Related Observation Info List
Get a list of RelatedObservationInfo objects.
GET /api/v3/relatedobservationinfos/?format=api&offset=900
{ "count": 1153, "next": "https://api.catalogue.ceda.ac.uk/api/v3/relatedobservationinfos/?format=api&limit=100&offset=1000", "previous": "https://api.catalogue.ceda.ac.uk/api/v3/relatedobservationinfos/?format=api&limit=100&offset=800", "results": [ { "ob_id": 962, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 42327, "uuid": "a508838f92c74005a26b9277eae59a7c", "short_code": "ob", "title": "HadUK-Grid Climate Observations by UK countries, v1.3.0.ceda (1836-2023)", "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 1 km resolution have been averaged across a set of discrete geographies defining UK countries consistent with data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n\r\n * Added data for calendar year 2023\r\n \r\n* Added newly digitised data for monthly sunshine 1910-1918\r\n\r\n * Added Rainfall Rescue version 2 doi:10.5281/zenodo.7554242\r\n\r\n * Updated shapefiles used for production of area average statistics https://github.com/ukcp-data/ukcp-spatial-files\r\n\r\n * Updated controlled vocabulary for metadata assignment https://github.com/ukcp-data/UKCP18_CVs\r\n\r\n * Updated assignment of timepoint for some periods so that the datetime is the middle of the period (e.g. season) rather than a fixed offset from the period start.\r\n\r\n * Updated ordering of regions within regional values files. Alphabetical ordering.\r\n\r\n * Files use netcdf level 4 compression using gzip https://www.unidata.ucar.edu/blogs/developer/entry/netcdf_compression\r\n\r\n* Net changes to the input station data used to generate this dataset:\r\n\r\n- Total of 125601744 observations\r\n\r\n- 122621050 (97.6%) unchanged\r\n\r\n- 26700 (0.02%) modified for this version\r\n\r\n- 2953994 (2.35%) added in this version\r\n\r\n- 16315 (0.01%) deleted from this version\r\n\r\n* Changes to monthly rainfall 1836-1960\r\n\r\n- Total of 4823973 observations\r\n\r\n- 3315657 (68.7%) unchanged\r\n\r\n- 21029 (0.4%) modified for this version\r\n\r\n- 1487287 (30.8%) added in this version\r\n\r\n- 11155 (0.2%) deleted from this version\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 963, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 42328, "uuid": "8a51496be92b4e9488954c7c0199f3f9", "short_code": "ob", "title": "HadUK-Grid Climate Observations by Administrative Regions over the UK, v1.3.0.ceda (1836-2023)", "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 1 km resolution have been averaged across a set of discrete geographies defining UK administrative regions consistent with data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023 but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 964, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 42326, "uuid": "b1282951f38947da93c0b0db31bb8419", "short_code": "ob", "title": "HadUK-Grid Climate Observations by UK river basins, v1.3.0.ceda (1836-2023)", "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 1 km resolution have been averaged across a set of discrete geographies defining UK river basins consistent with data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 965, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 42325, "uuid": "5a248096468640a6bfb0dfda8b018ac5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 12km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The dataset at 12 km resolution is derived from the associated 1 km x 1 km resolution to allow for comparison to data from climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation). \r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 966, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 42323, "uuid": "18ddbb686be549bfadfecbe0c673f405", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 25km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The dataset at 25 km resolution is derived from the associated 1 km x 1 km resolution to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 967, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 42322, "uuid": "5ba67d62cdc249a3bc5b1c38b339beb3", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 5km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The dataset at 5 km resolution is derived from the associated 1 km x 1 km resolution to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 968, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 42321, "uuid": "c22d0b462321447882d2d1367cc77d3c", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 60km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The dataset at 60 km resolution is derived from the associated 1 km x 1 km resolution to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution.\r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 969, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 42335, "uuid": "8070d47e1b7340468fa7cf654dee938b", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v202407", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1887 to 2023. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.\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": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 970, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 42331, "uuid": "91cb9985a6c2453d99084bde4ff5f314", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v202407", "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 2023.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.\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": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 971, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 42332, "uuid": "c50776e4903942cdb329589da70b83fe", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v202407", "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 2023.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.\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": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 972, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 42334, "uuid": "6c619c67138843b8839a5788ac749e12", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v202407", "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 2023.\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": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 973, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 42336, "uuid": "b7c6295b72c54fa9bcd8308fea2727e7", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v202407", "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 2023. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.\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": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 974, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 42337, "uuid": "8606115371e44b079e25d479cfec465c", "short_code": "ob", "title": "MIDAS Open: UK daily rainfall data, v202407", "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 2023. 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 (202308) of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.\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": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 975, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 42330, "uuid": "a6bb3e8def544b5790d4b05a6f37f901", "short_code": "ob", "title": "MIDAS Open: UK soil temperature data, v202407", "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 2023.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.\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": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 976, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 42333, "uuid": "0afba628c2f4462da68b0a81ebf1ff4c", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v202407", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light. \r\n\r\nFor details about the different measurements made and the limited number of sites making them please see the MIDAS Solar Irradiance table linked to in the online resources section of this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2023.\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 2023.\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": 42324, "uuid": "b963ead70580451aa7455782224479d5", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.3.0.ceda (1836-2023)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The datasets cover the UK at 1 km x 1 km resolution. These 1 km x 1 km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1836 to 2023, but the start time is dependent on climate variable and temporal resolution. \r\n\r\nThe gridded data are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the previous versions of this dataset which also superseded UKCP09 gridded observations. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2019, see linked documentation).\r\n\r\nThe changes for v1.3.0.ceda HadUK-Grid datasets are as follows:\r\n \r\n* Added data for calendar year 2023\r\n \r\n* Added newly digitised data for daily rainfall (62 Scottish stations for 1945-1960)\r\n \r\n* Daily rainfall data for Bolton, 1916-1919 have been corrected (previous values were corrupted and needed redigitising)\r\n \r\n* Daily rainfall data for Buxton, 1960 have been corrected (conversion from inches to mm had been applied incorrectly)\r\n \r\n* Rainfall data from EA and SEPA APIs are included for the last three months of the dataset (Oct-Dec 2023) (for all earlier months the rainfall data from partner agencies is obtained from the Met Office's MIDAS database)\r\n \r\n* The number of stations used for groundfrost, sunshine and windspeed have reduced at different points in the historical series when comparing v1.3.0.ceda to the previous version v1.2.0.ceda. These reductions in station numbers have been caused by changes made in the data processing steps upstream of the gridding process.\r\n \r\n* For groundfrost this reduction has been caused by an automated quality control process flagging the historical data which have been removed as suspect (mostly affecting data from 1961 to 1970).\r\n \r\n* For sunshine the small reduction in the 1960s has been caused by the removal of digitized monthly sunshine data through this period where we wish to reverify the data source.\r\n \r\n* For windspeed the reduction from 1969 to 2010 has been caused by changes to rules applied relating to data completeness when compiling daily mean windspeeds, which in turn have followed through to monthly statistics.\r\n \r\n* We plan to carry out a review of the data which have been excluded from this version. Some of it may be reintroduced in a future release.\r\n \r\n* Net changes to the input station data:\r\n \r\n- Total of 126970983 observations\r\n- 125384735 (98.75%) unchanged\r\n- 28487 (0.02%) modified for this version\r\n- 1557761 (1.23%) added in this version\r\n- 188522 (0.15%) deleted from this version\r\n \r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." } }, { "ob_id": 977, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 41610, "uuid": "5b1caf9095d7412282f5ba6b558034e3", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE product, Version 09.1", "abstract": "The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The ACTIVE product has been created by fusing scatterometer soil moisture products, derived from the active remote sensing instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created.\r\n\r\nThe v09.1 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2023-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896." }, "objectObservation": { "ob_id": 40763, "uuid": "b0f5fc3a10cf4806ab57326edd8daf65", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE product, Version 08.1", "abstract": "The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The ACTIVE product has been created by fusing scatterometer soil moisture products, derived from the active remote sensing instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created.\r\n\r\nThe v08.1 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2022-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896." } }, { "ob_id": 978, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 41611, "uuid": "ca55ac11fc814b0d95e68a34a10539c1", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE product, Version 09.1", "abstract": "The Soil Moisture CCI PASSIVE dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The PASSIVE product has been created by merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP passive remote sensing satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v09.1 PASSIVE 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 2023-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896." }, "objectObservation": { "ob_id": 40764, "uuid": "16dc7da110324e5196e922191d962157", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE product, Version 08.1", "abstract": "The Soil Moisture CCI PASSIVE dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The PASSIVE product has been created by merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP passive remote sensing satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v08.1 PASSIVE 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 2022-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896." } }, { "ob_id": 979, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 41612, "uuid": "0e346e1e1e164ac99c60098848537a29", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED product, Version 09.1", "abstract": "The Soil Moisture CCI COMBINED dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The COMBINED product has been created by directly merging Level 2 scatterometer ('active' remote sensing) and radiometer ('passive' remote sensing) soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v09.1 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 2023-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896." }, "objectObservation": { "ob_id": 40765, "uuid": "6f99cdb86a9e4d3da2d47c79612c00a2", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED product, Version 08.1", "abstract": "The Soil Moisture CCI COMBINED dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The COMBINED product has been created by directly merging Level 2 scatterometer ('active' remote sensing) and radiometer ('passive' remote sensing) soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v08.1 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 2022-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896." } }, { "ob_id": 980, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43056, "uuid": "7c95469ae2b7454cb389fc18ff5ce26b", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the ACTIVE, PASSIVE and COMBINED products, Version 09.1", "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 v09.1 Soil Moisture CCI data.\r\n\r\nThe ACTIVE, PASSIVE and COMBINED soil moisture products which these data were used to develop are fusions of scatterometer (i.e. active remote sensing) and radiometer (i.e. passive remote sensing) soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP 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 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. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896." }, "objectObservation": { "ob_id": 40766, "uuid": "010243ea38f3473a885d2ccd9cfb77ab", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the ACTIVE, PASSIVE and COMBINED products, Version 08.1", "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 v08.1 Soil Moisture CCI data.\r\n\r\nThe ACTIVE, PASSIVE and COMBINED soil moisture products which these data were used to develop are fusions of scatterometer (i.e. active remote sensing) and radiometer (i.e. passive remote sensing) soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP 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 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. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896." } }, { "ob_id": 981, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 40763, "uuid": "b0f5fc3a10cf4806ab57326edd8daf65", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE product, Version 08.1", "abstract": "The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The ACTIVE product has been created by fusing scatterometer soil moisture products, derived from the active remote sensing instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created.\r\n\r\nThe v08.1 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2022-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896." }, "objectObservation": { "ob_id": 38331, "uuid": "e235d2980d6a441895f7221ff4787a6f", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE product, Version 07.1", "abstract": "The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) 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 v07.1 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2021-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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" } }, { "ob_id": 982, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 40764, "uuid": "16dc7da110324e5196e922191d962157", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE product, Version 08.1", "abstract": "The Soil Moisture CCI PASSIVE dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The PASSIVE product has been created by merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP passive remote sensing satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v08.1 PASSIVE 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 2022-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896." }, "objectObservation": { "ob_id": 38332, "uuid": "63e14c1e66124ccc857ce4e73ab601ed", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE product, Version 07.1", "abstract": "The Soil Moisture CCI PASSIVE dataset is one of 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, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v07.1 PASSIVE 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 2021-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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" } }, { "ob_id": 983, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 40765, "uuid": "6f99cdb86a9e4d3da2d47c79612c00a2", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED product, Version 08.1", "abstract": "The Soil Moisture CCI COMBINED dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The COMBINED product has been created by directly merging Level 2 scatterometer ('active' remote sensing) and radiometer ('passive' remote sensing) soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v08.1 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 2022-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896." }, "objectObservation": { "ob_id": 38334, "uuid": "0ae6b18caf8a4aeba7359f11b8ad49ae", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Experimental Break-Adjusted COMBINED Product, Version 07.1", "abstract": "An experimental break-adjusted soil-moisture product has been generated by the ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci) project for their v07.1 data release. The product attempts to reduce breaks in the final CCI product by matching the statistics of the datasets between merging periods. At v07.1, the break-adjustment process (explained in Preimesberger et al. 2020) is applied only to the COMBINED product, using ERA5 soil moisture as a reference. The Soil Moisture CCI COMBINED dataset is one of 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, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v07.1 COMBINED break-adjusted 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 2021-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document and Preimesberger et al. 2020. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using all 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. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896." } }, { "ob_id": 984, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 40765, "uuid": "6f99cdb86a9e4d3da2d47c79612c00a2", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED product, Version 08.1", "abstract": "The Soil Moisture CCI COMBINED dataset is one of three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The COMBINED product has been created by directly merging Level 2 scatterometer ('active' remote sensing) and radiometer ('passive' remote sensing) soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v08.1 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 2022-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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. Preimesberger, W., Scanlon, T., Su, C. -H., Gruber, A. and Dorigo, W., \"Homogenization of Structural Breaks in the Global ESA CCI Soil Moisture Multisatellite Climate Data Record,\" in IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 4, pp. 2845-2862, April 2021, doi: 10.1109/TGRS.2020.3012896." }, "objectObservation": { "ob_id": 38333, "uuid": "c7e974411cfe4cf99cb077f7cb4d75d4", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED product, Version 07.1", "abstract": "The Soil Moisture CCI COMBINED dataset is one of 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, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v07.1 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 2021-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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" } }, { "ob_id": 985, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 38331, "uuid": "e235d2980d6a441895f7221ff4787a6f", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE product, Version 07.1", "abstract": "The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) 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 v07.1 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2021-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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" }, "objectObservation": { "ob_id": 38326, "uuid": "898c950f441e400d8b569216ebe41cab", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE product, Version 06.2", "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) 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 v06.2 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 is provided in percent of saturation [%] and covers the period (yyyy-mm-dd) 1991-08-05 to 2021-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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" } }, { "ob_id": 986, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 38332, "uuid": "63e14c1e66124ccc857ce4e73ab601ed", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE product, Version 07.1", "abstract": "The Soil Moisture CCI PASSIVE dataset is one of 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, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v07.1 PASSIVE 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 2021-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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" }, "objectObservation": { "ob_id": 38327, "uuid": "4dd145a7060143cd875325390d3b01c8", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE product, Version 06.2", "abstract": "The Soil Moisture CCI PASSIVE dataset is one of 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, SMOS, SMAP, FY-3B and GPM satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v06.2 PASSIVE 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 2021-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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" } }, { "ob_id": 987, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 38333, "uuid": "c7e974411cfe4cf99cb077f7cb4d75d4", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED product, Version 07.1", "abstract": "The Soil Moisture CCI COMBINED dataset is one of 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, FY-3B, FY-3C, FY3D, AMSR2, SMOS, GPM and SMAP satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v07.1 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 2021-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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" }, "objectObservation": { "ob_id": 38328, "uuid": "e83e62dd493447c5808f80c36b5acac7", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED product, Version 06.2", "abstract": "The Soil Moisture CCI COMBINED dataset is one of 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, SMOS, SMAP, FY-3B and GPM satellite instruments. PASSIVE and ACTIVE products have also been created.\r\n\r\nThe v06.2 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 2021-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project website.\r\n\r\nThe data set should be cited using 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" } }, { "ob_id": 988, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 40356, "uuid": "56ff07acabab42888afe2d20b488ec49", "short_code": "ob", "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from AVHRR (1979 - 2022), version 3.0", "abstract": "This dataset contains Daily Snow Cover Fraction (snow on ground) from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme. \r\n\r\nSnow cover fraction on ground (SCFG) indicates the area of snow observed from space over land surfaces, in forested areas corrected for the transmissivity of the forest canopy. The SCFG is given in percentage (%) per pixel. \r\n\r\nThe global SCFG product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.