Result List
Get a list of Result objects. Results have a 1:1 mapping with Observations.
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{ "count": 11555, "next": "https://api.catalogue.ceda.ac.uk/api/v3/results/?format=api&limit=100&offset=9400", "previous": "https://api.catalogue.ceda.ac.uk/api/v3/results/?format=api&limit=100&offset=9200", "results": [ { "ob_id": 36782, "uuid": "e241fa920d48499e9169253db5d40aed", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/spain/alicante/aemet-vaisala-cl31_B", "numberOfFiles": 1757, "volume": 4512033565, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 36783, "uuid": "b25b892e4d844fccbfdfa4a756cf3154", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from AEMET's Vaisala CL31 instrument B deployed at Alicante, Spain", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from La Agencia Estatal de Meteorología (AEMET)'s Vaisala CL31 deployed at Alicante, Spain.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-08360.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 36785, "uuid": "6966094f5fb0475cbcd89963243e8aa9", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/spain/base-aerea-de-moron/aemet-vaisala-cl31_B", "numberOfFiles": 1236, "volume": 3299896314, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 36786, "uuid": "f6560eafc86045818437e4630c9900ee", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from AEMET's Vaisala CL31 instrument B deployed at Base Aerea De Moron, Spain", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from La Agencia Estatal de Meteorología (AEMET)'s Vaisala CL31 deployed at Base Aerea De Moron, Spain.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-08397.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 36788, "uuid": "414e64880098426b97504d8676b2b4c8", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/spain/getafe/aemet-vaisala-cl31_B", "numberOfFiles": 1662, "volume": 2679823957, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 36789, "uuid": "a679576ef06c4f47b96d63c452f5c1eb", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from AEMET's Vaisala CL31 instrument B deployed at Getafe, Spain", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from La Agencia Estatal de Meteorología (AEMET)'s Vaisala CL31 deployed at Getafe, Spain.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-08224.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 36791, "uuid": "b13b5a2aec2e4ae9b3e392e4bbd11330", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/spain/ibiza/aemet-vaisala-cl31_B", "numberOfFiles": 1225, "volume": 2612739730, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 36792, "uuid": "d3bc5055d9824b258fe0902968001188", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from AEMET's Vaisala CL31 instrument B deployed at Ibiza, Spain", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from La Agencia Estatal de Meteorología (AEMET)'s Vaisala CL31 deployed at Ibiza, Spain.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-08373.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 36794, "uuid": "7f5bb4da5427423084a31245995e1b7c", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/spain/menorca/aemet-vaisala-cl31_B", "numberOfFiles": 1564, "volume": 2356109332, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 36795, "uuid": "5c2bd4bbee5743558ae8831e3172b040", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from AEMET's Vaisala CL31 instrument B deployed at Menorca, Spain", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from La Agencia Estatal de Meteorología (AEMET)'s Vaisala CL31 deployed at Menorca, Spain.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-08314.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 36797, "uuid": "9afb54b0c277433bb92d22e97991200e", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/spain/murcia/aemet-vaisala-cl31_B", "numberOfFiles": 1517, "volume": 2740627558, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 36798, "uuid": "a7235f89531e478e8d92517da52c23ab", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from AEMET's Vaisala CL31 instrument B deployed at Murcia, Spain", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from La Agencia Estatal de Meteorología (AEMET)'s Vaisala CL31 deployed at Murcia, Spain.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-08433.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 36800, "uuid": "25e8faa2d3004755a662ce553c4826f0", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/spain/tenerife-north/aemet-vaisala-cl31_B", "numberOfFiles": 1456, "volume": 3820426643, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 36801, "uuid": "150f69f30e1a4fe8b9c04ee3ed07a425", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from AEMET's Vaisala CL31 instrument B deployed at Tenerife North, Spain", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from La Agencia Estatal de Meteorología (AEMET)'s Vaisala CL31 deployed at Tenerife North, Spain.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-60015.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 36803, "uuid": "3c0dc7ce5f3045afbb7070bd607187b9", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/spain/valencia-aeropuerto/aemet-vaisala-cl31_B", "numberOfFiles": 1043, "volume": 1394255988, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 36804, "uuid": "25af4a2733734902b7430a7b4ec44d87", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from AEMET's Vaisala CL31 instrument B deployed at Valencia Aeropuerto, Spain", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from La Agencia Estatal de Meteorología (AEMET)'s Vaisala CL31 deployed at Valencia Aeropuerto, Spain.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-08284.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 36807, "uuid": "9cff9a55f54440b1b0d4252917bf5d29", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig41/v20211028", "numberOfFiles": 16, "volume": 201475223, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 33291, "uuid": "43b0c376ad184543a1bbceeceec0e85d", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.41 (v20211028)", "abstract": "Data for Figure 3.41 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 3.41 is a summary figure showing simulated and observed changes in key large-scale indicators of climate change across the climate system, for continental, ocean basin and larger scales. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates:\r\nEyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The data of each panel is provided in a single file.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This datasets contains global and regional anomaly time-series for:\r\n \r\n - near-surface air temperature (1850-2020)\r\n - precipitation (1950-2014)\r\n - sea ice extent (1979-2014)\r\n - ocean heat content (1850-2014)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\nnear-surface air temperature (tas)\r\n-fig_3_41_tas_global.nc, fig_3_41_tas_land.nc, fig_3_41_tas_north_america.nc, fig_3_41_tas_central_south_america.nc, fig_3_41_tas_europe_north_africa.nc, fig_3_41_tas_africa.nc, fig_3_41_tas_asia.nc, fig_3_41_tas_australasia.nc, fig_3_41_tas_antarctic.nc:\r\nbrown line: exp = 0, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile)\r\ngreen line: exp = 1, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile)\r\nblack line: exp = 4, stat = 0 (mean)\r\n\r\nocean heat content (ohc)\r\n-fig_3_41_ohc_global.nc:\r\nbrown line: ncl5 = 0, ncl6 = 0 (mean); shaded region: ncl6 = 1 (5th percentile) and 2 (95th percentile)\r\ngreen line: ncl5 = 1, ncl6 = 0 (mean); shaded region: ncl6 = 1 (5th percentile) and 2 (95th percentile)\r\nblack line: ncl5 = 2, ncl6 = 0 (mean)\r\n\r\nprecipitation (pr)\r\n-fig_3_41_pr_60N_90N.nc:\r\nbrown line: exp = 0, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile)\r\ngreen line: exp = 1, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile)\r\nblack line: exp = 2, stat = 0 (mean)\r\n\r\nsea ice extent (siconc)\r\n-fig_3_41_siconc_nh.nc, fig_3_41_siconc_sh.nc:\r\nbrown line: exp = 0, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile)\r\ngreen line: exp = 1, stat = 0 (mean); shaded region: stat = 1 (5th percentile) and 2 (95th percentile)\r\nblack line: exp = 2, stat = 0 (mean)\r\n\r\nThe ensemble spread (shaded regions) of CMIP6 data shown in figure 3.41 are the mean, 5th and 95th percentiles. \r\nThe in-file metadata labels the same ensemble spread with mean, min and max.\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 3)\r\n - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1\r\n - Link to the code for the figure, archived on Zenodo\r\n - Link to the figure on the IPCC AR6 website" }, "onlineresource_set": [] }, { "ob_id": 36808, "uuid": "78fa9242cc804919bd47982df0160d2f", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig06/v20220119", "numberOfFiles": 7, "volume": 357356, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34660, "uuid": "c3450dc769f044898ea5f3be784f354b", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.6 (v20220119)", "abstract": "Data for Figure 3.6 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 3.6 shows simulated internal variability of global surface air temperature (GSAT) versus observed changes. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates:\r\nEyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005.