Related Observation Info List
Get a list of RelatedObservationInfo objects.
GET /api/v3/relatedobservationinfos/?format=api&offset=300
{ "count": 1153, "next": "https://api.catalogue.ceda.ac.uk/api/v3/relatedobservationinfos/?format=api&limit=100&offset=400", "previous": "https://api.catalogue.ceda.ac.uk/api/v3/relatedobservationinfos/?format=api&limit=100&offset=200", "results": [ { "ob_id": 325, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30231, "uuid": "a963d9415bb74247830f8704f825aa90", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (SST_cci): GHRSST Multi-Product ensemble (GMPE), v2.0", "abstract": "The European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project (ESA SST_cci) has accurately determined the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified sea surface temperatures (SSTs) to a quality suitable for climate research. This GHRSST (Group for High Resolution Sea Surface Temperature) Multi-Product Ensemble (GMPE) dataset was produced by the ESA SST_cci project to facilitate comparison of its own spatially complete analyses with other level 4 SST analysis products. It provides the median and standard deviation of the ensemble of input analyses, differences between the individual analyses and the median, and gradients in the input data and the median. The outputs are provided on a 0.25˚ regular latitude-longitude grid. The product extends from 1 September 1981 to 31 December 2016.\r\n\r\nThe product was generated using the following inputs: ESA SST_cci Analysis version 2.0; ESA SST_cci Analysis version 1.1; E.U. Copernicus Marine Environment Monitoring Service (CMEMS) SST information (the Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) Reprocessing); National Centers for Environmental Information (NCEI) Advanced Very High Resolution Radiometer (AVHRR) Optimal Interpolation (OI) Global Blended SST Analysis; Canada Meteorological Center (CMC) 0.2-degree Global Foundation SST Analysis; Hadley Centre Sea Ice and Sea Surface Temperature (HadISST) Analysis version 2.2.0.0 (10 realisations); Japan Meteorological Agency (JMA) Merged satellite and in-situ Data Global Daily SST (MGDSST) Analysis. Full details of the data used to generate this product are provided in the associated documentation." }, "objectObservation": { "ob_id": 11697, "uuid": "e0659b01259145c8bfb0de6eb12c2690", "short_code": "ob", "title": "ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI): GHRSST Multi-Product ensemble (GMPE)", "abstract": "The ESA Sea Surface Temperature Climate Change Initiative (ESA SST CCI) dataset accurately maps the surface temperature of the global oceans over the period 1991 to 2010 using observations from many satellites. The data provides an independently quantified SST to a quality suitable for climate research. \r\n\r\nThe GHRSST Multi-Product Ensemble (GMPE) dataset is an ensemble median of the ESA SST CCI spatially complete analysis with other level 4 SST analysis products. Anomalies of the analyses relative to the median, and the ensemble standard deviation are also provided.\r\n\r\nAll the data in the GMPE files are regridded onto a common 0.25 degree regular latitude longitude grid and there are\r\nSST fields for each day. The GMPE for the ESA SST CCI long term product covers the period September 1991 to December\r\n2010. GMPE files are also available for ESA SST CCI demonstration product 1 (which covers June to August 2007)." } }, { "ob_id": 327, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 30245, "uuid": "bbf4d911abd4446eaa8c3ed79edb9593", "short_code": "ob", "title": "ECMWF ERA5t: surface level analysis parameter data", "abstract": "This dataset contains ERA5 initial release (ERA5t) surface level analysis parameter data. ERA5t is the European Centre for Medium-Range Weather Forecasts (ECWMF) ERA5 reanalysis project initial release available upto 5 days behind the present data. CEDA will maintain a 6 month rolling archive of these data with overlap to the verified ERA5 data - see linked datasets on this record. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record.\r\n\r\nModel level analysis and surface forecast data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset." }, "objectObservation": { "ob_id": 30244, "uuid": "29cdcc9438b94508aab17bb5ebcdfd51", "short_code": "ob", "title": "ECMWF ERA5t: surface level forecast parameter data", "abstract": "This dataset contains ERA5 initial release (ERA5t) surface level forecast parameter data. ERA5t is the European Centre for Medium-Range Weather Forecasts (ECWMF) ERA5 reanalysis project initial release available upto 5 days behind the present data. CEDA will maintain a 6 month rolling archive of these data with overlap to the verified ERA5 data - see linked datasets on this record. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record.\r\n\r\nSurface level and model level analysis data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset." } }, { "ob_id": 328, "relationType": "Continues", "subjectObservation": { "ob_id": 30245, "uuid": "bbf4d911abd4446eaa8c3ed79edb9593", "short_code": "ob", "title": "ECMWF ERA5t: surface level analysis parameter data", "abstract": "This dataset contains ERA5 initial release (ERA5t) surface level analysis parameter data. ERA5t is the European Centre for Medium-Range Weather Forecasts (ECWMF) ERA5 reanalysis project initial release available upto 5 days behind the present data. CEDA will maintain a 6 month rolling archive of these data with overlap to the verified ERA5 data - see linked datasets on this record. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record.\r\n\r\nModel level analysis and surface forecast data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset." }, "objectObservation": { "ob_id": 27572, "uuid": "c1145ccc4b6d4310a4fc7cce61041b63", "short_code": "ob", "title": "ECMWF ERA5: surface level analysis parameter data", "abstract": "This dataset contains ERA5 surface level analysis parameter data. ERA5 is the 5th generation reanalysis project from the European Centre for Medium-Range Weather Forecasts (ECWMF) - see linked documentation for further details. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record.\r\n\r\nModel level analysis and surface forecast data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset.\r\n\r\nThe ERA5 global atmospheric reanalysis of the covers 1979 to 2 months behind the present month. This follows on from the ERA-15, ERA-40 rand ERA-interim re-analysis projects.\r\n\r\nAn initial release of ERA5 data (ERA5t) is made roughly 5 days behind the present date. These will be subsequently reviewed ahead of being released by ECMWF as quality assured data within 3 months. CEDA holds a 6 month rolling copy of the latest ERA5t data. See related datasets linked to from this record. However, for the period 2000-2006 the initial ERA5 release was found to suffer from stratospheric temperature biases and so new runs to address this issue were performed resulting in the ERA5.1 release (see linked datasets). Note, though, that Simmons et al. 2020 (technical memo 859) report that \"ERA5.1 is very close to ERA5 in the lower and middle troposphere.\" but users of data from this period should read the technical memo 859 for further details." } }, { "ob_id": 330, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 30244, "uuid": "29cdcc9438b94508aab17bb5ebcdfd51", "short_code": "ob", "title": "ECMWF ERA5t: surface level forecast parameter data", "abstract": "This dataset contains ERA5 initial release (ERA5t) surface level forecast parameter data. ERA5t is the European Centre for Medium-Range Weather Forecasts (ECWMF) ERA5 reanalysis project initial release available upto 5 days behind the present data. CEDA will maintain a 6 month rolling archive of these data with overlap to the verified ERA5 data - see linked datasets on this record. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record.\r\n\r\nSurface level and model level analysis data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset." }, "objectObservation": { "ob_id": 30245, "uuid": "bbf4d911abd4446eaa8c3ed79edb9593", "short_code": "ob", "title": "ECMWF ERA5t: surface level analysis parameter data", "abstract": "This dataset contains ERA5 initial release (ERA5t) surface level analysis parameter data. ERA5t is the European Centre for Medium-Range Weather Forecasts (ECWMF) ERA5 reanalysis project initial release available upto 5 days behind the present data. CEDA will maintain a 6 month rolling archive of these data with overlap to the verified ERA5 data - see linked datasets on this record. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record.\r\n\r\nModel level analysis and surface forecast data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset." } }, { "ob_id": 331, "relationType": "Continues", "subjectObservation": { "ob_id": 30244, "uuid": "29cdcc9438b94508aab17bb5ebcdfd51", "short_code": "ob", "title": "ECMWF ERA5t: surface level forecast parameter data", "abstract": "This dataset contains ERA5 initial release (ERA5t) surface level forecast parameter data. ERA5t is the European Centre for Medium-Range Weather Forecasts (ECWMF) ERA5 reanalysis project initial release available upto 5 days behind the present data. CEDA will maintain a 6 month rolling archive of these data with overlap to the verified ERA5 data - see linked datasets on this record. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record.\r\n\r\nSurface level and model level analysis data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset." }, "objectObservation": { "ob_id": 30235, "uuid": "3e7ad71f09c244318f9bddf92e5fcc4b", "short_code": "ob", "title": "ECMWF ERA5: surface level forecast parameter data", "abstract": "This dataset contains ERA5 surface level forecast parameter data. ERA5 is the 5th generation reanalysis project from the European Centre for Medium-Range Weather Forecasts (ECWMF) - see linked documentation for further details. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record.\r\n\r\nModel and surface level analysis data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset.\r\n\r\nThe ERA5 global atmospheric reanalysis of the covers 1979 to 2 months behind the present month. This follows on from the ERA-15, ERA-40 rand ERA-interim re-analysis projects.\r\n\r\nAn initial release of ERA5 data (ERA5t) is made roughly 5 days behind the present date. These will be subsequently reviewed ahead of being released by ECMWF as quality assured data within 3 months. CEDA holds a 6 month rolling copy of the latest ERA5t data. See related datasets linked to from this record. However, for the period 2000-2006 the initial ERA5 release was found to suffer from stratospheric temperature biases and so new runs to address this issue were performed resulting in the ERA5.1 release (see linked datasets). Note, though, that Simmons et al. 2020 (technical memo 859) report that \"ERA5.1 is very close to ERA5 in the lower and middle troposphere.\" but users of data from this period should read the technical memo 859 for further details." } }, { "ob_id": 332, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 27572, "uuid": "c1145ccc4b6d4310a4fc7cce61041b63", "short_code": "ob", "title": "ECMWF ERA5: surface level analysis parameter data", "abstract": "This dataset contains ERA5 surface level analysis parameter data. ERA5 is the 5th generation reanalysis project from the European Centre for Medium-Range Weather Forecasts (ECWMF) - see linked documentation for further details. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record.\r\n\r\nModel level analysis and surface forecast data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset.\r\n\r\nThe ERA5 global atmospheric reanalysis of the covers 1979 to 2 months behind the present month. This follows on from the ERA-15, ERA-40 rand ERA-interim re-analysis projects.\r\n\r\nAn initial release of ERA5 data (ERA5t) is made roughly 5 days behind the present date. These will be subsequently reviewed ahead of being released by ECMWF as quality assured data within 3 months. CEDA holds a 6 month rolling copy of the latest ERA5t data. See related datasets linked to from this record. However, for the period 2000-2006 the initial ERA5 release was found to suffer from stratospheric temperature biases and so new runs to address this issue were performed resulting in the ERA5.1 release (see linked datasets). Note, though, that Simmons et al. 2020 (technical memo 859) report that \"ERA5.1 is very close to ERA5 in the lower and middle troposphere.\" but users of data from this period should read the technical memo 859 for further details." }, "objectObservation": { "ob_id": 30235, "uuid": "3e7ad71f09c244318f9bddf92e5fcc4b", "short_code": "ob", "title": "ECMWF ERA5: surface level forecast parameter data", "abstract": "This dataset contains ERA5 surface level forecast parameter data. ERA5 is the 5th generation reanalysis project from the European Centre for Medium-Range Weather Forecasts (ECWMF) - see linked documentation for further details. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record.\r\n\r\nModel and surface level analysis data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset.\r\n\r\nThe ERA5 global atmospheric reanalysis of the covers 1979 to 2 months behind the present month. This follows on from the ERA-15, ERA-40 rand ERA-interim re-analysis projects.\r\n\r\nAn initial release of ERA5 data (ERA5t) is made roughly 5 days behind the present date. These will be subsequently reviewed ahead of being released by ECMWF as quality assured data within 3 months. CEDA holds a 6 month rolling copy of the latest ERA5t data. See related datasets linked to from this record. However, for the period 2000-2006 the initial ERA5 release was found to suffer from stratospheric temperature biases and so new runs to address this issue were performed resulting in the ERA5.1 release (see linked datasets). Note, though, that Simmons et al. 2020 (technical memo 859) report that \"ERA5.1 is very close to ERA5 in the lower and middle troposphere.\" but users of data from this period should read the technical memo 859 for further details." } }, { "ob_id": 333, "relationType": "IsSupplementedBy", "subjectObservation": { "ob_id": 30235, "uuid": "3e7ad71f09c244318f9bddf92e5fcc4b", "short_code": "ob", "title": "ECMWF ERA5: surface level forecast parameter data", "abstract": "This dataset contains ERA5 surface level forecast parameter data. ERA5 is the 5th generation reanalysis project from the European Centre for Medium-Range Weather Forecasts (ECWMF) - see linked documentation for further details. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record.\r\n\r\nModel and surface level analysis data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset.\r\n\r\nThe ERA5 global atmospheric reanalysis of the covers 1979 to 2 months behind the present month. This follows on from the ERA-15, ERA-40 rand ERA-interim re-analysis projects.\r\n\r\nAn initial release of ERA5 data (ERA5t) is made roughly 5 days behind the present date. These will be subsequently reviewed ahead of being released by ECMWF as quality assured data within 3 months. CEDA holds a 6 month rolling copy of the latest ERA5t data. See related datasets linked to from this record. However, for the period 2000-2006 the initial ERA5 release was found to suffer from stratospheric temperature biases and so new runs to address this issue were performed resulting in the ERA5.1 release (see linked datasets). Note, though, that Simmons et al. 2020 (technical memo 859) report that \"ERA5.1 is very close to ERA5 in the lower and middle troposphere.\" but users of data from this period should read the technical memo 859 for further details." }, "objectObservation": { "ob_id": 27572, "uuid": "c1145ccc4b6d4310a4fc7cce61041b63", "short_code": "ob", "title": "ECMWF ERA5: surface level analysis parameter data", "abstract": "This dataset contains ERA5 surface level analysis parameter data. ERA5 is the 5th generation reanalysis project from the European Centre for Medium-Range Weather Forecasts (ECWMF) - see linked documentation for further details. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record.\r\n\r\nModel level analysis and surface forecast data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset.\r\n\r\nThe ERA5 global atmospheric reanalysis of the covers 1979 to 2 months behind the present month. This follows on from the ERA-15, ERA-40 rand ERA-interim re-analysis projects.\r\n\r\nAn initial release of ERA5 data (ERA5t) is made roughly 5 days behind the present date. These will be subsequently reviewed ahead of being released by ECMWF as quality assured data within 3 months. CEDA holds a 6 month rolling copy of the latest ERA5t data. See related datasets linked to from this record. However, for the period 2000-2006 the initial ERA5 release was found to suffer from stratospheric temperature biases and so new runs to address this issue were performed resulting in the ERA5.1 release (see linked datasets). Note, though, that Simmons et al. 2020 (technical memo 859) report that \"ERA5.1 is very close to ERA5 in the lower and middle troposphere.