Result List
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{ "count": 11555, "next": "https://api.catalogue.ceda.ac.uk/api/v3/results/?format=api&limit=100&offset=9600", "previous": "https://api.catalogue.ceda.ac.uk/api/v3/results/?format=api&limit=100&offset=9400", "results": [ { "ob_id": 37568, "uuid": "cb9434f2709248388a73a36d763f6761", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig27/v20220616", "numberOfFiles": 5, "volume": 471935, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37567, "uuid": "ceae289f1a56414ea708f43db83fc2c6", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.27 (v20220616)", "abstract": "Data for Figure 3.27 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 3.27 shows maps of multi-decadal salinity trends for the near-surface ocean.\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 Figure subpanels\r\n ---------------------------------------------------\r\n Technically there are two panels, they are named in the datasets as top and bottom, but the data is stored in the parent directory. Data provided for bottom panel.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n The dataset contains salinity data:\r\n \r\n - climatological mean from CMIP6 models (1950-2014)\r\n - simulated trend from CMIP6 models (1950-2014)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n - ocean_salinity_cmip6.nc: climatological salinity (1950-2014) from CMIP6 models (black contours) in a bottom panel\r\n - ocean_salinity_trends_cmip6.nc: salinity trends (1950-2014) from CMIP6 models (colored shades) in a bottom panel\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The observational data from here (top panel) is taken from the file:\r\n\r\nDurackandWijffels_GlobalOceanChanges_19500101-20191231__210122-205355_beta.nc. The field of interest are salinity_mean (shown as black contours) and salinity_change (shown in colourscale). The file was archived as input data for Figure 2.27. The link to this dataset is provided in the Related Documents section of this catalogue record.\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 input data figure 2.27\r\n - Link to the figure on the IPCC AR6 website" }, "onlineresource_set": [] }, { "ob_id": 37571, "uuid": "15400b0af9154606a6df3bd771e19a37", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig29/v20220616", "numberOfFiles": 4, "volume": 32912, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37570, "uuid": "a8915aca7806434984baab86835a1b18", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.29 (v20220616)", "abstract": "Data for Figure 3.29 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 3.29 shows simulated and observed global mean sea level change due to thermal expansion for CMIP6 models and observations relative to the baseline period 1850-1900. \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 List of data provided\r\n ---------------------------------------------------\r\n The dataset has contains timeseries for:\r\n \r\n - CMIP6 thermosteric sea level change anomalies from 1850-2014 simulated with anthropogenic and natural forcings (historical experiment)\r\n - CMIP6 thermosteric sea level change anomalies from 1850-2014 simulated with natural forcings only (hist-nat experiment)\r\n - CMIP6 thermosteric sea level change anomalies from 1850-2014 simulated with anthropogenic greenhouse gases forcings only (hist-GHG experiment)\r\n - CMIP6 thermosteric sea level change anomalies from 1850-2014 simulated with anthropogenic aerosol forcings only (hist-aer experiment)\r\n - observed thermosteric sea level change anomalies from 1971-2018\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n - global_mean_sea_level_anomalies.csv relates to brown, green, blue grey and black lines and shadings (1850-2019)\r\n Additional information about data provided in relation to figure in the file header.