\r\n\r\nThe SCFG time series provides daily products for the period 1979-2022. \r\n\r\nThe product is based on medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the CLARA-A3 cloud product. \r\n\r\nThe retrieval method of the snow_cci SCFG product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.63 µm and 1.61 µm (channel 3a or the reflective part of channel 3b (ref3b)), and an emissive band centred at about 10.8 µm. The snow_cci snow cover mapping algorithm is a three-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFG retrieval method is applied. Finally, a post-processing removes erroneous snow pixels caused either by falsely classified clouds in the tropics or by unreliable ref3b values at a global scale. \r\n\r\nThe following auxiliary data sets are used for product generation: i) ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 50 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map; ii) Forest canopy transmissivity map; this layer is based on the tree cover classes of the ESA CCI Land Cover 2000 data set and the tree cover density map from Landsat data for the year 2000 (Hansen et al., Science, 2013, DOI: 10.1126/science.1244693). This layer is used to apply a forest canopy correction and estimate in forested areas the fractional snow cover on ground.\r\n\r\nThe SCFG product is aimed to serve the needs of users working in cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\n\r\nThe Remote Sensing Research Group of the University of Bern, in cooperation with Gamma Remote Sensing is responsible for the SCFG product development and generation. ENVEO (ENVironmental Earth Observation IT GmbH) developed and prepared all auxiliary data sets used for the product generation.\r\n\r\nThe SCFG AVHRR product comprises a few data gaps in 1979 – 1986 (1979: 22.-24.Feb.; 01.-07.Oct.; 03.-04.Nov.; 07.Nov.; 17.-18.Nov.; 1980: 22.-27.Feb.; 01.March; 03.March; 15.-20.March; 30.March – 02.April; 26.-29.June; 12.-19.July; 12.-18.Dec.; 1981: 09.-11.May; 01.-03.Aug.; 14.-23.Aug.; 1982: 28.- 31.May; 25.-26. Oct.; 1983: 27.- 31. July; 01.- 02. and 06. Aug.; 1984: 14.-15.Jan.; 06. Dec.; 1985: 01.- 24.Feb; 1986: 15. March), resulting in a 99% data coverage over the entire study period of 43 years." }, "objectObservation": { "ob_id": 33062, "uuid": "3f034f4a08854eb59d58e1fa92d207b6", "short_code": "ob", "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from AVHRR (1982 - 2018), version 2.0", "abstract": "This dataset contains Daily Snow Cover Fraction (snow on ground) from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme. \r\n\r\nSnow cover fraction on ground (SCFG) indicates the area of snow observed from space over land surfaces, in forested areas corrected for the transmissivity of the forest canopy. The SCFG is given in percentage (%) per pixel. \r\n\r\nThe global SCFG product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.\r\n\r\nThe SCFG time series provides daily products for the period 1982-2018. \r\n\r\nThe product is based on medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the Cloud CCI cloud v3.0 mask product. \r\n\r\nThe retrieval method of the snow_cci SCFG product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.63 µm and 1.61 µm (channel 3a or the reflective part of channel 3b (ref3b)), and an emissive band centred at about 10.8 µm. The snow_cci snow cover mapping algorithm is a three-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFG retrieval method is applied. Finally, a post-processing removes erroneous snow pixels caused either by falsely classified clouds in the tropics or by unreliable ref3b values at a global scale. \r\n\r\nThe following auxiliary data sets are used for product generation: i) ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 50 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map; ii) Forest canopy transmissivity map; this layer is based on the tree cover classes of the ESA CCI Land Cover 2000 data set and the tree cover density map from Landsat data for the year 2000 (Hansen et al., Science, 2013, DOI: 10.1126/science.1244693). This layer is used to apply a forest canopy correction and estimate in forested areas the fractional snow cover on ground.\r\n\r\nThe SCFG product is aimed to serve the needs of users working in cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\n\r\nThe Remote Sensing Research Group of the University of Bern is responsible for the SCFG product development and generation. ENVEO developed and prepared all auxiliary data sets used for the product generation.\r\n\r\nThe SCFG AVHRR product comprises one longer data gap of 92 between November 1994 and January 1995, and 16 individual daily gaps, resulting in a 99% data coverage over the entire study period of 37 years." } }, { "ob_id": 989, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 40357, "uuid": "7491427f8c3442ce825ba5472c224322", "short_code": "ob", "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable (SCFV) from AVHRR (1979 - 2022), version 3.0", "abstract": "This dataset contains Daily Snow Cover Fraction of viewable snow from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme. \r\n\r\nSnow cover fraction viewable (SCFV) indicates the area of snow viewable from space over land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. \r\n\r\nThe global SCFV product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.\r\n\r\nThe SCFV time series provides daily products for the period 1979-2022. \r\n\r\nThe product is based on medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the CLARA-A3 cloud product. \r\n\r\nThe retrieval method of the snow_cci SCFV product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre- and post-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.630 µm and 1.61 µm (channel 3a or the reflective part of channel 3b (ref3b)), and an emissive band centred at about 10.8 µm. The snow_cci snow cover mapping algorithm is a three-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFV retrieval method is applied. Finally, a post-processing removes erroneous snow pixels caused either by falsely classified clouds in the tropics or by unreliable ref3b values at a global scale. \r\n\r\nThe following auxiliary data set is used for product generation: ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 50 percent of the pixel is classified as water; permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map.\r\n\r\nThe SCFV product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology and biology.\r\n\r\nThe Remote Sensing Research Group of the University of Bern, in cooperation with Gamma Remote Sensing is responsible for the SCFV product development and generation. ENVEO (ENVironmental Earth Observation IT GmbH) developed and prepared all auxiliary data sets used for the product generation. \r\n\r\nThe SCFV AVHRR product comprises a few data gaps in 1979 – 1986 (1979: 22.-24.Feb.; 01.-07.Oct.; 03.-04.Nov.; 07.Nov.; 17.-18.Nov.; 1980: 22.-27.Feb.; 01.March; 03.March; 15.-20.March; 30.March – 02.April; 26.-29.June; 12.-19.July; 12.-18.Dec.; 1981: 09.-11.May; 01.-03.Aug.; 14.-23.Aug.; 1982: 28.- 31.May; 25.-26. Oct.; 1983: 27.- 31. July; 01.- 02. and 06. Aug.; 1984: 14.-15.Jan.; 06. Dec.; 1985: 01.- 24.Feb; 1986: 15. March), resulting in a 99% data coverage over the entire study period of 43 years." }, "objectObservation": { "ob_id": 33061, "uuid": "763eb87e0682446cafa8c74488dd5fb8", "short_code": "ob", "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable (SCFV) from AVHRR (1982 - 2018), version 2.0", "abstract": "This dataset contains Daily Snow Cover Fraction of viewable snow from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme. \r\n\r\nSnow cover fraction viewable (SCFV) indicates the area of snow viewable from space over land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. \r\n\r\nThe global SCFV product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.\r\n\r\nThe SCFV time series provides daily products for the period 1982-2018. \r\n\r\nThe product is based on medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the Cloud CCI cloud v3.0 mask product. \r\n\r\nThe retrieval method of the snow_cci SCFV product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre- and post-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.630 µm and 1.61 µm (channel 3a or the reflective part of channel 3b (ref3b)), and an emissive band centred at about 10.8 µm. The snow_cci snow cover mapping algorithm is a three-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFV retrieval method is applied. Finally, a post-processing removes erroneous snow pixels caused either by falsely classified clouds in the tropics or by unreliable ref3b values at a global scale. \r\n\r\nThe following auxiliary data set is used for product generation: ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 50 percent of the pixel is classified as water; permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map.\r\n\r\nThe SCFV product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology and biology.\r\n\r\nThe Remote Sensing Research Group of the University of Bern is responsible for the SCFV product development and generation. ENVEO developed and prepared all auxiliary data sets used for the product generation. \r\n\r\nThe SCFV AVHRR product comprises one longer data gap of 92 between November 1994 and January 1995, and 16 individual daily gaps, resulting in a 99% data coverage over the entire study period of 37 years." } }, { "ob_id": 990, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 40355, "uuid": "e955813b0e1a4eb7af971f923010b4a3", "short_code": "ob", "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable snow (SCFV) from MODIS (2000 - 2022), version 3.0", "abstract": "This dataset contains Daily Snow Cover Fraction of viewable snow from the MODIS satellite instruments, produced by the Snow project of the ESA Climate Change Initiative programme. \r\n\r\nSnow cover fraction viewable (SCFV) indicates the area of snow viewable from space over all land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. \r\n\r\nThe global SCFV product is available at about 1 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets and permanent snow and ice areas. The coastal zones of Greenland are included. \r\n\r\nThe SCFV time series provides daily products for the period 2000 – 2022. \r\n\r\nThe SCFV product is based on Moderate resolution Imaging Spectroradiometer (MODIS) data on-board the Terra satellite. \r\n\r\nThe retrieval method of the Snow_cci SCFV product from MODIS data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module developed by ENVEO (ENVironmental Earth Observation IT GmbH). For the SCFV product generation from MODIS, multiple reflective and emissive spectral bands are used. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (Metsämäki et al., 2015). All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.55 µm and 1.6 µm, and an emissive band centred at about 11 µm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the Snow_cci SCFV retrieval method is applied. \r\n\r\nThe main differences of the Snow_cci snow cover mapping algorithm compared to the GlobSnow algorithm described in Metsämäki et al. (2015) are (i) improvements of the cloud screening approach applicable on a global scale, (ii) the pre-classification of snow free areas on global land areas, (iii) the adaptation of the retrieval method using of a spatially variable ground reflectance instead of global constant values for snow free land, (iv) the update of the constant value for wet snow based on analyses of spatially distributed reflectance time series of MODIS data to assure in forested areas consistency of the SCFV and the SCFG CRDP v3.0 from MODIS data (https://catalogue.ceda.ac.uk/uuid/80567d38de3f4b038ee6e6e53ed1af8a) using the same retrieval approach.\r\n\r\nPermanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the pixel spacing of the SCFV product. Water areas are masked if more than 30 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map. Salt lakes are masked based on a manual delineation from MODIS data. The product uncertainty for observed land pixels is provided as unbiased root mean square error (RMSE) per pixel in the ancillary variable.\r\n\r\nCompared to the SCFV CRDP v2.0 (https://catalogue.ceda.ac.uk/uuid/ebe625b6f77945a68bda0ab7c78dd76b/) the following improvements were applied for the generation of the SCFV CRDP v3.0: \r\n1) the pre-classification module to identify snow free areas has been relaxed to consider more pixels for the SCFG retrieval; \r\n2) the SCFG retrieval has been improved adapting the spectral reflectance value for wet snow;\r\n3) the uncertainty estimation of the SCFG has been updated to account for the changes in the retrieval algorithm;\r\n4) salt lakes retrieved by manual delineation from Terra MODIS data are masked in the SCFG CRDP v3.0 and a new class for salt lakes is added in the coding;\r\n5) the time series, starting in February 2000, was extended from December 2020 to December 2022;\r\n6) two additional layers are provided for each daily product: \r\n•\tthe sensor zenith angle in degree per pixel;\r\n•\tthe image acquisition time per pixel referring to the scanline time of the MODIS granule used for the classification of the pixel.\r\n\r\nThe SCFV product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\n\r\nENVEO is responsible for the SCFV product development and generation from MODIS data, SYKE supported the development.\r\n\r\nThere are a few days without any MODIS acquisitions in the years 2000, 2001, 2002, 2003, 2008, 2016 and 2022. On several days in the years 2000 to 2006, and on a few days in the years 2012, 2015 and 2016, the acquired MODIS data have either only limited coverage, or some of the MODIS data were corrupted during the download process. For these days, the SCFV products are available but have data gaps." }, "objectObservation": { "ob_id": 33059, "uuid": "ebe625b6f77945a68bda0ab7c78dd76b", "short_code": "ob", "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - viewable snow (SCFV) from MODIS (2000 - 2020), version 2.0", "abstract": "This dataset contains Daily Snow Cover Fraction of viewable snow from the MODIS satellite instruments, produced by the Snow project of the ESA Climate Change Initiative programme. \r\n\r\nSnow cover fraction viewable (SCFV) indicates the area of snow viewable from space over all land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. \r\n\r\nThe global SCFV product is available at about 1 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included. \r\n\r\nThe SCFV time series provides daily products for the period 2000 – 2020. \r\n\r\nThe SCFV product is based on Moderate resolution Imaging Spectroradiometer (MODIS) data on-board the Terra satellite. \r\n\r\nThe retrieval method of the Snow_cci SCFV product from MODIS data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module developed by ENVEO. For the SCFV product generation from MODIS, multiple reflective and emissive spectral bands are used. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (Metsämäki et al., 2015). All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.55 µm and 1.6 µm, and an emissive band centred at about 11 µm. The snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the Snow_cci SCFV retrieval method is applied. \r\n\r\nThe main differences of the Snow_cci snow cover mapping algorithm compared to the GlobSnow algorithm described in Metsämäki et al. (2015) are (i) improvements of the cloud screening approach applicable on a global scale, (ii) the pre-classification of snow free areas on global land areas, (iii) the adaptation of the retrieval method using of a spatially variable ground reflectance instead of global constant values for snow free land, (iv) the update of the constant value for wet snow based on analyses of spatially distributed reflectance time series of MODIS data to assure in forested areas consistency of the SCFV and the SCFG CRDP v2.0 from MODIS data (https://catalogue.ceda.ac.uk/uuid/ebe625b6f77945a68bda0ab7c78dd76b) using the same retrieval approach.\r\n\r\nImprovements of the Snow_cci SCFV version 2.0 compared to the Snow_cci version 1.0 include (i) the utilisation of an updated ground reflectance map derived from statistical analyses of an extended MODIS time series, (ii) an update of the forest mask used for the transmissivity estimation, and (iii) an update of the constant reflectance value for wet snow based on the analysis of time series of the MODIS reflectance at 0.55 µm.\r\n\r\nPermanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the pixel spacing of the SCFV product. Water areas are masked if more than 30 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map. The product uncertainty for observed land pixels is provided as unbiased root mean square error (RMSE) per pixel in the ancillary variable.\r\n\r\nThe SCFV product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\n\r\nENVEO is responsible for the SCFV product development and generation from MODIS data, SYKE supported the development.\r\n\r\nThere are a few days without any MODIS acquisitions in the years 2000, 2001, 2002, 2003, 2008, 2016 and 2018. On several days in the years 2000 to 2006, and on a few days in the years 2012, 2015 and 2016, the acquired MODIS data have either only limited coverage, or some of the MODIS data were corrupted during the download process. For these days, the SCFV products are available but have data gaps." } }, { "ob_id": 991, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 40354, "uuid": "80567d38de3f4b038ee6e6e53ed1af8a", "short_code": "ob", "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from MODIS (2000-2022), version 3.0", "abstract": "This dataset contains Daily Snow Cover Fraction (snow on ground) from MODIS, produced by the Snow project of the ESA Climate Change Initiative programme.\r\n\r\nSnow cover fraction on ground (SCFG) indicates the area of snow observed from space on land surfaces, in forested areas corrected for the masking effect of the forest canopy. The SCFG is given in percentage (%) per pixel. \r\n\r\nThe global SCFG product is available at about 1 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets and permanent snow and ice areas. The coastal zones of Greenland are included. \r\n\r\nThe SCFG time series provides daily products for the period 2000 – 2022. \r\n\r\nThe SCFG product is based on Moderate resolution Imaging Spectroradiometer (MODIS) data on-board the Terra satellite. \r\n\r\nThe retrieval method of the snow_cci SCFG product from MODIS data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module developed by ENVEO (ENVironmental Earth Observation IT GmbH). For the SCFG product generation from MODIS, multiple reflective and emissive spectral bands are used. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (Metsämäki et al., 2015). All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.55 µm and 1.6 µm, and an emissive band centred at about 11 µm. The Snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFG retrieval method is applied. \r\n\r\nThe main differences of the snow_cci snow cover mapping algorithm compared to the GlobSnow algorithm described in Metsämäki et al. (2015) are (i) improvements of the cloud screening approach applicable on a global scale, (ii) the pre-classification of snow free areas on global land areas, (iii) the usage of spatially variable background reflectance and forest reflectance maps instead of global constant values for snow free land and forest, (iv) the update of the constant value for wet snow based on analyses of spatially distributed reflectance time series of MODIS data, and (v) the update of the global forest canopy transmissivity based on forest density from Hansen et al. (2013) and forest type layers from Land Cover CCI (Defourny, 2019) to assure in forested areas consistency of the SCFG and the SCFV CRDP v3.0 from MODIS data (https://catalogue.ceda.ac.uk/uuid/e955813b0e1a4eb7af971f923010b4a3) using the same retrieval approach.\r\n\r\nPermanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the pixel spacing of the SCFG product. Water areas are masked if more than 30 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map. Salt lakes are masked based on a manual delineation from MODIS data. The product uncertainty for observed land pixels is provided as unbiased root mean square error (RMSE) per pixel in the ancillary variable.\r\n\r\nCompared to the SCFG CRDP v2.0 (https://catalogue.ceda.ac.uk/uuid/8847a05eeda646a29da58b42bdf2a87c/) the following improvements were applied for the generation of the SCFG CRDP v3.0: \r\n1) the pre-classification module to identify snow free areas has been relaxed to consider more pixels for the SCFG retrieval; \r\n2) the SCFG retrieval has been improved adapting the spectral reflectance value for wet snow;\r\n3) the uncertainty estimation of the SCFG has been updated to account for the changes in the retrieval algorithm;\r\n4) salt lakes retrieved by manual delineation from Terra MODIS data are masked in the SCFG CRDP v3.0 and a new class for salt lakes is added in the coding;\r\n5) the time series, starting in February 2000, was extended from December 2020 to December 2022;\r\n6) two additional layers are provided for each daily product: \r\n•\tthe sensor zenith angle in degree per pixel;\r\n\tthe image acquisition time per pixel referring to the scanline time of the MODIS granule used for the classification of the pixel. \r\n\r\nThe SCFG product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\nENVEO is responsible for the SCFG product development and generation from MODIS data, SYKE supported the development.\r\n\r\nThere are a few days without any MODIS acquisitions in the years 2000, 2001, 2002, 2003, 2008, 2016 and 2022. On several days in the years 2000 to 2006, and on a few days in the years 2012, 2015 and 2016, the acquired MODIS data have either only limited coverage, or some of the MODIS data were corrupted during the download process. For these days, the SCFG products are available but have data gaps." }, "objectObservation": { "ob_id": 33060, "uuid": "8847a05eeda646a29da58b42bdf2a87c", "short_code": "ob", "title": "ESA Snow Climate Change Initiative (Snow_cci): Daily global Snow Cover Fraction - snow on ground (SCFG) from MODIS (2000-2020), version 2.0", "abstract": "This dataset contains Daily Snow Cover Fraction (snow on ground) from MODIS, produced by the Snow project of the ESA Climate Change Initiative programme.\r\n\r\nSnow cover fraction on ground (SCFG) indicates the area of snow observed from space on land surfaces, in forested areas corrected for the transmissivity of the forest canopy. The SCFG is given in percentage (%) per pixel. \r\n\r\nThe global SCFG product is available at about 1 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included. \r\n\r\nThe SCFG time series provides daily products for the period 2000 – 2020. \r\n\r\nThe SCFG product is based on Moderate resolution Imaging Spectroradiometer (MODIS) data on-board the Terra satellite. \r\n\r\nThe retrieval method of the Snow_cci SCFG product from MODIS data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module developed by ENVEO. For the SCFG product generation from MODIS, multiple reflective and emissive spectral bands are used. In a first step, clouds are masked using an adapted version of the Simple Cloud Detection Algorithm version 2.0 (SCDA2.0) (Metsämäki et al., 2015). All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.55 µm and 1.6 µm, and an emissive band centred at about 11 µm. The Snow_cci snow cover mapping algorithm is a two-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFG retrieval method is applied. \r\n\r\nThe main differences of the Snow_cci snow cover mapping algorithm compared to the GlobSnow algorithm described in Metsämäki et al. (2015) are (i) improvements of the cloud screening approach applicable on a global scale, (ii) the pre-classification of snow free areas on global land areas, (iii) the usage of spatially variable background reflectance and forest reflectance maps instead of global constant values for snow free land and forest, (iv) the update of the constant value for wet snow based on analyses of spatially distributed reflectance time series of MODIS data, and (v) the update of the global forest canopy transmissivity based on forest density from Hansen et al. (2013) and forest type layers from Land Cover CCI (Defourny, 2019) to assure in forested areas consistency of the SCFG and the SCFV CRDP v2.0 from MODIS data (https://catalogue.ceda.ac.uk/uuid/ebe625b6f77945a68bda0ab7c78dd76b) using the same retrieval approach.\r\n\r\nImprovements of the Snow_cci SCFG version 2.0 compared to the Snow_cci version 1.0 include (i) the utilisation of an updated background reflectance map derived from statistical analyses of an extended MODIS time series, (ii) an update of the forest canopy transmissivity map, and (iii) an update of the constant reflectance value for wet snow based on the analysis of time series of the MODIS reflectance at 0.55 µm.