\" but users of data from this period should read the technical memo 859 for further details." } }, { "ob_id": 334, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30211, "uuid": "4ef9ebc392714b7cbc86ce601c6fd956", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the ACTIVE, PASSIVE and COMBINED products, Version 04.7", "abstract": "These ancillary datasets were used in the production of the ACTIVE, PASSIVE and COMBINED soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v04.7 Soil Moisture CCI data.\r\n\r\nThe ACTIVE, PASSIVE and COMBINED soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" }, "objectObservation": { "ob_id": 29935, "uuid": "4a29dbf40fc3445395d72927700fafe7", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the ACTIVE, PASSIVE and COMBINED products, Version 04.5", "abstract": "These ancillary datasets were used in the production of the ACTIVE, PASSIVE and COMBINED soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask. This version of the ancillary datasets were used in the production of the v04.5 Soil Moisture CCI data.\r\n\r\nThe ACTIVE, PASSIVE and COMBINED soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" } }, { "ob_id": 335, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30204, "uuid": "1d38c469bbd3411b9bc4cd1195c38331", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE Product, Version 04.7", "abstract": "The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created. \r\n\r\nThe v04.7 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2019-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" }, "objectObservation": { "ob_id": 29929, "uuid": "20babc8f4dc449eaac11f47708e9f721", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): ACTIVE Product, Version 04.5", "abstract": "The Soil Moisture CCI ACTIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by fusing scatterometer soil moisture products, derived from the instruments AMI-WS and ASCAT. PASSIVE and COMBINED products have also been created. \r\n\r\nThe v04.5 ACTIVE product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It covers the period 1991-08-05 to 2018-12-31 and is expressed in percent of saturation [%]. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" } }, { "ob_id": 336, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30206, "uuid": "2d4a50f390064820a9dcc2fcf7ac4b18", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED Product, Version 04.7", "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 and SMOS satellite instruments. \r\n\r\nThe v04.7 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 2019-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" }, "objectObservation": { "ob_id": 29931, "uuid": "34090d316d514b55b7080a4181a28f8f", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED Product, Version 04.5", "abstract": "The Soil Moisture CCI COMBINED dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by directly merging Level 2 scatterometer and radiometer soil moisture products derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. \r\n\r\nThe v04.5 COMBINED product, provided as global daily images in NetCDF-4 classic file format, presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. It is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2018-12-31. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" } }, { "ob_id": 337, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30208, "uuid": "ccc69467a0c74adbaada8c55b970ca19", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE Product, Version 04.7", "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 and SMOS satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v04.7 PASSIVE product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2019-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" }, "objectObservation": { "ob_id": 29933, "uuid": "4b344dac208f4a82a35d544f6837d111", "short_code": "ob", "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): PASSIVE Product, Version 04.5", "abstract": "The Soil Moisture CCI PASSIVE dataset is one of the three datasets created as part of the European Space Agency's (ESA) Soil Moisture Essential Climate Variable (ECV) Climate Change Initiative (CCI) project. The product has been created by merging data from the SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. ACTIVE and COMBINED products have also been created.\r\n\r\nThe v04.5 PASSIVE product presents a global coverage of surface soil moisture at a spatial resolution of 0.25 degrees. The product is provided in volumetric units [m3 m-3] and covers the period (yyyy-mm-dd) 1978-11-01 to 2018-12-31. It consists of global daily images stored within yearly folders and are NetCDF-4 classic file formatted. For information regarding the theoretical and algorithmic base of the product, please see the Algorithm Theoretical Baseline Document. Other additional reference documents and information relating to the dataset can also be found on the CCI Soil Moisture project web site or within the Product Specification Document.\r\n\r\nThe data set should be cited using all three of the following references:\r\n\r\n1. Gruber, A., Scanlon, T., van der Schalie, R., Wagner, W., and Dorigo, W. (2019). Evolution of the ESA CCI Soil Moisture climate data records and their underlying merging methodology, Earth Syst. Sci. Data, 11, 717–739, https://doi.org/10.5194/essd-11-717-2019\r\n\r\n2. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n3. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070" } }, { "ob_id": 338, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30262, "uuid": "58d87204bd974f04b14141eb275f4a1e", "short_code": "ob", "title": "CRU CY4.04: Climatic Research Unit year-by-year variation of selected climate variables by country version 4.04 (Jan. 1901 - Dec. 2019)", "abstract": "The Climatic Research Unit (CRU) Country (CY) data version 4.04 dataset consists of ten climate variables for country averages at a monthly, seasonal and annual frequency: including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure, potential evapotranspiration and wet day frequency. This version uses the updated set of country definitions, please see the appropriate Release Notes.\r\n\r\nThis dataset was produced in 2020 by CRU at the University of East Anglia and extends the CRU CY4.03 data to include 2019. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nSpatial averages are calculated using area-weighted means. CRU CY4.04 is derived directly from the CRU time series (TS) 4.04 dataset. CRU CY version 4.04 spans the period 1901-2019 for 292 countries.\r\n\r\nTo understand the CRU CY4.04 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS4.04. It is therefore recommended that all users read the Harris et al, 2020 paper and the CRU TS4.04 release notes listed in the online documentation on this record.\r\n\r\nCRU CY data are available for download to all CEDA users." }, "objectObservation": { "ob_id": 27492, "uuid": "d6768285fdc8408bbb9b02bb0f317774", "short_code": "ob", "title": "CRU CY 4.03: Climatic Research Unit year-by-year variation of selected climate variables by country version 4.03 (Jan. 1901 - Dec. 2018)", "abstract": "The Climatic Research Unit (CRU) Country (CY) data version 4.03 dataset consists of ten climate variables for country averages at a monthly, seasonal and annual frequency; including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and potential evapotranspiration. This version uses the updated set of country definitions, please see the appropriate Release Notes.\r\n\r\nThis dataset was produced in 2019 by CRU at the University of East Anglia and extends the CRU CY4.02 data to include 2018. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nSpatial averages are calculated using area-weighted means. CRU CY4.03 is derived directly from the CRU time series (TS) 4.03 dataset. CRU CY version 4.03 spans the period 1901-2018 for 292 countries.\r\n\r\nTo understand the CRU CY4.03 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS4.03. It is therefore recommended that all users read the Harris et al, 2020 paper and the CRU TS4.03 release notes listed in the online documentation on this record.\r\n\r\nCRU CY data are available for download to all CEDA users." } }, { "ob_id": 339, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30263, "uuid": "89e1e34ec3554dc98594a5732622bce9", "short_code": "ob", "title": "CRU TS4.04: Climatic Research Unit (CRU) Time-Series (TS) version 4.04 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2019)", "abstract": "The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.04 data are month-by-month variations in climate over the period 1901-2019, 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 TS4.04 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 2019.\r\n\r\nThe CRU TS4.04 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 TS4.04 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": 27493, "uuid": "10d3e3640f004c578403419aac167d82", "short_code": "ob", "title": "CRU TS4.03: Climatic Research Unit (CRU) Time-Series (TS) version 4.03 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2018)", "abstract": "The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.03 data are month-by-month variations in climate over the period 1901-2018, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia.\r\n\r\nThe CRU TS4.03 variables are cloud cover, diurnal temperature range, frost day frequency, potential evapotranspiration (PET), precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period January 1901 - December 2018.\r\n\r\nThe CRU TS4.03 data were produced using angular-distance weighting (ADW) interpolation. All version 4 releases used triangulation routines in IDL. Please see the release notes for full details of this version update. \r\n\r\nThe CRU TS4.03 data are monthly gridded fields based on monthly observational data calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and NetCDF data files both contain monthly mean values for the various parameters. The NetCDF versions contain an additional integer variable, ’stn’, which provides, for each datum in the main variable, a count (between 0 and 8) of the number of stations used in that interpolation. The missing value code for 'stn' is -999.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies." } }, { "ob_id": 340, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30054, "uuid": "18ef8247f52a4cb6a14013f8235cc1eb", "short_code": "ob", "title": "University of Leicester GOSAT Proxy XCH4 v9.0", "abstract": "The University of Leicester GOSAT Proxy XCH4 v9.0 data set contains column-averaged dry-air mole fraction of methane (XCH4) generated from the Greenhouse Gas Observing Satellite (GOSAT) Level 1B data using the University of Leicester Full-Physics retrieval scheme (UoL-FP) using the Proxy retrieval approach.\r\n\r\nThis data is an NCEO funded update/extension to the European Space Agency Climate Change Initiative (CCI) CH4_GOS_OCPR V7.0. and the Copernicus Climate Change Service (C3S) CH_4 v7.2 data sets. It's a full reprocessing, based on different underlying L1B radiance data with additional changes. The latest version of the GOSAT Level 1B files (version 210.210) was acquired directly from the National Institute for Environmental Studies (NIES) GOSAT Data Archive Service (GDAS) Data Server and are processed with the Leicester Retrieval Preparation Toolset to extract the measured radiances along with all required sounding-specific ancillary information such as the measurement time, location and geometry. These measured radiances have the recommended radiometric calibration and degradation corrections applied as per Yoshida et al., 2013 with an estimate of the spectral noise derived from the standard deviation of the out-of-band signal. The spectral data were then inputted into the UoL-FP retrieval algorithm where the Proxy retrieval approach is used to obtain the column-averaged dry-air mole fraction of methane (XCH4). Post-filtering and bias correction against the Total Carbon Column Observing Network is then performed. See process information and documentation for further details." }, "objectObservation": { "ob_id": 25928, "uuid": "f9154243fd8744bdaf2a59c39033e659", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged CH4 from GOSAT generated with the OCPR (UoL-PR) Proxy algorithm (CH4_GOS_OCPR), v7.0", "abstract": "This CH4_GOS_OCPR dataset is comprised of level 2, column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4.) The product has been produced using data acquired from the Thermal and Near Infrared Sensor for Carbon Observations (TANSO-FTS) NIR and SWIR spectra, onboard the Japanese Greenhouse gases Observing Satellite (GOSAT), using the OCPR University of Leicester Proxy Retrieval Algorithm. It has been generated as part of the European Space Agency (ESA) Greenhouse Gases Climate Change Initiative (GHG_cci). This version of the data is v7.0 and forms part of the Climate Research Data Package 4.\r\n\r\nThis algorithm has been designated the baseline algorithm for the GHG CCI proxy methane retrievals. A second product has also been generated from the TANSO-FTS data using an alternative algorithm, the RemoTeC Proxy algorithm. It is advised that users who aren't sure whether to use the baseline or alternative product use this product generated with the OCPR baseline algorithm. For more information regarding the differences between baseline and alternative algorithms please see the GHG-CCI data products webpage.\r\n\r\nThe product is stored in NetCDF format with all GOSAT soundings on a single day stored in one file. For further details on the product, including the UoL-PR algorithm and the TANSO-FTS instrument, please see the associated product user guide (PUG) or the Algorithm Theoretical Basis Documents." } }, { "ob_id": 341, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 20372, "uuid": "edf8febfdaad48abb2cbaf7d7e846a86", "short_code": "ob", "title": "CRU TS4.00: Climatic Research Unit (CRU) Time-Series (TS) version 4.00 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2015)", "abstract": "The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.00 data are month-by-month variations in climate over the period 1901-2015, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia.\r\n\r\nThe CRU TS4.00 variables are cloud cover, diurnal temperature range, frost day frequency, potential evapotranspiration (PET), precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period January 1901 - December 2015.\r\n\r\nThe CRU TS4.00 data were produced using angular-distance weighting (ADW) interpolation. All version 3 releases used triangulation routines in IDL. Please see the release notes for full details of this version update. CRU TS4.00 is a full release, differing only in methodology from the existing current release, v3.24.01. Both are released concurrently to support comparative evaluations between these two versions.\r\n\r\nThe CRU TS4.00 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 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.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies." }, "objectObservation": { "ob_id": 26866, "uuid": "7ad889f2cc1647efba7e6a356098e4f3", "short_code": "ob", "title": "CRU TS3.26: Climatic Research Unit (CRU) Time-Series (TS) Version 3.26 of High-Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2017)", "abstract": "The gridded CRU TS (time-series) 3.26 data are month-by-month variations in climate over the period 1901-2017, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nThis version of CRU TS supersedes version 3.25, additionally however these data are superseded by the CRU TS 4.02 data which has a new processing methodology. This concurrent release of CRU TS 3.26 and CRU TS 4.02 is made to support users during the transition to the CRU TS version 4 data. No further releases of version 3 are planned.\r\n\r\nCRU TS 3.26 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period Jan. 1901 - Dec. 2017.\r\n\r\nCRU TS 3.26 data were produced using the same methodology as for the 3.21, 3.22, 3.23, 3.24.01, 3.26 datasets. This version contains updates the dataset with 2016 data, some new stations have been added for TMP and PRE only. This release is the latest release of the CRU TS data. Known issues predating this release remain.\r\n\r\nThe CRU TS 3.26 data are monthly gridded fields based on monthly observational data, which are 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.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies." } }, { "ob_id": 342, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 6674, "uuid": "ac3e6be017970639a9278e64d3fd5508", "short_code": "ob", "title": "CRU TS3.10: Climatic Research Unit (CRU) Time-Series (TS) Version 3.10 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901 - Dec. 2009)", "abstract": "The gridded CRU TS (time-series) 3.10 data are month-by-month variations in climate over the period 1901-2009, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia. \r\n\r\nCRU TS 3.10 includes variables such as cloud cover, diurnal temperature range, PET, daily mean temperature, monthly average daily minimun/maximum temperature, and vapour pressure for the period 1901-2009. Note that a corrected run of precipitation data, based on the v3.10 precipitation station data are available (e.g cru_ts_3_10_01.1901.2009.pre.dat).