6-hourly output fields which were not available for all runs.\r\n\r\nWestern disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 500 hPa layer. This differs from those tracks from the ECMWF Era-Interim data which were carried out on the 450-300 hPa layer. See linked documentation for details of the algorithms used.\r\n\r\nBITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record." }, "objectObservation": { "ob_id": 20833, "uuid": "55eadfc10b6549ad8eb4de9ac562cfa5", "short_code": "ob", "title": "WCRP CMIP5: Institut Pierre-Simon Laplace (IPSL) IPSL-CM5A-LR model output for the midHolocene experiment", "abstract": "WCRP CMIP5: Institut Pierre-Simon Laplace (IPSL) IPSL-CM5A-LR model output for the mid-Holocene (midHolocene) experiment. These data cover the following realms: aerosol, atmos, land, ocean, ocnBgchem and seaIce; at the following frequencies: 6hr, day, fx and mon. The runs included the ensemble members: r0i0p0 and r1i1p1.\n\nThe WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5), was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the World Climate Research Program (WCRP) and provided input for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5)." } }, { "ob_id": 310, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 27673, "uuid": "3a49f746dcdb4ff98e17919c84acbd20", "short_code": "ob", "title": "BITMAP: Tracks of western disturbances transiting Pakistan and north India from various CMIP5 midHolocene experiments", "abstract": "This dataset contains tracks generated using a bespoke tracking algorithm developed within the BITMAP (Better understanding of Interregional Teleconnections for prediction in the Monsoon And Poles) project, identifying and linking upper-tropospheric vortices (described in Hunt et al, 2018, QJRMS - see linked documentation). The dataset was produced utilising data derived from from various simulation output for the WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5) 'mid-Holocene' experiment. Similar datasets were produced using various model output from the WRCP CMIP5 'Historical', 'RCP45' and 'RCP85' experiments and the ECMWF ERA-Interim reanalysis model output, also available within the parent dataset collection.\r\n\r\nThe mid-Holocene period were designed to simulate the climate 6000 years ago, thus the representative date range for these data is circa 4025-4000 BC. Not all available CMIP5 mid-Holocene experiments were chosen for this dataset as the algorithm required 6-hourly output fields which were not available for all runs.\r\n\r\nWestern disturbances (WDs) are upper-level vortices that can significantly impact the weather over Pakistan and north India. This is a catalogue of the tracks of WDs passing through the region (specifically 20-36.5N, 60-80E) on the 500 hPa layer. This differs from those tracks from the ECMWF Era-Interim data which were carried out on the 450-300 hPa layer. See linked documentation for details of the algorithms used.\r\n\r\nBITMAP was an Indo-UK-German project (NERC grant award NE/P006795/1) to develop better understanding of processes linking the Arctic and Asian monsoon, leading to better prospects for prediction on short, seasonal and decadal scales in both regions. Recent work had suggested that the pole-to-equator temperature difference is an essential ingredient driving variations in the monsoon. For further details on the project itself see the linked Project record." }, "objectObservation": { "ob_id": 22824, "uuid": "dbbcf3f64bc44f92b286eaf0c837d35f", "short_code": "ob", "title": "WCRP CMIP5: Max Planck Institute for Meteorology (MPI-M) MPI-ESM-P model output for the midHolocene experiment", "abstract": "WCRP CMIP5: Max Planck Institute for Meteorology (MPI-M) MPI-ESM-P model output for the mid-Holocene (midHolocene) experiment. These data cover the following realms: atmos, land, landIce, ocean and seaIce; at the following frequencies: 6hr, day, fx, mon and monClim. The runs included the ensemble members: r0i0p0, r1i1p1 and r1i1p2.\n\nThe WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5), was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the World Climate Research Program (WCRP) and provided input for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5)." } }, { "ob_id": 311, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 26982, "uuid": "2083b33b5c3d4cf0acb9a49226789caa", "short_code": "ob", "title": "FIDUCEO: Microwave Upper Troposheric Humidity and Uncertainties, Climate Data Record, 1994-2017, V1.2", "abstract": "The The FIDelity and Uncertainty in Climate data records from Earth Observations (FIDUCEO) project Upper Tropospheric Humidity (UTH) Climate Data Record version 1.2 dataset is derived from satellite brightness temperatures and uncertainties from the FIDUCEO Microwave Fundamental Climate Data Record (FCDR). The instantaneous observations from the FIDUCEO Microwave FCDR are used to derive a spatio-temporal averaged data record, which contains monthly mean UTH and brightness temperature mapped to a regular latitude/longitude grid covering the tropical region (-30° to 30° N), with a spatial resolution of 1° x 1°. It covers all mission years of the Special Senson Microwave for Temperature (SSMT2) instrument on the F11, F12, F14, F15 satellites, the Advanced Mircowave Sounding Unit (AMSU-B ) instrument on the NOAA 15-17 satellites and the Microwave Humidity Sounder (MHS) instruments on the NOAA18, NOAA19, MetopA, Metop-B satellites. \r\n\r\nFull documentation