\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has three panels. Files are not separated according to the panels. \r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n obs_gmst.nc contains\r\n - Observed GMST anomalies\r\n - Observed GMST difference between 2010-2019 and 1850-1900\r\n \r\n historical_cmip6_gsat.nc contains\r\n - Simulated GSAT anomalies\r\n - Simulated GSAT difference between 2010-2019 and 1850-1900\r\n of CMIP6 historical-ssp245 simulations\r\n \r\n piControl_cmip6_gsat.nc contains - Simulated GSAT anomalies\r\n - Simulated GSAT difference between the last 10 years and the first 51 years of a 170-year segment\r\n of the first 500 years of CMIP6 piControl simulations\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel a:\r\n - 5-year running mean of picontrol_tas_aa in piControl_cmip6_gsat.nc\r\n o BCC-CSM2-MR: E = 3\r\n o CMCC-CM2-SR5: E = 11\r\n o CNRM-CM6-1: E = 12\r\n o CNRM-ESM2-1: E = 13\r\n o EC-Earth3: E = 15\r\n o EC-Earth3-Veg: E = 16\r\n o EC-Earth3-Veg-LR: E = 17\r\n o IPSL-CM6A-LR: E = 29\r\n o KIOST-ESM: E = 30\r\n o MCM-UA-1-0: E = 31\r\n \r\n Panel b:\r\n - obs_tas_aa_trend in obs_gmst.nc: black vertical lines\r\n o HadCRUT5: dataset = 1\r\n o BerkeleyEarth: dataset = 2\r\n o NOAAGlobalTemp-Interim: dataset = 3\r\n o Kadow: dataset = 4\r\n - histogram of histssp_tas_aa_trend in historical_cmip6_gsat.nc: red shading\r\n - multimodel ensemble mean of histssp_tas_aa_trend in historical_cmip6_gsat.nc: red vertical line\r\n - histogram of picontrol_tas_aa_runtrend in piControl_cmip6_gsat.nc: blue shading\r\n - multimodel ensemble mean picontrol_tas_aa_runtrend in piControl_cmip6_gsat.nc: blue vertical line\r\n \r\n Panel c:\r\n - obs_tas_aa in obs_gmst.nc: grey curves, with their 5-year running means for black curves\r\n o HadCRUT5: dataset = 1\r\n o BerkeleyEarth: dataset = 2\r\n o NOAAGlobalTemp-Interim: dataset = 3\r\n o Kadow: dataset = 4\r\n\r\n\r\nAcronyms: CMIP - Coupled Model Intercomparison Project, GMST - Global mean surface temperature, GSAT - Global surface air temperature, BCC-CSM - Beijing Climate Center Climate System Model, CMMC CM - Centro Euro-Mediterraneo sui Cambiamenti Climatici Climate Model, CNRM - Centre National de Recherches Meteorologiques, IPSL - Institut Pierre-Simon Laplace, KIOST-ESM - Korea Institute of Ocean Science & Technology Earth System, CRU - Climatic Research Unit, NOAA - National Oceanic and Atmospheric Administration. \r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nMultimodel ensemble means and histograms of historical simulations are calculated after weighting individual members with the inverse of the ensemble size of the same model. ensemble_assign in each file provides the model number to which each ensemble member belongs. \r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 3)\r\n - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1" }, "onlineresource_set": [] }, { "ob_id": 36809, "uuid": "d16045a35e934268b7cfa3ad55fd5f1c", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/lakes/data/lake_products/L3S/v2.0/", "numberOfFiles": 10325, "volume": 670280729797, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34653, "uuid": "ab8d21568c81491fbb9a300c36884af7", "short_code": "ob", "title": "ESA Lakes Climate Change Initiative (Lakes_cci): Lake products, Version 2.0", "abstract": "This dataset contains the Lakes Essential Climate Variable, which is comprised of processed satellite observations at the global scale, over the period 1992-2020, for over 2000 inland water bodies. This dataset was produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project. For more information about the Lakes_cci please visit the project website. \r\n\r\nThis is version 2.0 of the dataset. The five thematic climate variables included in this dataset are:\r\n• Lake Water Level (LWL), derived from satellite altimetry, is fundamental to understand the balance between water inputs and water loss and their connection with regional and global climate change.\r\n• Lake Water Extent (LWE), modelled from the relation between LWL and high-resolution spatial extent observed at set time-points, describes the areal extent of the water body. This allows the observation of drought in arid environments, expansion in high Asia, or impact of large-scale atmospheric oscillations on lakes in tropical regions for example. .\r\n• Lake Surface Water temperature (LSWT), derived from optical and thermal satellite observations, is correlated with regional air temperatures and is informative about vertical mixing regimes, driving biogeochemical cycling and seasonality.\r\n• Lake Ice Cover (LIC), determined from optical observations, describes the freeze-up in autumn and break-up of ice in spring, which are proxies for gradually changing climate patterns and seasonality.\r\n• Lake Water-Leaving Reflectance (LWLR), derived from optical satellite observations, is a direct indicator of biogeochemical processes and habitats in the visible part of the water column (e.g. seasonal phytoplankton biomass fluctuations), and an indicator of the frequency of extreme events (peak terrestrial run-off, changing mixing conditions).\r\n\r\nData generated in the Lakes_cci are derived from multiple satellite sensors including: TOPEX/Poseidon, Jason, ENVISAT, SARAL, Sentinel 2-3, Landsat OLI, ERS, MODIS Terra/Aqua and Metop.\r\n\r\nDetailed information about the generation and validation of this dataset is available from the Lakes_cci documentation available on the project website." }, "onlineresource_set": [] }, { "ob_id": 36810, "uuid": "809be068f4b34158ae4d908b7245d53e", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig16/v20220105", "numberOfFiles": 25, "volume": 150391, "fileFormat": "NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34584, "uuid": "4e80c4a2933344259a3f423715771952", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.16 (v20220105)", "abstract": "Data for Figure 3.16 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure 3.16 shows observed and simulated changes in Hadley cell extent and Walker circulation strength.\r\n\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates:\r\nEyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005.\r\n \r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has six panels, with data provided for all panels in subdirectories named panel_a, panel_b, panel_c, panel_d, panel_e and panel_f.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n \r\n - Modelled and observed trends of the Northern Hemisphere annual-mean subtropical edge latitude of the Hadley cell for 1980-2014\r\n - Modelled and observed trends of the Southern Hemisphere annual-mean subtropical edge latitude of the Hadley cell for 1980-2014\r\n - Modelled and observed trends of the Southern Hemisphere December-January-February subtropical edge latitude of the Hadley cell for 1981-2000\r\n - Modelled and observed trends of the annual-mean Walker circulation strength for 1901-2010\r\n - Modelled and observed trends of the annual-mean Walker circulation strength for 1951-2010\r\n - Modelled and observed trends of the annual-mean Walker circulation strength for 1980-2014\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel a:\r\n - lat in panel_a/NHedge_ANN_1980-2014_ERA-Interim.nc; black dotted line\r\n - lat in panel_a/NHedge_ANN_1980-2014_ERA5.nc; black solid line\r\n - lat in panel_a/NHedge_ANN_1980-2014_JRA-55.nc; black dash-dotted line\r\n - lat in panel_a/NHedge_ANN_1980-2014_MERRA2.nc; black dashed line\r\n - lat in panel_a/NHedge_ANN_1980-2014_cmip5hist.nc; multimodel ensemble mean and percentiles for red open box-whisker\r\n - lat in panel_a/NHedge_ANN_1980-2014_cmip6GHG.nc; multimodel ensemble mean and confidence interval for brown filled box, with ensemble means of individual models for black dots\r\n - lat in panel_a/NHedge_ANN_1980-2014_cmip6aer.nc; multimodel ensemble mean and confidence interval for light blue filled box, with ensemble means of individual models for black dots\r\n - lat in panel_a/NHedge_ANN_1980-2014_cmip6amip.nc; multimodel ensemble mean and percentiles for orange open box-whisker\r\n - lat in panel_a/NHedge_ANN_1980-2014_cmip6hist.nc; multimodel ensemble mean and percentiles for red open box-whisker, and multimodel ensemble mean and confidence interval for red filled box, with ensemble means of individual models for black dots\r\n - lat in panel_a/NHedge_ANN_1980-2014_cmip6nat.nc; multimodel ensemble mean and confidence interval for green filled box, with ensemble means of individual models for black dots\r\n - lat in panel_a/NHedge_ANN_1980-2014_cmip6stratO3.nc; multimodel ensemble mean and confidence interval for purple filled box, with ensemble means of individual models for black dots\r\n - lat in panel_a/NHedge_ANN_35yrs_cmip6pi.nc; multimodel ensemble mean and percentiles for blue open box-whisker\r\n \r\n Panel b: As Panel a, but with\r\n - lat in panel_b/SHedge_ANN_1980-2014_ERA-Interim.nc\r\n - lat in panel_b/SHedge_ANN_1980-2014_ERA5.nc\r\n - lat in panel_b/SHedge_ANN_1980-2014_JRA-55.nc\r\n - lat in panel_b/SHedge_ANN_1980-2014_MERRA2.nc\r\n - lat in panel_b/SHedge_ANN_1980-2014_cmip5hist.nc\r\n - lat in panel_b/SHedge_ANN_1980-2014_cmip6GHG.nc\r\n - lat in panel_b/SHedge_ANN_1980-2014_cmip6aer.nc\r\n - lat in panel_b/SHedge_ANN_1980-2014_cmip6amip.nc\r\n - lat in panel_b/SHedge_ANN_1980-2014_cmip6hist.nc\r\n - lat in panel_b/SHedge_ANN_1980-2014_cmip6nat.nc\r\n - lat in panel_b/SHedge_ANN_1980-2014_cmip6stratO3.nc\r\n - lat in panel_b/SHedge_ANN_35yrs_cmip6pi.nc\r\n \r\n Panel c: As Panel a, but with\r\n - lat in panel_c/SHedge_DJF_1981-2000_ERA-Interim.nc; ERA-Interim\r\n - lat in panel_c/SHedge_DJF_1981-2000_ERA5.nc; ERA5\r\n - lat in panel_c/SHedge_DJF_1981-2000_JRA-55.nc; JRA-55\r\n - lat in panel_c/SHedge_DJF_1981-2000_MERRA2.ncl MERRA2\r\n - lat in panel_c/SHedge_DJF_1981-2000_cmip5hist.nc; CMIP5 historical-RCP4.5\r\n - lat in panel_c/SHedge_DJF_1981-2000_cmip6GHG.nc; CMIP6 hist-GHG\r\n - lat in panel_c/SHedge_DJF_1981-2000_cmip6aer.nc; CMIP6 hist-aer\r\n - lat in panel_c/SHedge_DJF_1981-2000_cmip6amip.nc; CMIP6 AMIP\r\n - lat in panel_c/SHedge_DJF_1981-2000_cmip6hist.nc; CMIP6 historical\r\n - lat in panel_c/SHedge_DJF_1981-2000_cmip6nat.nc; CMIP6 hist-nat\r\n - lat in panel_c/SHedge_DJF_1981-2000_cmip6stratO3.nc; CMIP6 hist-stratO3\r\n - lat in panel_c/SHedge_DJF_20yrs_cmip6pi.nc; CMIP6 piControl\r\n \r\n Panel d:\r\n - dslp in panel_d/WalkerStrength_ANN_1901-2010_20CRv3.nc; max-min range for grey diagonal hatching\r\n - dslp in panel_d/WalkerStrength_ANN_1901-2010_CERA-20C.nc; max-min range for grey vertical hatching\r\n - dslp in panel_d/WalkerStrength_ANN_1901-2010_ERA-20C.nc; grey dashed line\r\n - dslp in panel_d/WalkerStrength_ANN_1901-2010_HadSLP2.nc; grey solid line\r\n - dslp in panel_d/WalkerStrength_ANN_1901-2010_cmip5hist.nc; multimodel ensemble mean and percentiles for red open box-whisker\r\n - dslp in panel_d/WalkerStrength_ANN_1901-2010_cmip6GHG.nc; multimodel ensemble mean and confidence interval for brown filled box, with ensemble means of individual models for black dots\r\n - dslp in panel_d/WalkerStrength_ANN_1901-2010_cmip6aer.nc; multimodel ensemble mean and confidence interval for light blue filled box, with ensemble means of individual models for black dots\r\n - dslp in panel_d/WalkerStrength_ANN_1901-2010_cmip6amip-hist.nc; multimodel ensemble mean and percentiles for orange open box-whisker\r\n - dslp in panel_d/WalkerStrength_ANN_1901-2010_cmip6hist.nc; multimodel ensemble mean and percentiles for red open box-whisker, and multimodel ensemble mean and confidence interval for red filled box, with ensemble means of individual models for black dots\r\n - dslp in panel_d/WalkerStrength_ANN_1901-2010_cmip6nat.nc; multimodel