\r\n\r\nCRU provided the BADC with software to generate the CRU datasets in 2010, and this was used to produce CRU TS 3.10 at the BADC in early 2011. CRU TS 3.10 data were produced using the same methodology as for the 3.00 dataset. The main differences is that the 3.10 dataset extends from 1901-2009, and all of the data in this period can now be used. Slight differences may be noticed between the results for a given time/location between the 3.00 and 3.10 versions, due to additional data now being available. CRU have examined the 3.10 dataset in detail and are confident that such differences are not significant.\r\n\r\nThe CRU TS 3.10 data are monthly gridded fields based on monthly observational data, which are 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. \r\nAll CRU TS output files are actual values - NOT anomalies. \r\n\r\nCRU TS data are available for download to all CEDA users." }, "objectObservation": { "ob_id": 6670, "uuid": "c9dd2107e0b7e8c7b6aca7c34980f679", "short_code": "ob", "title": "CRU TS3.00: Climatic Research Unit (CRU) Time-Series (TS) Version 3.00 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901 - Dec.2006)", "abstract": "The gridded CRU TS (time-series) 3.00 data are month-by-month variations in climate over the period 1901-2006, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia. \r\n\r\nThe CRU TS 3.00 variables include cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum/min temperature, vapour pressure and wet day frequency.\r\n\r\nThe BADC holds the preliminary CRU TS3.00 datasets for the period 1901-2006. Note that these data are yearly files REGARDLESS of whether the data exists for the full year. In CRU TS3.00, the data up to 06/2006 *ONLY* has been used.\r\n\r\nThe CRU TS 3.00 data are monthly gridded fields based on monthly observational data, which are 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. \r\n\r\nAll CRU TS output files are actual values - NOT anomalies. \r\n\r\nCRU TS data are available for download to all CEDA users." } }, { "ob_id": 343, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 6677, "uuid": "2949a8a25b375c9e323c53f6b6cb2a3a", "short_code": "ob", "title": "CRU TS3.20: Climatic Research Unit (CRU) Time-Series (TS) Version 3.20 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901 - Dec. 2011)", "abstract": "The gridded CRU TS (time-series) 3.20 data are month-by-month variations in climate over the period 1901-2011, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia. CRU TS 3.20 data were produced using the same methodology as for the 3.00 and 3.10 datasets. \r\n\r\nCRU TS 3.20 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum temperature, vapour pressure and wet day frequency for the period 1901-2011.\r\n\r\nThe CRU TS 3.20 data are monthly gridded fields based on monthly observational data, which are 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. All CRU TS output files are actual values - NOT anomalies. \r\n\r\nCRU TS data are available for download to all CEDA users." }, "objectObservation": { "ob_id": 6674, "uuid": "ac3e6be017970639a9278e64d3fd5508", "short_code": "ob", "title": "CRU TS3.10: Climatic Research Unit (CRU) Time-Series (TS) Version 3.10 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901 - Dec. 2009)", "abstract": "The gridded CRU TS (time-series) 3.10 data are month-by-month variations in climate over the period 1901-2009, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia. \r\n\r\nCRU TS 3.10 includes variables such as cloud cover, diurnal temperature range, PET, daily mean temperature, monthly average daily minimun/maximum temperature, and vapour pressure for the period 1901-2009. Note that a corrected run of precipitation data, based on the v3.10 precipitation station data are available (e.g cru_ts_3_10_01.1901.2009.pre.dat).\r\n\r\nCRU provided the BADC with software to generate the CRU datasets in 2010, and this was used to produce CRU TS 3.10 at the BADC in early 2011. CRU TS 3.10 data were produced using the same methodology as for the 3.00 dataset. The main differences is that the 3.10 dataset extends from 1901-2009, and all of the data in this period can now be used. Slight differences may be noticed between the results for a given time/location between the 3.00 and 3.10 versions, due to additional data now being available. CRU have examined the 3.10 dataset in detail and are confident that such differences are not significant.\r\n\r\nThe CRU TS 3.10 data are monthly gridded fields based on monthly observational data, which are 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. \r\nAll CRU TS output files are actual values - NOT anomalies. \r\n\r\nCRU TS data are available for download to all CEDA users." } }, { "ob_id": 344, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 6679, "uuid": "ac4ecbd554d0dd52a9b575d9666dc42d", "short_code": "ob", "title": "CRU TS3.21: Climatic Research Unit (CRU) Time-Series (TS) Version 3.21 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2012)", "abstract": "The gridded Climatic Research Unit (CRU) TS (time-series) 3.21 datasets are month-by-month variations in climate over the period 1901-2012, on high-resolution (0.5 x 0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia. \r\n\r\nCRU TS 3.21 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and wet day frequency for the period Jan. 1901 - Dec. 2012. \r\n\r\nCRU TS 3.21 data were produced using the same methodology as for the 3.20 datasets.\r\nIn addition to updating the dataset with 2012 data, the v3.21 release corrects two errors in the v3.20 dataset. Please see the release notes in the docs section, which contain details of the errors.\r\n\r\nThis directory also contains an advisory note regarding an issue with 35 Mozambique stations that were new. After an investigation by the CRU, the comparison plots show that the only countries affected in a possibly significant way are Egypt and Eritrea. The details of these can be found in this directory.\r\n\r\nThe CRU TS 3.21 data are monthly gridded fields based on monthly observational data, which are 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.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies.\r\n\r\nCRU TS data are available for download to all CEDA users." }, "objectObservation": { "ob_id": 6677, "uuid": "2949a8a25b375c9e323c53f6b6cb2a3a", "short_code": "ob", "title": "CRU TS3.20: Climatic Research Unit (CRU) Time-Series (TS) Version 3.20 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901 - Dec. 2011)", "abstract": "The gridded CRU TS (time-series) 3.20 data are month-by-month variations in climate over the period 1901-2011, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia. CRU TS 3.20 data were produced using the same methodology as for the 3.00 and 3.10 datasets. \r\n\r\nCRU TS 3.20 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum temperature, vapour pressure and wet day frequency for the period 1901-2011.\r\n\r\nThe CRU TS 3.20 data are monthly gridded fields based on monthly observational data, which are 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. All CRU TS output files are actual values - NOT anomalies. \r\n\r\nCRU TS data are available for download to all CEDA users." } }, { "ob_id": 345, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 6681, "uuid": "4a6d071383976a5fb24b5b42e28cf28f", "short_code": "ob", "title": "CRU TS3.22: Climatic Research Unit (CRU) Time-Series (TS) Version 3.22 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2013)", "abstract": "The gridded CRU TS (time-series) 3.22 data are month-by-month variations in climate over the period 1901-2013, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nCRU TS 3.22 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and wet day frequency for the period Jan. 1901 - Dec. 2013.\r\n\r\nCRU TS 3.22 data were produced using the same methodology as for the 3.21 datasets. In addition to updating the dataset with 2013 data, the v3.22 release corrects an error in the v3.21 dataset. This is summarised in the document, CRU_Advisory_v3.2x_NE_Africa.txt, and affects PRE and WET variables only. There are several known issues with the current dataset which cannot be resolved in the timeframe of this release; they will be addressed in the future. This directory also contains an advisory note regarding an issue with 35 Mozambique stations that were new. After an investigation by the CRU, the comparison plots show that the only countries affected in a possibly significant way are Egypt and Eritrea. The details of these can be found in this directory.\r\n\r\nThe CRU TS 3.22 data are monthly gridded fields based on monthly observational data, which are 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.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies.\r\n\r\nCRU TS data are available for download to all CEDA users. The CEDA Web Processing Service (WPS) may be used to extract a subset of the data (please see link to WPS below)." }, "objectObservation": { "ob_id": 6679, "uuid": "ac4ecbd554d0dd52a9b575d9666dc42d", "short_code": "ob", "title": "CRU TS3.21: Climatic Research Unit (CRU) Time-Series (TS) Version 3.21 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2012)", "abstract": "The gridded Climatic Research Unit (CRU) TS (time-series) 3.21 datasets are month-by-month variations in climate over the period 1901-2012, on high-resolution (0.5 x 0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia. \r\n\r\nCRU TS 3.21 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and wet day frequency for the period Jan. 1901 - Dec. 2012. \r\n\r\nCRU TS 3.21 data were produced using the same methodology as for the 3.20 datasets.\r\nIn addition to updating the dataset with 2012 data, the v3.21 release corrects two errors in the v3.20 dataset. Please see the release notes in the docs section, which contain details of the errors.\r\n\r\nThis directory also contains an advisory note regarding an issue with 35 Mozambique stations that were new. After an investigation by the CRU, the comparison plots show that the only countries affected in a possibly significant way are Egypt and Eritrea. The details of these can be found in this directory.\r\n\r\nThe CRU TS 3.21 data are monthly gridded fields based on monthly observational data, which are 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.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies.\r\n\r\nCRU TS data are available for download to all CEDA users." } }, { "ob_id": 346, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 13151, "uuid": "5dca9487dc614711a3a933e44a933ad3", "short_code": "ob", "title": "CRU TS3.23: Climatic Research Unit (CRU) Time-Series (TS) Version 3.23 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2014)", "abstract": "The gridded CRU TS (time-series) 3.23 data are month-by-month variations in climate over the period 1901-2014, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nCRU TS 3.23 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period Jan. 1901 - Dec. 2014.\r\n\r\nCRU TS 3.23 data were produced using the same methodology as for the 3.21 datasets. In addition to updating the dataset with 2014 data, some new stations have been added for TMP and PRE only. Known issues predating this release remain; the 4.00 release, due soon, will address these.\r\n\r\nThe 4.00 release will utilise Angular-Distance Weighting (ADW) gridding, promising more accurate results with far greater adjustability and logging. It will cover the same spatial, temporal and variate spaces as version 3.23 (land areas excluding Antarctica at 0.5°x0.5°, monthly from 1901 to 2014 with no missing values, 10 variables).\r\n\r\nVersions 3.23 and 4.00 will run concurrently until 2016, after which the new (ADW) approach will be used. This is to allow comparisons between the methods and results to be made by users of the dataset.\r\n\r\n\r\nThe CRU TS 3.23 data are monthly gridded fields based on monthly observational data, which are 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.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies.\r\n\r\nCRU TS data are available for download to all CEDA users. The CEDA Web Processing Service (WPS) may be used to extract a subset of the data (please see link to WPS below)." }, "objectObservation": { "ob_id": 6681, "uuid": "4a6d071383976a5fb24b5b42e28cf28f", "short_code": "ob", "title": "CRU TS3.22: Climatic Research Unit (CRU) Time-Series (TS) Version 3.22 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2013)", "abstract": "The gridded CRU TS (time-series) 3.22 data are month-by-month variations in climate over the period 1901-2013, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nCRU TS 3.22 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and wet day frequency for the period Jan. 1901 - Dec. 2013.\r\n\r\nCRU TS 3.22 data were produced using the same methodology as for the 3.21 datasets. In addition to updating the dataset with 2013 data, the v3.22 release corrects an error in the v3.21 dataset. This is summarised in the document, CRU_Advisory_v3.2x_NE_Africa.txt, and affects PRE and WET variables only. There are several known issues with the current dataset which cannot be resolved in the timeframe of this release; they will be addressed in the future. This directory also contains an advisory note regarding an issue with 35 Mozambique stations that were new. After an investigation by the CRU, the comparison plots show that the only countries affected in a possibly significant way are Egypt and Eritrea. The details of these can be found in this directory.\r\n\r\nThe CRU TS 3.22 data are monthly gridded fields based on monthly observational data, which are 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.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies.\r\n\r\nCRU TS data are available for download to all CEDA users. The CEDA Web Processing Service (WPS) may be used to extract a subset of the data (please see link to WPS below)." } }, { "ob_id": 347, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 20361, "uuid": "3df7562727314bab963282e6a0284f24", "short_code": "ob", "title": "CRU TS3.24.01: Climatic Research Unit (CRU) Time-Series (TS) Version 3.24.01 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2015)", "abstract": "The gridded CRU TS (time-series) 3.24.01 data are month-by-month variations in climate over the period 1901-2015, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nCRU TS 3.24.01 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period Jan. 1901 - Dec. 2015.\r\n\r\nCRU TS 3.24.01 data were produced using the same methodology as for the 3.21 datasets. In addition to updating the dataset with 2015 data, some new stations have been added for TMP and PRE only. This release should be used in place of v3.24 which has been withdrawn. Known issues predating this release remain.\r\n\r\nThe CRU TS 3.24.01 data are monthly gridded fields based on monthly observational data, which are 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.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies." }, "objectObservation": { "ob_id": 13151, "uuid": "5dca9487dc614711a3a933e44a933ad3", "short_code": "ob", "title": "CRU TS3.23: Climatic Research Unit (CRU) Time-Series (TS) Version 3.23 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2014)", "abstract": "The gridded CRU TS (time-series) 3.23 data are month-by-month variations in climate over the period 1901-2014, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nCRU TS 3.23 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period Jan. 1901 - Dec. 2014.\r\n\r\nCRU TS 3.23 data were produced using the same methodology as for the 3.21 datasets. In addition to updating the dataset with 2014 data, some new stations have been added for TMP and PRE only. Known issues predating this release remain; the 4.00 release, due soon, will address these.\r\n\r\nThe 4.00 release will utilise Angular-Distance Weighting (ADW) gridding, promising more accurate results with far greater adjustability and logging. It will cover the same spatial, temporal and variate spaces as version 3.23 (land areas excluding Antarctica at 0.5°x0.5°, monthly from 1901 to 2014 with no missing values, 10 variables).\r\n\r\nVersions 3.23 and 4.00 will run concurrently until 2016, after which the new (ADW) approach will be used. This is to allow comparisons between the methods and results to be made by users of the dataset.\r\n\r\n\r\nThe CRU TS 3.23 data are monthly gridded fields based on monthly observational data, which are 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.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies.\r\n\r\nCRU TS data are available for download to all CEDA users. The CEDA Web Processing Service (WPS) may be used to extract a subset of the data (please see link to WPS below)." } }, { "ob_id": 348, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 25063, "uuid": "c311c7948e8a47b299f8f9c7ae6cb9af", "short_code": "ob", "title": "CRU TS3.25: Climatic Research Unit (CRU) Time-Series (TS) Version 3.25 of High-Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2016)", "abstract": "This version of CRU TS is superseded by version 4.01. It is being made available to assist with users moving to the new process. No further releases of version 3 are planned.