including product user guide, tutorials and relevant publications are available in the documentation" }, "objectObservation": { "ob_id": 26981, "uuid": "a8e9f44965434f3b861eba77688701ef", "short_code": "ob", "title": "FIDUCEO: Fundamental Climate Data Record of Microwave Brightness Temperatures with uncertainties, 1994 - 2017, v4.1", "abstract": "The FIDUCEO Microwave Fundamental Climate data record, v4.1, contains microwave brightness temperatures and uncertainties for series of satellite instruments (all mission years of SSMT2 on F11, F12, F14, F15; AMSU-B on NOAA15, NOAA16 and NOAA17; and MHS missions (NOAA18, NOAA19, MetopA,-B)). The presented FCDR is a long data record of increased consistency among the instruments compared to the operational data record and is a long enough data record to generate climate data records (CDRs) for climate research. The improvements are based on the strict application of the measurement equation as well as dedicated corrections and improvements within the calibration process. The data record contains quantified uncertainty components, respecting the correlation behaviour of underlying effects.\r\n\r\nFull documentation including product user guide, tutorials, the scientific basis and relevant publications are available in the documentation" } }, { "ob_id": 312, "relationType": "IsNewVersionOf", "subjectObservation": { "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." }, "objectObservation": { "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": 313, "relationType": "IsNewVersionOf", "subjectObservation": { "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." }, "objectObservation": { "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": 314, "relationType": "IsNewVersionOf", "subjectObservation": { "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." }, "objectObservation": { "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": 315, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 29931, "uuid": "34090d316d514b55b7080a4181a28f8f", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED Product, Version 04.5", "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) Climate Change Initiative (CCI) project. The product has been created by directly merging Level 2 scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. \r\n\r\nThe v04.5 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 2018-12-31. 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. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" }, "objectObservation": { "ob_id": 27110, "uuid": "a341b3dcb0d8416498acc70dd14faa6e", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED Product, Version 04.4", "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 directly merging Level 2 scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. \r\n\r\nThe v04.4 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 2018-06-30. 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": 316, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 29935, "uuid": "4a29dbf40fc3445395d72927700fafe7", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the ACTIVE, PASSIVE and COMBINED products, Version 04.5", "abstract": "These ancillary datasets were used in the production of the ACTIVE, PASSIVE and COMBINED soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v04.5 Soil Moisture CCI data.\r\n\r\nThe ACTIVE, PASSIVE and COMBINED soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" }, "objectObservation": { "ob_id": 27113, "uuid": "dff5410043ee4d2094cdf3b9b5284a63", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the ACTIVE, PASSIVE and COMBINED products, Version 04.4", "abstract": "These ancillary datasets were used in the production of the ACTIVE, PASSIVE and COMBINED soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v04.4 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": 317, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 29933, "uuid": "4b344dac208f4a82a35d544f6837d111", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE Product, Version 04.5", "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) Climate Change Initiative (CCI) project. The product has been created by merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v04.5 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 2018-12-31. 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. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" }, "objectObservation": { "ob_id": 27108, "uuid": "bac3632d641642988c4abf55c587eed0", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE Product, Version 04.4", "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 merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v04.4 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 2018-06-30. 