\r\n\r\nPermanent snow and ice, and water areas are masked based on the Land Cover CCI data set of the year 2000. Both classes were separately aggregated to the pixel spacing of the SCFG product. Water areas are masked if more than 30 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map. The product uncertainty for observed land pixels is provided as unbiased root mean square error (RMSE) per pixel in the ancillary variable.\r\n\r\nThe SCFG product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\n\r\nENVEO is responsible for the SCFG product development and generation from MODIS data, SYKE supported the development.\r\n\r\nThere are a few days without any MODIS acquisitions in the years 2000, 2001, 2002, 2003, 2008, 2016 and 2018. On several days in the years 2000 to 2006, and on a few days in the years 2012, 2015 and 2016, the acquired MODIS data have either only limited coverage, or some of the MODIS data were corrupted during the download process. For these days, the SCFG products are available but have data gaps." } }, { "ob_id": 992, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43202, "uuid": "9d9bfc488ec54b1297eca2c9662f9c81", "short_code": "ob", "title": "ESA Snow Climate Change Initiative (Snow_cci): Snow Water Equivalent (SWE) level 3C daily global climate research data package (CRDP) (1979 - 2022), version 3.1", "abstract": "This dataset contains v3.1 of the Daily Snow Water Equivalent (SWE) product from the ESA Climate Change Initiative (CCI) Snow project, at 0.1 degree resolution.\r\n\r\nSnow water equivalent (SWE) is the depth of liquid water that would result if the of snow cover melted completely, which equates to the snow cover mass per unit area. The SWE product covers the Northern Hemisphere from 1979/01 to 2022/05 with complex terrain, land ice, and large lakes masked. The dataset covers the Northern Hemisphere winter season (October – May; occasional data produced during June and September) at a daily frequency starting in October 1987 and every second day from 1979 to May 1987. Retrievals are not produced for coastal regions of Greenland. \r\n\r\nThe product combines passive microwave data with ground-based snow depth measurements, via Bayesian non-linear iterative assimilation, to estimate SWE. It is based on data from the recalibrated enhanced resolution CETB ESDR dataset (MEaSUREs Calibrated Enhanced-Resolution Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record (ESDR) https://nsidc.org/pmesdr/data/) resampled to the 12.5km EASE-Grid 2.0. \r\n\r\nA background snow-depth field, derived from re-gridded snow-depth observations made at synoptic weather stations, and a passive microwave emission model are the key components of the retrieval scheme. Snow density, which varies in both time and space, is parameterized from interpolated in situ observations from snow courses and snow pillows equipped with co-located snow depth sensors.\r\nThe dataset is aimed to serve the needs of users working on climate research and monitoring activities, including the detection of variability and trends, climate modelling, and aspects of hydrology and meteorology.\r\n\r\nThe Finnish Meteorological Institute is responsible for the SWE product generation. The SWE development is carried out in collaboration by FMI and Environment and Climate Change Canada (ECCC). \r\n\r\nChanges from v2.0 and v3.0\r\nv3.1 applies spatially and temporally varying snow densities within the SWE retrieval instead of during post-processing. The dry snow detection algorithm as well as the snow masking in post-production have also been updated. The time series has been extended from snow_cci version 2 by two years from 2020 to 2022. In comparison with in situ snow courses, the correlation and RMSE of v3.1 improved by 0.014 and 0.6 mm, respectively, relative to v2.0. The timing of peak snow mass is shifted two weeks later compared to v1.0 and reduction in peak snow mass presented in v2.0 is removed in v3.1. Differences between v3.0 and v.3.1 are minor, the resampling from 12.5km EASE-Grid 2.0 to the final 0.1 resolution grid has been changed for v.3.1 resulting in improved peak snow mass estimation." }, "objectObservation": { "ob_id": 40358, "uuid": "b06c4c5ea7694d30b33e1db04f0ecb6a", "short_code": "ob", "title": "ESA Snow Climate Change Initiative (Snow_cci): Snow Water Equivalent (SWE) level 3C daily global climate research data package (CRDP) (1979 - 2022), version 3.0", "abstract": "This dataset contains v3.0 of the Daily Snow Water Equivalent (SWE) product from the ESA Climate Change Initiative (CCI) Snow project, at 0.1 degree resolution.\r\n\r\nSnow water equivalent (SWE) indicates the amount of accumulated snow on land surfaces, in other words the amount of water contained within the snowpack. The SWE product time series covers the period from 1979/01 to 2022/12. Northern Hemisphere SWE products are available at daily temporal resolution with alpine areas masked. \r\n\r\nThe product is based on data from the Scanning Multichannel Microwave Radiometer (SMMR) operated on National Aeronautics and Space Administration’s (NASA) Nimbus-7 satellite, the Special Sensor Microwave / Imager (SSM/I) and the Special Sensor Microwave Imager / Sounder (SSMI/S) carried onboard the Defense Meteorological Satellite Program (DMSP) 5D- and F-series satellites. The satellite bands provide spatial resolutions between 15 and 69 km. The retrieval methodology combines satellite passive microwave radiometer (PMR) measurements with ground-based synoptic weather station observations by Bayesian non-linear iterative assimilation. A background snow-depth field from re-gridded surface snow-depth observations and a passive microwave emission model are required components of the retrieval scheme.\r\n\r\nThe dataset is aimed to serve the needs of users working on climate research and monitoring activities, including the detection of variability and trends, climate modelling, and aspects of hydrology and meteorology.\r\n\r\nThe Finnish Meteorological Institute is responsible for the SWE product development and generation. \r\n\r\nFor the period from 1979 to May 1987, the products are available every second day. From October 1987 till December 2022, the products are available daily. Products are only generated for the Northern Hemisphere winter seasons, usually from beginning of October till the middle of May. A limited number of SWE products are available for days in June and September; products are not available for the months July and August as there is usually no snow information reported on synoptic weather stations, which is required as input for the SWE retrieval. Because of known limitations in alpine terrain, a complex-terrain mask is applied based on the sub-grid variability in elevation determined from a high-resolution digital elevation model. All land ice and large lakes are also masked; retrievals are not produced for coastal regions of Greenland.\r\n\r\nPassive microwave radiometer data are obtained from the recalibrated enhanced resolution CETB ESDR dataset (MEaSUREs Calibrated Enhanced-Resolution Passive Microwave Daily EASE-Grid 2.0 Brightness Temperature (CETB) Earth System Data Record (ESDR) https://nsidc.org/pmesdr/data-sets/) Spatially and temporally varying snow density fields are implemented into the SWE retrieval, dry snow detection algorithm has been updated and snow masking in post-production has been improved. The time series has been extended from snow_cci version 2 by two years with data from 2020 to 2022 added.\r\n\r\nThe ESA CCI phased product development framework allowed for a systematic analysis of these changes in the snow density parameterization, snow dry detection and snow masking that occurred between v2 and v3 using a series of step-wise developmental datasets. In comparison with in-situ snow courses, the correlation and RMSE of v3 improved 0.014 and 0.6 mm, respectively, relative to v2. The timing of peak snow mass is shifted two weeks later compared to v1 and reduction in peak snow mass presented in v2 is removed in v3.\r\n\r\nThis dataset has been deprecated due to data errors in the v3.0 product." } }, { "ob_id": 994, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43488, "uuid": "198d56f5fbbf4144b8fd4932328be462", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column averaged carbon dioxide from OCO-2 generated with the FOCAL algorithm, version 11.0", "abstract": "This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (XCO2) data, generated using the fast atmospheric trace gas retrieval for OCO2 (FOCAL-OCO2). The FOCAL-OCO2 algorithm has been setup to retrieve XCO2 by analysing hyper spectral solar backscattered radiance measurements from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite. FOCAL includes a radiative transfer model which has been developed to approximate light scattering effects by multiple scattering at an optically thin scattering layer. This reduces the computational costs by several orders of magnitude. FOCAL's radiative transfer model is utilised to simulate the radiance in all three OCO-2 spectral bands allowing the simultaneous retrieval of CO2, H2O, and solar induced chlorophyll fluorescence. The product is limited to cloud-free scenes on the Earth's day side. This dataset is also referred to as CO2_OC2_FOCA.\r\n\r\nThis version of the data (v11) was produced as part of the European Space Agency's (ESA) \r\nClimate Change Initiative (CCI) Greenhouse Gases (GHG) project (GHG-CCI+, http://cci.esa.int/ghg).\r\nThe FOCAL OCO-2 XCO2 retrieval development, data processing and analysis has received co-funding from ESA’s Climate Change Initiative (CCI+) via project GHG-CCI+ (contract 4000126450/19/I-NB, https://climate.esa.int/en/projects/ghgs) EUMETSAT via the FOCAL-CO2M study (contract EUM/CO/19/4600002372/RL), the European Union via the Horizon 2020 (H2020) projects VERIFY (Grant Agreement No. 776810, http://verify.lsce.ipsl.fr) and CHE (Grant Agreement No. 776186, https://www.che-project.eu) and by the State and the University of Bremen.\r\n\r\nWhen citing this data, please also cite the following peer-reviewed publications:\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, V.Rozanov, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 1: Radiative Transfer and a Potential OCO-2 XCO2 Retrieval Setup, Remote Sensing, 9(11), 1159; doi:10.3390/rs9111159, 2017\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 2: Application to XCO2 Retrievals from OCO-2, Remote Sensing, 9(11), 1102; doi:10.3390/rs9111102, 2017" }, "objectObservation": { "ob_id": 41262, "uuid": "2c1cb1d606c4421e9339a3028839a41f", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column averaged carbon dioxide from OCO-2 generated with the FOCAL algorithm, version 10.1", "abstract": "This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (XCO2), using the fast atmospheric trace gas retrieval for OCO2 (FOCAL-OCO2). The FOCAL-OCO2 algorithm which has been setup to retrieve XCO2 by analysing hyper spectral solar backscattered radiance measurements from NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite. FOCAL includes a radiative transfer model which has been developed to approximate light scattering effects by multiple scattering at an optically thin scattering layer. This reduces the computational costs by several orders of magnitude. FOCAL's radiative transfer model is utilised to simulate the radiance in all three OCO-2 spectral bands allowing the simultaneous retrieval of CO2, H2O, and solar induced chlorophyll fluorescence. The product is limited to cloud-free scenes on the Earth's day side. This dataset is also referred to as CO2_OC2_FOCA.\r\n\r\nThis version of the data (v10.1) was produced as part of the European Space Agency's (ESA) \r\nClimate Change Initiative (CCI) Greenhouse Gases (GHG) project (GHG-CCI+, http://cci.esa.int/ghg)\r\nand got co-funding from the University of Bremen and EU H2020 projects CHE (grant agreement no. 776186) and VERIFY (grant agreement no. 776810).\r\n\r\nWhen citing this data, please also cite the following peer-reviewed publications:\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, V.Rozanov, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 1: Radiative Transfer and a Potential OCO-2 XCO2 Retrieval Setup, Remote Sensing, 9(11), 1159; doi:10.3390/rs9111159, 2017\r\n\r\nM.Reuter, M.Buchwitz, O.Schneising, S.Noël, H.Bovensmann and J.P.Burrows: A Fast Atmospheric Trace Gas Retrieval for Hyperspectral Instruments Approximating Multiple Scattering - Part 2: Application to XCO2 Retrievals from OCO-2, Remote Sensing, 9(11), 1102; doi:10.3390/rs9111102, 2017" } }, { "ob_id": 997, "relationType": "IsSupplementTo", "subjectObservation": { "ob_id": 43489, "uuid": "5ec6949356de45c2a3b3565d297a80fa", "short_code": "ob", "title": "The GEBCO_2024 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2024 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions largely outside of the Arctic Ocean area, the grid uses as a base Version 2.6 of the SRTM15_plus data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2024 Grid represents all data within the 2024 compilation. The compilation of the GEBCO_2024 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a ‘remove-restore’ blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2024 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute (AWI), Germany; Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research (NIWA), New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory (LDEO), Columbia University, USA; Arctic and North Pacific Oceans - jointly hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "objectObservation": { "ob_id": 43504, "uuid": "591c8f9d03ea45ce9053a8d67d65eb56", "short_code": "ob", "title": "The GEBCO_2024 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2024 Grid Collection is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2024 Grid Collection comprises the following data types: the standard grid (ice surface elevation), the standard grid including sub-ice topography information for Greenland and Antarctica, and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2024 Grid Collection also comprises all available data formats, including ESRI ASCII raster, GeoTIFF, and NetCDF. This data collection also contains the published and citable GEBCO_2024 grid (standard grid of ice surface elevation) available in NetCDF format. In regions largely outside of the Arctic Ocean area, the GEBCO_2024 grid uses as a base Version 2.6 of the SRTM15_plus data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2024 Grid represents all data within the 2024 compilation. The compilation of the GEBCO_2024 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a ‘remove-restore’ blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2024 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute (AWI), Germany; Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research (NIWA), New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory (LDEO), Columbia University, USA; Arctic and North Pacific Oceans - jointly hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." } }, { "ob_id": 998, "relationType": "IsSupplementTo", "subjectObservation": { "ob_id": 43496, "uuid": "bb0e44f6520f415e9a07601bb21ac3c8", "short_code": "ob", "title": "The GEBCO_2023 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2023 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2.5.5 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2023 Grid represents all data within the 2023 compilation. The compilation of the GEBCO_2023 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a 'remove-restore' blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2023 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "objectObservation": { "ob_id": 43505, "uuid": "c25d585d8c314cbba6faebb4f21ff4a3", "short_code": "ob", "title": "The GEBCO_2023 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2023 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2023 Grid Collection comprises the following data types: the standard grid (ice surface elevation), the standard grid including sub-ice topography information for Greenland and Antarctica, and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2023 Grid Collection also comprises all available data formats, including ESRI ASCII raster, GeoTIFF, and NetCDF. This data collection also contains the published and citable GEBCO_2023 grid (standard grid of ice surface elevation) available in NetCDF format. \r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2.5.5 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2023 Grid represents all data within the 2023 compilation. The compilation of the GEBCO_2023 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a 'remove-restore' blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2023 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." } }, { "ob_id": 1000, "relationType": "IsSupplementTo", "subjectObservation": { "ob_id": 43497, "uuid": "4ea04d633ecc43e195520fb65256cd5e", "short_code": "ob", "title": "The GEBCO_2022 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2022 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2.4 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2022 Grid represents all data within the 2022 compilation. The compilation of the GEBCO_2022 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a remove-restore blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2022 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "objectObservation": { "ob_id": 43506, "uuid": "b5a93cb47d934f5295e2784313ecfb00", "short_code": "ob", "title": "The GEBCO_2022 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2022 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2022 Grid Collection comprises the following data types: the standard grid (ice surface elevation), the standard grid including sub-ice topography information for Greenland and Antarctica, and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2022 Grid Collection also comprises all available data formats, including ESRI ASCII raster, GeoTIFF, and NetCDF. This data collection also contains the published and citable GEBCO_2022 grid (standard grid of ice surface elevation) available in NetCDF format. \r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2.4 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2022 Grid represents all data within the 2022 compilation. The compilation of the GEBCO_2022 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a remove-restore blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2022 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." } }, { "ob_id": 1002, "relationType": "IsSupplementTo", "subjectObservation": { "ob_id": 43498, "uuid": "eb4f211ef57745919dddb8a93518db00", "short_code": "ob", "title": "The GEBCO_2021 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2021 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2.2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2021 Grid represents all data within the 2021 compilation. The compilation of the GEBCO_2021 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base grid without any blending. 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The GEBCO_2021 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." } }, { "ob_id": 1016, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 43508, "uuid": "74583b230b1343d9b4b302b8fbb5414f", "short_code": "ob", "title": "The GEBCO_2020 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2020 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2020 Grid Collection comprises the following data types: the standard grid (ice surface elevation), and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2020 Grid Collection is delivered in NetCDF format only. This data collection also contains the published and citable GEBCO_2020 grid (standard grid of ice surface elevation) available in NetCDF format.\r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2020 Grid represents all data within the 2020 compilation. The compilation of the GEBCO_2020 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the gridded bathymetric data sets were supplied as sparse grids by the Regional Centers, i.e. only grid cells that contain data were populated. These sparse grids were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2020 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "objectObservation": { "ob_id": 43499, "uuid": "4ad3e42245174dee86ca27f8e1bb2e87", "short_code": "ob", "title": "The GEBCO_2020 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2020 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2020 Grid represents all data within the 2020 compilation. The compilation of the GEBCO_2020 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the gridded bathymetric data sets were supplied as sparse grids by the Regional Centers, i.e. only grid cells that contain data were populated. These sparse grids were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2020 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." } }, { "ob_id": 1018, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 43509, "uuid": "cefbb8b5fc874bfc84f75169a611de4f", "short_code": "ob", "title": "The GEBCO_2019 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2019 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2019 Grid Collection, comprises the following data types: the standard grid (ice surface elevation), the Source Identifier Grid (SID), and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2019 Grid Collection is available in NetCDF format only. This data collection also contains the published and citable GEBCO_2019 grid (standard grid of ice surface elevation) available in NetCDF format. \r\n\r\nThe grid uses as a base Version 1 of the SRTM15_plus data set (Sandwell et al). This data set is a fusion of land topography with measured and estimated seafloor topography. It is largely based on version 11 of SRTM30_plus (5). Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project, and from a number of international and national data repositories and regional mapping initiatives. The GEBCO_2019 Grid represents all data within the 2019 compilation. The compilation of the GEBCO_2019 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. The majority of the compilation was done using the remove-restore procedure (Smith and Sandwell, 1997; Becker, Sandwell and Smith, 2009 and Hell and Jakobsson, 2011). This is a two stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2019 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA)." }, "objectObservation": { "ob_id": 43500, "uuid": "2920b2ea41d244cd9bfd95be0f4dc4a9", "short_code": "ob", "title": "The GEBCO_2019 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2019 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The grid uses as a base Version 1 of the SRTM15_plus data set (Sandwell et al). This data set is a fusion of land topography with measured and estimated seafloor topography. It is largely based on version 11 of SRTM30_plus (5). Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project, and from a number of international and national data repositories and regional mapping initiatives. The GEBCO_2019 Grid represents all data within the 2019 compilation. The compilation of the GEBCO_2019 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. The majority of the compilation was done using the remove-restore procedure (Smith and Sandwell, 1997; Becker, Sandwell and Smith, 2009 and Hell and Jakobsson, 2011). This is a two stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2019 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA)." } }, { "ob_id": 1025, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43514, "uuid": "1e69e123a0c04e2a83539dec43f1bfdb", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 2.23", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 2.23 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. The IBCAO Version 2.23 Grid was released in March 2008.\r\n\r\nThe bathymetric grid released in IBCAO Version 2.23 is available in NetCDF or Esri ASCII raster format. The grid is available as a geographic grid (one arc-minute or two arc-minute intervals), or in a polar stereographic projection (2000 x 2000 m grid interval, true scale 75°N, WGS 84 datum). The one-minute geographic grid imagery is also available in KMZ format for Google Earth. A Source Identifier Grid is delivered as a JPEG image for IBCAO version 2.23, to provide information on the source data sets included in the IBCAO grid." }, "objectObservation": { "ob_id": 43513, "uuid": "8e50690c2ac84e249cbc2cba2e95f5e5", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 1", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 1.0 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. The IBCAO Version 1 Grid was released in July 2001.