ensemble mean and confidence interval for green filled box, with ensemble means of individual models for black dots\r\n - dslp in panel_d/WalkerStrength_ANN_1901-2010_cmip6stratO3.nc; multimodel ensemble mean and confidence interval for purple filled box, with ensemble means of individual models for black dots\r\n - dslp in panel_d/WalkerStrength_ANN_110yrs_cmip6pi.nc; multimodel ensemble mean and percentiles for blue open box-whisker\r\n \r\n Panel e: As Panel d, but with\r\n - dslp in panel_e/WalkerStrength_ANN_1951-2010_20CRv3.nc\r\n - dslp in panel_e/WalkerStrength_ANN_1951-2010_CERA-20C.nc\r\n - dslp in panel_e/WalkerStrength_ANN_1951-2010_ERA-20C.nc\r\n - dslp in panel_e/WalkerStrength_ANN_1951-2010_HadSLP2.nc\r\n - dslp in panel_e/WalkerStrength_ANN_1951-2010_cmip5hist.nc\r\n - dslp in panel_e/WalkerStrength_ANN_1951-2010_cmip6GHG.nc\r\n - dslp in panel_e/WalkerStrength_ANN_1951-2010_cmip6aer.nc\r\n - dslp in panel_e/WalkerStrength_ANN_1951-2010_cmip6amip-hist.nc\r\n - dslp in panel_e/WalkerStrength_ANN_1951-2010_cmip6hist.nc\r\n - dslp in panel_e/WalkerStrength_ANN_1951-2010_cmip6nat.nc\r\n - dslp in panel_e/WalkerStrength_ANN_1951-2010_cmip6stratO3.nc\r\n - dslp in panel_e/WalkerStrength_ANN_60yrs_cmip6pi.nc\r\n \r\n Panel f: As Panel d, but with\r\n - dslp in panel_f/WalkerStrength_ANN_1980-2014_20CRv3.nc\r\n - dslp in panel_f/WalkerStrength_ANN_1980-2014_ERA-Interim.nc; black dotted line\r\n - dslp in panel_f/WalkerStrength_ANN_1980-2014_ERA5.nc; black solid line\r\n - dslp in panel_f/WalkerStrength_ANN_1980-2014_JRA-55.nc; black dashed-dotted line\r\n - dslp in panel_f/WalkerStrength_ANN_1980-2014_MERRA2.nc; black dashed line\r\n - dslp in panel_f/WalkerStrength_ANN_1980-2014_cmip5hist.nc\r\n - dslp in panel_f/WalkerStrength_ANN_1980-2014_cmip6GHG.nc\r\n - dslp in panel_f/WalkerStrength_ANN_1980-2014_cmip6aer.nc\r\n - dslp in panel_f/WalkerStrength_ANN_1980-2014_cmip6amip-hist.nc\r\n - dslp in panel_f/WalkerStrength_ANN_1980-2014_cmip6hist.nc\r\n - dslp in panel_f/WalkerStrength_ANN_1980-2014_cmip6nat.nc\r\n - dslp in panel_f/WalkerStrength_ANN_1980-2014_cmip6stratO3.nc\r\n - dslp in panel_f/WalkerStrength_ANN_35yrs_cmip6pi.nc\r\n\r\nAcroynms: \r\nAnn - Annual GHG - Greenhouse gas, aer - aerosol, CMIP - Coupled Model Intercomparison Project, 20CRv3 - NOAA-CIRES-DOE Twentieth Century Reanalysis (V3), CERA-20C - Coupled climate reanalyses of the 20th century, HadSLP2 - Hadley Centre Sea Level Pressure dataset (HadSLP2), AMIP - Atmospheric Model Intercomparison Project (AMIP), JRA - The Japanese 55-year Reanalysis (JRA-55), MERRA-2 - Global Modeling and Assimilation Office - NASA.\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n Ensemble mean, interquartile ranges and 5th and 95th percentiles are calculated after weighting individual members with the inverse of the ensemble size of the same model, i.e. the inverse of the numbers given as the esize attribute in each variable.\r\n \r\nSuppose X(i) is the array of lat, and w(i) is the corresponding weight.\r\n\r\n- Mean should be suｍ_i(X(i) * w(i)) / sum_i(w(i))\r\n- For percentile values, \r\n 1. Sort X and w so that X is in the ascending order\r\n 2. Accumulate w until i = j so that accumulated(w)/sum_i(w(i)) equals or exceeds the specified percentile level (e.g. 0.05)\r\n 3. Use X(j) or (X(j) + X(j - 1))/2 as the percentile value\r\n- Finally, multiply by 10 all numbers for unit conversion.\r\n \r\nFilled boxes and black dots are evaluated based on the models with minimum 3 ensemble members. Model ID of each ensemble member is given as the model_id attribute in each variable. For the confidence interval, first the ensemble average of individual models (with minimum 3 ensemble members) are calculated and then the confidence interval is evaluated based on t statistic.\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 3)\r\n - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1\r\n - Link to the code for the figure, archived on Zenodo" }, "onlineresource_set": [] }, { "ob_id": 36832, "uuid": "04b87a9a3bd84b53b1574b4cceef5e53", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/faam/data/2021/c240-jun-07", "numberOfFiles": 18, "volume": 2151843887, "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 36833, "uuid": "318761643a8f4a4696456094822a1fbb", "short_code": "ob", "title": "FAAM C240 PICASSO flight: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft", "abstract": "Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft collected for Parameterizing Ice Clouds using Airborne obServationS and triple-frequency dOppler radar data (PICASSO) project." }, "onlineresource_set": [] }, { "ob_id": 36839, "uuid": "8f6f37fecdc544deb624e080927533a5", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/deposited2022/radar_data_triple_wavelength/data/", "numberOfFiles": 8, "volume": 35377972, "fileFormat": "Data are NetCDF formatted with version 1.6 CF-standard metadata.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 36838, "uuid": "1782a24b8eb7444ea72b7058c56bef0f", "short_code": "ob", "title": "Radar data from Chilbolton Triple Wavelength Experiment", "abstract": "Radar data collected in ice-phase clouds at the Chilbolton Observatory using radars at 3, 35 and 94 GHz during 2014-2015. The experimental setup is described in Stein et al (2015) DOI: 10.1002/2014GL062170 - see related documents section on this record. Raw pulse-to-pulse data were collected from all 3 radars, and have been post processed to common, synchronised time bins, for maximum ease of colocation.\r\n\r\nThese data were produced as part of the NERC funded Exploiting multi-wavelength radar Doppler spectra to characterise the microphysics of ice hydrometeors project (grant reference: NE/K012444/1)." }, "onlineresource_set": [] }, { "ob_id": 36842, "uuid": "5500960c894f418f8960e1fb2a7b16bf", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/cloud/data/phase-1/L3U/avhrr_noaa-15/", "numberOfFiles": 1, "volume": 1045, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [ { "ob_id": 13292, "uuid": "07960759e8454a4e8dedadf2c1f3da45", "short_code": "result", "title": null, "abstract": null } ], "observation": { "ob_id": 13291, "uuid": "1b38687fb67949a9b3ea1a6bae419a75", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud CCI): L3U cloud properties from AVHRR on NOAA 15, Version 1.0", "abstract": "Cloud properties derived from the AVHRR instrument on NOAA-15 by the ESA Cloud CCI project. The L3U datasets consists of cloud properties from L2 data granules remapped to a global space grid of 0.1 degree in latitiude and longitude, without combining any observations from overlapping orbits; only sampling is done. Common notations for this processing level are also L2b and L2G. Data is provided with a temporal resolution of 1 day.\r\n\r\nThis dataset is version 1.0 data from Phase 1 of the CCI project." }, "onlineresource_set": [] }, { "ob_id": 36843, "uuid": "94cfce3bb65947b8a52f31a55bd92926", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/cloud/data/phase-1/L3U/avhrr_noaa-16/", "numberOfFiles": 1, "volume": 1045, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [ { "ob_id": 13290, "uuid": "66867a1e51a74067b1f1e0f805574978", "short_code": "result", "title": null, "abstract": null } ], "observation": { "ob_id": 13289, "uuid": "fe86018b77d14929989a315245ab5973", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud CCI): L3U cloud properties from AVHRR on NOAA 16, Version 1.0", "abstract": "Cloud properties derived from the AVHRR instrument on NOAA-16 by the ESA Cloud CCI project. The L3U datasets consists of cloud properties from L2 data granules remapped to a global space grid of 0.1 degree in latitiude and longitude, without combining any observations from overlapping orbits; only sampling is done. Common notations for this processing level are also L2b and L2G. Data is provided with a temporal resolution of 1 day.\r\n\r\nThis dataset is version 1.0 data from Phase 1 of the CCI project." }, "onlineresource_set": [] }, { "ob_id": 36844, "uuid": "5c18e75421374af7ac230631a5af0a50", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/cloud/data/phase-1/L3U/avhrr_noaa-17/", "numberOfFiles": 1, "volume": 1045, "fileFormat": "Data are netCDf formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [ { "ob_id": 13288, "uuid": "58ea3e7421c046c5a565969be1cde9f5", "short_code": "result", "title": null, "abstract": null } ], "observation": { "ob_id": 13287, "uuid": "7da4e03f14ad4bc7ac8dc8b7b98cfae4", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud CCI): L3U cloud properties from AVHRR on NOAA 17, Version 1.0", "abstract": "Cloud properties derived from the AVHRR instrument on NOAA-17 by the ESA Cloud CCI project. The L3U datasets consists of cloud properties from L2 data granules remapped to a global space grid of 0.1 degree in latitiude and longitude, without combining any observations from overlapping orbits; only sampling is done. Common notations for this processing level are also L2b and L2G. Data is provided with a temporal resolution of 1 day.\r\n\r\nThis dataset is version 1.0 data from Phase 1 of the CCI project." }, "onlineresource_set": [] }, { "ob_id": 36845, "uuid": "008435568af7449c93cc082385b58b54", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/cloud/data/phase-1/L3U/avhrr_noaa-18/", "numberOfFiles": 1, "volume": 1045, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [ { "ob_id": 13286, "uuid": "3c0dc195ac1c4227aa565563a5eb13ed", "short_code": "result", "title": null, "abstract": null } ], "observation": { "ob_id": 13285, "uuid": "b3d30ea8969945f68383dfef511b2d78", "short_code": "ob", "title": "ESA Cloud Climate Change Initiative (Cloud CCI): L3U cloud properties from AVHRR on NOAA 18, Version 1.0", "abstract": "Cloud properties derived from the AVHRR instrument on NOAA-18 by the ESA Cloud CCI project. The L3U datasets consists of cloud properties from L2 data granules remapped to a global space grid of 0.1 degree in latitiude and longitude, without combining any observations from overlapping orbits; only sampling is done. Common notations for this processing level are also L2b and L2G. 