\r\n\r\nThe gridded CRU TS (time-series) 3.25 data are month-by-month variations in climate over the period 1901-2016, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nCRU TS 3.25 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period Jan. 1901 - Dec. 2016.\r\n\r\nCRU TS 3.25 data were produced using the same methodology as for the 3.21, 3.22, 3.23 and 3.24.01 datasets. This version contains updates the dataset with 2016 data, some new stations have been added for TMP and PRE only. This release is the latest release of the CRU TS data. Known issues predating this release remain.\r\n\r\nThe CRU TS 3.25 data are monthly gridded fields based on monthly observational data, which are 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.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies." }, "objectObservation": { "ob_id": 20361, "uuid": "3df7562727314bab963282e6a0284f24", "short_code": "ob", "title": "CRU TS3.24.01: Climatic Research Unit (CRU) Time-Series (TS) Version 3.24.01 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2015)", "abstract": "The gridded CRU TS (time-series) 3.24.01 data are month-by-month variations in climate over the period 1901-2015, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nCRU TS 3.24.01 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period Jan. 1901 - Dec. 2015.\r\n\r\nCRU TS 3.24.01 data were produced using the same methodology as for the 3.21 datasets. In addition to updating the dataset with 2015 data, some new stations have been added for TMP and PRE only. This release should be used in place of v3.24 which has been withdrawn. Known issues predating this release remain.\r\n\r\nThe CRU TS 3.24.01 data are monthly gridded fields based on monthly observational data, which are 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.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies." } }, { "ob_id": 349, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 26866, "uuid": "7ad889f2cc1647efba7e6a356098e4f3", "short_code": "ob", "title": "CRU TS3.26: Climatic Research Unit (CRU) Time-Series (TS) Version 3.26 of High-Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2017)", "abstract": "The gridded CRU TS (time-series) 3.26 data are month-by-month variations in climate over the period 1901-2017, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nThis version of CRU TS supersedes version 3.25, additionally however these data are superseded by the CRU TS 4.02 data which has a new processing methodology. This concurrent release of CRU TS 3.26 and CRU TS 4.02 is made to support users during the transition to the CRU TS version 4 data. No further releases of version 3 are planned.\r\n\r\nCRU TS 3.26 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period Jan. 1901 - Dec. 2017.\r\n\r\nCRU TS 3.26 data were produced using the same methodology as for the 3.21, 3.22, 3.23, 3.24.01, 3.26 datasets. This version contains updates the dataset with 2016 data, some new stations have been added for TMP and PRE only. This release is the latest release of the CRU TS data. Known issues predating this release remain.\r\n\r\nThe CRU TS 3.26 data are monthly gridded fields based on monthly observational data, which are 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.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies." }, "objectObservation": { "ob_id": 25063, "uuid": "c311c7948e8a47b299f8f9c7ae6cb9af", "short_code": "ob", "title": "CRU TS3.25: Climatic Research Unit (CRU) Time-Series (TS) Version 3.25 of High-Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2016)", "abstract": "This version of CRU TS is superseded by version 4.01. It is being made available to assist with users moving to the new process. No further releases of version 3 are planned.\r\n\r\nThe gridded CRU TS (time-series) 3.25 data are month-by-month variations in climate over the period 1901-2016, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nCRU TS 3.25 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period Jan. 1901 - Dec. 2016.\r\n\r\nCRU TS 3.25 data were produced using the same methodology as for the 3.21, 3.22, 3.23 and 3.24.01 datasets. This version contains updates the dataset with 2016 data, some new stations have been added for TMP and PRE only. This release is the latest release of the CRU TS data. Known issues predating this release remain.\r\n\r\nThe CRU TS 3.25 data are monthly gridded fields based on monthly observational data, which are 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.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies." } }, { "ob_id": 350, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30290, "uuid": "3e9f387293294f3b8a850524fcfc0c9c", "short_code": "ob", "title": "HadISDH land: gridded global monthly land surface humidity data version 4.2.0.2019f", "abstract": "This is the 4.2.0.2019f version of the HadISDH (Integrated Surface Database Humidity) land data. These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2019. \r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in either NetCDF or ASCII format.\r\n\r\nThis version extends the 4.1.0.2018f version to the end of 2019 and constitutes a minor update to HadISDH due to changing some of the code base from IDL to Python 3 and detecting and fixing various bugs in the process. These have led to small changes in regional and global average values and coverage. All other processing steps for HadISDH remain identical. Users are advised to read the update document in the Docs section for full details. \r\n\r\nAs in previous years, the annual scrape of NOAA’s Integrated Surface Dataset for HadISD.3.1.0.2019f, which is the basis of HadISDH.land, has pulled through some historical changes to stations. This, and the additional year of data, results in small changes to station selection. There has been an issue with data for April 2015 whereby it is missing for most of the globe. This will hopefully be resolved by next year’s update. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014.\r\n\r\nDunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more detail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013." }, "objectObservation": { "ob_id": 25974, "uuid": "de33ae6e5b724a41be34d0f107a65ce2", "short_code": "ob", "title": "HadISDH: gridded global monthly land surface humidity data version 4.0.0.2017f", "abstract": "This is the 4.0.0.2017f version of the HadISDH land data. These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2017. \r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in either NetCDF or ASCII format.\r\n\r\nThis version extends the 3.0.0.2016p version to the end of 2017 and constitutes a major update to HadISDH due to a change to using the 1981-2010 period as its climatological reference period both to make it more consistent with other monitoring products and to maximise station coverage now that it uses the larger station database of HadISD2. Users are advised to read the update document in the docs section for full details. This version now uses the 1981-2010 period as its climatological reference period both to make it more consistent with other monitoring products and to maximise station coverage now that it uses the larger station database of HadISD2. \r\n\r\nAdditionally, there has been a small methodological change. Stations with large adjustments made during homogenisation are removed based on thresholds for q (>3g/kg), RH (>15%rh), T (>5degC) and Td (>5degC) rather than just T and Td. This results in 54 stations being removed as opposed to 29 last year. All other processing steps for HadISDH remain identical. \r\n\r\nThe new version of HadISD2 (2.0.2.2017p) has pulled through some historical changes to stations which are passed on to HadISDH. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data. \r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nWillett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014. \r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nWe strongly recommend that you read these papers before making use of the data, more detail on the dataset can be found in an earlier publication:\r\n\r\nWillett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013." } }, { "ob_id": 351, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30531, "uuid": "ffeb0c718baf49ad845f30677944610a", "short_code": "ob", "title": "HadISDH marine: gridded global monthly ocean surface humidity data version 1.0.0.2019f", "abstract": "This is the 1.0.0.2019f version of the HadISDH (Integrated Surface Database Humidity) marine data. These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2019.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in either NetCDF or ASCII format.\r\n\r\nThis version extends the 1.0.0.2018f version to the end of 2019 and constitutes with no changes other than the addition of 2019 data. Users are advised to read the update document in the Docs section for full details. \r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I.: Development of the HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data, in review, doi:XX.XXXX/essd-XX-XXXX-2020, 2020.\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E., Berry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J., Rayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to the historical marine climate record. International Journal of Climatology. doi:10.1002/joc.4775." }, "objectObservation": { "ob_id": 30532, "uuid": "463b2fcd6a264a39b1e3249dab16c177", "short_code": "ob", "title": "HadISDH marine: gridded global monthly ocean surface humidity data version 1.0.0.2018f", "abstract": "This is the 1.0.0.2018f version of the HadISDH (Integrated Surface Database Humidity) marine data and the first version to be produced. These data are provided by the Met Office Hadley Centre. This version spans 1/1/1973 to 31/12/2018.\r\n\r\nThe data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD). Data are provided in NetCDF format.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: http://hadisdh.blogspot.co.uk/\r\n\r\nReferences:\r\n\r\nWhen using the dataset in a paper please cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference):\r\n\r\nWillett, K. M., Dunn, R. J. H., Kennedy, J. J. and Berry, D. I.: Development of the HadISDH marine humidity climate monitoring dataset. Earth System Sciences Data, in review, doi:XX.XXXX/essd-XX-XXXX-2020, 2020.\r\n\r\nFreeman, E., Woodruff, S. D., Worley, S. J., Lubker, S. J., Kent, E. C., Angel, W. E., Berry, D. I., Brohan, P., Eastman, R., Gates, L., Gloeden, W., Ji, Z., Lawrimore, J., Rayner, N. A., Rosenhagen, G. and Smith, S. R., ICOADS Release 3.0: A major update to the historical marine climate record. International Journal of Climatology. doi:10.1002/joc.4775." } }, { "ob_id": 352, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30640, "uuid": "f1ad922db5f94bad8c0a9aa82599ba8f", "short_code": "ob", "title": "EUSTACE: Global land station daily air temperature measurements with non-climatic discontinuities identified, for 1850-2015, v1.1", "abstract": "This dataset consists of a global collection of land surface air temperature data from meteorological stations covering the period from 1850-2015. It has been compiled as part of the European Union Horizon 2020 EUSTACE (EU Surface Temperature for All Corners of Earth) project. This version 1.1 is an update to the v1.0 dataset that fixes a bug in the time values in the original files; the data is otherwise identical.\r\n\r\nThe dataset provides daily maximum and minimum temperatures from stations globally, brought together from a number of public databases: Global Historical Climatology Network Daily Temperatures (GHCN-D); European Climate Assessment & Dataset (ECA&D) non-blended; International Surface Temperature Initiative (ISTI); DECADE (Data on Climate and Extreme weather for the Central Andes); and ERA-CLIM (European Reanalysis of Global Climate Observations). These data have then been quality controlled through the removal of duplicates and unreliable data sources, and come with a large amount of additional information on quality, homogeneity and resolution.\r\n\r\nThese data are available for non-commercial use." }, "objectObservation": { "ob_id": 20093, "uuid": "7925ded722d743fa8259a93acc7073f2", "short_code": "ob", "title": "EUSTACE: Global land station daily air temperature measurements with non-climatic discontinuities identified, for 1850-2015", "abstract": "This dataset consists of a global collection of land surface air temperature data from meteorological stations covering the period from 1850-2015. It has been compiled as part of the European Union Horizon 2020 EUSTACE (EU Surface Temperature for All Corners of Earth) project.\r\n\r\nThe dataset provides daily maximum and minimum temperatures from stations globally, brought together from a number of public databases: Global Historical Climatology Network Daily Temperatures (GHCN-D); European Climate Assessment & Dataset (ECA&D) non-blended; International Surface Temperature Initiative (ISTI); DECADE (Data on Climate and Extreme weather for the Central Andes); and ERA-CLIM (European Reanalysis of Global Climate Observations). These data have then been quality controlled through the removal of duplicates and unreliable data sources, and come with a large amount of additional information on quality, homogeneity and resolution.\r\n\r\nThis data is available for non-commercial use." } }, { "ob_id": 353, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30588, "uuid": "aeae1a19608347f7b802691db6984343", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global ocean colour data products gridded on a geographic projection (All Products), Version 4.2", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 4.2 generated ocean colour products on a geographic projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Data are also available as monthly climatologies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, "objectObservation": { "ob_id": 27806, "uuid": "175105e9c36b49d7b98ebf43579c5cdd", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global ocean colour data products gridded on a geographic projection (All Products), Version 4.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 4.0 generated ocean colour products on a geographic projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Data are also available as monthly climatologies.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." } }, { "ob_id": 354, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30590, "uuid": "51fc11a9438b466db2ec8bd098efe7d5", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global remote sensing reflectance gridded on a geographic projection, Version 4.2", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 4.2 Remote Sensing Reflectance product on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data. Note, this dataset is also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, "objectObservation": { "ob_id": 27805, "uuid": "f56fe5c95e374c1fbaa73dcca8144787", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global remote sensing reflectance gridded on a geographic projection, Version 4.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 4.0 Remote Sensing Reflectance product on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data. Note, this dataset is also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." } }, { "ob_id": 355, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30592, "uuid": "88c2bc7af4f0402d8ceecad611c58cc5", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global dataset of inherent optical properties (IOP) gridded on a geographic projection, Version 4.2", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 4.2 inherent optical properties (IOP) product (in mg/m3) on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, this the IOP data is also included in the 'All Products' dataset. \r\n\r\nThe inherent optical properties (IOP) dataset consists of the total absorption and particle backscattering coefficients, and, additionally, the fraction of detrital & dissolved organic matter absorption and phytoplankton absorption. The total absorption (units m-1), the total backscattering (m-1), the absorption by detrital and coloured dissolved organic matter, the backscattering by particulate matter, and the absorption by phytoplankton share the same spatial resolution of ~4 km. The values of IOP are reported for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm). \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, "objectObservation": { "ob_id": 27804, "uuid": "b9269d708e3e413fba6fbf7cb3419b3a", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global dataset of inherent optical properties (IOP) gridded on a geographic projection, Version 4.