\r\n\r\nThe bathymetric grid released in IBCAO Version 1 is available in NetCDF or Esri ASCII raster format. The grid is available as a geographic grid (one arc-minute intervals), or in a polar stereographic projection (2500 x 2500 m grid interval, true scale 75°N, WGS 84 datum). Postscript plots in polar stereographic projection are also available in IBCAO Version 1, showing shaded relief and contours. Shaded relief imagery is also provided in JPEG format. A Source Identifier Grid is delivered as a Postscript plot for IBCAO Version 1, to provide information on the source data sets included in the IBCAO grid." } }, { "ob_id": 1026, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43499, "uuid": "4ad3e42245174dee86ca27f8e1bb2e87", "short_code": "ob", "title": "The GEBCO_2020 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2020 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2020 Grid represents all data within the 2020 compilation. The compilation of the GEBCO_2020 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the gridded bathymetric data sets were supplied as sparse grids by the Regional Centers, i.e. only grid cells that contain data were populated. These sparse grids were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2020 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "objectObservation": { "ob_id": 43500, "uuid": "2920b2ea41d244cd9bfd95be0f4dc4a9", "short_code": "ob", "title": "The GEBCO_2019 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2019 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The grid uses as a base Version 1 of the SRTM15_plus data set (Sandwell et al). This data set is a fusion of land topography with measured and estimated seafloor topography. It is largely based on version 11 of SRTM30_plus (5). Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project, and from a number of international and national data repositories and regional mapping initiatives. The GEBCO_2019 Grid represents all data within the 2019 compilation. The compilation of the GEBCO_2019 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. The majority of the compilation was done using the remove-restore procedure (Smith and Sandwell, 1997; Becker, Sandwell and Smith, 2009 and Hell and Jakobsson, 2011). This is a two stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2019 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA)." } }, { "ob_id": 1031, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43504, "uuid": "591c8f9d03ea45ce9053a8d67d65eb56", "short_code": "ob", "title": "The GEBCO_2024 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2024 Grid Collection is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2024 Grid Collection comprises the following data types: the standard grid (ice surface elevation), the standard grid including sub-ice topography information for Greenland and Antarctica, and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2024 Grid Collection also comprises all available data formats, including ESRI ASCII raster, GeoTIFF, and NetCDF. This data collection also contains the published and citable GEBCO_2024 grid (standard grid of ice surface elevation) available in NetCDF format. In regions largely outside of the Arctic Ocean area, the GEBCO_2024 grid uses as a base Version 2.6 of the SRTM15_plus data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2024 Grid represents all data within the 2024 compilation. The compilation of the GEBCO_2024 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a ‘remove-restore’ blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2024 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute (AWI), Germany; Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research (NIWA), New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory (LDEO), Columbia University, USA; Arctic and North Pacific Oceans - jointly hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "objectObservation": { "ob_id": 43505, "uuid": "c25d585d8c314cbba6faebb4f21ff4a3", "short_code": "ob", "title": "The GEBCO_2023 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2023 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2023 Grid Collection comprises the following data types: the standard grid (ice surface elevation), the standard grid including sub-ice topography information for Greenland and Antarctica, and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2023 Grid Collection also comprises all available data formats, including ESRI ASCII raster, GeoTIFF, and NetCDF. This data collection also contains the published and citable GEBCO_2023 grid (standard grid of ice surface elevation) available in NetCDF format. \r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2.5.5 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2023 Grid represents all data within the 2023 compilation. The compilation of the GEBCO_2023 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a 'remove-restore' blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2023 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." } }, { "ob_id": 1032, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43498, "uuid": "eb4f211ef57745919dddb8a93518db00", "short_code": "ob", "title": "The GEBCO_2021 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2021 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2.2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2021 Grid represents all data within the 2021 compilation. The compilation of the GEBCO_2021 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2021 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "objectObservation": { "ob_id": 43499, "uuid": "4ad3e42245174dee86ca27f8e1bb2e87", "short_code": "ob", "title": "The GEBCO_2020 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2020 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2020 Grid represents all data within the 2020 compilation. The compilation of the GEBCO_2020 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the gridded bathymetric data sets were supplied as sparse grids by the Regional Centers, i.e. only grid cells that contain data were populated. These sparse grids were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2020 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." } }, { "ob_id": 1033, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43497, "uuid": "4ea04d633ecc43e195520fb65256cd5e", "short_code": "ob", "title": "The GEBCO_2022 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2022 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2.4 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2022 Grid represents all data within the 2022 compilation. The compilation of the GEBCO_2022 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a remove-restore blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2022 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "objectObservation": { "ob_id": 43498, "uuid": "eb4f211ef57745919dddb8a93518db00", "short_code": "ob", "title": "The GEBCO_2021 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2021 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2.2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2021 Grid represents all data within the 2021 compilation. The compilation of the GEBCO_2021 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2021 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." } }, { "ob_id": 1034, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43496, "uuid": "bb0e44f6520f415e9a07601bb21ac3c8", "short_code": "ob", "title": "The GEBCO_2023 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2023 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2.5.5 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2023 Grid represents all data within the 2023 compilation. The compilation of the GEBCO_2023 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a 'remove-restore' blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2023 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "objectObservation": { "ob_id": 43497, "uuid": "4ea04d633ecc43e195520fb65256cd5e", "short_code": "ob", "title": "The GEBCO_2022 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2022 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2.4 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2022 Grid represents all data within the 2022 compilation. The compilation of the GEBCO_2022 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a remove-restore blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2022 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." } }, { "ob_id": 1035, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43508, "uuid": "74583b230b1343d9b4b302b8fbb5414f", "short_code": "ob", "title": "The GEBCO_2020 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2020 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2020 Grid Collection comprises the following data types: the standard grid (ice surface elevation), and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2020 Grid Collection is delivered in NetCDF format only. This data collection also contains the published and citable GEBCO_2020 grid (standard grid of ice surface elevation) available in NetCDF format.\r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2020 Grid represents all data within the 2020 compilation. The compilation of the GEBCO_2020 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the gridded bathymetric data sets were supplied as sparse grids by the Regional Centers, i.e. only grid cells that contain data were populated. These sparse grids were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2020 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "objectObservation": { "ob_id": 43509, "uuid": "cefbb8b5fc874bfc84f75169a611de4f", "short_code": "ob", "title": "The GEBCO_2019 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2019 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2019 Grid Collection, comprises the following data types: the standard grid (ice surface elevation), the Source Identifier Grid (SID), and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2019 Grid Collection is available in NetCDF format only. This data collection also contains the published and citable GEBCO_2019 grid (standard grid of ice surface elevation) available in NetCDF format. \r\n\r\nThe grid uses as a base Version 1 of the SRTM15_plus data set (Sandwell et al). This data set is a fusion of land topography with measured and estimated seafloor topography. It is largely based on version 11 of SRTM30_plus (5). Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project, and from a number of international and national data repositories and regional mapping initiatives. The GEBCO_2019 Grid represents all data within the 2019 compilation. The compilation of the GEBCO_2019 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. The majority of the compilation was done using the remove-restore procedure (Smith and Sandwell, 1997; Becker, Sandwell and Smith, 2009 and Hell and Jakobsson, 2011). This is a two stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2019 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA)." } }, { "ob_id": 1036, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43507, "uuid": "b978db2f6e4e4bc49ca8ca026495aaac", "short_code": "ob", "title": "The GEBCO_2021 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2021 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2021 Grid Collection comprises the following data types: the standard grid (ice surface elevation), the standard grid including sub-ice topography information for Greenland and Antarctica, and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2021 Grid Collection also comprises all available data formats, including ESRI ASCII raster, GeoTIFF, and NetCDF. This data collection also contains the published and citable GEBCO_2021 grid (standard grid of ice surface elevation) available in NetCDF format.\r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2.2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2021 Grid represents all data within the 2021 compilation. The compilation of the GEBCO_2021 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2021 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "objectObservation": { "ob_id": 43508, "uuid": "74583b230b1343d9b4b302b8fbb5414f", "short_code": "ob", "title": "The GEBCO_2020 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2020 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2020 Grid Collection comprises the following data types: the standard grid (ice surface elevation), and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2020 Grid Collection is delivered in NetCDF format only. This data collection also contains the published and citable GEBCO_2020 grid (standard grid of ice surface elevation) available in NetCDF format.\r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2020 Grid represents all data within the 2020 compilation. The compilation of the GEBCO_2020 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the gridded bathymetric data sets were supplied as sparse grids by the Regional Centers, i.e. only grid cells that contain data were populated. These sparse grids were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2020 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." } }, { "ob_id": 1037, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43506, "uuid": "b5a93cb47d934f5295e2784313ecfb00", "short_code": "ob", "title": "The GEBCO_2022 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2022 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2022 Grid Collection comprises the following data types: the standard grid (ice surface elevation), the standard grid including sub-ice topography information for Greenland and Antarctica, and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2022 Grid Collection also comprises all available data formats, including ESRI ASCII raster, GeoTIFF, and NetCDF. This data collection also contains the published and citable GEBCO_2022 grid (standard grid of ice surface elevation) available in NetCDF format. \r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2.4 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2022 Grid represents all data within the 2022 compilation. The compilation of the GEBCO_2022 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a remove-restore blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2022 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "objectObservation": { "ob_id": 43507, "uuid": "b978db2f6e4e4bc49ca8ca026495aaac", "short_code": "ob", "title": "The GEBCO_2021 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2021 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2021 Grid Collection comprises the following data types: the standard grid (ice surface elevation), the standard grid including sub-ice topography information for Greenland and Antarctica, and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2021 Grid Collection also comprises all available data formats, including ESRI ASCII raster, GeoTIFF, and NetCDF. This data collection also contains the published and citable GEBCO_2021 grid (standard grid of ice surface elevation) available in NetCDF format.\r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2.2 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2021 Grid represents all data within the 2021 compilation. The compilation of the GEBCO_2021 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base grid without any blending. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2021 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." } }, { "ob_id": 1038, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43505, "uuid": "c25d585d8c314cbba6faebb4f21ff4a3", "short_code": "ob", "title": "The GEBCO_2023 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2023 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2023 Grid Collection comprises the following data types: the standard grid (ice surface elevation), the standard grid including sub-ice topography information for Greenland and Antarctica, and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2023 Grid Collection also comprises all available data formats, including ESRI ASCII raster, GeoTIFF, and NetCDF. This data collection also contains the published and citable GEBCO_2023 grid (standard grid of ice surface elevation) available in NetCDF format. \r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2.5.5 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2023 Grid represents all data within the 2023 compilation. The compilation of the GEBCO_2023 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a 'remove-restore' blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2023 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "objectObservation": { "ob_id": 43506, "uuid": "b5a93cb47d934f5295e2784313ecfb00", "short_code": "ob", "title": "The GEBCO_2022 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2022 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2022 Grid Collection comprises the following data types: the standard grid (ice surface elevation), the standard grid including sub-ice topography information for Greenland and Antarctica, and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2022 Grid Collection also comprises all available data formats, including ESRI ASCII raster, GeoTIFF, and NetCDF. This data collection also contains the published and citable GEBCO_2022 grid (standard grid of ice surface elevation) available in NetCDF format. \r\n\r\nIn regions outside of the Arctic Ocean area, the grid uses as a base Version 2.4 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2022 Grid represents all data within the 2022 compilation. The compilation of the GEBCO_2022 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a remove-restore blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2022 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." } }, { "ob_id": 1039, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43515, "uuid": "ca9e188d6141435eb7d851d40416a645", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 3.0", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 3.0 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. The IBCAO Version 3.0 Grid was released in June 2012.\r\n\r\nAt the time of its publication, IBCAO Version 3.0 represented the largest improvement in the data set since 1999. Taking advantage of new data sets collected by the circum-Arctic nations, opportunistic data collected from fishing vessels, data acquired from US Navy submarines and from research ships of various nations.\r\n\r\nBuilt using an improved gridding algorithm, the grid is on a 500 meter spacing, revealing much greater details of the Arctic seafloor than IBCAO Version 1.0 (2.5 km) and Version 2.0 (2.0 km). The area covered by multibeam surveys has increased from ~6 % in Version 2.0 to ~11% in Version 3.0.\r\n\r\nThe bathymetric grid released in IBCAO Version 3.0 is available in NetCDF, Esri ASCII or data GeoTIFF raster format. The IBCAO V3 data are built using the WGS84 horizontal datum, where the vertical datum is referenced to Mean Sea Level. Elevation values are provided in metres (negative below the sea surface). The IBCAO V3 dataset comprises polar stereographic grids at 500 x 500m grid intervals, true scale 75°N, in both smoothed (SM) and remove-restore (RR) method formats. The IBCAO V3 dataset also comprises geographic grids at 30 arc-second resolution in both smoothed (SM) and remove-restore (RR) method formats." }, "objectObservation": { "ob_id": 43514, "uuid": "1e69e123a0c04e2a83539dec43f1bfdb", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 2.23", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 2.23 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. The IBCAO Version 2.23 Grid was released in March 2008.\r\n\r\nThe bathymetric grid released in IBCAO Version 2.23 is available in NetCDF or Esri ASCII raster format. The grid is available as a geographic grid (one arc-minute or two arc-minute intervals), or in a polar stereographic projection (2000 x 2000 m grid interval, true scale 75°N, WGS 84 datum). The one-minute geographic grid imagery is also available in KMZ format for Google Earth. A Source Identifier Grid is delivered as a JPEG image for IBCAO version 2.23, to provide information on the source data sets included in the IBCAO grid." } }, { "ob_id": 1040, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43501, "uuid": "ec1c8283e5e1412a81b341a94033382f", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.0", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.0 is a gridded continuous terrain model covering ocean and land of the Arctic region. The grid has been compiled from sounding data covering an area of approximately 19.8% of the Arctic Ocean floor, of which 14.3% is comprised of multibeam bathymetry and about 5.5% with other sources, excluding digitized depth contours. IBCAO Version 4.0 has been compiled with support from the Nippon Foundation-GEBCO-Seabed 2030 Project, an international effort whose goal it is to see the entire world ocean mapped by 2030. A geographic version of the Polar Stereographic grid serves as input to the General Bathymetric Chart of Oceans (GEBCO) global gridded terrain model." }, "objectObservation": { "ob_id": 43515, "uuid": "ca9e188d6141435eb7d851d40416a645", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 3.0", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 3.0 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. The IBCAO Version 3.0 Grid was released in June 2012.\r\n\r\nAt the time of its publication, IBCAO Version 3.0 represented the largest improvement in the data set since 1999. Taking advantage of new data sets collected by the circum-Arctic nations, opportunistic data collected from fishing vessels, data acquired from US Navy submarines and from research ships of various nations.\r\n\r\nBuilt using an improved gridding algorithm, the grid is on a 500 meter spacing, revealing much greater details of the Arctic seafloor than IBCAO Version 1.0 (2.5 km) and Version 2.0 (2.0 km). The area covered by multibeam surveys has increased from ~6 % in Version 2.0 to ~11% in Version 3.0.\r\n\r\nThe bathymetric grid released in IBCAO Version 3.0 is available in NetCDF, Esri ASCII or data GeoTIFF raster format. The IBCAO V3 data are built using the WGS84 horizontal datum, where the vertical datum is referenced to Mean Sea Level. Elevation values are provided in metres (negative below the sea surface). The IBCAO V3 dataset comprises polar stereographic grids at 500 x 500m grid intervals, true scale 75°N, in both smoothed (SM) and remove-restore (RR) method formats. The IBCAO V3 dataset also comprises geographic grids at 30 arc-second resolution in both smoothed (SM) and remove-restore (RR) method formats." } }, { "ob_id": 1041, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43516, "uuid": "ae9cfa35e2454137a672f15ca00d0e64", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.1", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.1 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. In 2017, the IBCAO merged its efforts with the Nippon Foundation-GEBCO Seabed 2030 Project, with the goal of mapping the global seafloor by 2030. The IBCAO Version 4.1 Grid was released in July 2021, updated from IBCAO Version 4 to include new bathymetric data/compilations.\r\n\r\nThe bathymetric grid released in IBCAO Version 4.1 is available in NetCDF or data GeoTIFF raster format. Elevation values are provided in metres (negative below the sea surface). The IBCAO Version 4.1 dataset comprises a grid with Greenland ice sheet data at 200 x 200m grid cell spacing, and 400 x 400m grid cell spacing. A version of the 4.1 grid without Greenland ice sheet data is also available. Alongside the bathymetric grid, a data Type Identifier Grid (TID) and Source Identifier Grid (SID) are also provided, each at 200 x 200m resolution. The TID indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on, whilst the SID has a unique number for each of the source data sets included in the bathymetric grid. \r\n\r\nThe data are made available in Polar Stereographic projection co-ordinates (meters), EPSG:3996, true scale set at 75°N. The horizontal datum for the data set is WGS 84 and vertical datum can assumed to be Mean Sea Level (however, note there may be datum issues for older data, which can be to chart datum). Elevation values are in meters (floating point)." }, "objectObservation": { "ob_id": 43501, "uuid": "ec1c8283e5e1412a81b341a94033382f", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.0", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.0 is a gridded continuous terrain model covering ocean and land of the Arctic region. The grid has been compiled from sounding data covering an area of approximately 19.8% of the Arctic Ocean floor, of which 14.3% is comprised of multibeam bathymetry and about 5.5% with other sources, excluding digitized depth contours. IBCAO Version 4.0 has been compiled with support from the Nippon Foundation-GEBCO-Seabed 2030 Project, an international effort whose goal it is to see the entire world ocean mapped by 2030. A geographic version of the Polar Stereographic grid serves as input to the General Bathymetric Chart of Oceans (GEBCO) global gridded terrain model." } }, { "ob_id": 1042, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43517, "uuid": "c46755ee7d604d8591fee4dc5f56b9e3", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.2", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.2 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. In 2017, the IBCAO merged its efforts with the Nippon Foundation-GEBCO Seabed 2030 Project, with the goal of mapping the global seafloor by 2030. The IBCAO Version 4.2 Grid was released in August 2022, updated from IBCAO Version 4.1 to include new bathymetric data/compilations.