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Image files may be PNG formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37067, "uuid": "b5dd56ec21aa47f19585e67b0aecf156", "short_code": "result", "curationCategory": "A", "dataPath": "/bodc/USO220011/CHIMNEY_OBS_passive", "numberOfFiles": 21079, "volume": 646089806422, "fileFormat": "Data are miniseed formatted data files, file naming convention is a logger identifer fiollowed by the date and time of the drop in <YYYY><DOY>HHMMSS format,", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37066, "uuid": "a07ea49c7b754f15af99005cd351f550", "short_code": "ob", "title": "Passive seismicity recorded using four-component ocean bottom seismometers deployed in and around an active fluid flow structure: Scanner Pockmark, North Sea", "abstract": "A passive source seismic dataset was acquired during RRS James Cook cruise JC152, around the Scanner Pockmark Complex in the North Sea. Data were recorded on 25 four-component ocean bottom seismometers (OBS - hydrophone and three-component geophone), deployed in and around Scanner Pockmark, recording at a sampling rate of 4 kHz. The OBS recorded continuously between deployment and recovery (28/08/2017 to 05/09/2017) including through periods of active source seismic data acquisition, indicated in the cruise report (Bull, 2017).\r\n\r\nData are provided in miniSEED format. The receiver drop locations are provided in the associated metadata directory. The data were acquired as part of the 'Characterization of major overburden leakage pathways above sub-seafloor CO2 storage reservoirs in the North Sea' (CHIMNEY) project, funded by the Natural Environment Research Council (NERC) under grant reference NE/N016130/1." }, "onlineresource_set": [] }, { "ob_id": 37073, "uuid": "43885dabe2874d98b75de5dbdf6f1039", "short_code": "result", "curationCategory": "A", "dataPath": "/bodc/USO220011/CHIMNEY_MCS", "numberOfFiles": 203638, "volume": 561573583472, "fileFormat": "Data are segd formatted data files", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37072, "uuid": "96dc6996b5534052ab44f3098a99a357", "short_code": "ob", "title": "Multi-frequency, multi-channel seismic dataset acquired around an active fluid flow structure: Scanner Pockmark, North Sea.", "abstract": "A multi-channel seismic dataset was acquired during RRS James Cook cruise JC152 (August - September 2017), around the Scanner Pockmark Complex in the North Sea. Data were recorded using a number of different seismic sources, comprising: \r\n\r\n1) a GI airgun array, used in two different configurations for separate parts of the survey, \r\ni) a 420 ci (2 x 105/105 ci) array operated in harmonic mode and fired at 8 s intervals, and \r\nii) a 300 ci (2 x 45/105 ci) array operated in true GI mode and fired at 6 s intervals, both towed at 2 m depth below sea surface; \r\n\r\n2) an Applied Acoustic Engineering Squid sparker (1750 or 2000 J), towed at the sea surface and triggered at 2 s intervals; and, \r\n\r\n3) a Duraspark sparker (2000 J), towed at the sea surface and triggered at 2 s intervals. Signals produced by the GI airguns and surface sparkers were recorded on two towed multi-channel streamers: \r\na) a 60 channel, 1 m group interval streamer recorded on a Geometrics Strataview R60 recording system, and \r\nb), a 120 channel, 1.56 m group interval GeoEel streamer, at sampling rates between 0.125 and 0.5 ms depending on the streamer and source pairing. \r\n\r\nData are provided in standard SEG-D format. The data were acquired as part of the 'Characterization of major overburden leakage pathways above sub-seafloor CO2 storage reservoirs in the North Sea' (CHIMNEY) project, funded by the Natural Environment Research Council (NERC) under grant reference NE/N016130/1." }, "onlineresource_set": [] }, { "ob_id": 37089, "uuid": "65472c0ed58145fa9d05608b6ca05da4", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/snap/data/post-cmip6/SNAPSI/SNAP/SNAPSI-REF", "numberOfFiles": 114, "volume": 352016376483, "fileFormat": "netCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37090, "uuid": "540a4c4cdfa6497993bbfa7c3e3df51a", "short_code": "ob", "title": "Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): Reference state data", "abstract": "Reference state data derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis for the nudging experiments of the Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) project. \r\nThese reference states are used to nudge the stratosphere towards a specified evolution in the ensemble forecasts carried out by the SNAPSI project.\r\nThe data contain: \r\n(a) lightly processed horizontal winds and temperatures from ERA5 spanning three case studies of sudden stratospheric warmings from 2018 to 2019 and \r\n(b) climatological horizontal winds and temperatures." }, "onlineresource_set": [] }, { "ob_id": 37091, "uuid": "40107cb38cd24249a794d8bb3a57d519", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_02/ch2_fig11/v20211207/", "numberOfFiles": 8, "volume": 99809, "fileFormat": "csv, txt", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 33420, "uuid": "b953c9c8b41d4339b2a0a80fdc3cb840", "short_code": "ob", "title": "Chapter 2 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 2.11 (v20211207)", "abstract": "Data for Figure 2.11 from Chapter 2 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 2.11 includes mapped and time-series data showing global surface temperature relative to 1850 - 1900 over multiple time scales\r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates:\r\nGulev, S.K., P.W. Thorne, J. Ahn, F.J. Dentener, C.M. Domingues, S. Gerland, D. Gong, D.S. Kaufman, H.C. Nnamchi, J. Quaas, J.A. Rivera, S. Sathyendranath, S.L. Smith, B. Trewin, K. von Schuckmann, and R.S. Vose, 2021: Changing State of the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change[Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 287–422, doi:10.1017/9781009157896.004.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n---------------------------------------------------\r\n Figure has three panels, with data provided for panel (a) (center and right part), and panel (c).\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n---------------------------------------------------\r\n Global surface temperature, relative to 1850 - 1900 for:\r\n\r\n Panel a: \r\n \r\n - 1000 to 1900 CE - from PAGES 2k Consortium (modified from the version 2019: 10.1038/s41561-019-0400-0)\r\n - 1850 to 2020 from AR6 assessed mean (same as Figure 2.11c).\r\n\r\n Panel c: \r\n \r\n - Annual and decadal means from instrumental data for 1850–2020, along with the uncertainty range from HadCRUT5.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n---------------------------------------------------\r\n Panel a:\r\n \r\n - Data file: Figure_2_11a-PAGES_2k_Consortium.csv (yearly data, 1000 to 1900); relates to the center part of the figure showing global surface temperature relative to 1850 -1900. (bold solid green line, column 2, median 10-yr smooth adjusted (+0.37°C), thin solid green lines: 5th (column 3) and 95th (column 4) percentiles of the ensemble members).\r\n - Data file: Figure2_11_panel_a.csv (yearly data, 1850 to 2020); relates to the right part of the figure showing global temperature anomaly AR6 assessed mean. (bold solid violet line, column 2)\r\n\r\nPanel c: \r\n \r\n - Data file: Figure_2_11c-land_and_ocean_time_series.csv (yearly data, 1850 to 2020); relates to the upper part of the figure showing global surface temperature relative to 1850 -1900. (Land, column 2, red line; Ocean, column 3, blue line).\r\n - Data file: Figure_2_11c-lower_panel.csv, (annual and decadal mean, 1850 to 2020); relates to the lower part of the figure. (black line, column 2, HadCRUT 5.0; cyan line, column 3, NOAA Global Temp; pink line, column 4, Berkeley Earth; orange line, column 5, Kadow et al.; grey shadow, columns 6 and 7, HadCRUT confidence limit)\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 2)\r\n - Link to the Supplementary Material for Chapter 2, which contains details on the input data used in Table 2.SM.1\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37112, "uuid": "855b288abc204df6ae74b70fbcae5e09", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/deposited2022/candiflos/data/oden_surface_flux2014", "numberOfFiles": 3, "volume": 1596390, "fileFormat": "Data are NetCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37111, "uuid": "c6f1b1ff16f8407386e2d643bc5b916a", "short_code": "ob", "title": "CANDIFLOS : Surface fluxes from ACSE measurement campaign on icebreaker Oden, 2014", "abstract": "Characterising and Interpreting FLuxes Over Sea Ice (CANDIFLOS) is a data analysis project drawing upon data from multiple field campaigns. It aims to improve the parameterization of surface fluxes over sea ice. This data set consists of the processed surface heat fluxes and sea ice fractions from the Arctic Clouds Summer Experiment (ACSE) project (2014) conducted on icebreaker Oden. Matching data from the AO2016 cruise are provided as a separate data set." }, "onlineresource_set": [] }, { "ob_id": 37115, "uuid": "6dce0eba916d4ba3a926907e3c38cf27", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/deposited2022/candiflos/data/oden_surface_flux2016", "numberOfFiles": 3, "volume": 723131, "fileFormat": "Data are NetCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37114, "uuid": "614752d35dc147a598d5421443fb50e8", "short_code": "ob", "title": "CANDIFLOS : Surface fluxes from AO2016 measurement campaign on icebreaker Oden, 2016", "abstract": "Characterising and Interpreting FLuxes Over Sea Ice (CANDIFLOS) is a data analysis project drawing upon data from multiple field campaigns. It aims to improve the parameterization of surface fluxes over sea ice. This data set consists of the processed surface heat fluxes and sea ice fractions from the Arctic Ocean 2016 (AO2016) project (2016) conducted on the icebreaker Oden. Matching data from the Arctic Clouds Summer Experiment (ACSE) cruise (2014) are provided as a separate data set." }, "onlineresource_set": [] }, { "ob_id": 37116, "uuid": "0a3479cb40f34dc89eb1f3929924d34b", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig17/v20211208", "numberOfFiles": 4, "volume": 1226552, "fileFormat": "netCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 33428, "uuid": "71c2e401df5e4798b917ae4a353daff1", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.17 (v20211208)", "abstract": "Data for Figure 3.17 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFigure 3.17 shows observed and simulated global monsoon domain, intensity, and circulation. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates:\r\nEyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has four panels, with data provided for all panels in a single file. \r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains\r\n \r\n - Observed and simulated global monsoon domain and summer minus winter precipitation and 850hPa wind velocity\r\n - Global land monsoon precipitation index and Northern Hemisphere summer monsoon circulation index.