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": 318, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 29929, "uuid": "20babc8f4dc449eaac11f47708e9f721", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE Product, Version 04.5", "abstract": "The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created. \r\n\r\nThe v04.5 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 2018-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" }, "objectObservation": { "ob_id": 27092, "uuid": "8d4360b5c6cd48eb967286da31b33567", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE Product, Version 04.4", "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. \r\n\r\nThe v04.4 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 2018-06-30 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014" } }, { "ob_id": 319, "relationType": "IsNewVersionOf", "subjectObservation": { "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." }, "objectObservation": { "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": 320, "relationType": "IsNewVersionOf", "subjectObservation": { "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." }, "objectObservation": { "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": 321, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30114, "uuid": "4ca242208e904efe830af45f1697f730", "short_code": "ob", "title": "A simulated Northern Hemisphere terrestrial climate dataset for the past 60,000 years (version 2)", "abstract": "We present a continuous land climate reconstruction dataset extending from 60 kyr before present to the pre-industrial period at 0.5deg resolution on a monthly timestep for 0degN to 90degN. It has been generated from 42 discrete snapshot simulations using the HadCM3B-M2.1 coupled general circulation model. We incorporate Dansgaard-Oeschger (DO) and Heinrich events to represent millennial scale variability, based on a temperature reconstruction from Greenland ice-cores, with a spatial fingerprint based on a freshwater hosing simulation with HadCM3B-M2.1. Interannual variability is also added and derived from the initial snapshot simulations. Model output has been downscaled to 0.5deg resolution (using simple bilinear interpolation) and bias corrected using either the University of East Anglia, Climate Research Unit observational data (for temperature, precipitation, windchill, and minimum monthly temperature), or the EWEMBI dataset (for incoming shortwave energy). Here we provide datasets for; surface air temperature, precipitation, incoming shortwave energy, wind-chill, snow depth (as snow water equivalent), number of rainy days per month, minimum monthly temperature, and the land-sea mask and ice fractions used in the simulations. The datasets are in the form of NetCDF files. The variables are represented by a set of 24 files that have been compressed into nine folders: temp, precip, down_sw, wind_chill, snow, rainy_days, tempmonmin, landmask and icefrac. Each file represents 2500 years. The landmask and ice fraction are provided annually, whereas the climate variables are given as monthly files equivalent to 30000 months, between the latitudes 0deg to 90degN at 0.5deg resolution. Each of the climate files therefore have the dimensions 180 (lat) x 720 (lon) x 30000 (month). We also provide an example subset of the temperature dataset, which gives decadal averages for each month for 0-2500 years." }, "objectObservation": { "ob_id": 26559, "uuid": "de6591c3d5d44b08b4d954410f353c6e", "short_code": "ob", "title": "A simulated Northern Hemisphere terrestrial climate dataset for the past 60,000 years", "abstract": "We present a continuous land climate reconstruction dataset extending from 60 kyr before present to the pre-industrial period at 0.5deg resolution on a monthly timestep for 0degN to 90degN. It has been generated from 42 discrete snapshot simulations using the HadCM3B-M2.1 coupled general circulation model. We incorporate Dansgaard-Oeschger (DO) and Heinrich events to represent millennial scale variability, based on a temperature reconstruction from Greenland ice-cores, with a spatial fingerprint based\r\n on a freshwater hosing simulation with HadCM3B-M2.1. Interannual variability is also added and derived from the initial snapshot simulations. Model output has been downscaled to 0.5deg resolution (using simple bilinear interpolation) and bias corrected using either the University of East Anglia, Climate Research Unit observational data (for temperature, precipitation, windchill, and minimum monthly temperature), or the EWEMBI dataset (for incoming shortwave energy). Here we provide datasets for; surface air temperature, precipitation, incoming shortwave energy, wind-chill, snow depth (as snow water equivalent), number of rainy days per month, minimum monthly temperature, and the land-sea mask and ice fractions used in the simulations. The datasets are in the form of NetCDF files. The variables are represented by a set of 24 files that have been compressed into nine folders: temp, precip, down_sw, wind_chill, snow, rainy_days, tempmonmin, landmask and icefrac. Each file represents 2500 years. The landmask and ice fraction are provided annually, whereas the climate variables are given as monthly files equivalent to 30000 months, between the latitudes 0deg to 90degN at 0.5deg resolution. Each of the climate files therefore have the dimensions 180 (lat) x 720 (lon) x 30000 (month). We also provide an example subset of the temperature dataset, which gives decadal averages for each month for 0-2500 years." } }, { "ob_id": 322, "relationType": "IsNewVersionOf", "subjectObservation": { "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" }, "objectObservation": { "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": 323, "relationType": "IsNewVersionOf", "subjectObservation": { "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." }, "objectObservation": { "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": 324, "relationType": "IsNewVersionOf", "subjectObservation": { "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." }, "objectObservation": { "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." } } ] }