\r\n\r\nThe bathymetric grid released in IBCAO Version 4.2 is available in NetCDF or data GeoTIFF raster format. Elevation values are provided in metres (negative below the sea surface). The IBCAO Version 4.2 dataset comprises a grid with Greenland ice sheet data at 200 x 200m grid cell spacing, and 400 x 400m grid cell spacing. A version of the 4.2 grid without Greenland ice sheet data is also available. Alongside the bathymetric grid, a data Type Identifier Grid (TID) and Source Identifier Grid (SID) are also provided, each at 200 x 200m resolution. The TID indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on, whilst the SID has a unique number for each of the source data sets included in the bathymetric grid. \r\n\r\nThe data are made available in Polar Stereographic projection co-ordinates (meters), EPSG:3996, true scale set at 75°N. The horizontal datum for the data set is WGS 84 and vertical datum can assumed to be Mean Sea Level (however, note there may be datum issues for older data, which can be to chart datum). Elevation values are in meters (floating point)." }, "objectObservation": { "ob_id": 43516, "uuid": "ae9cfa35e2454137a672f15ca00d0e64", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.1", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.1 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. In 2017, the IBCAO merged its efforts with the Nippon Foundation-GEBCO Seabed 2030 Project, with the goal of mapping the global seafloor by 2030. The IBCAO Version 4.1 Grid was released in July 2021, updated from IBCAO Version 4 to include new bathymetric data/compilations.\r\n\r\nThe bathymetric grid released in IBCAO Version 4.1 is available in NetCDF or data GeoTIFF raster format. Elevation values are provided in metres (negative below the sea surface). The IBCAO Version 4.1 dataset comprises a grid with Greenland ice sheet data at 200 x 200m grid cell spacing, and 400 x 400m grid cell spacing. A version of the 4.1 grid without Greenland ice sheet data is also available. Alongside the bathymetric grid, a data Type Identifier Grid (TID) and Source Identifier Grid (SID) are also provided, each at 200 x 200m resolution. The TID indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on, whilst the SID has a unique number for each of the source data sets included in the bathymetric grid. \r\n\r\nThe data are made available in Polar Stereographic projection co-ordinates (meters), EPSG:3996, true scale set at 75°N. The horizontal datum for the data set is WGS 84 and vertical datum can assumed to be Mean Sea Level (however, note there may be datum issues for older data, which can be to chart datum). Elevation values are in meters (floating point)." } }, { "ob_id": 1043, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43518, "uuid": "5846574e36e942a29b778534980280b9", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.2.13", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.2.13 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. In 2017, the IBCAO merged its efforts with the Nippon Foundation-GEBCO Seabed 2030 Project, with the goal of mapping the global seafloor by 2030. The IBCAO Version 4.2.13 Grid was released in August 2022, updated from IBCAO Version 4.2 to include new bathymetric data/compilations.\r\n\r\nThe bathymetric grid released in IBCAO Version 4.2.13 is available in NetCDF or data GeoTIFF raster format. Elevation values are provided in metres (negative below the sea surface). The IBCAO Version 4.2.13 dataset comprises a grid with Greenland ice sheet data at 200 x 200m grid cell spacing, and 400 x 400m grid cell spacing. A version of the 4.2.13 grid without Greenland ice sheet data is also available. Alongside the bathymetric grid, a data Type Identifier Grid (TID) and Source Identifier Grid (SID) are also provided, each at 200 x 200m resolution. The TID indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on, whilst the SID has a unique number for each of the source data sets included in the bathymetric grid. \r\n\r\nThe data are made available in Polar Stereographic projection co-ordinates (meters), EPSG:3996, true scale set at 75°N. The horizontal datum for the data set is WGS 84 and vertical datum can assumed to be Mean Sea Level (however, note there may be datum issues for older data, which can be to chart datum). Elevation values are in meters (floating point)." }, "objectObservation": { "ob_id": 43517, "uuid": "c46755ee7d604d8591fee4dc5f56b9e3", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.2", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.2 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. In 2017, the IBCAO merged its efforts with the Nippon Foundation-GEBCO Seabed 2030 Project, with the goal of mapping the global seafloor by 2030. The IBCAO Version 4.2 Grid was released in August 2022, updated from IBCAO Version 4.1 to include new bathymetric data/compilations.\r\n\r\nThe bathymetric grid released in IBCAO Version 4.2 is available in NetCDF or data GeoTIFF raster format. Elevation values are provided in metres (negative below the sea surface). The IBCAO Version 4.2 dataset comprises a grid with Greenland ice sheet data at 200 x 200m grid cell spacing, and 400 x 400m grid cell spacing. A version of the 4.2 grid without Greenland ice sheet data is also available. Alongside the bathymetric grid, a data Type Identifier Grid (TID) and Source Identifier Grid (SID) are also provided, each at 200 x 200m resolution. The TID indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on, whilst the SID has a unique number for each of the source data sets included in the bathymetric grid. \r\n\r\nThe data are made available in Polar Stereographic projection co-ordinates (meters), EPSG:3996, true scale set at 75°N. The horizontal datum for the data set is WGS 84 and vertical datum can assumed to be Mean Sea Level (however, note there may be datum issues for older data, which can be to chart datum). Elevation values are in meters (floating point)." } }, { "ob_id": 1044, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43519, "uuid": "3bc493d393a843ee9422f9c610fcd437", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 5", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 5 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. In 2017, the IBCAO merged its efforts with the Nippon Foundation-GEBCO Seabed 2030 Project, with the goal of mapping the global seafloor by 2030. The IBCAO Version 5 Grid was released in 2024, updated from IBCAO Version 4.2.13 to include new bathymetric data/compilations.\r\n\r\nThe bathymetric grid released in IBCAO Version 5 is available in NetCDF or data GeoTIFF raster format. Elevation values are provided in metres (negative below the sea surface). The IBCAO Version 5 dataset comprises a grid with Greenland ice sheet data at 100 m, 200 m and 400 m grid cell spacing. A Version 5 grid without Greenland ice sheet data is also available. IBCAO Version 5 imagery is also provided in .tiff format at 100m grid cell spacing. \r\n\r\nAlongside the bathymetric grid, a data Type Identifier Grid (TID) and Source Identifier Grid (SID) are also provided, each at 100 m resolution. The TID indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on, whilst the SID has a unique number for each of the source data sets included in the bathymetric grid. \r\n\r\nThe data are made available in Polar Stereographic projection co-ordinates (meters), EPSG:3996, true scale set at 75°N. The horizontal datum for the data set is WGS 84 and vertical datum can assumed to be Mean Sea Level (however, note there may be datum issues for older data, which can be to chart datum). Elevation values are in meters (floating point)." }, "objectObservation": { "ob_id": 43518, "uuid": "5846574e36e942a29b778534980280b9", "short_code": "ob", "title": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.2.13", "abstract": "The International Bathymetric Chart of the Arctic Ocean (IBCAO) Version 4.2.13 is a gridded continuous terrain model covering ocean and land of the Arctic region. The International Bathymetric Chart of the Arctic Ocean was initiated in 1997 and has since been the authoritative source of bathymetry for the Arctic Ocean. In 2017, the IBCAO merged its efforts with the Nippon Foundation-GEBCO Seabed 2030 Project, with the goal of mapping the global seafloor by 2030. The IBCAO Version 4.2.13 Grid was released in August 2022, updated from IBCAO Version 4.2 to include new bathymetric data/compilations.\r\n\r\nThe bathymetric grid released in IBCAO Version 4.2.13 is available in NetCDF or data GeoTIFF raster format. Elevation values are provided in metres (negative below the sea surface). The IBCAO Version 4.2.13 dataset comprises a grid with Greenland ice sheet data at 200 x 200m grid cell spacing, and 400 x 400m grid cell spacing. A version of the 4.2.13 grid without Greenland ice sheet data is also available. Alongside the bathymetric grid, a data Type Identifier Grid (TID) and Source Identifier Grid (SID) are also provided, each at 200 x 200m resolution. The TID indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on, whilst the SID has a unique number for each of the source data sets included in the bathymetric grid. \r\n\r\nThe data are made available in Polar Stereographic projection co-ordinates (meters), EPSG:3996, true scale set at 75°N. The horizontal datum for the data set is WGS 84 and vertical datum can assumed to be Mean Sea Level (however, note there may be datum issues for older data, which can be to chart datum). Elevation values are in meters (floating point)." } }, { "ob_id": 1045, "relationType": "IsSupplementTo", "subjectObservation": { "ob_id": 43500, "uuid": "2920b2ea41d244cd9bfd95be0f4dc4a9", "short_code": "ob", "title": "The GEBCO_2019 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2019 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The grid uses as a base Version 1 of the SRTM15_plus data set (Sandwell et al). This data set is a fusion of land topography with measured and estimated seafloor topography. It is largely based on version 11 of SRTM30_plus (5). Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project, and from a number of international and national data repositories and regional mapping initiatives. The GEBCO_2019 Grid represents all data within the 2019 compilation. The compilation of the GEBCO_2019 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. The majority of the compilation was done using the remove-restore procedure (Smith and Sandwell, 1997; Becker, Sandwell and Smith, 2009 and Hell and Jakobsson, 2011). This is a two stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2019 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA)." }, "objectObservation": { "ob_id": 43509, "uuid": "cefbb8b5fc874bfc84f75169a611de4f", "short_code": "ob", "title": "The GEBCO_2019 Grid Collection - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2019 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. The GEBCO_2019 Grid Collection, comprises the following data types: the standard grid (ice surface elevation), the Source Identifier Grid (SID), and the Type Identifier Grid (TID). The Type Identifier Grid indicates the type of source data that the corresponding grid cell in the bathymetric grid is based on. The GEBCO_2019 Grid Collection is available in NetCDF format only. This data collection also contains the published and citable GEBCO_2019 grid (standard grid of ice surface elevation) available in NetCDF format. \r\n\r\nThe grid uses as a base Version 1 of the SRTM15_plus data set (Sandwell et al). This data set is a fusion of land topography with measured and estimated seafloor topography. It is largely based on version 11 of SRTM30_plus (5). Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project, and from a number of international and national data repositories and regional mapping initiatives. The GEBCO_2019 Grid represents all data within the 2019 compilation. The compilation of the GEBCO_2019 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. The majority of the compilation was done using the remove-restore procedure (Smith and Sandwell, 1997; Becker, Sandwell and Smith, 2009 and Hell and Jakobsson, 2011). This is a two stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2019 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA)." } }, { "ob_id": 1046, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43489, "uuid": "5ec6949356de45c2a3b3565d297a80fa", "short_code": "ob", "title": "The GEBCO_2024 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2024 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions largely outside of the Arctic Ocean area, the grid uses as a base Version 2.6 of the SRTM15_plus data set (Tozer et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2024 Grid represents all data within the 2024 compilation. The compilation of the GEBCO_2024 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a ‘remove-restore’ blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2024 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute (AWI), Germany; Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research (NIWA), New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory (LDEO), Columbia University, USA; Arctic and North Pacific Oceans - jointly hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." }, "objectObservation": { "ob_id": 43496, "uuid": "bb0e44f6520f415e9a07601bb21ac3c8", "short_code": "ob", "title": "The GEBCO_2023 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2023 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 15 arc seconds. In regions outside of the Arctic Ocean area, the grid uses as a base Version 2.5.5 of the SRTM15_plus data set (Tozer, B. et al, 2019). This data set is a fusion of land topography with measured and estimated seafloor topography. Included on top of this base grid are gridded bathymetric data sets developed by the four Regional Centers of The Nippon Foundation-GEBCO Seabed 2030 Project. The GEBCO_2023 Grid represents all data within the 2023 compilation. The compilation of the GEBCO_2023 Grid was carried out at the Seabed 2030 Global Center, hosted at the National Oceanography Centre, UK, with the aim of producing a seamless global terrain model. Outside of Polar regions, the Regional Centers provide their data sets as sparse grids i.e. only grid cells that contain data are populated. These data sets were included on to the base using a 'remove-restore' blending procedure. This is a two-stage process of computing the difference between the new data and the base grid and then gridding the difference and adding the difference back to the existing base grid. The aim is to achieve a smooth transition between the new and base data sets with the minimum of perturbation of the existing base data set. The data sets supplied in the form of complete grids (primarily areas north of 60N and south of 50S) were included using feather blending techniques from GlobalMapper software. The GEBCO_2023 Grid has been developed through the Nippon Foundation-GEBCO Seabed 2030 Project. This is a collaborative project between the Nippon Foundation of Japan and the General Bathymetric Chart of the Oceans (GEBCO). It aims to bring together all available bathymetric data to produce the definitive map of the world ocean floor by 2030 and make it available to all. Funded by the Nippon Foundation, the four Seabed 2030 Regional Centers include the Southern Ocean - hosted at the Alfred Wegener Institute, Germany; South and West Pacific Ocean - hosted at the National Institute of Water and Atmospheric Research, New Zealand; Atlantic and Indian Oceans - hosted at the Lamont-Doherty Earth Observatory, Columbia University, USA; Arctic and North Pacific Oceans - hosted at Stockholm University, Sweden and the Center for Coastal and Ocean Mapping at the University of New Hampshire, USA." } }, { "ob_id": 1047, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43535, "uuid": "0c9dfec287bf4b6c84435d1182825389", "short_code": "ob", "title": "The GEBCO_2014 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2014 Grid is a global continuous terrain model for ocean and land with a spatial resolution of 30 arc-seconds. The GEBCO_2019 Grid Collection, comprises the following data types: the standard grid (ice surface elevation), and the Source Identifier Grid (SID). The GEBCO_2014 Grid Collection is available in NetCDF format only. Please note the GEBCO 2014 grid is a legacy dataset that has been superseded by more recent releases." }, "objectObservation": { "ob_id": 43536, "uuid": "e7b366a8516240b7a023edb25fdaf1bf", "short_code": "ob", "title": "The GEBCO_2008 Grid - a continuous terrain model of the global oceans and land", "abstract": "The GEBCO_2008 Grid is a global continuous terrain model for ocean and land with a spatial resolution of one arc-minute. The GEBCO_2008 Grid, comprises the one minute grid in NetCDF format only, alongside accompanying terms of use and documentation. Please note that the GEBCO 2008 One Minute Grid is a legacy dataset that has been superseded by subsequent releases of the GEBCO grid." } }, { "ob_id": 1048, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43287, "uuid": "0397ca6f625e47f489684bad2bd533bb", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Monthly sea surface salinity product for the Southern Hemisphere on a 25km EASE grid, v5.5, for 2010 to 2023", "abstract": "This dataset contains Sea Surface Salinity (SSS) v5.5 data at a spatial resolution of 50km and a time resolution of 1 month. It is spatially sampled on a SH polar 25km EASE (Equal Area Scalable Earth) grid with 15 days of time sampling. This product is also available separately on a regular lat/lon grid. A weekly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page." }, "objectObservation": { "ob_id": 41235, "uuid": "249d2907975a45a8b078e1a8bd4a7343", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Monthly sea surface salinity product for the Southern Hemisphere on a 25km EASE grid, v04.41, for 2010 to 2022", "abstract": "This dataset contains Sea Surface Salinity (SSS) v04.41 data at a spatial resolution of 50km and a time resolution of 1 month. It is spatially sampled on a SH polar 25km EASE (Equal Area Scalable Earth) grid with 15 days of time sampling. This product is also available separately on a regular lat/lon grid. A weekly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page.\r\n\r\nCompared to version 3.21 of the data, version 04.41 SSS is of similar or improved quality. The main improvements concern high latitude regions (reduced seasonal biases and better ice flagging). The v04.41 dataset covers a longer period (Jan 2010-Oct 2022)." } }, { "ob_id": 1049, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43288, "uuid": "3339dec1fbd94599802aba7f1c665679", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Monthly sea surface salinity product on a 0.25 degree global grid, v5.5, for 2010 to 2023", "abstract": "This dataset contains Sea Surface Salinity (SSS) v5.5 data at a spatial resolution of 50km and a time resolution of 1 month. It is spatially sampled on a 0.25 degree grid and 15 days of time sampling. This product is also available separately on polar 25km EASE (Equal Area Scalable Earth) grids. A weekly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page." }, "objectObservation": { "ob_id": 41234, "uuid": "7cc16c0d8d2f49278ed5ebf8341ed40b", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Monthly sea surface salinity product on a global grid, v04.41, for 2010 to 2022", "abstract": "This dataset contains Sea Surface Salinity (SSS) v04.41 data at a spatial resolution of 50km and a time resolution of 1 month. It is spatially sampled on a 0.25 degree grid and 15 days of time sampling. This product is also available separately on polar 25km EASE (Equal Area Scalable Earth) grids. A weekly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page.\r\n\r\nCompared to version 3.21 of the data, version 04.41 SSS is of similar or improved quality. The main improvements concern high latitude regions (reduced seasonal biases and better ice flagging). The v04.41 dataset covers a longer period (Jan 2010-Oct 2022)." } }, { "ob_id": 1050, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43291, "uuid": "5b48a34fb4134bbd99acace7767e5b3e", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Weekly sea surface salinity product for the Northern Hemisphere on a 25km EASE grid, v5.5, for 2010 to 2023", "abstract": "This dataset contains Sea Surface Salinity (SSS) v5.5 data at a spatial resolution of 50km and a time resolution of 1 week. It is spatially sampled on a NH polar 25km EASE (Equal Area Scalable Earth) grid with 1 day of time sampling. This product is also available separately on a regular lat/lon grid. A monthly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page." }, "objectObservation": { "ob_id": 41231, "uuid": "471698c7db45451cbf3b7d834ecab9fd", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Weekly sea surface salinity product for the Northern Hemisphere on a 25km EASE grid, v04.41, for 2010 to 2022", "abstract": "This dataset contains Sea Surface Salinity (SSS) v04.41 data at a spatial resolution of 50km and a time resolution of 1 week. It is spatially sampled on a NH polar 25km EASE (Equal Area Scalable Earth) grid with 1 day of time sampling. This product is also available separately on a regular lat/lon grid. A monthly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page.\r\n\r\nCompared to version 3.21 of the data, version 04.41 SSS is of similar or improved quality. The main improvements concern high latitude regions (reduced seasonal biases and better ice flagging). The v04.41 dataset covers a longer period (Jan 2010-Oct 2022)." } }, { "ob_id": 1051, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43289, "uuid": "c302b1dceb8a4c39a31d18b60f236d09", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Weekly sea surface salinity product for the Southern Hemisphere on a 25km EASE grid, v5.5, for 2010 to 2023", "abstract": "This dataset contains Sea Surface Salinity (SSS) v5.5 data at a spatial resolution of 50km and a time resolution of 1 week. It is spatially sampled on a SH polar 25km EASE (Equal Area Scalable Earth) grid with 1 day of time sampling. This product is also available separately on a regular lat/lon grid. A monthly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page." }, "objectObservation": { "ob_id": 41233, "uuid": "a601f52222ba486aa9f0a18db3a009b7", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Weekly sea surface salinity product for the Southern Hemisphere on a 25km EASE grid, v04.41, for 2010 to 2022", "abstract": "This dataset contains Sea Surface Salinity (SSS) v04.41 data at a spatial resolution of 50km and a time resolution of 1 week. It is spatially sampled on a SH polar 25km EASE (Equal Area Scalable Earth) grid with 1 day of time sampling. This product is also available separately on a regular lat/lon grid. A monthly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page.\r\n\r\nCompared to version 3.21 of the data, version 04.41 SSS is of similar or improved quality. The main improvements concern high latitude regions (reduced seasonal biases and better ice flagging). The v04.41 dataset covers a longer period (Jan 2010-Oct 2022)." } }, { "ob_id": 1052, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43290, "uuid": "4321d9b540fe48f8943179aa3ef06c79", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Weekly sea surface salinity product on a 0.25 degree global grid, v5.5, for 2010 to 2023", "abstract": "This dataset contains Sea Surface Salinity (SSS) v5.5 data at a spatial resolution of 50km and a time resolution of 1 week. It is spatially sampled on a 0.25 degree grid and 1 day of time sampling. This product is also available separately on polar 25km EASE (Equal Area Scalable Earth) grids. A monthly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page." }, "objectObservation": { "ob_id": 41232, "uuid": "0d0f4a942a144d9cab9263de3949a5d6", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Weekly sea surface salinity product on a global grid, v04.41, for 2010 to 2022", "abstract": "This dataset contains Sea Surface Salinity (SSS) v04.41 data at a spatial resolution of 50km and a time resolution of 1 week. It is spatially sampled on a 0.25 degree grid and 1 day of time sampling. This product is also available separately on polar 25km EASE (Equal Area Scalable Earth) grids. A monthly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page.