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n All data are given in global_monsoon.nc file.\r\n\r\nPanel a:\r\n \r\n - uRef & vRef: vector\r\n - prRef: shading\r\n - domainRef: domain (1 = monsoon, 0 = not monsoon)\r\n\r\nPanel b:\r\n \r\n - uMME & vMME: vector\r\n - prMME: shading\r\n - domainMME: monsoon domain (1 = monsoon, 0 = not monsoon)\r\n\r\nPanel c:\r\n \r\n - Multimodel ensemble mean and 5th-95th percentiles of GMprecip_cmip6: red curve and shading\r\n - Multimodel ensemble mean and 5th-95th percentiles of GMprecip_cmip5: blue curve and shading\r\n - Multimodel ensemble mean and 5th-95th percentiles of GMprecip_amip: yellow curve and shading\r\n - GMprecip_CMAP: black dotted curve\r\n - GMprecip_CRU-TS: black solid curve\r\n - GMprecip_GPCC: black dashed-dotted curve\r\n - GMprecip_GPCP-SG: black dashed curve\r\n\r\n\r\nPanel d:\r\n \r\n - Multimodel ensemble mean and 5th-95th percentiles of NHMcirc_cmip6: red curve and shading\r\n - Multimodel ensemble mean and 5th-95th percentiles of NHMcirc_cmip5: blue curve and shading\r\n - Multimodel ensemble mean and 5th-95th percentiles of NHMcirc_amip: yellow curve and shading\r\n - Max-min range of NHMcirc_20CRv3: grey hatching\r\n - NHMcirc_ERA-20C: black dash-dotted curve\r\n - NHMcirc_ERA5: black solid curve\r\n - NHMcirc_JRA-55: dashed curve\r\n - NHMcirc_MERRA2: dotted curve\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n Multimodel ensemble means and percentiles are calculated after weighting individual members with the inverse of the ensemble size of the same model, which is given as the weight attribute of each variable.\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 3)\r\n - Link to the Supplementary Material for Chapter 3, which contains supporting information on the figure in Section and details on the input data used in Table 3.SM.1\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37117, "uuid": "1eb5885826dc4623b3f2828995376de2", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig31/v20211203", "numberOfFiles": 7, "volume": 122031, "fileFormat": "netCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 33399, "uuid": "a4cbbffe1bd44c7ba3e8608ee9c54547", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.31 (v20211203)", "abstract": "Data for Figure 3.31 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 3.31 shows evaluation of historical emission-driven CMIP6 simulations for 1850-2014. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates:\r\nEyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has four panels, with data provided for all panels in subdirectories named panel_a, panel_b, panel_c and panel_d.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n \r\n - Observed and simulated change in global mean atmospheric CO2 concentration (1850-2014)\r\n - Observed and simulated air surface temperature anomaly (1850-2014)\r\n - Observed and simulated change in land carbon uptake (1850-2014)\r\n - Observed and simulated change in ocean carbon uptake (1850-2014)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n panel_a/fig_3_31_panel_a.nc:\r\n \r\n - dim0 = 0: 'ACCESS-ESM1-5 ', (turquoise solid line), Australian Community Climate and Earth System Simulator - Earth System Model\r\n - dim0 = 1: 'CNRM-ESM2-1', (light green solid line), National Centre for Meteorological Research\r\n - dim0 = 2: 'CanESM5-CanOE ', (orange solid line), Canadian Earth System Model - Canadian Ocean Ecosystem model\r\n - dim0 = 3: 'CanESM5', (dark green solid line).\r\n - dim0 = 4: 'MIROC-ES2L', (light purple solid line), Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and Centre for Climate System Research / National Institute for Environmental Studies, Japan.\r\n - dim0 = 5: 'MPI-ESM1-2-LR ', (teal solid line), Max Planck Institute Earth System Model \r\n - dim0 = 6: 'MRI-ESM2-0', (lime solid line), Meteorological Research Institute of the Japan Meteorological Agency\r\n - dim0 = 7: 'NorESM2-LM', (pink solid line), The Norwegian Earth System Model\r\n - dim0 = 8: 'UKESM1-0-LL', (dark purple solid line), UK Earth System Model\r\n - dim0 = 9: 'MultiModelMean', (red solid line).\r\n - dim0 = 10: 'ESRL' (OBS), (black solid line).\r\n\r\npanel_b/fig_3_31_panel_b.nc\r\n \r\n - dim0_0 = 0: 'ACCESS-ESM1-5',\r\n - dim0_0 = 1: 'ACCESS-ESM1-5_historical'.\r\n - dim0_0 = 2: 'CNRM-ESM2-1'.\r\n - dim0_0 = 3: 'CNRM-ESM2-1_historical'.\r\n - dim0_0 = 4: 'CanESM5-CanOE '.\r\n - dim0_0 = 5: 'CanESM5-CanOE_historical'.\r\n - dim0_0 = 6: 'CanESM5'.\r\n - dim0_0 = 7: 'CanESM5_historical'.\r\n - dim0_0 = 8: 'MIROC-ES2L'.\r\n - dim0_0 = 9: 'MIROC-ES2L_historical'.\r\n - dim0_0 = 10: 'MPI-ESM1-2-LR '.\r\n - dim0_0 = 11: 'MPI-ESM1-2-LR_historical '.\r\n - dim0_0 = 12: 'MRI-ESM2-0'.\r\n - dim0_0 = 13: 'MRI-ESM2-0_historical'.\r\n - dim0_0 = 14: 'NorESM2-LM'.\r\n - dim0_0 = 15: 'NorESM2-LM_historical'.\r\n - dim0_0 = 16: 'UKESM1-0-LL'.\r\n - dim0_0 = 17: 'UKESM1-0-LL_historical'.\r\n - dim0_0 = 18: 'HadCRUT5' (OBS), Met Office Hadley Centre\r\n\r\n\r\npanel_c/fig_3_31_panel_c.nc\r\n \r\n - dim0 = 0: 'ACCESS-ESM1-5 '.\r\n - dim0 = 1: 'CNRM-ESM2-1'.\r\n - dim0 = 2: 'CanESM5-CanOE '.\r\n - dim0 = 3: 'CanESM5'.\r\n - dim0 = 4: 'MIROC-ES2L'.\r\n - dim0 = 5: 'MPI-ESM1-2-LR '.\r\n - dim0 = 6: 'MRI-ESM2-0'.\r\n - dim0 = 7: 'NorESM2-LM'.\r\n - dim0 = 8: 'UKESM1-0-LL'.\r\n - dim0 = 9: 'MultiModelMean'.\r\n - dim0 = 10: 'GCP' (OBS), Global Carbon Project (GCP)\r\n\r\n\r\npanel_d/fig_3_31_panel_d.nc\r\n \r\n - dim0 = 0: 'ACCESS-ESM1-5 '.\r\n - dim0 = 1: 'CNRM-ESM2-1'.\r\n - dim0 = 2: 'CanESM5-CanOE '.\r\n - dim0 = 3: 'CanESM5'.\r\n - dim0 = 4: 'MIROC-ES2L'.\r\n - dim0 = 5: 'MPI-ESM1-2-LR '.\r\n - dim0 = 6: 'MRI-ESM2-0'.\r\n - dim0 = 7: 'NorESM2-LM'.\r\n - dim0 = 8: 'UKESM1-0-LL'.\r\n - dim0 = 9: 'MultiModelMean'.\r\n - dim0 = 10: 'GCP' (OBS).\r\n\r\n\r\nLabels and colors for all figures are the same as for panel a. Historical values in panel b are plotted with the same colors as the corresponding simulation, but using dotted lines.\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 3)\r\n - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1\r\n - Link to the code for the figure, archived on Zenodo\r\n - Link to the figure on the IPCC AR6 website" }, "onlineresource_set": [] }, { "ob_id": 37118, "uuid": "df9f6d2ac4ff4dd6a6a4f44017e89772", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig32/v20211210", "numberOfFiles": 5, "volume": 32114, "fileFormat": "netCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 33446, "uuid": "25d4a6597d954721bc4a616d094b0cda", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.32 (v20211210)", "abstract": "Data for Figure 3.32 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 3.32 shows relative change in the amplitude of the seasonal cycle of global land carbon uptake in the historical CMIP6 simulations from 1961-2014. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates:\r\nEyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005.\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n - Observed seasonal cycle amplitude of global land carbon uptake\r\n - Simulated seasonal cycle amplitude of global land carbon uptake\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n fig_3_32_main.nc:\r\n \r\n - Multi-Model Mean: dim0 = 0, red solid line. [red shaded region: (dim0=0) +- (dim0=1))]\r\n - JMA-TRANSCOM: dim0 = 2, black dotted line.\r\n - CO2-MLO: dim0 = 3, black solid line. [black shaded region: (dim0=3) +- (dim0=4))]\r\n - CO2-GLOBAL: dim0 = 5, black dashed line.\r\n\r\nfig_3_32_inset.nc:\r\n \r\n - Multi-Model Mean for 1961-1970 (orange): dim0 = 0 (shaded region(dim0=0) +- (dim0=1))\r\n - Multi-Model Mean for 2005-2014 (green): dim0 = 2 (shaded region(dim0=2) +- (dim0=3))\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 3)\r\n - Link to the Supplementary Material for Chapter 3, which contains details on the input data used in Table 3.SM.1\r\n - Link to the code for the figure, archived on Zenodo\r\n - Link to the figure on the IPCC AR6 website." }, "onlineresource_set": [] }, { "ob_id": 37119, "uuid": "754ea60f8c43437b8b413ef09ce513d8", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig33/v20211209", "numberOfFiles": 15, "volume": 247214943, "fileFormat": "netCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 33440, "uuid": "4fe1afacdc524c118989c16a1bccd51e", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.33 (v20211209)", "abstract": "Data for Figure 3.33 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 3.33 shows observed and simulated Northern Annular Mode (NAM), North Atlantic Oscillation (NAO) and Southern Annular Mode (SAM) in boreal winter. \r\n\r\n---------------------------------------------------\r\n How to cite this dataset\r\n ---------------------------------------------------\r\n When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates:\r\n Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has twelve panels, with data provided for panels (a), (d), (g) and (j) in the subdirectory named panel_adgj, panels (b), (e), (h) and (k) in the subdirectory named panel_behk, and panels (c), (f), (i) and (l) in the subdirectory named panel_cfil. \r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains: \r\n - Observed sea level pressure anomalies associated with NAM.\r\n - Observed sea level pressure anomalies associated with NAO.\r\n - Observed sea level pressure anomalies associated with SAM.\r\n - Simulated sea level pressure anomalies associated with NAM.\r\n - Simulated sea level pressure anomalies associated with NAO.\r\n - Simulated sea level pressure anomalies associated with SAM.\r\n - Taylor statistics of sea level pressure anomalies associated with NAM.\r\n - Taylor statistics of sea level pressure anomalies associated with NAO.\r\n - Taylor statistics of sea level pressure anomalies associated with SAM.\r\n - 1958-2014 trends of the NAM index.\r\n - 1958-2014 trends of the NAO index.\r\n - 1979-2014 trends of the SAM index.