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 4.0 inherent optical properties (IOP) product (in mg/m3) on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, this the IOP data is also included in the 'All Products' dataset. \r\n\r\nThe inherent optical properties (IOP) dataset consists of the total absorption and particle backscattering coefficients, and, additionally, the fraction of detrital & dissolved organic matter absorption and phytoplankton absorption. The total absorption (units m-1), the total backscattering (m-1), the absorption by detrital and coloured dissolved organic matter, the backscattering by particulate matter, and the absorption by phytoplankton share the same spatial resolution of ~4 km. The values of IOP are reported for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm). \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." } }, { "ob_id": 356, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30594, "uuid": "5400de38636d43de9808bfc0b500e863", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global chlorophyll-a data products gridded on a geographic projection, Version 4.2", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 4.2 chlorophyll-a product (in mg/m3) on a geographic projection at 4 km spatial resolution and at number of time resolutions (daily, 5day, 8day and monthly composites). Note, this chlor_a data is also included in the 'All Products' dataset. \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, "objectObservation": { "ob_id": 27803, "uuid": "eef36ac7c892491aa862097e79827f68", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global chlorophyll-a data products gridded on a geographic projection, Version 4.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 4.0 chlorophyll-a product (in mg/m3) on a geographic projection at 4 km spatial resolution and at number of time resolutions (daily, 5day, 8day and monthly composites). Note, this chlor_a data is also included in the 'All Products' dataset. \r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." } }, { "ob_id": 357, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30596, "uuid": "db32212d86f9431dae67076dd122565e", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a geographic projection, Version 4.2", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 4.2 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). It is computed from the Ocean Colour CCI Version 4.2 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, these data are also contained within the 'All Products' dataset.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, "objectObservation": { "ob_id": 27802, "uuid": "6f891faf986349f792043ebac64f7938", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a geographic projection, Version 4.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 4.0 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a geographic projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). It is computed from the Ocean Colour CCI Version 4.0 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, these data are also contained within the 'All Products' dataset.\r\n\r\nThis data product is on a geographic grid projection, which is a direct conversion of latitude and longitude coordinates to a rectangular grid, typically a fixed multiplier of 360x180. The netCDF files follow the CF convention for this projection with a resolution of 8640x4320. (A separate dataset is also available for data on a sinusoidal projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." } }, { "ob_id": 358, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30604, "uuid": "07eeca6888c645d89a7ef91de0290eca", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a sinusoidal projection, Version 4.2", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 4.2 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). It is computed from the Ocean Colour CCI Version 4.2 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, these data are also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, "objectObservation": { "ob_id": 27797, "uuid": "3200894e4add4049b31f8df132c0d664", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global attenuation coefficient for downwelling irradiance (Kd490) gridded on a sinusoidal projection, Version 4.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 4.0 Kd490 attenuation coefficient (m-1) for downwelling irradiance product on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). It is computed from the Ocean Colour CCI Version 4.0 inherent optical properties dataset at 490 nm and the solar zenith angle. Note, these data are also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." } }, { "ob_id": 359, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30603, "uuid": "99348189bd33459cbd597a58c30d8d10", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global chlorophyll-a data products gridded on a sinusoidal projection, Version 4.2", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 4.2 chlorophyll-a product (in mg/m3) on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, the chlorophyll-a data are also included in the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, "objectObservation": { "ob_id": 27798, "uuid": "fa199424852d49f4ba85afddd850eae6", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global chlorophyll-a data products gridded on a sinusoidal projection, Version 4.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 4.0 chlorophyll-a product (in mg/m3) on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, the chlorophyll-a data are also included in the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." } }, { "ob_id": 360, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30602, "uuid": "d6d0d7b4cf3540448b4ddcaed2f54b81", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global remote sensing reflectance gridded on a sinusoidal projection, Version 4.2", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 4.2 Remote Sensing Reflectance product on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data. Note, these data are also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, "objectObservation": { "ob_id": 27800, "uuid": "846a55c8a91b43bba6f3b97aa3e776e2", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global remote sensing reflectance gridded on a sinusoidal projection, Version 4.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains the Version 4.0 Remote Sensing Reflectance product on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Values for remote sensing reflectance at the sea surface are provided for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm) with pixel-by-pixel uncertainty estimates for each wavelength. These are merged products based on SeaWiFS, MERIS and Aqua-MODIS data. Note, these data are also contained within the 'All Products' dataset. \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection).\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." } }, { "ob_id": 361, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30600, "uuid": "1f84f9465e65416ca45cd20bc415b522", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global dataset of inherent optical properties (IOP) gridded on a sinusoidal projection, Version 4.2", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 4.2 inherent optical properties (IOP) product (in mg/m3) on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, the IOP data are also included in the 'All Products' dataset. \r\n\r\nThe inherent optical properties (IOP) dataset consists of the total absorption and particle backscattering coefficients, and, additionally, the fraction of detrital & dissolved organic matter absorption and phytoplankton absorption. The total absorption (units m-1), the total backscattering (m-1), the absorption by detrital and coloured dissolved organic matter, the backscattering by particulate matter, and the absorption by phytoplankton share the same spatial resolution of ~4 km. The values of IOP are reported for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm). \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, "objectObservation": { "ob_id": 27799, "uuid": "8fd7c9c728104c209fd88604c2022f26", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global dataset of inherent optical properties (IOP) gridded on a sinusoidal projection, Version 4.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains their Version 4.0 inherent optical properties (IOP) product (in mg/m3) on a sinusoidal projection at approximately 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). Note, the IOP data are also included in the 'All Products' dataset. \r\n\r\nThe inherent optical properties (IOP) dataset consists of the total absorption and particle backscattering coefficients, and, additionally, the fraction of detrital & dissolved organic matter absorption and phytoplankton absorption. The total absorption (units m-1), the total backscattering (m-1), the absorption by detrital and coloured dissolved organic matter, the backscattering by particulate matter, and the absorption by phytoplankton share the same spatial resolution of ~4 km. The values of IOP are reported for the standard SeaWiFS wavelengths (412, 443, 490, 510, 555, 670nm). \r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." } }, { "ob_id": 362, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30598, "uuid": "aab98144131244f58ce1b56e7342ff3e", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global ocean colour data products gridded on a sinusoidal projection (All Products), Version 4.2", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 4.2 generated ocean colour products on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). \r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." }, "objectObservation": { "ob_id": 27801, "uuid": "b0b9fb9cd7434323b65bbe1dae0a2e94", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Global ocean colour data products gridded on a sinusoidal projection (All Products), Version 4.0", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains all their Version 4.0 generated ocean colour products on a sinusoidal projection at 4 km spatial resolution and at a number of time resolutions (daily, 5-day, 8-day and monthly composites). \r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nThis data product is on a sinusoidal equal-area grid projection, matching the NASA standard level 3 binned projection. The default number of latitude rows is 4320, which results in a vertical bin cell size of approximately 4 km. The number of longitude columns varies according to the latitude, which permits the equal area property. Unlike the NASA format, where the bin cells that do not contain any data are omitted, the CCI format retains all cells and simply marks empty cells with a NetCDF fill value. (A separate dataset is also available for data on a geographic projection.)\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." } }, { "ob_id": 363, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27640, "uuid": "b382ebe6679d44b8b0e68ea4ef4b701c", "short_code": "ob", "title": "ESA Land Cover Climate Change Initiative (Land_Cover_cci): Global Land Cover Maps, Version 2.0.7", "abstract": "As part of the ESA Land Cover Climate Change Initiative (CCI) project a new set of Global Land Cover Maps have been produced. These maps are available at 300m spatial resolution for each year between 1992 and 2015.\r\n\r\nEach pixel value corresponds to the classification of a land cover class defined based on the UN Land Cover Classification System (LCCS). The reliability of the classifications made are documented by the four quality flags (decribed further in the Product User Guide) that accompany these maps. Data are provided in both NetCDF and GeoTiff format.\r\n\r\nFurther Land Cover CCI products, user tools and a product viewer are available at: http://maps.elie.ucl.ac.be/CCI/viewer/index.php . Maps for the 2016-2020 time period have been produced in the context of the Copernicus Climate Change service, and can be downloaded from the Copernicus Climate Data Store (CDS)." }, "objectObservation": { "ob_id": 14427, "uuid": "4761751d7c844e228ec2f5fe11b2e3b0", "short_code": "ob", "title": "ESA Land Cover Climate Change Initiative (Land_Cover_cci): Global Land Cover Maps, Version 1.6.1", "abstract": "As part of the ESA Land Cover Climate Change Initiative (CCI) project a set of Global Land Cover Maps have been produced. These are available at 300m spatial resolution for three epochs centred on the year 2010 (2008-2012), 2005 (2003-2007) and 2000 (1998-2002), where each epoch covers a 5-year period.\r\n\r\nEach pixel value corresponds to the label of a land cover class defined using UN-LCCS classifiers. For each epoch, the land cover map is delivered along with 4 quality flags which document the reliability of the classification. These are described further in the Product User Guides.\r\n\r\nFurther Land Cover CCI products, user tools and a product viewer are available at: http://maps.elie.ucl.ac.be/CCI/viewer/index.php" } }, { "ob_id": 364, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31791, "uuid": "2e656d34d016414c8d6bced18634772c", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol_cci): Level 3 aerosol products from the Multi-Sensor UV Absorbing Aerosol Index (MS UVAI) algorithm, Version 1.7", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. This dataset comprises Level 3 Absorbing Aerosol Index (AAI) products, using the Multi-Sensor UVAI algorithm, Version 1.7. L3 products are provided as daily and monthly gridded products as well as a monthly climatology. \r\n\r\nFor further details about these data products please see the linked documentation." }, "objectObservation": { "ob_id": 19106, "uuid": "828e521e9ebe4df896341736bff0f369", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from the Multi-Sensor UVAI algorithm (MS UVAI), Version 1.5.7", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises Level 3 Absorbing Aerosol Index (AAI) products, using the Multi-Sensor UVAI algorithm, Version 1.5.7. L3 products are provided as Daily and Monthly gridded products as well as a monthly climatology. \r\n\r\nFor further details about these data products please see the linked documentation." } }, { "ob_id": 365, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 19106, "uuid": "828e521e9ebe4df896341736bff0f369", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from the Multi-Sensor UVAI algorithm (MS UVAI), Version 1.5.7", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises Level 3 Absorbing Aerosol Index (AAI) products, using the Multi-Sensor UVAI algorithm, Version 1.5.7. L3 products are provided as Daily and Monthly gridded products as well as a monthly climatology. \r\n\r\nFor further details about these data products please see the linked documentation." }, "objectObservation": { "ob_id": 13328, "uuid": "337661f6cb6a438ea305869ae00463fb", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol monthly products (MS UVAI algorithm), Version 1.4.7", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises monthly products of Absorbing Aerosol Index (AAI), produced using the Multi-Sensor UVAI algorithm, Version 1.4.7. \r\n\r\nFor further details about these data products please see the documentation section." } }, { "ob_id": 366, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 19106, "uuid": "828e521e9ebe4df896341736bff0f369", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from the Multi-Sensor UVAI algorithm (MS UVAI), Version 1.5.7", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises Level 3 Absorbing Aerosol Index (AAI) products, using the Multi-Sensor UVAI algorithm, Version 1.5.7. L3 products are provided as Daily and Monthly gridded products as well as a monthly climatology. \r\n\r\nFor further details about these data products please see the linked documentation." }, "objectObservation": { "ob_id": 13326, "uuid": "f15aa17184884515a860a92634aa73ff", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol daily products (MS UVAI algorithm), Version 1.4.7", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises daily Level 3 Absorbing Aerosol Index (AAI) products, using the Multi-Sensor UVAI algorithm, Version 1.4.7. \r\n\r\nFor further details about these data products please see the linked documentation." } }, { "ob_id": 367, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 19106, "uuid": "828e521e9ebe4df896341736bff0f369", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from the Multi-Sensor UVAI algorithm (MS UVAI), Version 1.5.7", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises Level 3 Absorbing Aerosol Index (AAI) products, using the Multi-Sensor UVAI algorithm, Version 1.5.7. 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It covers the period from 1995-2003.\r\n\r\nFor further details about these data products please see the linked documentation." }, "objectObservation": { "ob_id": 19134, "uuid": "c4d4c347455341aa938bedfefa2964a1", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from ATSR2 (ADV algorithm), Version 2.30", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol products from ATSR-2, using the ADV algorithm, version 2.30. Both daily and monthly gridded products are available\r\n\r\nFor further details about these data products please see the linked documentation." } }, { "ob_id": 388, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27685, "uuid": "a7e11745933a4f37b5aa1d4b23d71a83", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol_cci): Level 2 aerosol products from ATSR-2 (ADV algorithm), Version 2.31", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. This dataset comprises Level 2 aerosol products from the ATSR-2 instrument on the ERS-2 satellite, derived using the ADV algorithm, version 2.31. Data are available for the period 1995-2002.