\r\n\r\nCompared to version 3.21 of the data, version 04.41 SSS is of similar or improved quality. The main improvements concern high latitude regions (reduced seasonal biases and better ice flagging). The v04.41 dataset also covers a longer period (Jan 2010-Oct 2022)." } }, { "ob_id": 1053, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43286, "uuid": "3d3e52e597fe40b0ab5984cc0ee82de3", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Monthly sea surface salinity product for the Northern Hemisphere on a 25km EASE grid, v5.5, for 2010 to 2023", "abstract": "This dataset contains Sea Surface Salinity (SSS) v5.5 data at a spatial resolution of 50km and a time resolution of 1 month. It is spatially sampled on a NH polar 25km EASE (Equal Area Scaleable Earth) grid with 15 days of time sampling. This product is also available separately on a regular lat/lon grid. A weekly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page." }, "objectObservation": { "ob_id": 41236, "uuid": "ecc355e395ed4c5597c613ae7f9c53b0", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Monthly sea surface salinity product for the Northern Hemisphere on a 25km EASE grid, v04.41, for 2010 to 2022", "abstract": "This dataset contains Sea Surface Salinity (SSS) v04.41 data at a spatial resolution of 50km and a time resolution of 1 month. It is spatially sampled on a NH polar 25km EASE (Equal Area Scaleable Earth) grid with 15 days of time sampling. This product is also available separately on a regular lat/lon grid. A weekly product is also available. In addition to salinity, information on uncertainties are provided. For more information see the user guide and other product documentation available from the linked Sea Surface Salinity CCI web page.\r\n\r\nCompared to version 3.21 of the data, version 04.41 SSS is of similar or improved quality. The main improvements concern high latitude regions (reduced seasonal biases and better ice flagging). The v04.41 dataset covers a longer period (Jan 2010-Oct 2022)." } }, { "ob_id": 1054, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43540, "uuid": "2b8c6a8f1abd40a6b0ce07c40b1c57ff", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from Sentinel-5P, generated with the WFM-DOAS algorithm, version 1.8, November 2017 - June 2024", "abstract": "This product is the column-average dry-air mole fraction of atmospheric methane, denoted XCH4. It has been retrieved from radiance measurements from the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite in the 2.3 µm spectral range of the solar spectral range, using the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS or WFMD) retrieval algorithm. This dataset is also referred to as CH4_S5P_WFMD. This version of the product is version 1.8, and covers the period from November 2017 - June 2024. \r\n\r\nThe WFMD algorithm is based on iteratively fitting a simulated radiance spectrum to the measured spectrum using a least-squares method. The algorithm is very fast as it is based on a radiative transfer model based look-up table scheme. The product is limited to cloud-free scenes on the Earth's day side.\r\n\r\nThese data were produced as part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project.\r\n\r\nWhen citing this dataset, please also cite the following peer-reviewed publication: \r\nSchneising, O., Buchwitz, M., Hachmeister, J., Vanselow, S., Reuter, M., Buschmann, M., Bovensmann, H., and Burrows, J. P.: Advances in retrieving XCH4 and XCO from Sentinel-5 Precursor: improvements in the scientific TROPOMI/WFMD algorithm, Atmos. Meas. Tech., 16, 669–694, https://doi.org/10.5194/amt-16-669-2023, 2023." }, "objectObservation": { "ob_id": 41358, "uuid": "8175ede3a1d642deba8f4cce49d7bda8", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from Sentinel-5P, generated with the WFM-DOAS algorithm, version 1.8, November 2017 - October 2023", "abstract": "This product is the column-average dry-air mole fraction of atmospheric methane, denoted XCH4. It has been retrieved from radiance measurements from the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite in the 2.3 µm spectral range of the solar spectral range, using the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS or WFMD) retrieval algorithm. This dataset is also referred to as CH4_S5P_WFMD. This version of the product is version 1.8, and covers the period from November 2017 - October 2023. \r\n\r\nThe WFMD algorithm is based on iteratively fitting a simulated radiance spectrum to the measured spectrum using a least-squares method. The algorithm is very fast as it is based on a radiative transfer model based look-up table scheme. The product is limited to cloud-free scenes on the Earth's day side.\r\n\r\nThese data were produced as part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project.\r\n\r\nWhen citing this dataset, please also cite the following peer-reviewed publication: \r\nSchneising, O., Buchwitz, M., Hachmeister, J., Vanselow, S., Reuter, M., Buschmann, M., Bovensmann, H., and Burrows, J. P.: Advances in retrieving XCH4 and XCO from Sentinel-5 Precursor: improvements in the scientific TROPOMI/WFMD algorithm, Atmos. Meas. Tech., 16, 669–694, https://doi.org/10.5194/amt-16-669-2023, 2023." } }, { "ob_id": 1055, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43344, "uuid": "dcad505a8203486e8a3b530a6dff00ca", "short_code": "ob", "title": "ATSR-2: Multimission land and sea surface temperature data. Fourth Reprocessing (v4) AT_1_RBT", "abstract": "The Along Track Scanning Radiometer2 (ATSR2) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThe ERS2 ATSR2 Level 1B Brightness Temperature/Radiance product (RBT) contains top of atmosphere (TOA) brightness temperature (BT) values for the infra-red channels and radiance values for the visible channels, on a 1-km pixel grid. Values for each channel and for the nadir and oblique views occupy separate NetCDF files within the Sentinel-SAFE format, along with associated uncertainty estimates. Additional files contain cloud flags, land and water masks, and confidence flags for each image pixel, as well as instrument and ancillary meteorological information.\r\n\r\nThis A/ATSR product [ENV_AT_1_RBT] in NetCDF format stemming from the 4th AATSR reprocessing, is a continuation of ERS ATSR data and a precursor of Sentinel-3 SLSTR data. It has replaced the former L1B product [ATS_TOA_1P] in Envisat format from the 3rd reprocessing. Users with Envisat-format products are recommended to move to the new Sentinel-SAFE like/NetCDF format products. \r\n\r\nThe 4th reprocessing of Envisat AATSR data was completed in 2022." }, "objectObservation": { "ob_id": 19743, "uuid": "62407e5f98d54104a5165e22a60c9968", "short_code": "ob", "title": "ATSR-2: Multimission land and sea surface temperature data, v2.0", "abstract": "Along-Track Scanning Radiometer (ATSR) mission was funded jointly by the UK Department of Energy and Climate Change External Link (DECC) and the Australian Department of Innovation, Industry, Science and Research External Link (DIISR).\r\n\r\nThis dataset collection contains version 2.0 ATSR2 Multimission land and sea surface temperature data.\r\n\r\nThe instrument uses thermal channels at 3.7, 10.8, and 12 microns wavelength; and reflected visible/near infra-red channels at 0.555, 0.659, 0.865, and 1.61 microns wavelength. Level 1b products contain gridded brightness temperature and reflectance. Level 2 products contain land and sea-surface temperature, and NDVI at a range of spatial resolutions. The third reprocessing was done to implement updated algorithms, processors, and auxiliary files. The data were acquired by the European Space Agency's (ESA) Envisat satellite, and the NERC Earth Observation Data Centre (NEODC) mirrors the data for UK users." } }, { "ob_id": 1058, "relationType": "IsSupplementTo", "subjectObservation": { "ob_id": 43592, "uuid": "1d2020153f84407ba2852acfd8579886", "short_code": "ob", "title": "Mean, Minimum and Maximum Central England Temperature (HadCET) series post 1973 static adjustments, v2.0.0.0", "abstract": "The Central England Temperature (HadCET) daily mean series is anchored to Gordon Manley’s original temperature record prior to 1973. Between 1848 and 1878, adjustments are applied to account for periods when only a single station was in use.\r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nFrom 1973 onwards, multiple adjustments ensure continuity with Manley’s series, homogenise the current station selection with Manley’s original dataset, and correct for the effects of increasing urbanisation.\r\n \r\nThese static adjustments are calculated on a monthly basis and are applied uniformly to all daily values within each month from 1973 to the present. \r\n \r\nUrbanisation adjustments remain static from November 2004 onward, while adjustments between 1974 and October 2004 are graded to reflect a progressive increase in urbanisation effects over time.\r\n \r\nThis dataset contains the post-Manley extended adjustments, station homogenisation adjustments, and static urban corrections.\r\n\r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n\r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" }, "objectObservation": { "ob_id": 43589, "uuid": "0363d592dd3548febaa6fc4056a618a9", "short_code": "ob", "title": "Daily Mean, Minimum and Maximum Central England Temperature series v2.0.0.0", "abstract": "The Central England Temperature (HadCET) daily series start in 1772 for mean temperature and 1878 for minimum and maximum temperature.\r\n \r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nPrior to 1973, the daily mean temperature series is anchored to the mean temperature series constructed by Gordon Manley, with the daily minimum and maximum temperature series adjusted to the mean temperature series to ensure values are consistent.\r\n \r\nAlthough the station selection has changed through time, the series is homogenised and adjusted to ensure consistency with Manley's selection and for periods when only a single station value was used.\r\n \r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n \r\nFor more information on the change in station selection, please refer to the papers supplied with the data collection.\r\n \r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" } }, { "ob_id": 1059, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43591, "uuid": "06f14deceb27463c86f350ad278245ca", "short_code": "ob", "title": "Seasonal Mean, Minimum and Maximum Central England Temperature (HadCET) series v2.0.0.0", "abstract": "The Central England Temperature (HadCET) seasonal series starts in 1659 for mean temperature and 1878 for minimum and maximum temperature.\r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nThe seasonal temperature series are derived as the mean of the monthly temperature series values.\r\n\r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n \r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" }, "objectObservation": { "ob_id": 13872, "uuid": "268cfd67e1d148fe8120655c6b8de402", "short_code": "ob", "title": "Seasonal Mean, Minimum and Maximum Central England Temperature series", "abstract": "The longest available instrumental record of temperature in the world is now available at the BADC. The seasonal data starts in 1659.\r\n\r\nThe mean, minimum and maximum datasets are updated monthly, with data for a month usually available by the 3rd of the next month. A provisional CET value for the current month is calculated on a daily basis. The mean monthly data series begins in 1659. Mean maximum and minimum daily and monthly data are also available, beginning in 1878. \r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London). \r\n\r\nThe following stations are used by the Met Office to compile the CET data: Rothamsted, Malvern, Squires Gate and Ringway.\r\n\r\nBut in November 2004, the weather station Stonyhurst replaced Ringway and revised urban warming and bias adjustments have now been applied to the Stonyhurst data after a period of reduced reliability from the station in the summer months. \r\n\r\nThe data set is compiled by the Met Office Hadley Centre." } }, { "ob_id": 1061, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 43590, "uuid": "6d41468a8cd4462e923b4fc4f28b2dda", "short_code": "ob", "title": "Monthly Mean, Minimum and Maximum Central England Temperature (HadCET) series v2.0.0.0", "abstract": "The Central England Temperature (HadCET) monthly series start in 1659 for mean temperature and 1878 for minimum and maximum temperature.\r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nThe monthly temperature series are derived as the mean of the daily temperature series values.\r\n \r\nFor mean temperature, the monthly values from 1659 to 1771 are derived directly from Gordon Manley's monthly mean values.\r\n\r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n \r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" }, "objectObservation": { "ob_id": 43589, "uuid": "0363d592dd3548febaa6fc4056a618a9", "short_code": "ob", "title": "Daily Mean, Minimum and Maximum Central England Temperature series v2.0.0.0", "abstract": "The Central England Temperature (HadCET) daily series start in 1772 for mean temperature and 1878 for minimum and maximum temperature.\r\n \r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nPrior to 1973, the daily mean temperature series is anchored to the mean temperature series constructed by Gordon Manley, with the daily minimum and maximum temperature series adjusted to the mean temperature series to ensure values are consistent.\r\n \r\nAlthough the station selection has changed through time, the series is homogenised and adjusted to ensure consistency with Manley's selection and for periods when only a single station value was used.\r\n \r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n \r\nFor more information on the change in station selection, please refer to the papers supplied with the data collection.\r\n \r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" } }, { "ob_id": 1062, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 43591, "uuid": "06f14deceb27463c86f350ad278245ca", "short_code": "ob", "title": "Seasonal Mean, Minimum and Maximum Central England Temperature (HadCET) series v2.0.0.0", "abstract": "The Central England Temperature (HadCET) seasonal series starts in 1659 for mean temperature and 1878 for minimum and maximum temperature.\r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nThe seasonal temperature series are derived as the mean of the monthly temperature series values.\r\n\r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n \r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" }, "objectObservation": { "ob_id": 43590, "uuid": "6d41468a8cd4462e923b4fc4f28b2dda", "short_code": "ob", "title": "Monthly Mean, Minimum and Maximum Central England Temperature (HadCET) series v2.0.0.0", "abstract": "The Central England Temperature (HadCET) monthly series start in 1659 for mean temperature and 1878 for minimum and maximum temperature.\r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nThe monthly temperature series are derived as the mean of the daily temperature series values.\r\n \r\nFor mean temperature, the monthly values from 1659 to 1771 are derived directly from Gordon Manley's monthly mean values.\r\n\r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n \r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" } }, { "ob_id": 1063, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43590, "uuid": "6d41468a8cd4462e923b4fc4f28b2dda", "short_code": "ob", "title": "Monthly Mean, Minimum and Maximum Central England Temperature (HadCET) series v2.0.0.0", "abstract": "The Central England Temperature (HadCET) monthly series start in 1659 for mean temperature and 1878 for minimum and maximum temperature.\r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nThe monthly temperature series are derived as the mean of the daily temperature series values.\r\n \r\nFor mean temperature, the monthly values from 1659 to 1771 are derived directly from Gordon Manley's monthly mean values.\r\n\r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n \r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" }, "objectObservation": { "ob_id": 13870, "uuid": "37acfb4514ca4ef7b711e2cf568280a4", "short_code": "ob", "title": "Monthly Mean, Minimum and Maximum Central England Temperature series", "abstract": "The longest available instrumental record of temperature in the world is now available at the BADC. The monthly data starts in 1659.\r\n\r\nThe mean, minimum and maximum datasets are updated monthly, with data for a month usually available by the 3rd of the next month. A provisional CET value for the current month is calculated on a daily basis. The mean monthly data series begins in 1659. Mean maximum and minimum daily and monthly data are also available, beginning in 1878. \r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London). \r\n\r\nThe following stations are used by the Met Office to compile the CET data: Rothamsted, Malvern, Squires Gate and Ringway.\r\n\r\nBut in November 2004, the weather station Stonyhurst replaced Ringway and revised urban warming and bias adjustments have now been applied to the Stonyhurst data after a period of reduced reliability from the station in the summer months. \r\n\r\nThe data set is compiled by the Met Office Hadley Centre." } }, { "ob_id": 1064, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43589, "uuid": "0363d592dd3548febaa6fc4056a618a9", "short_code": "ob", "title": "Daily Mean, Minimum and Maximum Central England Temperature series v2.0.0.0", "abstract": "The Central England Temperature (HadCET) daily series start in 1772 for mean temperature and 1878 for minimum and maximum temperature.\r\n \r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nPrior to 1973, the daily mean temperature series is anchored to the mean temperature series constructed by Gordon Manley, with the daily minimum and maximum temperature series adjusted to the mean temperature series to ensure values are consistent.\r\n \r\nAlthough the station selection has changed through time, the series is homogenised and adjusted to ensure consistency with Manley's selection and for periods when only a single station value was used.\r\n \r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n \r\nFor more information on the change in station selection, please refer to the papers supplied with the data collection.\r\n \r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" }, "objectObservation": { "ob_id": 25, "uuid": "b621ef77b07d3c8e116b5b31fd5eb92b", "short_code": "ob", "title": "Daily Mean, Minimum and Maximum Central England Temperature series", "abstract": "The longest available instrumental record of temperature in the world is now available at the BADC. The daily data starts in 1772. \r\n\r\nThe mean, minimum and maximum datasets are updated monthly, with data for a month usually available by the 3rd of the next month. A provisional CET value for the current month is calculated on a daily basis. The mean daily data series begins in 1772. Mean maximum and minimum daily and monthly data are also available, beginning in 1878. Yearly files are provided from 1998 onwards.\r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London). \r\n\r\nThe following stations are used by the Met Office to compile the CET data: Rothamsted, Malvern, Squires Gate and Ringway.\r\n\r\nBut in November 2004, the weather station Stonyhurst replaced Ringway and revised urban warming and bias adjustments have now been applied to the Stonyhurst data after a period of reduced reliability from the station in the summer months. \r\n\r\nThe data set is compiled by the Met Office Hadley Centre." } }, { "ob_id": 1065, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43483, "uuid": "8978580336864f6d8282656d58771b32", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Nimbus-5 ESMR Sea Ice Concentration, version 1.1", "abstract": "This dataset provides Sea Ice Concentration (SIC) for the polar regions, derived from the Nimbus-5 Electrical Scanning Microwave Radiometer (ESMR), which operated between 1972 and 1977. It is processed with an algorithm using the single channel ESMR data (19.35 GHz), and has been gridded at 25 km grid spacing. This is the second version of the product, v1.1.\r\n\r\nThis product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project." }, "objectObservation": { "ob_id": 39465, "uuid": "34a15b96f1134d9e95b9e486d74e49cf", "short_code": "ob", "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci): Nimbus-5 ESMR Sea Ice Concentration, version 1.0", "abstract": "This dataset provides Sea Ice Concentration (SIC) for the polar regions, derived from the Nimbus-5 Electrical Scanning Microwave Radiometer (ESMR), which operated between 1972 and 1977. It is processed with an algorithm using the single channel ESMR data (19.35 GHz), and has been gridded at 25 km grid spacing. This is the first version of the product, v1.0.\r\n\r\nThis product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea Ice CCI (Sea_Ice_cci) project." } }, { "ob_id": 1066, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43607, "uuid": "5934d2a5706c4a3c9caa15188d9ed24b", "short_code": "ob", "title": "Met Office Cardington: vertical profile measurements from Vaisala radiosonde ascents, 1996-2024", "abstract": "This repository provides data from all radiosondes launched at Cardington between 1996-2024.\r\nThe sonde unit was operated by the Met Office Observation-based research Boundary Layer Facility, at the semi-rural field site (18 Ha) of Cardington (52° 06′ N, 00° 25′ W, 29 m ± 1 m amsl) in central-southern England.\r\n\r\nSonde launches were performed with a mean ascent rate of 2.5 m s-1. The slower ascent rate compared to an operational sonde ascent rate enables improved vertical sampling resolution in the atmospheric boundary layer whilst maintaining a sufficient ventilation rate over the sensors. From 1996-2002, a RS80 device was used with ThermoCap, HumiCap, BaroCap sensors, and between 2006-2014 a RS92-SGPB device was used with ThermoCap, HumiCap, capacitive pressure sensors. Sonde launches from 2014-2024 used an RS41-SG(P) device with PRT, silicon capacitive pressure (SGP), and HumiCap sensors.\r\n\r\nThe launches of radiosondes were performed on a project related basis only and all available ascent data has been provided from the Cardington facility. Please note that there were no ascents in 2022.\r\n\r\nA full list of NetCDF variables can be found in \"Continuous meteorological surface and soil records (2004-2024) at the Met Office surface site of Cardington, UK.\" Osborne et al. ESSD (2025). This paper should be referenced in any research/publications pertaining to this dataset.\r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included." }, "objectObservation": { "ob_id": 14546, "uuid": "cacbb519cd544ba2af1f31bc0585d6ea", "short_code": "ob", "title": "Met Office radiosonde measurements from Cardington, Bedfordshire", "abstract": "The Met Office's research unit based in Cardington, Bedfordshire, study boundary-layer meteorology and surface processes to help with the development of numerical weather prediction methods. Surface meteorological data and high resolution radiosonde data are collected from the Met Office's research site and elsewhere. \r\n\r\nThe dataset contains recorded radiosonde measurements of pressure, temperature and humidity." } }, { "ob_id": 1067, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43618, "uuid": "040f19261fa24683988bff79b255f0a8", "short_code": "ob", "title": "Atmospheric trace gas observations from the UK Deriving Emissions linked to Climate Change (DECC) Network and associated data - Version 25.01", "abstract": "This version 25.01 dataset collection consists of atmospheric trace gas observations made as part of the UK Deriving Emissions linked to Climate Change (DECC) Network. It includes core DECC Network measurements, funded by the UK Government Department for Energy Security and Net Zero (TRN1028/06/2015, TRN1537/06/2018, TRN5488/11/2021 and prj_1604) and through the National Measurement System at the National Physical Laboratory, supplemented by observations funded through other associated projects. The core DECC network consists of five sites in the UK and Ireland measuring greenhouse and ozone-depleting gases.