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel a:\r\n - nam_patterns(0, :, :) in panel_adgj/nam.obs.nc; shading\r\n - nam_pattern_significance in panel_adgj/nam.obs.nc; cross marker\r\n \r\n Panel b:\r\n - nao_patterns(0, :, :) in panel_behk/nao.obs.nc; shading\r\n - nao_pattern_significance in panel_behk/nao.obs.nc; cross marker\r\n \r\n Panel c:\r\n - sam_patterns(0, :, :) in panel_cfil/sam.obs.nc; shading\r\n - sam_pattern_significance in panel_cfil/sam.obs.nc; cross marker\r\n\r\n Panel d:\r\n - nam_patterns in panel_adgj/nam.hist.cmip6.nc; multimodel ensemble mean for shading, and sign agreement for hatching\r\n \r\n Panel e: \r\n - nao_patterns in panel_behk/nao.hist.cmip6.nc; multimodel ensemble mean for shading, and sign agreement for hatching\r\n \r\n Panel f: \r\n - sam_patterns in panel_cfil/sam.hist.cmip6.nc; multimodel ensemble mean for shading, and sign agreement for hatching\r\n \r\n Panel g: \r\n - nam_tay_stat(:, 0:1) in panel_adgj/nam.amip.cmip6.nc: multimodel ensemble mean for the orange dot\r\n - nam_tay_stat(:, 0:1) in panel_adgj/nam.hist.cmip5.nc: blue crosses, with multimodel ensemble mean for the blue dot\r\n - nam_tay_stat(:, 0:1) in panel_adgj/nam.hist.cmip6.nc: red crosses, with multimodel ensemble mean for the red dot\r\n - nam_tay_stat(:, 0:1) in panel_adgj/nam.obs.nc: black dots\r\n \r\n Panel h: \r\n - nao_tay_stat(:, 0:1) in panel_behk/nao.amip.cmip6.nc: multimodel ensemble mean for the orange dot\r\n - nao_tay_stat(:, 0:1) in panel_behk/nao.hist.cmip5.nc: blue crosses, with multimodel ensemble mean for the blue dot\r\n - nao_tay_stat(:, 0:1) in panel_behk/nao.hist.cmip6.nc: red crosses, with multimodel ensemble mean for the red dot\r\n - nao_tay_stat(:, 0:1) in panel_behk/nao.obs.nc: black dots\r\n \r\n Panel i: \r\n - sam_tay_stat(:, 0:1) in panel_cfil/sam.amip.cmip6.nc: multimodel ensemble mean for the orange dot\r\n - sam_tay_stat(:, 0:1) in panel_cfil/sam.hist.cmip5.nc: blue crosses, with multimodel ensemble mean for the blue dot\r\n - sam_tay_stat(:, 0:1) in panel_cfil/sam.hist.cmip6.nc: red crosses, with multimodel ensemble mean for the red dot\r\n - sam_tay_stat(:, 0:1) in panel_cfil/sam.obs.nc: black dots\r\n \r\n Panel j: \r\n - nam_pc_trends in panel_adgj/nam.amip.cmip6.nc: multimodel ensemble mean for orange vertical line\r\n - nam_pc_trends in panel_adgj/nam.hist.cmip5.nc: multimodel ensemble mean for blue vertical line\r\n - nam_pc_trends in panel_adgj/nam.hist.cmip6.nc: histogram, with multimodel ensemble mean for red vertical line\r\n - nam_pc_trends in panel_adgj/nam.obs.nc: black vertical lines\r\n \r\n Panel k: \r\n - nao_pc_trends in panel_behk/nao.amip.cmip6.nc: multimodel ensemble mean for orange vertical line\r\n - nao_pc_trends in panel_behk/nao.hist.cmip5.nc: multimodel ensemble mean for blue vertical line\r\n - nao_pc_trends in panel_behk/nao.hist.cmip6.nc: histogram, with multimodel ensemble mean for red vertical line\r\n - nao_pc_trends in panel_behk/nao.obs.nc: black vertical lines\r\n \r\n Panel l: \r\n - sam_pc_trends in panel_cfil/sam.amip.cmip6.nc: multimodel ensemble mean for orange vertical line\r\n - sam_pc_trends in panel_cfil/sam.hist.cmip5.nc: multimodel ensemble mean for blue vertical line\r\n - sam_pc_trends in panel_cfil/sam.hist.cmip6.nc: histogram, with multimodel ensemble mean for red vertical line\r\n - sam_pc_trends in panel_cfil/sam.obs.nc: black vertical lines\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n Multimodel ensemble means and histograms are obtained after weighting individual members with the inverse of the ensemble size of the same model. ensemble_assign in each file provides the model number to which each ensemble member belongs. This weighting does not apply to the sign agreement calculation.\r\n\r\nMultimodel ensemble mean of the pattern correlation in Taylor statistics is calculated via Fisher z-transformation and back transformation.\r\n\r\n---------------------------------------------------\r\n Sources of additional information\r\n ---------------------------------------------------\r\n The following weblinks are provided in the Related Documents section of this catalogue record:\r\n - Link to the report component containing the figure (Chapter 3)\r\n - Link to the Supplementary Material for Chapter 3, which contains supporting information on the figure in Section and details on the input data used in Table 3.SM.1\r\n - Link to the code for the figure, archived on Zenodo\r\n - Link to the figure on the IPCC AR6 website" }, "onlineresource_set": [] }, { "ob_id": 37131, "uuid": "d9c84d55799b40f29f2c7ad18c9b2e35", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/deposited2022/Oxford_MansfieldRd_roadside_NO", "numberOfFiles": 0, "volume": 0, "fileFormat": "Data are CSV formatted with an explanatory text file (Guide_for_DATA.txt).", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37134, "uuid": "ff28357774284381b23561a8382509d0", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/deposited2022/Oxford_MansfieldRd_roadside_NO", "numberOfFiles": 0, "volume": 0, "fileFormat": "Data are CSV formatted with an explanatory text file (Guide_for_DATA.txt).", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37138, "uuid": "45ea77a5733c4e1f9f0ef41731ca5ba2", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/deposited2022/Oxford_MansfieldRd_roadside_NO", "numberOfFiles": 33, "volume": 1772688612, "fileFormat": "Data are CSV formatted with an explanatory text file (Guide_for_DATA.txt).", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37137, "uuid": "53a1acaf5adb4b22b19397bf08d229ef", "short_code": "ob", "title": "Transition Air: Street side measurements of dispersed NO from an NO bottle in Oxford.", "abstract": "This dataset contains measurements of dispersed Nitric Oxide (NO) made at a relatively low traffic area, Mansfield Road, in the city of Oxford, U.K. as part of project funded through the TRANSITION AIR QUALITY Network. NO was released from a bottle with a known concentration of 10,000ppm NO in nitrogen mounted at the back of an electric van and the dispersed NO measured at the roadside using fast response sensors provided by Cambustion Ltd. These measurements were then used to validate Computational Fluid Dynamics Models. The tests were carried out during a single day at different locations on the road. Wind direction, wind speed and the concentration of sensed NO are recorded and presented in the archived dataset." }, "onlineresource_set": [] }, { "ob_id": 37144, "uuid": "3a4f932d48c544a09ab7679e15b820cf", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/esacci/fire/data/burned_area/Sentinel3_SYN/grid/v1.0/", "numberOfFiles": 13, "volume": 25977800, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34729, "uuid": "3aaaaf94813e48f18f2b83242a8dacbe", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): Sentinel-3 SYN Burned Area Grid product, version 1.0", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. The Sentinel-3 SYN Fire_cci v1.0 grid product described here contains gridded data on global burned area derived from surface reflectance data from the OLCI and SLSTR instruments (combined as the Synergy (SYN) product) onboard the Sentinel-3 A&B satellites, complemented by VIIRS thermal information. This product, called FireCCIS310 for short, is currently available for 2019, but it is foreseen to be extended for additional years.\r\n\r\nThis gridded dataset has been derived from the FireCCIS310 pixel product (also available) by summarising its burned area information into a regular grid covering the Earth at 0.25 x 0.25 degrees resolution and at monthly temporal resolution. Information on burned area is included in 22 individual quantities: sum of burned area, standard error, fraction of burnable area, fraction of observed area, and the burned area for 18 land cover classes, as defined by the Copernicus Climate Change Initiative(C3S) Land Cover v2.1.1 product. For further information on the product and its format see the Product User Guide in the linked documentation." }, "onlineresource_set": [] }, { "ob_id": 37145, "uuid": "e4cc60b14ff34da88894e412c0a6f20e", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/esacci/fire/data/burned_area/Sentinel3_SYN/pixel/v1.0/", "numberOfFiles": 361, "volume": 12497999502, "fileFormat": "Data are in GeoTiff format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34730, "uuid": "c98515f1934a4db68d2007b47c5a8d04", "short_code": "ob", "title": "ESA Fire Climate Change Initiative (Fire_cci): Sentinel-3 SYN Burned Area Pixel product, version 1.0", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned area derived from satellite observations. The Sentinel-3 SYN Fire_cci v1.0 pixel product is distributed as 6 continental tiles and is based upon surface reflectance data from the OLCI and SLSTR instruments (combined as the Synergy (SYN) product) onboard the Sentinel-3 A&B satellites. This information is complemented by VIIRS thermal information. This product, called FireCCIS310 for short, is currently available for 2019, but it is foreseen to be extended for additional years.\r\n\r\nThe FireCCIS310 Pixel product described here includes maps at 0.002777-degree (approx. 300m) resolution. Burned area (BA) information includes 3 individual files, packed in a compressed tar.gz file: date of BA detection (labelled JD), the confidence level (CL, a probability value estimating the confidence that a pixel is actually burned), and the land cover (LC) information as defined in the Copernicus Climate Change Service (C3S) Land Cover v2.1.1 product. An unpacked version of the data is also available. For further information on the product and its format see the Product User Guide in the linked documentation." }, "onlineresource_set": [] }, { "ob_id": 37149, "uuid": "3c562d89e23d40a1a354777480091fc7", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/cru/data/cru_ts/cru_ts_3.23_clim", "numberOfFiles": 41, "volume": 995759026, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37093, "uuid": "10ff77c6b52143d987ab1f4a46834f5c", "short_code": "ob", "title": "CRU TS3.23_clim: 30 year climatologies derived from 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": "These data are 30 year climatologies produced from 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. 4 sets of climatologies are produced covering the periods: 1901-1930, 1931-1960, 1961 - 1990 and 1984-2013.