\r\n\r\nFor further details about these data products please see the linked documentation." }, "objectObservation": { "ob_id": 19128, "uuid": "9659f50c3cc34a1e9f017ccba69dbe5c", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 2 aerosol products from ATSR2 (ADV algorithm), Version 2.30", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 2 aerosol products from ATSR-2, using the ADV algorithm, version 2.30. \r\n\r\nFor further details about these data products please see the linked documentation." } }, { "ob_id": 389, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 27692, "uuid": "7fb8fd2761484b1eae4f7df4a3e65f75", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol_cci): Level 3 aerosol products from GOMOS (AERGOM algorithm), Version 3.00", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. This dataset comprises Level 3 gridded stratospheric aerosol properties from the GOMOS instrument on the ENVISAT satellite. This version of the data is version 3.00, and has been derived using the AERGOM algorithm by BIRA (Belgian Institute for Space Aeronomy). \r\n\r\nFor further details about these data products please see the linked documentation." }, "objectObservation": { "ob_id": 19112, "uuid": "91a7029627754d60912e58255b686836", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from GOMOS (AERGOM algorithm), Version 2.19", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol monthly products from GOMOS, using the AERGOM algorithm, version 2.19 and was produced by BIRA (Belgian Institute for Space Aeronomy). \r\n\r\nThe data are stored as 5 day averages and standard deviations of a range of aerosol variables, on global 2.5 degree x 10 degree latitutude/longitude grids, and in NetCDF format. The horizontal resolution is 0.5km. \r\n\r\nThe variables included are: Stratospheric Aerosol Optical Depth (AOD), Angstrom coefficient, extinction profile. \r\n\r\n\r\nFor further details about these data products please see the linked documentation." } }, { "ob_id": 390, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 19112, "uuid": "91a7029627754d60912e58255b686836", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol products from GOMOS (AERGOM algorithm), Version 2.19", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol monthly products from GOMOS, using the AERGOM algorithm, version 2.19 and was produced by BIRA (Belgian Institute for Space Aeronomy). \r\n\r\nThe data are stored as 5 day averages and standard deviations of a range of aerosol variables, on global 2.5 degree x 10 degree latitutude/longitude grids, and in NetCDF format. The horizontal resolution is 0.5km. \r\n\r\nThe variables included are: Stratospheric Aerosol Optical Depth (AOD), Angstrom coefficient, extinction profile. \r\n\r\n\r\nFor further details about these data products please see the linked documentation." }, "objectObservation": { "ob_id": 13316, "uuid": "67a411e3fa24477eab54500519af4514", "short_code": "ob", "title": "ESA Aerosol Climate Change Initiative (Aerosol CCI): Level 3 aerosol monthly products from GOMOS (AERGOM algorithm), Version 2.1", "abstract": "The ESA Climate Change Initiative Aerosol project has produced a number of global aerosol Essential Climate Variable (ECV) products from a set of European satellite instruments with different characteristics. \r\n\r\nThis dataset comprises the Level 3 aerosol monthly products from GOMOS, using the AERGOM algorithm, version 2.1 and was produced by BIRA (Belgian Institute for Space Aeronomy). \r\n\r\nThe data are stored as monthly averages and standard deviations of a range of aerosol variables, on global 2.5 degree x 10 degree latitutude/longitude grids, and in NetCDF format. The horizontal resolution is 0.5km. \r\n\r\nThe variables included are: Stratospheric Aerosol Optical Depth (AOD), Angstrom coefficient, extinction profile. \r\n\r\n\r\nFor further details about these data products please see the linked documentation." } }, { "ob_id": 391, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30644, "uuid": "eacb7580e1b54afeaabb0fd2b0a53828", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Weekly sea surface salinity product, v2.31, for 2010 to 2019", "abstract": "The ESA Sea Surface Salinity CCI consortium has produced global, level 4, multi-sensor Sea Surface Salinity maps covering the 2010-2019 period.\r\n\r\nThis dataset contains Sea Surface Salinity (SSS) v2.31 data at a spatial resolution of 50 km and a time resolution of 1 week. It has been spatially sampled on a 25 km EASE (Equal Area Scalable Earth) grid and 1 day of time sampling. A monthly product is also available. In addition to salinity, information on errors are provided (see more in the user guide and product documentation available below and on the Sea Surface Salinity CCI web page).\r\n\r\nAn overview paper about CCI SSS is now published:\r\n\r\nBoutin, J., N. Reul, J. Koehler, A. Martin, R. Catany, S. Guimbard, F. Rouffi, et al. (2021), Satellite-Based Sea Surface Salinity Designed for Ocean and Climate Studies, Journal of Geophysical Research: Oceans, 126(11), e2021JC017676, doi:https://doi.org/10.1029/2021JC017676.\r\n\r\nAn updated version of CCI SSS (version 3.21) is now available on: https://catalogue.ceda.ac.uk/uuid/5920a2c77e3c45339477acd31ce62c3c ; version 3 SSS and associated uncertainties are more precise and cover a longer period (Jan 2010-sept 2020); version 3 SSS are provided closer to land than version 2 SSS, with a possible degraded quality. Users might remove these additional near land data by using the lsc_qc flag." }, "objectObservation": { "ob_id": 28123, "uuid": "e5666094722c4ca787e323a9585b0a92", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Weekly Sea Surface Salinity product v1.8", "abstract": "This dataset provides Sea Surface Salinity (SSS) data derived as part of the European Space Agency (ESA) Climate Change Initiative (CCI) programme. In this product the data has been produced at a spatial resolution of 50km and a time resolution of 1 week. This has then been spatially resampled on a 25km EASE (Equal Area Scalable Earth) grid and 1 day of time sampling. A monthly product is also available.\r\n\r\nThis first version of the CCI+SSS products is a preliminary version issued for evaluation purposes by voluntary scientists and for framing future CCI+SSS products. This product has not been fully validated yet and may contain flaws. In case you discover some, the CCI salinity team (Mngt_CCI-Salinity@argans.co.uk) are very keen to get your feedback. In case you would like to use them in a presentation or publication, please be aware of the following caveats:\r\n\r\nCAVEATS\r\n\r\n- The SSS random error in the weekly product is overestimated by a factor ~1.4. \r\n- The Number of outliers is wrongly set to 'NaN' in the case where it is equal to zero. \r\n- Products have not yet been not optimised for some issues encountered at high latitudes (i.e. remaining ice, RFI pollution, biases due to land-sea contamination and dielectric constant in cold waters).\r\n- The criteria for flagging data close to land (including islands) are conservative and likely to be too restrictive in places. \r\n- There is a systematic global underestimation (-0.08) of SSS starting at the beginning of the data set, and gradually disappearing at the end of 2010.\r\n- There is a seasonal varying bias (~0.1, peaking in the middle of the year) in the Pacific North of 25°N.\r\n\r\nAcknowledgements: The authors thank the CCI+ SSS validation team, in particular S. Guimbard (ODL) and A. Martin (NOC), for their feedback on the products, R. Catany (ARGANS) for managing the project and P. Cipollini and C. Donlon (ESA) for their sound advice." } }, { "ob_id": 392, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 30645, "uuid": "7813eb75a131474a8d908f69c716b031", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Monthly sea surface salinity product, v2.31, for 2010 to 2019", "abstract": "The ESA Sea Surface Salinity CCI consortium has produced global, level 4, multi-sensor Sea Surface Salinity maps covering the 2010-2019 period.\r\n\r\nThis dataset provides Sea Surface Salinity (SSS) data at a spatial resolution of 25 km and a time resolution of 1 month. This has been spatially sampled on a 25 km EASE (Equal Area Scalable Earth) grid and 15 days of time sampling. A weekly product is also available. In addition to salinity, information on errors are provided (see more in the user guide and product documentation available below and on the Sea Surface Salinity CCI web page).\r\n\r\nAn overview paper about CCI SSS is now published:\r\n\r\nBoutin, J., N. Reul, J. Koehler, A. Martin, R. Catany, S. Guimbard, F. Rouffi, et al. (2021), Satellite-Based Sea Surface Salinity Designed for Ocean and Climate Studies, Journal of Geophysical Research: Oceans, 126(11), e2021JC017676, doi:https://doi.org/10.1029/2021JC017676.\r\n\r\nAn updated version of CCI SSS (version 3.21) is now available on: https://catalogue.ceda.ac.uk/uuid/5920a2c77e3c45339477acd31ce62c3c ; version 3 SSS and associated uncertainties are more precise and cover a longer period (Jan 2010-sept 2020); version 3 SSS are provided closer to land than version 2 SSS, with a possible degraded quality. Users might remove these additional near land data by using the lsc_qc flag." }, "objectObservation": { "ob_id": 28233, "uuid": "aea368301bff448bbbea7e90e66819e5", "short_code": "ob", "title": "ESA Sea Surface Salinity Climate Change Initiative (Sea_Surface_Salinity_cci): Monthly Sea Surface Salinity product v1.8", "abstract": "This dataset provides monthly Sea Surface Salinity (SSS) data derived as part of the European Space Agency (ESA) Climate Change Initiative (CCI) programme. In this product the data has been produced at a spatial resolution of 25km and a time resolution of 1 month. This has then been spatially resampled on a 25km EASE (Equal Area Scalable Earth) grid and 15 days of time sampling. A monthly product is also available.\r\n\r\nThis first version of the CCI+SSS products is a preliminary version issued for evaluation purposes by voluntary scientists and for framing future CCI+SSS products. This product has not been fully validated yet and may contain flaws. In case you discover some, the CCI salinity team (Mngt_CCI-Salinity@argans.co.uk) are very keen to get your feedback. In case you would like to use them in a presentation or publication, please be aware of the following caveats:\r\n\r\nCAVEATS\r\n\r\n- The SSS random error in the weekly product is overestimated by a factor ~1.4. \r\n- The Number of outliers is wrongly set to 'NaN' in the case where it is equal to zero. \r\n- Products have not yet been not optimised for some issues encountered at high latitudes (i.e. remaining ice, RFI pollution, biases due to land-sea contamination and dielectric constant in cold waters).\r\n- The criteria for flagging data close to land (including islands) are conservative and likely to be too restrictive in places. \r\n- There is a systematic global underestimation (-0.08) of SSS starting at the beginning of the data set, and gradually disappearing at the end of 2010.\r\n- There is a seasonal varying bias (~0.1, peaking in the middle of the year) in the Pacific North of 25°N.\r\n\r\nAcknowledgements: The authors thank the CCI+ SSS validation team, in particular S. Guimbard (ODL) and A. Martin (NOC), for their feedback on the products, R. Catany (ARGANS) for managing the project and P. Cipollini and C. Donlon (ESA) for their sound advice." } }, { "ob_id": 393, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31889, "uuid": "064f3a982cfc4b07bc5de627cd8676f1", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v202007", "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 2019. 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. Of particular note, however, is that as well as including data for 2019, historical data recovery has added temperature and weather data for Bude (1937-1958), Teignmouth (1912-1930), and Eskdalemuir (1915-1948).\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": 27815, "uuid": "b37382e8c1e74b849831a5fa13afdcae", "short_code": "ob", "title": "MIDAS Open: UK daily temperature data, v201908", "abstract": "The UK daily temperature data contain maximum and minimum temperatures (air, grass and concrete slab) measured over a period of up to 24 hours. The measurements were recorded by observation stations operated by the Met Office across the UK and transmitted within NCM, DLY3208 or AWSDLY messages. The data span from 1853 to 2018. For details on measurement techniques, including calibration information and changes in measurements, see section 5.2 of the MIDAS User Guide linked to from this record. Soil temperature data may be found in the UK soil temperature datasets linked from this record.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily temperature observations within the full MIDAS collection." } }, { "ob_id": 394, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31888, "uuid": "77187ac1e0a341ca993c3366f8c59c3c", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v202007", "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 2019.\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": 27822, "uuid": "a58b9c8a724e4ec795a40a74455462b7", "short_code": "ob", "title": "MIDAS Open: UK hourly rainfall data, v201908", "abstract": "The UK hourly rainfall data contain the rainfall amount (and duration from tilting syphon gauges) during the hour (or hours) ending at the specified time. The data also contains precipitation amounts, however precipitation measured over 24 hours are not stored. Over time a range of rain gauges have been used - see the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSHRLY, DLY3208, SREW and SSER. The data spans from 1915 to 2018.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset." } }, { "ob_id": 395, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31887, "uuid": "ec9e894089434b03bd9532d7b343ec4b", "short_code": "ob", "title": "MIDAS Open: UK daily rainfall data, v202007", "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 2019. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection." }, "objectObservation": { "ob_id": 27817, "uuid": "cb47cc464c5a41de8c718d117437b4e6", "short_code": "ob", "title": "MIDAS Open: UK daily rainfall data, v201908", "abstract": "The UK daily rainfall data contain rainfall accumulation and precipitation amounts over a 24 hour period. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: NCM, AWSDLY, DLY3208 and SSER. The data spans from 1853 to 2018. Over time a range of rain gauges have been used - see section 5.6 and the relevant message type information in the linked MIDAS User Guide for further details.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. A large proportion of the UK raingauge observing network (associated with WAHRAIN, WADRAIN and WAMRAIN for hourly, daily and monthly rainfall measurements respectively) is operated by other agencies beyond the Met Office, and are consequently currently excluded from the Midas-open dataset. Currently this represents approximately 13% of available daily rainfall observations within the full MIDAS collection." } }, { "ob_id": 396, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31890, "uuid": "1dc8578eb7434a7d8a661744d53eedf9", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v202007", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2019.\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": 27819, "uuid": "d6bbe115245042dc93ee68caa253d60b", "short_code": "ob", "title": "MIDAS Open: UK hourly solar radiation data, v201908", "abstract": "The UK hourly solar radiation data contain the amount of solar irradiance received during the hour ending at the specified time. All sites report 'global' radiation amounts. This is also known as 'total sky radiation' as it includes both direct solar irradiance and 'diffuse' irradiance as a result of light scattering. Some sites also provide separate diffuse and direct irradiation amounts, depending on the instrumentation at the site. For these the sun's path is tracked with two pyrometers - one where the path to the sun is blocked by a suitable disc to allow the scattered sunlight to be measured to give the diffuse measurement, while the other has a tube pointing at the sun to measure direct solar irradiance whilst blanking out scattered sun light.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThe data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, MODLERAD, ESAWRADT and DRADR35 messages. The data spans from 1947 to 2018.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." } }, { "ob_id": 397, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31885, "uuid": "f7e09e89de234c15964a4cc7a75f3f74", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v202007", "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 2019.