\r\n\r\nThe four UK-based sites (Ridge Hill, Herefordshire; Tacolneston, Norfolk; Bilsdale, North Yorkshire; and Heathfield, East Sussex) sample air from elevated inlets on tall telecommunications towers. Mace Head, situated on the west coast of Ireland, samples from an inlet within 10 metres of ground level and is ideally situated to intercept baseline air from the North Atlantic Ocean. The measurement site at Weybourne, Norfolk, funded by the National Centre for Atmospheric Science (NCAS) and operated by the University of East Anglia, is also affiliated with the network. Mace Head and Weybourne data are archived separately - see links in documentation. Data from the UK DECC network are used to assess atmospheric trends and quantify UK emissions, and feed into other international research programs, including the Integrated Carbon Observation System (ICOS) and Advanced Global Atmospheric Gases Experiment (AGAGE) networks." }, "objectObservation": { "ob_id": 43187, "uuid": "bd7164851bcc491b912f9d650fcf7981", "short_code": "ob", "title": "Atmospheric trace gas observations from the UK Deriving Emissions linked to Climate Change (DECC) Network and associated data - Version 24.09", "abstract": "This version 24.09 dataset consists of atmospheric trace gas observations made as part of the UK Deriving Emissions linked to Climate Change (DECC) Network. It includes core DECC Network measurements, funded by the UK Government Department for Energy Security and Net Zero (TRN: 5488/11/2021) and through the National Measurement System at the National Physical Laboratory, supplemented by observations funded through other associated projects. \r\nThe core DECC network consists of five sites in the UK and Ireland measuring greenhouse and ozone-depleting gases. The four UK-based sites (Ridge Hill, Herefordshire; Tacolneston, Norfolk; Bilsdale, North Yorkshire; and Heathfield, East Sussex) sample air from elevated inlets on tall telecommunications towers. Mace Head, situated on the west coast of Ireland, samples from an inlet 10 metres above ground level and is ideally situated to intercept baseline air from the North Atlantic Ocean. The measurement site at Weybourne, Norfolk, funded by the National Centre for Atmospheric Science (NCAS) and operated by the University of East Anglia, is also affiliated with the network. Mace Head and Weybourne data are archived separately - see links in documentation. Data from the UK DECC network are used to assess atmospheric trends and quantify UK emissions, and feed into other international research programs, including the Integrated Carbon Observation System (ICOS) and Advanced Global Atmospheric Gases Experiment (AGAGE) networks." } }, { "ob_id": 1068, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43601, "uuid": "fe75afd7723140c19edfdeb75fed1e48", "short_code": "ob", "title": "Met Office Cardington: 1 min averages of surface to 50 m meteorology, radiation and subsoil measurements, 2004-2024", "abstract": "This repository provides a continuous hydrometeorological record of the Met Office Observation-based research Boundary Layer Facility at the semi-rural field site (18 Ha) of Cardington (52° 06′ N, 00° 25′ W, 29 m ± 1 m amsl) in central-southern England between 2004 and 2024. The dataset contains recorded surface meteorology, radiation and subsoil from sensor measurements at 1 minute averaging period and measured by instruments mounted on 2 m, 10 m, 25 m and 50 m masts.\r\n\r\nInstruments mounted on 2 m, 10 m, 25 m and 50 m masts include:\r\n•\tVector Instruments T302 PRT temperature sensors were located at all heights.\r\n•\tScreened and aspirated HMP155s were located at all heights.\r\n•\tGill HS50 3-D horizontally symmetric ultrasonic anemometers were located at all heights.\r\n•\tLicor Li-7500 open-path hygrometer was located at 10m.\r\n•\tSetra Model 270 transducer measured barometric pressure at 1.5 m.\r\n•\tMichell chilled mirror hygrometer measured dew and frost point temperature at 1.2 m\r\n\r\nSurface instrumentation includes:\r\n•\tRainfall is measured with a Met Office Mk5 tipping-bucket gauge with a 0.2 mm accuracy.\r\n•\tScreened and aspirated Rotronics Hydroclip2 measured grass canopy air temperature and RH located at 0.4 m, 0.15 m and 0.08 m.\r\n\r\nRadiation instrumentation includes:\r\n•\tClear-domed Kipp and Zonen CM21 pyranometers located at 2 m measured global downwelling, diffuse downwelling, and upwelling components (of wavelength between 0.3-3 μm).\r\n•\tKipp and Zonen CG4 pyrgeometers located at 2 m measured the downwelling and upwelling longwave radiation (4.5–40 μm).\r\n•\tGrass canopy, or skin temperature was measured radiometrically with the Heitronics KT15 pyrometer.\r\n\r\nAerosol and visibility instrumentation includes:\r\n\r\n•\tA Belfort 6230A instrument located at 2 m measured visual range through air (visibility) (2004-April 2011).\r\n•\tA Biral HSS VPF-730 instrument located at 2 m measured visual range through air (visibility), and for the determination of present weather (April 2011-2024).\r\n•\tVisible total scattering coefficients were measured with MRI integrating nephelometer (2004-2011) and Optec integrating nephelometer (2011-2024) located at 3 m.\r\nSubsoil instrumentation includes:\r\n•\tDelta-T ML2/ML3 theta probes measured volumetric soil moisture at depths of 10, 22, 57 and 160 cm.\r\n•\tDelta-T PRT measured soil temperature at 1, 4, 7, 10, 17, 35, 65 and 100 cm (2004-March 2012).\r\n•\tDelta-T ST2-396 thermistor probes measured soil temperature at 1, 4, 7, 10, 17, 35, 65 and 100 cm (March 2012-2024).\r\n•\tHukseflux HFP01SC flux plate measured ground heat flux.\r\n•\tDruck 1830 pressure transducer measured water table depth.\r\n\r\n\r\nA full list of NetCDF variables can be found in “A continuous hydrometeorological record (2004–2024) at the Met Office surface site of Cardington, UK.” Osborne et al. (2025). This paper should be referenced in any research/publications pertaining to this dataset.\r\n\r\nTo ensure optimal traceability and transparency of data, comprehensive metadata is included." }, "objectObservation": { "ob_id": 14759, "uuid": "20923d5a6a194340a94dcf4feda018a6", "short_code": "ob", "title": "Met Office surface measurements from Cardington, Bedfordshire Version 1 (2006 to 2017)", "abstract": "The Met Office's research unit based in Cardington, Bedfordshire, study boundary-layer meteorology and surface processes to help with the development of numerical weather prediction methods. Surface meteorological data and high resolution radiosonde data are collected from the Met Office's research site and elsewhere. \r\n\r\nThe dataset contains recorded surface meteorology and radiation measurements timed at 1, 10 and 30 minute intervals and measured by instruments mounted on 10, 25 and 50 metre masts." } }, { "ob_id": 1069, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43669, "uuid": "2a01faf75de64308b2bf4c7b43d393ef", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2024, v3.4.1.2024f", "abstract": "This is version v3.4.1.2024f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data.\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20250101_v3.4.1.2024f.nc. The station codes can be found under the docs tab. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note.\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." }, "objectObservation": { "ob_id": 41388, "uuid": "b82b58d085d0433b821f4ae31cb608de", "short_code": "ob", "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2023, v3.4.0.2023f", "abstract": "This is version v3.4.0.2023f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data.\r\n\r\nThis update (v3.4.0.2023f) to HadISD corrects a long-standing bug which was discovered in autumn 2023 whereby the neighbour checks (and associated [un]flagging for some other tests) were not being implemented. For more details see the posts on the HadISD blog: https://hadisd.blogspot.com/2023/10/bug-in-buddy-checks.html & https://hadisd.blogspot.com/2024/01/hadisd-v3402023f-future-look.html\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20240101_v3.4.1.2023f.nc. The station codes can be found under the docs tab. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note.\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014." } }, { "ob_id": 1070, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43819, "uuid": "91e0fde681204723b26a5f82fb9dd4d4", "short_code": "ob", "title": "MICROSCOPE: SNR winds from the NCAS Mobile Radar Wind Profiler unit 1 deployed at Davidstow Airfield and Cornwall at War Museum, Cornwall, v8.0 (20130627-20130831)", "abstract": "Vertical profiles of signal to noise ratio (SNR) and winds measurements from the NCAS Mobile Radar Wind Profiler unit 1 deployed at Davidstow Airfield and Cornwall at War Museum, Cornwall. These observations were taken as part of The NERC MICROphysicS of COnvective PrEcipitation (MICROSCOPE) project as part of the COnvective Precipitation Experiment (COPE) between 20130627 and 20130831.\r\n\r\nData products from this deployment include: snr-winds\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." }, "objectObservation": { "ob_id": 6287, "uuid": "09a132eb7e46945b4682869ee6b128df", "short_code": "ob", "title": "MICROSCOPE: Vertical wind profile data from the NCAS Atmospheric Measurement Facility's (AMF) 1290mhz Degreane Mobile Wind Profiler from Davidstow", "abstract": "This dataset contains vertical profiles of horizontal and vertical wind components as well as signal-to-noise (SNR) and spectral width measurements were collected at the Davidstow Airfield and Cornwall at War Museum, Cornwall, between June and August 2013 as part of the MICROphysicS of COnvective PrEcipitation (MICROSCOPE) project. These data were collected by the National Centre for Atmospheric Science (NCAS) Atmospheric Measurement Facility's (AMF) 1290 MHz Mobile Wind Profiler, owned and operated by the University of Manchester and previously known as the aber-radar-1290mhz. The data are available at 15 minute intervals as netCDF files to all MICROSCOPE project participants." } }, { "ob_id": 1071, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43756, "uuid": "28b0d1ced8f944d593446d45d02d8894", "short_code": "ob", "title": "NAMBLEX: SNR winds from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Mace Head Atmospheric Research Facility, Ireland, v8.0 (20020801-20020831)", "abstract": "Vertical profiles of signal to noise ratio (SNR) and winds measurements from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Mace Head Atmospheric Research Facility, Ireland. These observations were taken as part of North Atlantic Marine Boundary Layer EXperiment (NAMBLEX) between 20020801 and 20020831.\r\n\r\nData products from this deployment include: snr-winds\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." }, "objectObservation": { "ob_id": 7593, "uuid": "964614ac2120d3743a0cebaa292181b8", "short_code": "ob", "title": "NAMBLEX: Vertical Wind Profile Data from UFAM's 1290mhz Degreane Mobile Wind Profiler Radar Deployed at the Mace Head Research Facility, Ireland", "abstract": "The University of Wales, Aberystwyth, 1290mhz mobile wind profiler - now referred to as the University of Manchester mobile wind profiler - was operated at the Mace Head Research Facility in County Galway, Ireland, as part of the North Atlantic Marine Boundary Layer EXperiment (NAMBLEX) field campaign in August 2002. During this period the mobile wind profiler obtained vertical profiles of the horizontal and vertical wind components. For each signal beam profiles of the signal to noise (SNR) ratio and spectral widths were also taken." } }, { "ob_id": 1072, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43774, "uuid": "a3890d55fded4af2baafb70ee4b85841", "short_code": "ob", "title": "NCAS Long Term Observations: SNR winds from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the NCAS Capel Dewi Atmospheric Observatory (CDAO), v8.0 (20040805-20050519)", "abstract": "Vertical profiles of signal to noise ratio (SNR) and winds measurements from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the NCAS Capel Dewi Atmospheric Observatory (CDAO). These observations were taken as part of the National Centre for Atmospheric Science (NCAS) long term observations between 20040805 and 20050519.\r\n\r\nData products from this deployment include: snr-winds\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." }, "objectObservation": { "ob_id": 5430, "uuid": "d406437a0dfa3b56b4186fcd089d1afa", "short_code": "ob", "title": "Vertical wind profile data from 31st August 2004 to 1st June 2005 measured by the University of Manchester 1290 mhz mobile wind profiler deployed on long term observations at Capel Dewi, Wales", "abstract": "Vertical profiles of horizontal and vertical wind components as well as signal-to-noise (SNR) and spectal width measurements were collected at the NERC Mesosphere-Stratosphere-Troposphere radar facility site, Capel Dewi, near Aberystwyth, Ceredigion, Wales, between 31st August 2004 and 1st June 2005 as part of ongoing long term observations made by the NERC National Centre for Atmospheric Science (NCAS). These data were collected by the NCAS Atmospheric Measreument Facility's (AMF) 1290 MHz Mobile Wind Profiler, owned and operated by the University of Manchester and previously known as the aber-radar-1290mhz at the time of these observations. The data are available at 15 minute intervals as netCDF files to all registered BADC users under the Open Government License.\r\n\r\nThe dataset contains the following measurements:\r\n\r\nEastward wind velocity component\r\nNorthward wind velocity component\r\nUpward air velocity\r\nDirection the wind is from\r\nSignal to noise ratio\r\nAltitude of instrument above the ground\r\nLongitude of instrument\r\nLatitude of instrument\r\nSpectral width" } }, { "ob_id": 1073, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 43589, "uuid": "0363d592dd3548febaa6fc4056a618a9", "short_code": "ob", "title": "Daily Mean, Minimum and Maximum Central England Temperature series v2.0.0.0", "abstract": "The Central England Temperature (HadCET) daily series start in 1772 for mean temperature and 1878 for minimum and maximum temperature.\r\n \r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nPrior to 1973, the daily mean temperature series is anchored to the mean temperature series constructed by Gordon Manley, with the daily minimum and maximum temperature series adjusted to the mean temperature series to ensure values are consistent.\r\n \r\nAlthough the station selection has changed through time, the series is homogenised and adjusted to ensure consistency with Manley's selection and for periods when only a single station value was used.\r\n \r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n \r\nFor more information on the change in station selection, please refer to the papers supplied with the data collection.\r\n \r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" }, "objectObservation": { "ob_id": 43592, "uuid": "1d2020153f84407ba2852acfd8579886", "short_code": "ob", "title": "Mean, Minimum and Maximum Central England Temperature (HadCET) series post 1973 static adjustments, v2.0.0.0", "abstract": "The Central England Temperature (HadCET) daily mean series is anchored to Gordon Manley’s original temperature record prior to 1973. Between 1848 and 1878, adjustments are applied to account for periods when only a single station was in use.\r\n\r\nThese historical temperature series are representative of the Midlands region in England, UK (a roughly triangular area of the United Kingdom enclosed by Bristol, Lancashire and London).\r\n \r\nFrom 1973 onwards, multiple adjustments ensure continuity with Manley’s series, homogenise the current station selection with Manley’s original dataset, and correct for the effects of increasing urbanisation.\r\n \r\nThese static adjustments are calculated on a monthly basis and are applied uniformly to all daily values within each month from 1973 to the present. \r\n \r\nUrbanisation adjustments remain static from November 2004 onward, while adjustments between 1974 and October 2004 are graded to reflect a progressive increase in urbanisation effects over time.\r\n \r\nThis dataset contains the post-Manley extended adjustments, station homogenisation adjustments, and static urban corrections.\r\n\r\nStations used in the construction of the CET daily series between 1772 and 1852 include: Kennington, Crane Court, Lyndon Hall, Syon House, Somerset House, Greenwich Observatory, Chiswick\r\n \r\nStations used in the construction of the CET daily series from 1853 onwards include: Radcliffe (Oxford), Cambridge (legacy), Ross-on-Wye, Rothamsted, Malvern, Stonyhurst, Ringway, Squires Gate, Pershore College\r\n \r\nThe current station selection used is Rothamsted, Stonyhurst and Pershore College.\r\n\r\nThe dataset is compiled by the Met Office Hadley Centre.\r\n\r\nLatest provisional release data are available via the Hadley Centre Observations website (https://www.metoffice.gov.uk/hadobs/hadcet/data/download.html)" } }, { "ob_id": 1074, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43891, "uuid": "95913ffb6467447ca72c4e9d8cf30501", "short_code": "ob", "title": "ESA Biomass Climate Change Initiative (Biomass_cci): Global datasets of forest above-ground biomass for the years 2007, 2010, 2015, 2016, 2017, 2018, 2019, 2020, 2021 and 2022, v6.0", "abstract": "This dataset comprises estimates of forest above-ground biomass (AGB) for the years 2007, 2010, 2015, 2016, 2017, 2018, 2019, 2020, 2021 and 2022. They are derived from a combination of Earth observation data, depending on the year, from the Copernicus Sentinel-1 mission, Envisat’s ASAR (Advanced Synthetic Aperture Radar) instrument and JAXA’s (Japan Aerospace Exploration Agency) Advanced Land Observing Satellite (ALOS-1 and ALOS-2), along with additional information from Earth observation sources. The data has been produced as part of the European Space Agency's (ESA's) Climate Change Initiative (CCI) programme by the Biomass CCI team.\r\n\r\nThis release of the data is version 6. Compared to version 5, version 6 consists of an update of the maps of AGB for the years 2010, 2015, 2016, 2017, 2018, 2019, 2020, 2021 and new AGB maps for 2007 and 2022. AGB change maps have been created for consecutive years (e.g., 2020-2019), for a decadal interval (2020-2010) as well as for the interval 2010-2007. The pool of remote sensing data includes multi-temporal observations at L-band for all biomes and for all years and extended ICESat-2 observations to calibrate retrieval models. A cost function that preserves the temporal features as expressed in the remote sensing data has been refined to limit biases between the 2007-2010 and the 2015+ maps.\r\n\r\nThe data products consist of two (2) global layers that include estimates of:\r\n1) above ground biomass (AGB, unit: tons/ha i.e., Mg/ha) (raster dataset). This is defined as the mass, expressed as oven-dry weight of the woody parts (stem, bark, branches and twigs) of all living trees excluding stump and roots per unit area\r\n2) per-pixel estimates of above-ground biomass uncertainty expressed as the standard deviation in Mg/ha (raster dataset)\r\n\r\nAdditionally provided in this version release are aggregated data products. These aggregated products of the AGB and AGB change data layers are available at coarser resolutions (1, 10, 25 and 50km).\r\n\r\nIn addition, files describing the AGB change between two consecutive years (i.e., 2016-2015, 2017-2016, 2018-2017, 2019-2018, 2020-2019, 2021-2020, 2022-2021), over a decade (2020-2010) and over 2010-2007 are provided. Each AGB change product consists of two sets of maps: the standard deviation of the AGB change and a quality flag of the AGB change. Note that the change itself can be simply computed as the difference between two AGB maps, so is not provided directly.\r\n\r\nData are provided in both netcdf and geotiff format." }, "objectObservation": { "ob_id": 43090, "uuid": "bf535053562141c6bb7ad831f5998d77", "short_code": "ob", "title": "ESA Biomass Climate Change Initiative (Biomass_cci): Global datasets of forest above-ground biomass for the years 2010, 2015, 2016, 2017, 2018, 2019, 2020 and 2021, v5.01", "abstract": "This dataset comprises estimates of forest above-ground biomass for the years 2010, 2015, 2016, 2017, 2018, 2019, 2020 and 2021. They are derived from a combination of Earth observation data, depending on the year, from the Copernicus Sentinel-1 mission, Envisat’s ASAR (Advanced Synthetic Aperture Radar) instrument and JAXA’s (Japan Aerospace Exploration Agency) Advanced Land Observing Satellite (ALOS-1 and ALOS-2), along with additional information from Earth observation sources. The data has been produced as part of the European Space Agency's (ESA's) Climate Change Initiative (CCI) programme by the Biomass CCI team. \r\n\r\nThis release of the data is version 5. Compared to version 4, version 5 consists of an update of the three maps of AGB (aboveground biomass) for the years 2010, 2017, 2018, 2019, 2020 and new AGB maps for 2015, 2016 and 2021. New AGB change maps have been created for consecutive years (2015-2016, 2016-2017 and 2020-2021), alongside an update of change maps for years 2010-2020, 2017-2018, 2018-2019 and 2019-2020, and for a decadal interval (2020-2010). The pool of remote sensing data now includes multi-temporal observations at L-band for all biomes and for all years. The AGB maps rely on revised allometries which are now based on a longer record of spaceborne LiDAR data from the GEDI and ICESat-2 missions. Temporal information is now implemented in the retrieval algorithm to preserve biomass dynamics as expressed in the remote sensing data. Biases between 2010 and more recent years have been reduced.\r\n\r\nThe data products consist of two (2) global layers that include estimates of:\r\n1) above ground biomass (AGB, unit: tons/ha i.e., Mg/ha) (raster dataset). This is defined as the mass, expressed as oven-dry weight of the woody parts (stem, bark, branches and twigs) of all living trees excluding stump and roots\r\n2) per-pixel estimates of above-ground biomass uncertainty expressed as the standard deviation in Mg/ha (raster dataset)\r\n\r\nAdditionally provided in this version release are new aggregated data products. These aggregated products of the AGB and AGB change data layers are available at coarser resolutions (1, 10, 25 and 50km).\r\n\r\nIn addition, files describing the AGB change between two consecutive years (i.e., 2015-2016, 2016-2017, 2018-2017, 2019-2018, 2019-2020, 2020-2021) and over a decade (2020-2010) are provided (labelled as 2015_2016, 2016_2017, 2017_2018, 2018_2019, 2019_2020 and 2020_2010). Each AGB change product consists of two sets of maps: the standard deviation of the AGB change and a quality flag of the AGB change. Note that the change itself can be simply computed as the difference between two AGB maps, so is not provided directly.\r\n\r\n\r\nData are provided in both netcdf and geotiff format.\r\n\r\nThis version represents an update of v5.0 which was missing a number of tiles covering islands on the Pacific and Indian Ocean and one tile covering Scandinavia north of 70 deg latitude." } }, { "ob_id": 1075, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43866, "uuid": "bf5f4731e8bd456082e2e43f97f4430e", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Gravimetric Mass Balance from GRACE data, derived by DTU Space, v3.0", "abstract": "This dataset provides a Gravimetric Mass Balance (GMB) product for the Greenland Ice Sheet (GIS), generated by DTU Space, based on monthly snapshots of the Earth’s gravity field provided by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on satellite mission (GRACE-FO). The product relies on monthly gravity field solutions (L2) of release 06 generated at the Center for Space Research (University of Texas at Austin) and spans the period from April 2002 through May 2024.\r\n\r\nThe GMB product covers the full GRACE mission period (April 2002 - June 2017) and is extended by means of GRACE-FO data starting from June 2018, thus including 200 monthly solutions. The mass change estimation is based on inversion method developed at DTU Space.\r\n\r\nTwo different types of products are available. First, the gridded mass trends product is comprised of ice mass change trends for cells of equal area with 44 km resolution covering the whole GIS and different drainage basins. Second, the mass change time series product provides time series of integrated mass changes for 8 drainage basins and the entire GIS over different 5-year periods between 2002 and 2024. Basin definitions and further data descriptions can be found in the Algorithm Theoretical Baseline Document and the Product Specification Document which are provided on the project website. \r\n\r\nReference:\r\nBarletta, V. R., Sørensen, L. S., and Forsberg, R. (2013) 'Scatter of mass changes estimates at basin scale for Greenland and Antarctica', The Cryosphere, 7, 1411-1432, doi:10.5194/tc-7-1411-2013." }, "objectObservation": { "ob_id": 37276, "uuid": "48cd535e93574c8da8e80b91e06c7d51", "short_code": "ob", "title": "ESA Greenland Ice Sheet Climate Change Initiative (Greenland_Ice_Sheet_cci): Greenland Gravimetric Mass Balance from GRACE data, derived by DTU Space, v2.2", "abstract": "This dataset provides a Gravimetric Mass Balance (GMB) product for the Greenland Ice Sheet (GIS), generated by DTU Space, based on monthly snapshots of the Earth’s gravity field provided by the Gravity Recovery and Climate Experiment (GRACE) and its follow-on satellite mission (GRACE-FO). The product relies on monthly gravity field solutions (L2) of release 06 generated at the Center for Space Research (University of Texas at Austin) and spans the period from April 2002 through August 2021.\r\n\r\nThe GMB product covers the full GRACE mission period (April 2002 - June 2017) and is extended by means of GRACE-FO data starting from June 2018, thus including 200 monthly solutions. The mass change estimation is based on inversion method developed at DTU Space.