\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The observational datasets are the ones used in Chapter 2 and Chapter 9 CCB1 ('AR6_FGD_assessment_timeseries_ThSL.csv'). The link to this dataset is provided in the Related Documents section of this catalogue record.\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 dataset for figure CCB1 Chapter 9\r\n - Link to input data figure 2.27\r\n - Link to the figure on the IPCC AR6 website" }, "onlineresource_set": [] }, { "ob_id": 37576, "uuid": "5df86916450c40b3abf34305e1900ed4", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/deposited2022/modis_cdnc_sampling_gridded/data/", "numberOfFiles": 14338, "volume": 127148603021, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37566, "uuid": "864a46cc65054008857ee5bb772a2a2b", "short_code": "ob", "title": "Cloud droplet number concentration, calculated from the MODIS (Moderate resolution imaging spectroradiometer) cloud optical properties retrieval and gridded using different sampling strategies", "abstract": "This dataset contains cloud droplet number concentrations (CDNC), gridded to 1 by 1 degree resolution using a variety of sampling methods to select valid retrievals. Data from the MODIS (Moderate resolution imaging spectroradiometer) instruments on both the Terra (morning overpass) and Aqua (Afternoon overpass) satellites are available (indicated by a T or A in the filename). This product is gridded using the MODIS collection 6 definition of a day. These sampling methods have been compared against multiple flight campaigns, see Gryspeerdt et al., The impact of sampling strategy on the cloud droplet number concentration estimated from satellite data. Atmos. Meas. Tech. 2022.\"\r\n\r\nErrata: The latitude values in these files are currently inverted, resulting in the data in the files appearing 'upside-down'. As a work-around, the data arrays can be reversed along the latitude axis. Corrected versions of the files will be uploaded shortly.'" }, "onlineresource_set": [] }, { "ob_id": 37578, "uuid": "b61b01d05a114880b2714b64653ea4f9", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/capeverde/data/cv-ozone/", "numberOfFiles": 132, "volume": 103077604, "fileFormat": "Nasa-Ames and NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37049, "uuid": "ac3e18f7ef954b28990d9ec12cb77f2b", "short_code": "ob", "title": "Cape Verde Atmospheric Observatory: Ozone measurements (2006 onwards)", "abstract": "Data from observations made at the Cape Verde Atmospheric Observatory (CVAO) which exists to advance understanding of climatically significant interactions between the atmosphere and ocean and to provide a regional focal point and long-term data. \r\n\r\nThe observatory is based on Calhau Island of São Vicente, Cape Verde at 16.848N, 24.871W, in the tropical Eastern North Atlantic Ocean, a region which is data poor but plays a key role in atmosphere-ocean interactions of climate-related and biogeochemical parameters including greenhouse