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nFor further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." }, "objectObservation": { "ob_id": 27820, "uuid": "ddcfd8bb1ff44cd2855e81838b40b17c", "short_code": "ob", "title": "MIDAS Open: UK mean wind data, v201908", "abstract": "The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2018.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nFor further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record." } }, { "ob_id": 398, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31884, "uuid": "f8612c43a1244fda9463787313d3892a", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v202007", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1889 to 2019. 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. Of particular note, however, is that as well as including data for 2019, historical data recovery has added temperature and weather data for Bude (1937-1958), Teignmouth (1912-1930), and Eskdalemuir (1915-1948).\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": 27816, "uuid": "6ad6792f44c84c228651b01d182d9d73", "short_code": "ob", "title": "MIDAS Open: UK daily weather observation data, v201908", "abstract": "The UK daily weather observation data contain meteorological values measured on a 24 hour time scale. The measurements of sunshine duration, concrete state, snow depth, fresh snow depth, and days of snow, hail, thunder and gail were attained by observation stations operated by the Met Office across the UK operated and transmitted within DLY3208, NCM, AWSDLY and SYNOP messages. The data span from 1889 to 2018. For details of observations see the relevant sections of the MIDAS User Guide linked from this record for the various message types.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Currently this represents approximately 95% of available daily weather observations within the full MIDAS collection." } }, { "ob_id": 399, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31883, "uuid": "8d85f664fc614ba0a28af3a2d7ef4533", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v202007", "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 2019.\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. Of particular note, however, is that as well as including data for 2019, historical data recovery has added temperature and weather data for Bude (1937-1958), Teignmouth (1912-1930), and Eskdalemuir (1915-1948).\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": 27818, "uuid": "6c441aea187b44819b9e929e575b0d7e", "short_code": "ob", "title": "MIDAS Open: UK hourly weather observation data, v201908", "abstract": "The UK hourly weather observation data contain meteorological values measured on an hourly time scale. The measurements of the concrete state, wind speed and direction, cloud type and amount, visibility, and temperature were recorded by observation stations operated by the Met Office across the UK and transmitted within SYNOP, DLY3208, AWSHRLY and NCM messages. The sunshine duration measurements were transmitted in the HSUN3445 message. The data spans from 1875 to 2018.\r\n\r\nThis version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data.\r\n\r\nFor details on observing practice see the message type information in the MIDAS User Guide linked from this record and relevant sections for parameter types.\r\n\r\nThis dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record. Note, METAR message types are not included in the Open version of this dataset. Those data may be accessed via the full MIDAS hourly weather data." } }, { "ob_id": 400, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31903, "uuid": "e091188f36ff41fcae8c30da1ae77ea0", "short_code": "ob", "title": "HadUK-Grid Climate Observations by Administrative Regions over the UK, v1.0.2.1 (1862-2019)", "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 1862 to 2019, 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. (2018, see linked documentation).\r\n\r\nFor this version of note is that historical data recovery has improved monthly rainfall 1862-1910, daily rainfall 1883-1910, monthly temperature 1900-1909, and additional sunshine grids for 1919-1928 have been added.\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 28141, "uuid": "e4d28cddec7b4e1ab50eae189070f7dc", "short_code": "ob", "title": "HadUK-Grid Climate Observations by Administrative Regions over the UK, v1.0.1.0 (1862-2018)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. These data at 1km resolution have been averaged across a set of discrete geographies defining UK administrative regions consistent with data from UKCP18 climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." } }, { "ob_id": 401, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31904, "uuid": "df33c78736a44019b8ceb20ab440cae1", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 60km grid over the UK, v1.0.2.1 (1862-2019)", "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 1862 to 2019, 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. (2018, see linked documentation).\r\n\r\nFor this version of note is that historical data recovery has improved monthly rainfall 1862-1910, daily rainfall 1883-1910, monthly temperature 1900-1909, and additional sunshine grids for 1919-1928 have been added.\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 28140, "uuid": "75f2c9746d8245b29ad80c04a6a202fd", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 60km grid over the UK, v1.0.1.0 (1862-2018)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The data set at 60 km resolution is derived from the associated 1km x 1km resolution to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." } }, { "ob_id": 402, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31905, "uuid": "725e1339c06344cc813e4cb123c12f81", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 25km grid over the UK, v1.0.2.1 (1862-2019)", "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 1862 to 2019, 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. (2018, see linked documentation).\r\n\r\nFor this version of note is that historical data recovery has improved monthly rainfall 1862-1910, daily rainfall 1883-1910, monthly temperature 1900-1909, and additional sunshine grids for 1919-1928 have been added.\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 28139, "uuid": "e84aabcd886c41c488b4bd84558ab974", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 25km grid over the UK, v1.0.1.0 (1862-2018)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The data set at 25 km resolution is derived from the associated 1km x 1km resolution to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." } }, { "ob_id": 403, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31906, "uuid": "1bea761180674b9f9b1830f9aabfac15", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 12km grid over the UK, v1.0.2.1 (1862-2019)", "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 1862 to 2019, 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. (2018, see linked documentation). \r\n\r\nFor this version of note is that historical data recovery has improved monthly rainfall 1862-1910, daily rainfall 1883-1910, monthly temperature 1900-1909, and additional sunshine grids for 1919-1928 have been added. Additionally, this version has corrected the grid definition used for the 12 km grid product to match UKCP18 climate model products.\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 28138, "uuid": "8929d37209c24f44ba33a5e11910c363", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 12km grid over the UK, v1.0.1.0 (1862-2018)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The data set at 12 km resolution is derived from the associated 1km x 1km resolution to allow for comparison to data from climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." } }, { "ob_id": 404, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31907, "uuid": "89908dfcb97b4a28976df806b4818639", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.0.2.1 (1862-2019)", "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 1862 to 2019, 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. (2018, see linked documentation).\r\n\r\nFor this version of note is that historical data recovery has improved monthly rainfall 1862-1910, daily rainfall 1883-1910, monthly temperature 1900-1909, and additional sunshine grids for 1919-1928 have been added.\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 28137, "uuid": "d134335808894b2bb249e9f222e2eca8", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 1km grid over the UK, v1.0.1.0 (1862-2018)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The data sets cover the UK at 1km x 1km resolution. These 1km x 1km data have been used to provide a range of other resolutions and across countries, administrative regions and river basins to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." } }, { "ob_id": 405, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31908, "uuid": "2fd7c824e7e549809c1bc6a128ad74db", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 5km grid over the UK, v1.0.2.1 (1862-2019)", "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 1862 to 2019, 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. (2018, see linked documentation).\r\n\r\nFor this version of note is that historical data recovery has improved monthly rainfall 1862-1910, daily rainfall 1883-1910, monthly temperature 1900-1909, and additional sunshine grids for 1919-1928 have been added.\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 28144, "uuid": "d715d2ac53f14f21acc6952a0278817d", "short_code": "ob", "title": "HadUK-Grid Gridded Climate Observations on a 5km grid over the UK, v1.0.1.0 (1862-2018)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. The data set at 5 km resolution is derived from the associated 1km x 1km resolution to allow for comparison to data from UKCP18 climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." } }, { "ob_id": 406, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31901, "uuid": "4f165fc3b96b430fb6e35b859758c9ce", "short_code": "ob", "title": "HadUK-Grid Climate Observations by UK countries, v1.0.2.1 (1862-2019)", "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 1862 to 2019, 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. (2018, see linked documentation).\r\n\r\nFor this version of note is that historical data recovery has improved monthly rainfall 1862-1910, daily rainfall 1883-1910, monthly temperature 1900-1909, and additional sunshine grids for 1919-1928 have been added.\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 28143, "uuid": "1715a1c03e544f47a3e803324f0bf4ca", "short_code": "ob", "title": "HadUK-Grid Climate Observations by UK countries, v1.0.1.0 (1862-2018)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. These data at 1km resolution have been averaged across a set of discrete geographies defining UK countries consistent with data from UKCP18 climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." } }, { "ob_id": 407, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31902, "uuid": "7d205e6cb7b4441eb3cdd5bbc4fd7829", "short_code": "ob", "title": "HadUK-Grid Climate Observations by UK river basins, v1.0.2.1 (1862-2019)", "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 1862 to 2019, 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. (2018, see linked documentation).\r\n\r\nFor this version of note is that historical data recovery has improved monthly rainfall 1862-1910, daily rainfall 1883-1910, monthly temperature 1900-1909, and additional sunshine grids for 1919-1928 have been added.\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." }, "objectObservation": { "ob_id": 28142, "uuid": "131fd45e37d74bcc82d9a6e12fc1d366", "short_code": "ob", "title": "HadUK-Grid Climate Observations by UK river basins, v1.0.1.0 (1862-2018)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. These data at 1km resolution have been averaged across a set of discrete geographies defining UK river basins consistent with data from UKCP18 climate projections. The dataset spans the period from 1862 to 2018, but the start time is dependent on climate variable and temporal resolution. The grids are produced for daily, monthly, seasonal and annual timescales, as well as long term averages for a set of climatological reference periods. Variables include air temperature (maximum, minimum and mean), precipitation, sunshine, mean sea level pressure, wind speed, relative humidity, vapour pressure, days of snow lying, and days of ground frost.\r\n\r\nThis data set supersedes the UKCP09 gridded observations and the earlier v1.0.0.0 version. Subsequent versions may be released in due course and will follow the version numbering as outlined by Hollis et al. (2018, see linked documentation).\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The data recovery activity to supplement 19th and early 20th Century data availability has also been funded by the Natural Environment Research Council (NERC grant ref: NE/L01016X/1) project \"Analysis of historic drought and water scarcity in the UK\". The dataset is provided under Open Government Licence." } }, { "ob_id": 408, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 31913, "uuid": "ef09d81517a84979ac60329e4859f449", "short_code": "ob", "title": "NCEO: Monthly global Particulate Organic Carbon (POC) (produced from the Ocean Colour Climate Change Initiative, Version 4.2 dataset)", "abstract": "The National Centre for Earth Observation (NCEO): Monthly global Particulate Organic Carbon (POC) dataset contains POC concentrations gridded on both sinusoidal (SIN) and geographic (GEO) grid projections at 4 km spatial resolution for 1997-2020. The POC dataset has been produced using the Ocean Colour Climate Change Initiative Remote Sensing Reflectance (Rrs) products, Version 4.2. The dataset includes the Rrs at 443 nm and 555 nm with pixel-by-pixel uncertainty estimates for each wavelength.\r\n\r\nFor more details on the algorithm and its validation, please see papers by Stramski et al. (2008) and Evers-King et al. (2017). Please note that the validation of the POC algorithm is a continuing process. To increase the accuracy of POC algorithms, further in situ POC data need to be collected with high spatial and temporal resolution." }, "objectObservation": { "ob_id": 30641, "uuid": "37e8a29d208d4a87ae4dbe1d16b2c0ef", "short_code": "ob", "title": "ESA Ocean Colour Climate Change Initiative (Ocean_Colour_cci): Monthly climatology of global ocean colour data products, Version 4.2", "abstract": "The ESA Ocean Colour CCI project has produced global level 3 binned multi-sensor time-series of satellite ocean-colour data with a particular focus for use in climate studies.\r\n\r\nThis dataset contains a monthly climatology of the generated ocean colour products.\r\n\r\nData products being produced include: phytoplankton chlorophyll-a concentration; remote-sensing reflectance at six wavelengths; total absorption and backscattering coefficients; phytoplankton absorption coefficient and absorption coefficients for dissolved and detrital material; and the diffuse attenuation coefficient for downwelling irradiance for light of wavelength 490nm. Information on uncertainties is also provided.\r\n\r\nPlease note, this dataset has been superseded. Later versions of the data are now available." } }, { "ob_id": 409, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31941, "uuid": "ee378533af6243899bc93653cbd41eaa", "short_code": "ob", "title": "HadEX3: Global land-surface climate extremes indices v3.0.1 (1901-2018)", "abstract": "HadEX3 is a land-surface dataset of climate extremes indices available on a 1.875 x 1.25 longitude-latitude grid. These 29 indices have been developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). Daily precipitation, as well as maximum and minimum temperature observations, are used to calculate these indices at each station. The daily data, as well as indices, have been supplied, quality controlled and combined to make a gridded set of NetCDF files covering 1901-2018 (inclusive). \r\n\r\nSpatial coverage is determined by the number of stations present at each time point as well as the spatial correlation structure between the stations for each index. The spatial coverage is lowest at the beginning of the dataset, rising until around 1960 where it plateaus, and then declines slightly after 2010.\r\n\r\nAll indices are available as annual quantities, with a subset also available on a monthly basis. A number of the indices use a reference period to determine thresholds. For these, we provide two versions, one set using 1961-1990 and another using the more recent 1981-2010 (these reference periods have been indicated in the file name as either 'ref-6190' or 'ref-8110').