\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\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)." }, "onlineresource_set": [] }, { "ob_id": 37151, "uuid": "f8884ff09d194213a211ca34dadddae2", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/deposited2022/GorgonIPShocks", "numberOfFiles": 101, "volume": 58985008523, "fileFormat": "Data are HDF5 formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37150, "uuid": "a3231e64ffea42e7ab9ff0cf72302050", "short_code": "ob", "title": "SWIGS: Gorgon Magnetohydrodyamic Code Simulation Data: Magnetospheric and Ionospheric Conditions during Sudden Commencement", "abstract": "This dataset contains outputs generated using the Gorgon Magnetohydrodynamic (MHD) code, for simulations of the magnetosphere-ionosphere system during impact by a series of interplanetary shocks with different solar wind conditions and dipole magnetic field orientations. \r\n\r\nThe MHD equations were solved in the magnetosphere on a regular 3-D cartesian grid of resolution 0.25 RE (Earth radii), covering a domain of dimensions (-30,90) RE in X, (-40,40) RE in Y and (-40,40) RE in Z with an inner boundary at 3 RE. In this coordinate system the Sun lies in the negative X-direction, the Z axis is aligned to the dipole in the 0 degree tilt case (where positive tilt points the north magnetic pole towards the Sun), and Y completes the right-handed set. The ionospheric variables were calculated on a separate 2-D spherical grid of dimensions 128x256 in latitude and longitude (with the north pole at 90 degrees latitude and the Sun at 180 degrees longitude), coupled to the magnetospheric domain at the inner boundary. \r\n\r\n5 different shocks were simulated in total, with the following solar wind jump conditions injected at the sunward edge at 7200s simulation time:\r\n\r\nShocks 1-4: n = 5 /cm^3 -> 10 /cm^3 (number density) \r\n v = 400 km/s -> 600 km/s (velocity) \r\n T = 5 eV -> 417 eV (temperature) \r\n B = 2 nT -> 4 nT (interplanetary magnetic field) \r\n\r\nShock 5: n = 5 /cm^3 -> 20 /cm^3 (number density) \r\n v = 400 km/s -> 1000 km/s (velocity)\r\n T = 5 eV -> 1250 eV (temperature) \r\n B = 2 nT -> 4 nT (interplanetary magnetic field) \r\n\r\nShocks 1, 3 and 5 had an interplanetary magnetic field (IMF) clock angle of 180 degrees, i.e. B = Bz = -2 nT, whereas Shocks 2 and 3 had IMF clock angles of 135 degrees and 90 degrees, respectively. In addition, Shocks 1, 2, 3 and 5 had zero dipole tilt, whereas Shock 4 had a tilt angle of 30 degrees. These simulations employed zero electrical resistivity. The simulations of Shocks 1, 3 and 5 were then repeated utilising an explicit resistivity eta with value of eta/mu_0 = 5e10 m^2/s. The full set of 8 simulations are labelled 'Shock1', 'Shock2', 'Shock3', 'Shock4', 'Shock5' for the zero resistivity runs and 'Shock1_res', 'Shock3_res' and 'Shock5_res' for those with explicit resistivity. \r\n\r\nOutput grid data are timestamped in seconds and are defined at the centre of the grid cells, stored as .hdf5 files for each timestep. Output time-series data are for a single variable over a simulation time range, stored in .csv files. The simulation data corresponding to each shock are stored in separate directories, according to the simulation labels listed above.\r\n\r\nThe magnetospheric variables are stored in the files 'Gorgon_[YYYYMMDD]_[RUN]_MS_params_[XXXX]s.hdf5' where RUN is the simulation label and XXXX is the simulation time in seconds. The magnetospheric data are in SI units and include the magnetic field vector ('Bvec_c'), electric current density vector ('jvec') and ion thermal pressure ('P') for multiple timesteps following initialisation at 7200s of simulation time. The dataset for each magnetospheric variable is of shape (480,320,320,3) for vectors and (480,320,320) for scalars, where the first 3 dimensions are the grid indices in (X,Y,Z) indexed from negative to positive, and the final dimension is the cartesian vector components in (i,j,k).\r\n\r\nSimilarly, the ionospheric data are stored as 'Gorgon_[YYYYMMDD]_[RUN]_IS_params_[XXXX]s.hdf5', containing the field-aligned current density ('FAC') in SI units for multiple timesteps following initialisation at 7200s of simulation time. The dataset for each ionospheric variable is of shape (130, 256) where the first dimension is the grid index in colatitude, indexed from the north towards the south (i.e. 0 to 180 degrees), and the second dimension is the grid index in longitude, indexed from midnight towards noon via dawn (i.e. 0 to 360 degrees).\r\n\r\nFinally, the time-series data are stored as 'Gorgon_[YYYYMMDD]_[RUN]_[XXX].csv' where 'X' is the simulation label and 'XXX' is the time-series variable. These include the subsolar magnetopause standoff distance 'RMP' in RE, and the North (and South) polar cap flux content 'FPC' in Wb*RE^2; in each case the first column contains the simulation time in seconds, with the variables in the second (and third) column(s). NE/P017142/1" }, "onlineresource_set": [] }, { "ob_id": 37154, "uuid": "9c4729d7a225481dbfa161ecbba20f79", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/deposited2021/bbubl/data/bham-avian-sensor", "numberOfFiles": 102, "volume": 102093452, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 33121, "uuid": "f5a2bbcadec2428cab157653a7039919", "short_code": "ob", "title": "BBUBL: airborne meteorological measurements from various avian sensor packages for flights in 2018-19 over the Birmingham conurbation", "abstract": "This dataset contains data from Avian-Meteorology-Instrument Packages (AvMIPs) from a series of flights over Birmingham as part of the Biotelemetry/Bio-aerial-platforms for the Urban Boundary Layer (BBUBL) project (NERC grant: NE/N003195/1), also known as City Flocks. The flights took place in 2018 and 2019.\r\n\r\nThe BBUBL project utilised Biotelemetry/bio-aerial-platforms as a novel and practicable solution to the data paucity above urban rooftops in the Urban Boundary Layer. The project developed a suite of low-cost Avian-Meteorology-Instrument Packages (AvMIPs) for ensemble deployment in Birmingham as a suitably large and heterogeneous test case.\r\n\r\nA range of different sensor packages were used which were subsequently further characterised through air-tunnel tests. See Thomas et al. (2018) citation (DOI:10.1175/BAMS-D-16-0181.1) listed in the online resources section of this record for further details, including a precursor system flown on a larger bird species. In summary, temperature sensors were compared against U.K. Accreditation Service (UKAS)-accredited sensors in a controlled temperature chamber (WKL 34/40; Weiss Technik, Belgium and Germany) and in ambient conditions at the University of Birmingham weather station.\r\n\r\nAdditional material by Thomas et al. (2018) included in the online resource section of this record provide additional material regarding the project and instrumentation usage.\r\n\r\nNote, within the data there are a range of sensor packet and bird IDs used to denote the different bird-sensor package combinations used. A range of sensor packets were used, with one lost and others found unusable, resulting in the sensor packet numbers shown in the data. Bird ID were taken from the bird ring numbers unless clashes existed, in which case an alternative two digit number was used, therefore are not consecutive and no other data from other bird and sensor package combinations are available." }, "onlineresource_set": [] }, { "ob_id": 37161, "uuid": "af032e49b61c462092e8689f2a8cc940", "short_code": "result", "curationCategory": "C", "dataPath": "/badc/ukmo-nimrod/data/single-site/druima-starraig/raw-dual-polar", "numberOfFiles": 1, "volume": 977, "fileFormat": "Data are NIMROD binary formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37160, "uuid": "fd841b4cf6d0403f99f1f9a9252fc0e2", "short_code": "ob", "title": "Druim a'Starraig C-band rain radar dual polar products", "abstract": "Dual-polar products from the Met Office's Druim a'Starraig C-band rain radar, Isle of Lewis, Scotland. Data from this site includes augmented ldr (linear depolarisation ratio) and zdr (differential reflectivity) scan data (both long and short pulse) available from August 2018 at present. The radar is a C-band (5.3 cm wavelength) radar and data are received by the Nimrod system at 5 minute intervals." }, "onlineresource_set": [] }, { "ob_id": 37162, "uuid": "77ee27f9fe85489d8ef9214074fe284a", "short_code": "result", "curationCategory": "C", "dataPath": "/badc/ukmo-nimrod/data/single-site/holehead/raw-dual-polar", "numberOfFiles": 1, "volume": 969, "fileFormat": "Data are NIMROD binary formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37159, "uuid": "00c64fb29e89467098e2bd4f62c7ff81", "short_code": "ob", "title": "Holehead C-band rain radar dual polar products", "abstract": "Dual-polar products from the Met Office's Holehead C-band rain radar, Stirling, Scotland. Data from this site include augmented ldr (linear depolarisation ratio) and zdr (differential reflectivity) scan data (both long and short pulse) available from August 2018 at present. The radar is a C-band (5.3 cm wavelength) radar and data are received by the Nimrod system at 5 minute intervals." }, "onlineresource_set": [] }, { "ob_id": 37164, "uuid": "6a300e9cb1624a1090930f53e9202f96", "short_code": "result", "curationCategory": "C", "dataPath": "/badc/ukmo-nimrod/data/single-site/crug-y-gorrllwyn/raw-dual-polar", "numberOfFiles": 1, "volume": 976, "fileFormat": "Data are NIMROD binary formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37163, "uuid": "fb667df2622f4a95bab00635ec6f233b", "short_code": "ob", "title": "Crug-y-Gorllwyn C-band rain radar dual polar products", "abstract": "Dual-polar products from the Met Office's Crug-y-Gorllwyn C-band rain radar, Carmarthen, Wales. Data from this site include augmented ldr (linear depolarization ratio) and zdr (differential reflectivity) scan data (both long and short pulse), available from August 2018 to present. The radar is a C-band (5.3 cm wavelength) radar and data are received by the Nimrod system at 5 minute intervals." }, "onlineresource_set": [] }, { "ob_id": 37166, "uuid": "669fa0cda36640e2b68d14f3f4aa6b65", "short_code": "result", "curationCategory": "C", "dataPath": "/badc/ukmo-nimrod/data/single-site/clee-hill/raw-dual-polar", "numberOfFiles": 1, "volume": 970, "fileFormat": "Data are NIMROD binary formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37165, "uuid": "23357b1190f2439789a4ec3cbb9a88bf", "short_code": "ob", "title": "Clee Hill C-band rain radar dual polar products", "abstract": "Dual-polar products from the Met Office's Clee Hill C-band rain radar, Shropshire, England. Data from this site include augmented ldr (linear depolarisation ratio) and zdr (differential reflectivity) scan data (both long and short pulse), available from August 2018 to present. The radar is a C-band (5.3 cm wavelength) radar and data are received by the Nimrod system at 5 minute intervals." }, "onlineresource_set": [] }, { "ob_id": 37167, "uuid": "9d17a2805ccc4c67bb18be804a5d2c69", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/belgium/beauvechain/belgium-defence-vaisala-cl31_A", "numberOfFiles": 1378, "volume": 2113400013, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37168, "uuid": "258dec56a96d496a869b07e8f986118f", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 instrument deployed at Beauvechain, Belgium", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 deployed at Beauvechain, Belgium.