gases. It is an open-ocean site that is representative of a region likely to be sensitive to future climate change, and is minimally influenced by local effects and intermittent continental pollution. \r\n\r\nThe dataset contains a longterm record of ozone mixing ratio measurements made from several instruments at the Cape Verde Observatory." }, "onlineresource_set": [] }, { "ob_id": 37582, "uuid": "b45be70fe48842a59861d7477cd70e8a", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig36/v20220620", "numberOfFiles": 4, "volume": 389746, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37581, "uuid": "8af00e7bba784c1cbf4c16fef984aeb6", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.36 (v20220620)", "abstract": "Data for Figure 3.36 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 3.36 shows observed and simulated life cycle of El Niño and La Niña events.\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. All the data are provided in enso_lifecycle.nc file.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains\r\n \r\n - Composite time series of the ENSO index for El Niño events\r\n - Composite time series of the ENSO index for La Niña events\r\n - Mean duration of El Niño events\r\n - Mean duration of La Niña events\r\n\r\nin observations, CMIP5 historical-RCP4.5 and and CMIP6 historical simulations.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel a:\r\n - ts_elnino_obs; black curves\r\n . ERSSTv5, dashed lines: dataset = 1\r\n . HadISST, solid lines: dataset = 2\r\n - ts_elnino_cmip5: The ENSO index time series in each ensemble member of CMIP5 models; blue curve and shading\r\n - ts_elnino_cmip6: The ENSO index time series in each ensemble member of CMIP6 models; red curve and shading\r\n \r\n Panel b:\r\n - ts_lanina_obs; black curves\r\n . ERSSTv5, dashed lines: dataset = 1\r\n . HadISST, solid lines: dataset = 2\r\n - ts_lanina_cmip5: The ENSO index time series in each ensemble member of CMIP5 models; blue curve and shading\r\n - ts_lanina_cmip6: The ENSO index time series in each ensemble member of CMIP6 models; red curve and shading\r\n \r\n Panel c:\r\n - duration_elnino_obs; black vertical lines and numbers in the top right box\r\n . ERSSTv5, dashed lines: dataset = 1\r\n . HadISST, solid lines: dataset = 2\r\n - duration_elnino_cmip5: El Nino duration in each ensemble member of CMIP5 models; blue box-whisker and number in the top right box\r\n - duration_elnino_cmip6; El Nino duration in each ensemble member of CMIP6 models; red dots, red box-whisker and number in the top right box\r\n . ACCESS-CM2: ens_cmip6 = 1 - 3\r\n . ACCESS-ESM1-5: ens_cmip6 = 4 - 23\r\n . AWI-CM-1-1-MR: ens_cmip6 = 24 - 28\r\n . AWI-ESM-1-1-LR: ens_cmip6 = 29\r\n . BCC-CSM2-MR: ens_cmip6 = 30 - 32\r\n . BCC-ESM1: ens_cmip6 = 33 - 35\r\n . CAMS-CSM1-0: ens_cmip6 = 36-38\r\n . CanESM5-CanOE: ens_cmip6 = 39 - 41\r\n . CanESM5: ens_cmip6 = 42 - 106\r\n . CESM2-FV2: ens_cmip6 = 107 - 109\r\n . CESM2: ens_cmip6 = 110 - 120\r\n . CESM2-WACCM-FV2: ens_cmip6 = 121 - 123\r\n . CESM2-WACCM: ens_cmip6 = 124 - 126\r\n . CIESM: ens_cmip6 = 127 - 129\r\n . CMCC-CM2-HR4: ens_cmip6 = 130\r\n . CMCC-CM2-SR5: ens_cmip6 = 131\r\n . CMCC-ESM2: ens_cmip6 = 132\r\n . CNRM-CM6-1-HR: ens_cmip6 = 133\r\n . CNRM-CM6-1: ens_cmip6 = 134 - 162\r\n . CNRM-ESM2-1: ens_cmip6 = 163 - 172\r\n . E3SM-1-0: ens_cmip6 = 173 - 177\r\n . E3SM-1-1-ECA: ens_cmip6 = 178\r\n . E3SM-1-1: ens_cmip6 = 