\r\n\r\nIn September 2020, a user identified some issues in the DTR and TN90p (61-90) indices. These were found to have arisen from erroneous values in a few stations which were not picked up by any quality control checks. These stations were noted on the bad list and these two indices re-run, hence v3.0.1." }, "objectObservation": { "ob_id": 31823, "uuid": "311f2fe74f4b4298be467f6622ded76b", "short_code": "ob", "title": "HadEX3: Global land-surface climate extremes indices v3.0.0 (1901-2018)", "abstract": "HadEX3 is a land-surface dataset of climate extremes indices available on a 1.875 x 1.25 longitude-latitude grid. These 29 indices have been developed by the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). Daily precipitation, as well as maximum and minimum temperature observations, are used to calculate these indices at each station. The daily data, as well as indices, have been supplied, quality controlled and combined to make a gridded set of NetCDF files covering 1901-2018 (inclusive). \r\n\r\nSpatial coverage is determined by the number of stations present at each time point as well as the spatial correlation structure between the stations for each index. The spatial coverage is lowest at the beginning of the dataset, rising until around 1960 where it plateaus, and then declines slightly after 2010.\r\n\r\nAll indices are available as annual quantities, with a subset also available on a monthly basis. A number of the indices use a reference period to determine thresholds. For these, we provide two versions, one set using 1961-1990 and another using the more recent 1981-2010 (these reference periods have been indicated in the file name as either 'ref-6190' or 'ref-8110')." } }, { "ob_id": 410, "relationType": "IsDerivedFrom", "subjectObservation": { "ob_id": 31825, "uuid": "a386504aa8ae492f9f2af04c109346e9", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): A database of coastal sea level anomalies and associated trends from Jason satellite altimetry from 2002 to 2018", "abstract": "This dataset contains 17-year-long (June 2002 to May 2018 ), high-resolution (20 Hz), along-track sea level dataset in coastal zones of six regions: Mediterranean Sea, Northeast Atlantic, West Africa, North Indian Ocean, Southeast Asia and Australia. Up to now, satellite altimetry has provided global gridded sea level time series up to 10-15 km from the coast only, preventing the estimation of how sea level changes very close to the coast on interannual to decadal time scales. \r\n\r\nThis dataset has been derived from the ESA SL_cci+ v1.1 dataset of coastal sea level anomalies (also available in the catalogue, DOI:10.5270/esa-sl_cci-xtrack_ales_sla-200206_201805-v1.1-202005), which is based on the reprocessing of raw radar altimetry waveforms from the Jason-1, Jason-2 and Jason-3 satellite missions to derive satellite-sea surface ranges as close as possible to the coast (a process called ‘retracking’) and optimization of the geophysical corrections applied to the range measurements to produce sea level time series. This large amount of coastal sea level estimates has been further analysed to produce the present dataset: it consists in a selection of 429 portions of satellite tracks crossing land for which valid sea level time series are provided at monthly interval together with the associated sea level trends over the 17-year time span at each along-track 20-Hz point, from 20 km offshore to the coast.\r\n\r\nThe main objective of this dataset is to analyze the sea level trends close to the coast and compare them with the sea level trends observed in the open ocean and to determine the causes of the potential differences.\r\n\r\nThe product has been developed within the sea level project of the extension phase of the European Space Agency (ESA) Climate Change Initiative (SL_cci+). See 'The Climate Change Coastal Sea Level Team (2020). Sea level anomalies and associated trends estimated from altimetry from 2002 to 2018 at selected coastal sites. Scientific Data (Nature), in press'.\r\n\r\nThis dataset has a DOI: https://doi.org/10.17882/74354" }, "objectObservation": { "ob_id": 31822, "uuid": "222cf11f49a94d2da8a6da239df2efc4", "short_code": "ob", "title": "ESA Sea Level Climate Change Initiative (Sea_Level_cci): Altimeter along-track high resolution sea level anomalies in some coastal regions (2002-2018) from the JASON satellites, v1.1", "abstract": "This dataset contains along-track sea level anomalies derived from satellite altimetry. Altimeter along-track sea level measurements from the Jason-1, Jason -2 and Jason-3 satellite missions have been processed to produce high resolution (20 Hz, corresponding to an along-track distance of ~300m) sea level anomalies, in order to provide long-term homogeneous sea level time series as close to the coast as possible in six different coastal regions (North-East Atlantic, Mediterranean Sea, Western Africa, North Indian Ocean, South-East Asia and Australia). These six time series cover the period from 15 January 2002 to 30 May 2018.\r\n\r\nThe product benefits from the spatial resolution provided by high-rate data, the Adaptive Leading Edge Subwaveform Retracker (ALES) and the post-processing strategy of the along-track (X-TRACK) algorithm, both developed for the processing of coastal altimetry data, as well as the best possible set of geophysical corrections. \r\n\r\nThe main objective of this product is to provide accurate altimeter Sea Level Anomalies (SLA) time series as close to the coast as possible in order to assess whether the coastal sea level trends experienced at the coast are similar to the observed sea level trends in the open ocean and to determine the causes of the potential discrepancies.\r\n\r\nThe product has been developed within the sea level project of the extension phase of the European Space Agency (ESA) Climate Change Initiative (SL_cci+). During the project, the product will be extended in spatial coverage and with additional altimeter missions. This version of the dataset is v1.1. (DOI: 10.5270/esa-sl_cci-xtrack_ales_sla-200206_201805-v1.1-202005)" } }, { "ob_id": 411, "relationType": "IsSupplementTo", "subjectObservation": { "ob_id": 31957, "uuid": "80791eb6d92542cea867727f3c44d49a", "short_code": "ob", "title": "FRANC: Wardon Hill C-band rain radar helical scan products", "abstract": "Helical scans from the Met Office's Wardon Hill C-band rain radar, Dorset, England produced in support of the NERC funded \"Forecasting Rainfall exploiting new data Assimilation techniques and Novel observations of Convection\" (FRANC) project. These data are opportunistic observations made by the radar as it transitioned between horizontal and vertically pointing scans and vice versa obtained during the period of the FRANC project.\r\n\r\nThe radar is a C-band (5.3 cm wavelength) radar and data are received by the Nimrod system at 5 minute intervals." }, "objectObservation": { "ob_id": 5719, "uuid": "910f888f47966082800a228a25ee76aa", "short_code": "ob", "title": "Wardon Hill C-band rain radar dual polar products", "abstract": "Dual-polar products from the Met Office's Wardon Hill C-band rain radar, Dorset, England. Data include augmented ldr (both long and short pulse), augmented zdr (both long and short pulse) and augmented refractivity scan data. The radar is a C-band (5.3 cm wavelength) radar and data are received by the Nimrod system at 5 minute intervals.\r\n\r\nPlease note that this radar is operated for research purposes only and thus subject to changes in operation and data are subject to interruptions. \r\n\r\nData from the Cobbacombe Cross, Dean Hill or Jersey radars provide coverage for the same area covered by the Wardon Hill radar." } }, { "ob_id": 412, "relationType": "IsSupplementTo", "subjectObservation": { "ob_id": 31957, "uuid": "80791eb6d92542cea867727f3c44d49a", "short_code": "ob", "title": "FRANC: Wardon Hill C-band rain radar helical scan products", "abstract": "Helical scans from the Met Office's Wardon Hill C-band rain radar, Dorset, England produced in support of the NERC funded \"Forecasting Rainfall exploiting new data Assimilation techniques and Novel observations of Convection\" (FRANC) project. These data are opportunistic observations made by the radar as it transitioned between horizontal and vertically pointing scans and vice versa obtained during the period of the FRANC project.\r\n\r\nThe radar is a C-band (5.3 cm wavelength) radar and data are received by the Nimrod system at 5 minute intervals." }, "objectObservation": { "ob_id": 12222, "uuid": "befddc832f8947e8834188df4661565d", "short_code": "ob", "title": "Wardon Hill C-band rain radar 5 km rainfall rate data", "abstract": "5 km resolution rain rate data from Met Office's Wardon Hill C-band rain radar, Dorset, England as part of the NIMROD, very short range forecasting system used by the Met Office. 5 km rain rate data are available from 2006 until present. Radar images from the C-band (5.3 cm wavelength) radar are received by the Nimrod system 5 minute intervals respectively.\r\n\r\nPlease note that this radar is operated for research purposes only and thus subject to changes in operation and data are subject to interruptions. \r\n\r\nData from the Cobbacombe Cross, Dean Hill or Jersey radars provide coverage for the same area covered by the Wardon Hill radar." } }, { "ob_id": 413, "relationType": "IsSupplementTo", "subjectObservation": { "ob_id": 31957, "uuid": "80791eb6d92542cea867727f3c44d49a", "short_code": "ob", "title": "FRANC: Wardon Hill C-band rain radar helical scan products", "abstract": "Helical scans from the Met Office's Wardon Hill C-band rain radar, Dorset, England produced in support of the NERC funded \"Forecasting Rainfall exploiting new data Assimilation techniques and Novel observations of Convection\" (FRANC) project. These data are opportunistic observations made by the radar as it transitioned between horizontal and vertically pointing scans and vice versa obtained during the period of the FRANC project.\r\n\r\nThe radar is a C-band (5.3 cm wavelength) radar and data are received by the Nimrod system at 5 minute intervals." }, "objectObservation": { "ob_id": 5750, "uuid": "fec3e0939484ebe85d64c02790d1fc40", "short_code": "ob", "title": "Wardon Hill C-band rain radar 2 km rainfall rate data", "abstract": "2 km resolution rain rate data from Met Office's Wardon Hill C-band rain radar, Dorset, England as part of the NIMROD, very short range forecasting system used by the Met Office. 1 km rain rate data are available from 2006 until present. Radar images from the C-band (5.3 cm wavelength) radar are received by the Nimrod system 5 minute intervals respectively.\r\n\r\nPlease note that this radar is operated for research purposes only and thus subject to changes in operation and data are subject to interruptions. \r\n\r\nData from the Cobbacombe Cross, Dean Hill or Jersey radars provide coverage for the same area covered by the Wardon Hill radar." } }, { "ob_id": 414, "relationType": "IsVariantFormOf", "subjectObservation": { "ob_id": 5722, "uuid": "2039ee8a46a62123a2d2fa033e9201d9", "short_code": "ob", "title": "Predannack C-band rain radar 1 km rainfall rate data", "abstract": "1 km resolution rain rate data from Met Office's Predannack C-band rain radar, Cornwall, England as part of the NIMROD, very short range forecasting system used by the Met Office. 1 km rain rate data are available from 2011 until present. Radar images from the C-band (5.3 cm wavelength) radar are received by the Nimrod system 5 minute intervals respectively." }, "objectObservation": { "ob_id": 12216, "uuid": "96775747be204b4fa7b69b7526eaae8b", "short_code": "ob", "title": "Predannack C-band rain radar 2 km rainfall rate data", "abstract": "2 km resolution rain rate data from Met Office's Predannack C-band rain radar, Cornwall, England as part of the NIMROD, very short range forecasting system used by the Met Office. 2 km rain rate data are available from 2004 until present. Radar images from the C-band (5.3 cm wavelength) radar are received by the Nimrod system 5 minute intervals respectively." } }, { "ob_id": 415, "relationType": "IsVariantFormOf", "subjectObservation": { "ob_id": 5722, "uuid": "2039ee8a46a62123a2d2fa033e9201d9", "short_code": "ob", "title": "Predannack C-band rain radar 1 km rainfall rate data", "abstract": "1 km resolution rain rate data from Met Office's Predannack C-band rain radar, Cornwall, England as part of the NIMROD, very short range forecasting system used by the Met Office. 1 km rain rate data are available from 2011 until present. 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The radar is a C-band (5.3 cm wavelength) radar and data are received by the Nimrod system at 5 minute intervals." } }, { "ob_id": 426, "relationType": "IsNewVersionOf", "subjectObservation": { "ob_id": 31963, "uuid": "10d2c73e5a7d46f4ada08b0a26302ef7", "short_code": "ob", "title": "CRU JRA v2.1: A forcings dataset of gridded land surface blend of Climatic Research Unit (CRU) and Japanese reanalysis (JRA) data; Jan.1901 - Dec.2019.", "abstract": "The CRU JRA V2.1 dataset is a 6-hourly, land surface, gridded time series of ten meteorological variables produced by the Climatic Research Unit (CRU) at the University of East Anglia (UEA), and is intended to be used to drive models. The variables are provided on a 0.5 deg latitude x 0.5 deg longitude grid, the grid is near global but excludes Antarctica (this is same as the CRU TS grid, though the set of variables is different). The data are available at a 6 hourly time-step from January 1901 to December 2019.\r\n\r\nThe dataset is constructed by regridding data from the Japanese Reanalysis data (JRA) produced by the Japanese Meteorological Agency (JMA), adjusting where possible to align with the CRU TS 4.04 data (see the Process section and the ReadMe file for full details).\r\n\r\nThe CRU JRA data consists of the following ten meteorological variables: 2-metre temperature, 2-metre maximum and minimum temperature, total precipitation, specific humidity, downward solar radiation flux, downward long wave radiation flux, pressure and the zonal and meridional components of wind speed (see the ReadMe file for further details).\r\n\r\nThe CRU JRA dataset is intended to be a replacement of the CRU NCEP forcing dataset. The CRU JRA dataset follows the style of Nicolas Viovy's original CRU NCEP dataset rather than that which is available from UCAR. A link to the CRU NCEP documentation for comparison is provided in the documentation section. \r\n\r\nIf this dataset is used in addition to citing the dataset as per the data citation string users must also cite the following:\r\n\r\nHarris, I., Osborn, T.J., Jones, P. et al. Version 4 of the CRU TS\r\nmonthly high-resolution gridded multivariate climate dataset.\r\nSci Data 7, 109 (2020). https://doi.org/10.1038/s41597-020-0453-3\r\n\r\nHarris, I., Jones, P.D., Osborn, T.J. and Lister, D.H. (2014), Updated\r\nhigh-resolution grids of monthly climatic observations - the CRU TS3.10\r\nDataset. International Journal of Climatology 34, 623-642.\r\n\r\nKobayashi, S., et. al., The JRA-55 Reanalysis: General Specifications and\r\nBasic Characteristics. J. Met. Soc. Jap., 93(1), 5-48\r\nhttps://dx.doi.org/10.2151/jmsj.2015-001" }, "objectObservation": { "ob_id": 27491, "uuid": "7f785c0e80aa4df2b39d068ce7351bbb", "short_code": "ob", "title": "CRU JRA v2.0: A forcings dataset of gridded land surface blend of Climatic Research Unit (CRU) and Japanese reanalysis (JRA) data; Jan.1901 - Dec.2018.", "abstract": "The CRU JRA V2.0 dataset is a 6-hourly, land surface, gridded time series of ten meteorological variables produced by the Climatic Research Unit (CRU) at the University of East Anglia (UEA), and is intended to be used to drive models. The variables are provided on a 0.5 deg latitude x 0.5 deg longitude grid, the grid is near global but excludes Antarctica (this is same as the CRU TS grid, though the set of variables is different) . The data are available at a 6 hourly time-step from January 1901 to December 2018.\r\n\r\nThe dataset is constructed by combining data from the Japanese Reanalysis data (JRA) produced by the Japanese Meteorological Agency (JMA) and adjusted where possible to align with the CRU TS 4.03 data (see the Process section and the ReadMe file for full details).\r\n\r\nThe CRU JRA data consists of the following ten meteorological variables: 2-metre temperature, 2-metre maximum and minimum temperature, total precipitation, specific humidity, downward solar radiation flux, downward long wave radiation flux, pressure and the zonal and meridional components of wind speed (see the ReadMe file for further details).\r\n\r\nThe CRU JRA dataset is intended to be a replacement of the CRU NCEP forcing dataset. The CRU JRA dataset follows the style of Nicolas Viovy's original CRU NCEP dataset rather than that which is available from UCAR. A link to the CRU NCEP documentation for comparison is provided in the documentation section. \r\n\r\nIf this dataset is used in addition to citing the dataset as per the data citation string users must also cite the following:\r\n\r\nHarris, I., Jones, P.D., Osborn, T.J. and Lister, D.H. (2014), Updated\r\nhigh-resolution grids of monthly climatic observations - the CRU TS3.10\r\nDataset. International Journal of Climatology 34, 623-642.\r\n\r\nKobayashi, S., et. al., The JRA-55 Reanalysis: General Specifications and\r\nBasic Characteristics. J. Met. Soc. Jap., 93(1), 5-48\r\nhttps://dx.doi.org/10.2151/jmsj.2015-001" } } ] }