\r\n\r\nTwo different types of products are available. First, the gridded mass trends product is comprised of ice mass change trends for cells of equal area with 50 km resolution covering the whole GIS. Second, the mass change time series product provides time series of integrated mass changes for 8 drainage basins and the entire GIS.\r\n\r\nReference:\r\nBarletta, V. R., Sørensen, L. S., and Forsberg, R. (2013) 'Scatter of mass changes estimates at basin scale for Greenland and Antarctica', The Cryosphere, 7, 1411-1432, doi:10.5194/tc-7-1411-2013.\"," } }, { "ob_id": 1076, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43789, "uuid": "4df47ea26bf74da8a696d96d6cf3ee30", "short_code": "ob", "title": "COPS: SNR winds from the NCAS Mobile Radar Wind Profiler unit 1 deployed at Achern, Germany, v8.0 (20070613-20070807)", "abstract": "Vertical profiles of signal to noise ratio (SNR) and winds measurements from the NCAS Mobile Radar Wind Profiler unit 1 deployed at Achern, Germany. These observations were taken as part of Convective and Orographically-induced Precipitation Study (COPS) between 20070613 and 20070807.\r\n\r\nData products from this deployment include: snr-winds\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." }, "objectObservation": { "ob_id": 3038, "uuid": "104700b95640c9eb22726248ab187d87", "short_code": "ob", "title": "COPS: vertical wind profiles from the Facility for Ground-based Atmospheric Measurements' (FGAM) 1290 MHz Degreane Mobile Wind Profiler located at Archern, Germany", "abstract": "Data were collected by the 1290 mhz wind profiler, previously known as the Aberystwyth radar, at Achern, Germany, in support of the Convective and Orographically-induced Precipitation Study (COPS) Project from the 13th of June 2007 to the 17th of August 2007. The dataset contains measurements of wind speed, wind direction, signal to noise ratio and spectral width. Data are available in netCDF.\r\n\r\nThe dataset contains the following measurements:\r\n\r\nEastward wind velocity component\r\nNorthward wind velocity component\r\nUpward air velocity\r\nDirection the wind is from\r\nSignal to noise ratio\r\nAltitude of instrument above the ground\r\nLongitude of instrument\r\nLatitude of instrument\r\nSpectral width" } }, { "ob_id": 1077, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43792, "uuid": "c4846909fcad4480903857e7ef486743", "short_code": "ob", "title": "NCAS Long Term Observations: SNR winds from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Met Office Meteorological Research Unit, Cardington, v8.0 (20070821-20071029)", "abstract": "Vertical profiles of signal to noise ratio (SNR) and winds measurements from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Met Office Meteorological Research Unit, Cardington. These observations were taken as part of the National Centre for Atmospheric Science (NCAS) long term observations between 20070821 and 20071029.\r\n\r\nData products from this deployment include: snr-winds\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." }, "objectObservation": { "ob_id": 5421, "uuid": "7247aba134f4c69e6d2732347c6f508c", "short_code": "ob", "title": "Vertical wind profile data from the 21st August to 14th November 2007 measured by the University of Manchester 1290 mhz mobile wind profiler deployed on long term observations at Met Office Research Unit, Cardington, Bedfordshire", "abstract": "Vertical profiles of horizontal and vertical wind components as well as signal-to-noise (SNR) and spectal width measurements were collected at the Met Office Research Unit, Cardington, Bedfordshire, UK, between 21st August and 14th November 2007 as part of ongoing long term observations made by the NERC National Centre for Atmospheric Science (NCAS). These data were collected by the NCAS Atmospheric Measreument Facility's (AMF) 1290 MHz Mobile Wind Profiler, owned and operated by the University of Manchester and previously known as the aber-radar-1290mhz at the time of these observations. The data are available at 15 minute intervals as netCDF files to all registered BADC users under the Open Government License.\r\n\r\nThe dataset contains the following measurements:\r\n\r\nEastward wind velocity component\r\nNorthward wind velocity component\r\nUpward air velocity\r\nDirection the wind is from\r\nSignal to noise ratio\r\nAltitude of instrument above the ground\r\nLongitude of instrument\r\nLatitude of instrument\r\nSpectral width" } }, { "ob_id": 1078, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43780, "uuid": "eb352545ce1b4476b2580a3e5885c00d", "short_code": "ob", "title": "NCAS Long Term Observations: SNR winds from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Met Office Meteorological Research Unit, Cardington, v8.0 (20060407-20060927)", "abstract": "Vertical profiles of signal to noise ratio (SNR) and winds measurements from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Met Office Meteorological Research Unit, Cardington. These observations were taken as part of the National Centre for Atmospheric Science (NCAS) long term observations between 20060407 and 20060927.\r\n\r\nData products from this deployment include: snr-winds\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." }, "objectObservation": { "ob_id": 5418, "uuid": "3da566d8a06363ca962b0069cbf1477f", "short_code": "ob", "title": "Vertical wind profile data from 7th April to 27th September 2006 measured by the University of Manchester 1290 mhz mobile wind profiler deployed on long term observations at Met Office Research Unit, Cardington, Bedfordshire", "abstract": "Vertical profiles of horizontal and vertical wind components as well as signal-to-noise (SNR) and spectal width measurements were collected at the Met Office Research Unit, Cardington, Bedfordshire, UK, between 7th April and 27th September 2006 as part of ongoing long term observations made by the NERC National Centre for Atmospheric Science (NCAS). These data were collected by the NCAS Atmospheric Measreument Facility's (AMF) 1290 MHz Mobile Wind Profiler, owned and operated by the University of Manchester and previously known as the aber-radar-1290mhz at the time of these observations. The data are available at 15 minute intervals as netCDF files to all registered BADC users under the Open Government License.\r\n\r\nThe dataset contains the following measurements:\r\n\r\nEastward wind velocity component\r\nNorthward wind velocity component\r\nUpward air velocity\r\nDirection the wind is from\r\nSignal to noise ratio\r\nAltitude of instrument above the ground\r\nLongitude of instrument\r\nLatitude of instrument\r\nSpectral width" } }, { "ob_id": 1079, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43786, "uuid": "34166e18f6dc4f08a370cf156e6b0559", "short_code": "ob", "title": "NCAS Long Term Observations: SNR winds from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the NCAS Capel Dewi Atmospheric Observatory (CDAO), v8.0 (20070328-20070517)", "abstract": "Vertical profiles of signal to noise ratio (SNR) and winds measurements from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the NCAS Capel Dewi Atmospheric Observatory (CDAO). These observations were taken as part of the National Centre for Atmospheric Science (NCAS) long term observations between 20070328 and 20070517.\r\n\r\nData products from this deployment include: snr-winds\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." }, "objectObservation": { "ob_id": 5424, "uuid": "db9130403ef721b6d4348204756d5b1a", "short_code": "ob", "title": "Vertical wind profile data from 28th March to 16th May 2007 measured by the University of Manchester 1290 mhz mobile wind profiler deployed on long term observations at Capel Dewi, Wales", "abstract": "Vertical profiles of horizontal and vertical wind components as well as signal-to-noise (SNR) and spectal width measurements were collected at the NERC Mesosphere-Stratosphere-Troposphere radar facility site, Capel Dewi, near Aberystwyth, Ceredigion, Wales, between 28th March and 16th May 2007 as part of ongoing long term observations made by the NERC National Centre for Atmospheric Science (NCAS). These data were collected by the NCAS Atmospheric Measreument Facility's (AMF) 1290 MHz Mobile Wind Profiler, owned and operated by the University of Manchester and previously known as the aber-radar-1290mhz at the time of these observations. The data are available at 15 minute intervals as netCDF files to all registered BADC users under the Open Government License.\r\n\r\nThe dataset contains the following measurements:\r\n\r\nEastward wind velocity component\r\nNorthward wind velocity component\r\nUpward air velocity\r\nDirection the wind is from\r\nSignal to noise ratio\r\nAltitude of instrument above the ground\r\nLongitude of instrument\r\nLatitude of instrument\r\nSpectral width" } }, { "ob_id": 1080, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43804, "uuid": "36d4e72b2ea8477aaba3eb6d0f052fad", "short_code": "ob", "title": "NCAS Long Term Observations: SNR winds from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Met Office Meteorological Research Unit, Cardington, v8.0 (20100416-20110324)", "abstract": "Vertical profiles of signal to noise ratio (SNR) and winds measurements from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Met Office Meteorological Research Unit, Cardington. These observations were taken as part of the National Centre for Atmospheric Science (NCAS) long term observations between 20100416 and 20110324.\r\n\r\nData products from this deployment include: snr-winds\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." }, "objectObservation": { "ob_id": 5427, "uuid": "04f0c7cfdea6316df21bfdcd08a2073b", "short_code": "ob", "title": "Vertical wind profile data from 14th April 2010 to 25th May 2011 measured by the University of Manchester 1290 mhz mobile wind profiler deployed on long term observations at Met Office Research Unit, Cardington, Bedfordshire", "abstract": "Vertical profiles of horizontal and vertical wind components as well as signal-to-noise (SNR) and spectal width measurements were collected at the Met Office Research Unit, Cardington, Bedfordshire, UK, between 14th April 2010 and 25th May 2011 as part of ongoing long term observations made by the NERC National Centre for Atmospheric Science (NCAS). These data were collected by the NCAS Atmospheric Measreument Facility's (AMF) 1290 MHz Mobile Wind Profiler, owned and operated by the University of Manchester and previously known as the aber-radar-1290mhz at the time of these observations. The data are available at 15 minute intervals as netCDF files to all registered BADC users under the Open Government License.\r\n\r\nThe dataset contains the following measurements:\r\n\r\nEastward wind velocity component\r\nNorthward wind velocity component\r\nUpward air velocity\r\nDirection the wind is from\r\nSignal to noise ratio\r\nAltitude of instrument above the ground\r\nLongitude of instrument\r\nLatitude of instrument\r\nSpectral width" } }, { "ob_id": 1081, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43813, "uuid": "630bfe7dd2824b83a964819e9d6de162", "short_code": "ob", "title": "NCAS Long Term Observations: SNR winds from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Met Office Meteorological Research Unit, Cardington, v8.0 (20120307-20130305)", "abstract": "Vertical profiles of signal to noise ratio (SNR) and winds measurements from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Met Office Meteorological Research Unit, Cardington. These observations were taken as part of the National Centre for Atmospheric Science (NCAS) long term observations between 20120307 and 20130305.\r\n\r\nData products from this deployment include: snr-winds\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." }, "objectObservation": { "ob_id": 27418, "uuid": "14a787cefc3a40538f46247dc52f89eb", "short_code": "ob", "title": "Vertical wind profile data from 7th March to 27th June 2012 measured by the University of Manchester 1290 mhz mobile wind profiler deployed on long term observations at Met Office Research Unit, Cardington, Bedfordshire", "abstract": "Vertical profiles of horizontal and vertical wind components as well as signal-to-noise (SNR) and spectal width measurements were collected at the Met Office Research Unit, Cardington, Bedfordshire, UK, between 7th March and 27th June 2012 as part of ongoing long term observations made by the NERC National Centre for Atmospheric Science (NCAS). These data were collected by the NCAS Atmospheric Measurement Facility's (AMF) 1290 MHz Mobile Wind Profiler, owned and operated by the University of Manchester and previously known as the aber-radar-1290mhz at the time of these observations. The data are available at 15 minute intervals as netCDF files to all registered BADC users under the Open Government License.\r\n\r\nThe dataset contains the following measurements:\r\n\r\nEastward wind velocity component\r\nNorthward wind velocity component\r\nUpward air velocity\r\nDirection the wind is from\r\nSignal to noise ratio\r\nAltitude of instrument above the ground\r\nLongitude of instrument\r\nLatitude of instrument\r\nSpectral width" } }, { "ob_id": 1082, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43822, "uuid": "9885fb709fbe4caba054bac772cefdd5", "short_code": "ob", "title": "NCAS Long Term Observations: SNR winds from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Met Office Meteorological Research Unit, Cardington, v8.0 (20131106-20140831)", "abstract": "Vertical profiles of signal to noise ratio (SNR) and winds measurements from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Met Office Meteorological Research Unit, Cardington. These observations were taken as part of the National Centre for Atmospheric Science (NCAS) long term observations between 20131106 and 20140831.\r\n\r\nData products from this deployment include: snr-winds\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." }, "objectObservation": { "ob_id": 12411, "uuid": "ecbecb0fbf6e4a4e93bb3ee2cf9854cd", "short_code": "ob", "title": "Vertical wind profile data from 6th November 2013 to 18th January 2016 measured by the University of Manchester 1290 mhz mobile wind profiler deployed on long term observations at Met Office Research Unit, Cardington, Bedfordshire", "abstract": "Vertical profiles of horizontal and vertical wind components as well as signal-to-noise (SNR) and spectal width measurements were collected at the Met Office Research Unit, Cardington, Bedfordshire, UK, from 6th November 2013 to 18th January 2016 as part of ongoing long term observations made by the NERC National Centre for Atmospheric Science (NCAS). These data were collected by the NCAS Atmospheric Measurement Facility's (AMF) 1290 MHz Mobile Wind Profiler, owned and operated by the University of Manchester and previously known as the aber-radar-1290mhz at the time of these observations. The data are available at 15 minute intervals as netCDF files to all registered BADC users under the Open Government License.\r\n\r\nPlease note, the data between 1st September and 31st December 2014 should be treated with caution as there were various logged errors during this period.\r\n\r\nThe dataset contains the following measurements:\r\n\r\nEastward wind velocity component\r\nNorthward wind velocity component\r\nUpward air velocity\r\nDirection the wind is from\r\nSignal to noise ratio\r\nAltitude of instrument above the ground\r\nLongitude of instrument\r\nLatitude of instrument\r\nSpectral width" } }, { "ob_id": 1083, "relationType": "Continues", "subjectObservation": { "ob_id": 43825, "uuid": "ca9b5288ad62491f8fb226eff22a0486", "short_code": "ob", "title": "NCAS Long Term Observations: SNR winds from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Met Office Meteorological Research Unit, Cardington, v8.0 (20150101-20160118)", "abstract": "Vertical profiles of signal to noise ratio (SNR) and winds measurements from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Met Office Meteorological Research Unit, Cardington. These observations were taken as part of the National Centre for Atmospheric Science (NCAS) long term observations between 20150101 and 20160118.\r\n\r\nData products from this deployment include: snr-winds\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." }, "objectObservation": { "ob_id": 43822, "uuid": "9885fb709fbe4caba054bac772cefdd5", "short_code": "ob", "title": "NCAS Long Term Observations: SNR winds from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Met Office Meteorological Research Unit, Cardington, v8.0 (20131106-20140831)", "abstract": "Vertical profiles of signal to noise ratio (SNR) and winds measurements from the NCAS Mobile Radar Wind Profiler unit 1 deployed at the Met Office Meteorological Research Unit, Cardington. These observations were taken as part of the National Centre for Atmospheric Science (NCAS) long term observations between 20131106 and 20140831.\r\n\r\nData products from this deployment include: snr-winds\r\n\r\nFor further details of this deployment and the associated dataset please see the internal file metadata.\r\n\r\nThese data conform to the NCAS data standards and are available under the UK Government Open Licence agreement. Acknowledgement of NCAS as the data provider is required whenever and wherever these data are used." } }, { "ob_id": 1084, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 44088, "uuid": "9cf07e92afaa405da4f40b6733f362d3", "short_code": "ob", "title": "CRU TS4.09: Climatic Research Unit (CRU) Time-Series (TS) version 4.09 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2024)", "abstract": "The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.09 data are month-by-month variations in climate over the period 1901-2024, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia and funded by the UK National Centre for Atmospheric Science (NCAS), a NERC collaborative centre.\r\n\r\nThe CRU TS4.09 variables are cloud cover, diurnal temperature range, frost day frequency, wet 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 2024.\r\n\r\nThe CRU TS4.09 data were produced using angular-distance weighting (ADW) interpolation. All versions prior to 4.00 used triangulation routines in IDL. Please see the release notes for full details of this version update. \r\n\r\nThe CRU TS4.09 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": 43100, "uuid": "715abce1604a42f396f81db83aeb2a4b", "short_code": "ob", "title": "CRU TS4.08: Climatic Research Unit (CRU) Time-Series (TS) version 4.08 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2023)", "abstract": "The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.08 data are month-by-month variations in climate over the period 1901-2023, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia and funded by the UK National Centre for Atmospheric Science (NCAS), a NERC collaborative centre.\r\n\r\nThe CRU TS4.08 variables are cloud cover, diurnal temperature range, frost day frequency, wet 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 2023.\r\n\r\nThe CRU TS4.08 data were produced using angular-distance weighting (ADW) interpolation. All versions prior to 4.00 used triangulation routines in IDL. Please see the release notes for full details of this version update. \r\n\r\nThe CRU TS4.08 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": 1085, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43624, "uuid": "e95903ef0e0a4bfa92f528b86c4a8b0f", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged carbon dioxide from GOSAT-2, derived using the SRFP (RemoTeC) full physics algorithm (CO2_GO2_SRFP), version 2.0.3", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of carbon dioxide (XCO2). It has been produced using Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the Remote Sensing of Greenhouse Gases for Carbon Cycle Modeling (RemoTeC) SRON Full Physics (SRFP) retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." }, "objectObservation": { "ob_id": 41427, "uuid": "875f25069b5d4bd9a7101ca1206ee4f0", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged carbon dioxide from GOSAT-2, derived using the SRFP (RemoTeC) full physics algorithm (CO2_GO2_SRFP), version 2.0.2", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of carbon dioxide (XCO2). It has been produced using Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the Remote Sensing of Greenhouse Gases for Carbon Cycle Modeling (RemoTeC) SRON Full Physics (SRFP) retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." } }, { "ob_id": 1086, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43625, "uuid": "9d3304ed60884e4c8ec4719b6e5c57b1", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from GOSAT-2, generated with the SRFP (RemoTeC) full physics retrieval algorithm (CH4_GO2_SRFP), version 2.0.3", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the Remote Sensing of Greenhouse Gases for Carbon Cycle Modeling (RemoTeC) SRON Full Physics (SRFP) retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." }, "objectObservation": { "ob_id": 41425, "uuid": "c14874e943cc453a8e63ce5841ecc9b0", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from GOSAT-2, generated with the SRFP (RemoTeC) full physics retrieval algorithm (CH4_GO2_SRFP), version 2.0.2", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the Remote Sensing of Greenhouse Gases for Carbon Cycle Modeling (RemoTeC) SRON Full Physics (SRFP) retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." } }, { "ob_id": 1087, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 43626, "uuid": "1097a848fd464ac8af3e8ab93032a19c", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from GOSAT-2, generated with the SRPR (RemoTeC) proxy retrieval algorithm (CH4_GO2_SRPR), version 2.0.3", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the Remote Sensing of Greenhouse Gases for Carbon Cycle Modeling (RemoTeC) SRON Proxy (SRPR) retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." }, "objectObservation": { "ob_id": 41429, "uuid": "3fc7927499fa49e0b6ace6c807972259", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from GOSAT-2, generated with the SRPR (RemoTeC) proxy retrieval algorithm (CH4_GO2_SRPR), version 2.0.2", "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the Remote Sensing of Greenhouse Gases for Carbon Cycle Modeling (RemoTeC) SRON Proxy (SRPR) retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme." } }, { "ob_id": 1089, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 44239, "uuid": "f06f0b7bd1404ffda0d3142f4cd166fb", "short_code": "ob", "title": "CRUTEM.5.0.2.0: Climatic Research Unit (CRU) gridded near-surface air temperature anomalies over land", "abstract": "CRUTEM (Climatic Research Unit TEMperature) is a gridded dataset of global historical near-surface air temperature anomalies over land at a monthly timescale. It is a collaborative product of the Climatic Research Unit at the University of East Anglia, the Met Office Hadley Centre and the National Centre for Atmospheric Science. CRUTEM also contributes the land air temperature station data to the global (land and ocean) temperature dataset called HadCRUT.\r\n \r\nCRUTEM5 is the fifth major version of the dataset, covering the time period from 1850, with a spatial resolution of 5° latitude by 5° longitude and a monthly-mean time resolution. The gridded temperature anomaly fields are based on a compilation of monthly-mean temperature observational records from weather stations. This compilation contains 10639 station records, but only 7983 records had the necessary coverage to be used for producing the gridded dataset. Anomalies are differences from average conditions in the 1961-1990 period. Hemispheric and global mean time series of land air temperature anomalies are also provided.\r\n\r\nCRUTEM.5.0.2.0 updates the version number from CRUTEM.5.0.1.0 to maintain consistency with versioning of the HadCRUT5 data set. This update includes no changes to the CRUTEM5 processing workflow." }, "objectObservation": { "ob_id": 32021, "uuid": "901f576dacae4e049630ab879d6fb476", "short_code": "ob", "title": "CRUTEM.5.0.0.0: Climatic Research Unit (CRU) gridded near-surface air temperature anomalies over land", "abstract": "CRUTEM (Climatic Research Unit TEMperature) is a gridded dataset of global historical near-surface air temperature anomalies over land at a monthly timescale. It is a collaborative product of the Climatic Research Unit at the University of East Anglia, the Met Office Hadley Centre and the National Centre for Atmospheric Science. CRUTEM also contributes the land air temperature station data to the global (land and ocean) temperature dataset called HadCRUT.\r\n \r\nCRUTEM5 is the fifth major version of the dataset, covering the time period from 1850, with a spatial resolution of 5° latitude by 5° longitude and a monthly-mean time resolution. The gridded temperature anomaly fields are based on a compilation of monthly-mean temperature observational records from weather stations. This compilation contains 10639 station records, but only 7983 records had the necessary coverage to be used for producing the gridded dataset. Anomalies are differences from average conditions in the 1961-1990 period. Hemispheric and global mean time series of land air temperature anomalies are also provided." } } ] }