179\r\n . EC-Earth3-AerChem: ens_cmip6 = 180, 181\r\n . EC-Earth3-CC: ens_cmip6 = 182\r\n . EC-Earth3: ens_cmip6 = 183 - 204\r\n . EC-Earth3-Veg-LR: ens_cmip6 = 205 - 207\r\n . EC-Earth3-Veg: ens_cmip6 = 208 - 215\r\n . FGOALS-f3-L: ens_cmip6 = 216 - 218\r\n . FGOALS-g3: ens_cmip6 = 219 - 224\r\n . FIO-ESM-2-0: ens_cmip6 = 225 - 227\r\n . GFDL-CM4: ens_cmip6 = 228\r\n . GFDL-ESM4: ens_cmip6 = 229 - 231\r\n . GISS-E2-1-G-CC: ens_cmip6 = 232\r\n . GISS-E2-1-G: ens_cmip6 = 233 - 278\r\n . GISS-E2-1-H: ens_cmip6 = 279 - 302\r\n . HadGEM3-GC31-LL: ens_cmip6 = 303 - 306\r\n . HadGEM3-GC31-MM: ens_cmip6 = 307 - 310\r\n . IITM-ESM: ens_cmip6 = 311\r\n . INM-CM4-8: ens_cmip6 = 312\r\n . INM-CM5-0: ens_cmip6 = 313 - 322\r\n . IPSL-CM5A2-INCA: ens_cmip6 = 323\r\n . IPSL-CM6A-LR: ens_cmip6 = 324 - 355\r\n . KACE-1-0-G: ens_cmip6 = 356-358\r\n . KIOST-ESM: ens_cmip6 = 359\r\n . MCM-UA-1-0: ens_cmip6 = 360, 361\r\n . MIROC6: ens_cmip6 = 362 - 411\r\n . MIROC-ES2L: ens_cmip6 = 412 - 421\r\n . MPI-ESM-1-2-HAM: ens_cmip6 = 422 - 424\r\n . MPI-ESM1-2-HR: ens_cmip6 = 425 - 434\r\n . MPI-ESM1-2-LR: ens_cmip6 = 435 - 444\r\n . MRI-ESM2-0: ens_cmip6 = 445 - 450\r\n . NESM3: ens_cmip6 = 451 - 455\r\n . NorCPM1: ens_cmip6 = 456 - 485\r\n . NorESM2-LM: ens_cmip6 = 486 - 488\r\n . NorESM2-MM: ens_cmip6 = 489 - 490\r\n . SAM0-UNICON: ens_cmip6 = 491\r\n . TaiESM1: ens_cmip6 = 492\r\n . UKESM1-0-LL: ens_cmip6 = 493 - 510\r\n \r\n Panel d:\r\n - duration_lanina_obs; black vertical lines and numbers in the top right box\r\n . ERSSTv5, dashed lines: dataset = 1\r\n . HadISST, solid lines: dataset = 2\r\n - duration_lanina_cmip5; La Nina duration in each ensemble member of CMIP5 models; blue box-whisker and number in the top right box\r\n - duration_lanina_cmip6; La Nina duration in each ensemble member of CMIP6 models; red dots, red box-whisker and number in the top right box\r\n . ACCESS-CM2: ens_cmip6 = 1 - 3\r\n . ACCESS-ESM1-5: ens_cmip6 = 4 - 23\r\n . AWI-CM-1-1-MR: ens_cmip6 = 24 - 28\r\n . AWI-ESM-1-1-LR: ens_cmip6 = 29\r\n . BCC-CSM2-MR: ens_cmip6 = 30 - 32\r\n . BCC-ESM1: ens_cmip6 = 33 - 35\r\n . CAMS-CSM1-0: ens_cmip6 = 36-38\r\n . CanESM5-CanOE: ens_cmip6 = 39 - 41\r\n . CanESM5: ens_cmip6 = 42 - 106\r\n . CESM2-FV2: ens_cmip6 = 107 - 109\r\n . CESM2: ens_cmip6 = 110 - 120\r\n . CESM2-WACCM-FV2: ens_cmip6 = 121 - 123\r\n . CESM2-WACCM: ens_cmip6 = 124 - 126\r\n . CIESM: ens_cmip6 = 127 - 129\r\n . CMCC-CM2-HR4: ens_cmip6 = 130\r\n . CMCC-CM2-SR5: ens_cmip6 = 131\r\n . CMCC-ESM2: ens_cmip6 = 132\r\n . CNRM-CM6-1-HR: ens_cmip6 = 133\r\n . CNRM-CM6-1: ens_cmip6 = 134 - 162\r\n . CNRM-ESM2-1: ens_cmip6 = 163 - 172\r\n . E3SM-1-0: ens_cmip6 = 173 - 177\r\n . E3SM-1-1-ECA: ens_cmip6 = 178\r\n . E3SM-1-1: ens_cmip6 = 179\r\n . EC-Earth3-AerChem: ens_cmip6 = 180, 181\r\n . EC-Earth3-CC: ens_cmip6 = 182\r\n . EC-Earth3: ens_cmip6 = 183 - 204\r\n . EC-Earth3-Veg-LR: ens_cmip6 = 205 - 207\r\n . EC-Earth3-Veg: ens_cmip6 = 208 - 215\r\n . FGOALS-f3-L: ens_cmip6 = 216 - 218\r\n . FGOALS-g3: ens_cmip6 = 219 - 224\r\n . FIO-ESM-2-0: ens_cmip6 = 225 - 227\r\n . GFDL-CM4: ens_cmip6 = 228\r\n . GFDL-ESM4: ens_cmip6 = 229 - 231\r\n . GISS-E2-1-G-CC: ens_cmip6 = 232\r\n . GISS-E2-1-G: ens_cmip6 = 233 - 278\r\n . GISS-E2-1-H: ens_cmip6 = 279 - 302\r\n . HadGEM3-GC31-LL: ens_cmip6 = 303 - 306\r\n . HadGEM3-GC31-MM: ens_cmip6 = 307 - 310\r\n . IITM-ESM: ens_cmip6 = 311\r\n . INM-CM4-8: ens_cmip6 = 312\r\n . INM-CM5-0: ens_cmip6 = 313 - 322\r\n . IPSL-CM5A2-INCA: ens_cmip6 = 323\r\n . IPSL-CM6A-LR: ens_cmip6 = 324 - 355\r\n . KACE-1-0-G: ens_cmip6 = 356-358\r\n . KIOST-ESM: ens_cmip6 = 359\r\n . MCM-UA-1-0: ens_cmip6 = 360, 361\r\n . MIROC6: ens_cmip6 = 362 - 411\r\n . MIROC-ES2L: ens_cmip6 = 412 - 421\r\n . MPI-ESM-1-2-HAM: ens_cmip6 = 422 - 424\r\n . MPI-ESM1-2-HR: ens_cmip6 = 425 - 434\r\n . MPI-ESM1-2-LR: ens_cmip6 = 435 - 444\r\n . MRI-ESM2-0: ens_cmip6 = 445 - 450\r\n . NESM3: ens_cmip6 = 451 - 455\r\n . NorCPM1: ens_cmip6 = 456 - 485\r\n . NorESM2-LM: ens_cmip6 = 486 - 488\r\n . NorESM2-MM: ens_cmip6 = 489 - 490\r\n . SAM0-UNICON: ens_cmip6 = 491\r\n . TaiESM1: ens_cmip6 = 492\r\n . UKESM1-0-LL: ens_cmip6 = 493 - 510\r\n\r\n\r\nAcronyms: ENSO - El Niño–Southern Oscillation, CMIP - Coupled Model Intercomparison Project, RCP - Representative Concentration Pathway, ERSST - Extended Reconstructed Sea Surface Temperature, HadISST - Hadley Centre Sea Ice and Sea Surface Temperature, ACCESS- CM2 – Australian Community Climate and Earth System Simulator coupled climate model, ACCESS- ESM – Australian Community Climate and Earth System Simulator Earth system model, AWI - Alfred Wegener Institute, BCC-CSM - Beijing Climate Center Climate System Model, CAMS - Chinese Academy of Meteorological Sciences, CanOE - Canadian Ocean Ecosystem, CESM2 - Community Earth System Model, WACCM - Whole Atmosphere Community Climate Model, CIESM - Community Integrated Earth System Model, CNCC - Centro Euro-Mediterraneo per I Cambiamenti Climatici, CNRM - Centre National de Recherches Météorologiques, E3SM - Energy Exascale Earth System Model, FGOALS - Flexible Global Ocean-Atmosphere-Land System Model, FIO-ESM - First Institute of Oceanography Earth System Model, GFDL - Geophysical Fluid Dynamics Laboratory, GISS - Goddard Institute for Space Studies, IITM - Indian Institute of Tropical Meteorology, INM - Institute for Numerical Mathematics, IPSL - Institut Pierre-Simon Laplace, KIOST-ESM - Korea Institute of Ocean Science & Technology Earth System, MIROC - Model for Interdisciplinary Research on Climate, MPI - Max-Planck-Institut für Meteorologie, NESM - Nanjing University of Information Science and Technology Earth System Model, NorCPM - Norwegian Climate Prediction Model, SAM0-UNICON - Seoul National University Atmosphere Model version 0 with a Unified Convection Scheme (SAM0-UNICON), TaiESM1 - Taiwan Earth System Model version 1, UKESM - The UK Earth System Modelling project.\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. The weight is provided as the weight attribute of ens_cmip5 and ens_cmip6.\r\nIf X(i) is the array, and w(i) the corresponding weight.\r\n\r\n\r\n- Mean shoud be suｍ_i(X(i) * w(i)) / sum_i(w(i))\r\n\r\n- For percentile values, \r\n\r\n1. Sort X and w so that X is in the ascending order\r\n\r\n2. 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\r\n3. Use X(j) or (X(j) + X(j - 1))/2 as the percentile value\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": 37585, "uuid": "bfebc56e228d42eca15df240b8266e43", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig37/v20220620", "numberOfFiles": 4, "volume": 55568, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37584, "uuid": "babcd0de678e4d10aef395f1a265da03", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.37 (v20220620)", "abstract": "Data for Figure 3.37 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 3.37 shows observed and simulated seasonality of ENSO.