\r\n\r\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\r\n\r\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-06458. See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\r\n \r\nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 37172, "uuid": "b243c7fadd924f9a837de6e8e58d42aa", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/belgium/chievres/belgium-defence-vaisala-cl31_A", "numberOfFiles": 365, "volume": 516052282, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37173, "uuid": "8666c40642f44e8eba0e93d779d15303", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 instrument deployed at Chievres, Belgium", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 deployed at Chievres, Belgium.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-06432.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 37176, "uuid": "83f9fc7850e0417985e49a62bbe0f7dd", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/belgium/elsenborn/belgium-defence-vaisala-cl31_A", "numberOfFiles": 1322, "volume": 1867049446, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37177, "uuid": "8245a8523e1b440782f3e99500c93a4d", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 instrument deployed at Elsenborn, Belgium", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 deployed at Elsenborn, Belgium.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-06496.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 37180, "uuid": "a1f57af493a34dada4a174016e3c768b", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/belgium/florennes/belgium-defence-vaisala-cl31_A", "numberOfFiles": 1364, "volume": 2244605500, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37181, "uuid": "b3b175d8181b4e72a1a69999b627bbbd", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 instrument deployed at Florennes, Belgium", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 deployed at Florennes, Belgium.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-06456.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 37184, "uuid": "42ddf312d32649efb66606dd6ce4db0c", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/belgium/kleine-brogel/belgium-defence-vaisala-cl31_A", "numberOfFiles": 1370, "volume": 2302860365, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37185, "uuid": "0717e78630d745b7923468f0af15e68f", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 instrument deployed at Kleine Brogel, Belgium", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 deployed at Kleine Brogel, Belgium.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-06479.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 37188, "uuid": "a4060f189a1e43fab1527d3226cadd59", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/belgium/koksijde/belgium-defence-vaisala-cl31_A", "numberOfFiles": 1362, "volume": 2016626529, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37189, "uuid": "c2c34192c96f4c87b4ce1ac7770bc493", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 instrument deployed at Koksijde, Belgium", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 deployed at Koksijde, Belgium.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-06400.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 37192, "uuid": "b3ecf8f473b4461bac2c4ab8b6fc37fe", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/belgium/schaffen/belgium-defence-vaisala-cl31_A", "numberOfFiles": 1361, "volume": 1426149674, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37193, "uuid": "f86ab20b7ab848d2a3e2f263fef26218", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 instrument deployed at Schaffen, Belgium", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 deployed at Schaffen, Belgium.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-06465.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 37196, "uuid": "97d3ca8fd6ba49909bdb95d6ee856174", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/belgium/semmerzake/belgium-defence-vaisala-cl31_A", "numberOfFiles": 366, "volume": 731831338, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37197, "uuid": "d162da75989b4009835ae85a18894428", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 instrument deployed at Semmerzake, Belgium", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Belgium Defence's Vaisala CL31 deployed at Semmerzake, Belgium.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-06428.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 37200, "uuid": "f3a78a4bd8294bf9afe0b56326294ac7", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/spain/valladolid/granada-university-lufft-chm15k_B", "numberOfFiles": 3, "volume": 3112486, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37201, "uuid": "155ea5ef2f3f441e9937a8c92b6000a9", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from UGR's Lufft CHM15k \"Nimbus\" instrument B deployed at Valladolid, Spain", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from University of Granada (UGR)'s Lufft CHM15k \"Nimbus\" deployed at Valladolid, Spain.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20008-0-UVA.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 37203, "uuid": "79a5cf63a56945ed9d6643e2d842368a", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/switzerland/grenchen/meteoswiss-vaisala-cl31_A", "numberOfFiles": 1403, "volume": 2280270354, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37204, "uuid": "ac7ca49f9c3f4531b2e6a075f0b044bb", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from MeteoSwiss's Vaisala CL31 instrument deployed at Grenchen, Switzerland", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from MeteoSwiss's Vaisala CL31 deployed at Grenchen, Switzerland.\n\nThese data were produced by the EUMETNET's E-PROFILE processing hub as part of the ceilometer and lidar network operated as part of the by EUMETNET members. This network covers most of Europe with additional sites worldwide.\n\nThe site has a corresponding WMO Integrated Global Observing System (WIGOS) id: 0-20000-0-06632.\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool.\n \nEUMETNET is a grouping of 31 European National Meteorological Services that provides a framework to organise co-operative programmes between its Members in the various fields of basic meteorological activities. One such programme is the EUMETNET Profiling Programme: E-PROFILE. See EUMETNET page linked from this record for further details of EUMETNET's activities." }, "onlineresource_set": [] }, { "ob_id": 37215, "uuid": "0ecec808856e4b88980edc000a7cf2ae", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadUK-Grid/v1.1.0.0/river", "numberOfFiles": 163, "volume": 26918190, "fileFormat": "Data are NetCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37207, "uuid": "39b1337028d147d9b572ae352490bed0", "short_code": "ob", "title": "HadUK-Grid Climate Observations by UK river basins, v1.1.0.0 (1836-2021)", "abstract": "HadUK-Grid is a collection of gridded climate variables derived from the network of UK land surface observations. The data have been interpolated from meteorological station data onto a uniform grid to provide complete and consistent coverage across the UK. These data at 1 km resolution have been averaged across a set of discrete geographies defining UK river basins consistent with data from UKCP18 climate projections. The dataset spans the period from 1836 to 2021, 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\nThe changes for v1.1.0.0 HadUK-Grid datasets are as follows:\r\n\r\n* The addition of data for calendar year 2021\r\n\r\n* The addition of 30 year averages for the new reference period 1991-2020\r\n\r\n* An update to 30 year averages for 1961-1990 and 1981-2010. This is an order of operation change. In this version 30 year averages have been calculated from the underlying monthly/seasonal/annual grids (grid-then-average) in previous version they were grids of interpolated station average (average-then-grid). This order of operation change results in small differences to the values, but provides improved consistency with the monthly/seasonal/annual series grids. However this order of operation change means that 1961-1990 averages are not included for sfcWind or snowlying variables due to the start date for these variables being 1969 and 1971 respectively.\r\n\r\n* A substantial new collection of monthly rainfall data have been added for the period before 1960. These data originate from the rainfall rescue project (Hawkins et al. 2022) and this source now accounts for 84% of pre-1960 monthly rainfall data, and the monthly rainfall series has been extended back to 1836.\r\n\r\nNet changes to the input station data used to generate this dataset:\r\n\r\n-Total of 122664065 observations\r\n\r\n-118464870 (96.5%) unchanged\r\n\r\n-4821 (0.004%) modified for this version\r\n\r\n-4194374 (3.4%) added in this version\r\n\r\n-5887 (0.005%) deleted from this version\r\n\r\nThe primary purpose of these data are to facilitate monitoring of UK climate and research into climate change, impacts and adaptation. The datasets have been created by the Met Office with financial support from the Department for Business, Energy and Industrial Strategy (BEIS) and Department for Environment, Food and Rural Affairs (DEFRA) in order to support the Public Weather Service Customer Group (PWSCG), the Hadley Centre Climate Programme, and the UK Climate Projections (UKCP18) project. The output from a number of data recovery activities relating to 19th and early 20th Century data have been used in the creation of this dataset, these activities were supported by: the Met Office Hadley Centre Climate Programme; the Natural Environment Research Council project \"Analysis of historic drought and water scarcity in the UK\"; the UK Research & Innovation (UKRI) Strategic Priorities Fund UK Climate Resilience programme; The UK Natural Environment Research Council (NERC) Public Engagement programme; the National Centre for Atmospheric Science; National Centre for Atmospheric Science and the NERC GloSAT project; and the contribution of many thousands of public volunteers. The dataset is provided under Open Government Licence." }, "onlineresource_set": [] } ] }