\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 two panels. All the data are provided in enso_seasonality.nc.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains\r\n \r\n - Climatological standard deviation of the ENSO index\r\n - A seasonality metric of the ENSO index\r\n \r\n in observations, CMIP5 historical-RCP4.5 and CMIP6 historical simulations.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel a:\r\n - stdv_enso_obs; black curves\r\n . ERSSTv5, dashed lines: dataset = 1\r\n . HadISST, solid lines: dataset = 2\r\n - stdv_enso_cmip5: Climatological standard deviation of the ENSO index time series in each ensemble member of CMIP5 models blue curve and shading\r\n - stdv_enso_cmip6: Climatological standard deviation of the ENSO index time series in each ensemble member of CMIP6 models; red curve and shading\r\n . ACCESS-CM2: ens_cmip6 = 1 - 3\r\n . ACCESS-ESM1-5: ens_cmip6 = 4 - 23\r\n . AWI-CM-1-1-MR: ens_cmip6 = 24 - 28\r\n . AWI-ESM-1-1-LR: ens_cmip6 = 29\r\n . BCC-CSM2-MR: ens_cmip6 = 30 - 32\r\n . BCC-ESM1: ens_cmip6 = 33 - 35\r\n . CAMS-CSM1-0: ens_cmip6 = 36-38\r\n . CanESM5-CanOE: ens_cmip6 = 39 - 41\r\n . CanESM5: ens_cmip6 = 42 - 106\r\n . CESM2-FV2: ens_cmip6 = 107 - 109\r\n . CESM2: ens_cmip6 = 110 - 120\r\n . CESM2-WACCM-FV2: ens_cmip6 = 121 - 123\r\n . CESM2-WACCM: ens_cmip6 = 124 - 126\r\n . CIESM: ens_cmip6 = 127 - 129\r\n . CMCC-CM2-HR4: ens_cmip6 = 130\r\n . CMCC-CM2-SR5: ens_cmip6 = 131\r\n . CMCC-ESM2: ens_cmip6 = 132\r\n . CNRM-CM6-1-HR: ens_cmip6 = 133\r\n . CNRM-CM6-1: ens_cmip6 = 134 - 162\r\n . CNRM-ESM2-1: ens_cmip6 = 163 - 172\r\n . E3SM-1-0: ens_cmip6 = 173 - 177\r\n . E3SM-1-1-ECA: ens_cmip6 = 178\r\n . E3SM-1-1: ens_cmip6 = 179\r\n . EC-Earth3-AerChem: ens_cmip6 = 180, 181\r\n . EC-Earth3-CC: ens_cmip6 = 182\r\n . EC-Earth3: ens_cmip6 = 183 - 204\r\n . EC-Earth3-Veg-LR: ens_cmip6 = 205 - 207\r\n . EC-Earth3-Veg: ens_cmip6 = 208 - 215\r\n . FGOALS-f3-L: ens_cmip6 = 216 - 218\r\n . FGOALS-g3: ens_cmip6 = 219 - 224\r\n . FIO-ESM-2-0: ens_cmip6 = 225 - 227\r\n . GFDL-CM4: ens_cmip6 = 228\r\n . GFDL-ESM4: ens_cmip6 = 229 - 231\r\n . GISS-E2-1-G-CC: ens_cmip6 = 232\r\n . GISS-E2-1-G: ens_cmip6 = 233 - 278\r\n . GISS-E2-1-H: ens_cmip6 = 279 - 302\r\n . HadGEM3-GC31-LL: ens_cmip6 = 303 - 306\r\n . HadGEM3-GC31-MM: ens_cmip6 = 307 - 310\r\n . IITM-ESM: ens_cmip6 = 311\r\n . INM-CM4-8: ens_cmip6 = 312\r\n . INM-CM5-0: ens_cmip6 = 313 - 322\r\n . IPSL-CM5A2-INCA: ens_cmip6 = 323\r\n . IPSL-CM6A-LR: ens_cmip6 = 324 - 355\r\n . KACE-1-0-G: ens_cmip6 = 356-358\r\n . KIOST-ESM: ens_cmip6 = 359\r\n . MCM-UA-1-0: ens_cmip6 = 360, 361\r\n . MIROC6: ens_cmip6 = 362 - 411\r\n . MIROC-ES2L: ens_cmip6 = 412 - 421\r\n . MPI-ESM-1-2-HAM: ens_cmip6 = 422 - 424\r\n . MPI-ESM1-2-HR: ens_cmip6 = 425 - 434\r\n . MPI-ESM1-2-LR: ens_cmip6 = 435 - 444\r\n . MRI-ESM2-0: ens_cmip6 = 445 - 450\r\n . NESM3: ens_cmip6 = 451 - 455\r\n . NorCPM1: ens_cmip6 = 456 - 485\r\n . NorESM2-LM: ens_cmip6 = 486 - 488\r\n . NorESM2-MM: ens_cmip6 = 489 - 490\r\n . SAM0-UNICON: ens_cmip6 = 491\r\n . TaiESM1: ens_cmip6 = 492\r\n . UKESM1-0-LL: ens_cmip6 = 493 - 510\r\n \r\n Panel b:\r\n - seasonality_enso_obs; black vertical lines and numbers in the top right box\r\n . ERSSTv5, dashed lines: dataset = 1\r\n . HadISST, solid lines: dataset = 2\r\n - seasonality_enso_cmip5; Seasonality metric in each ensemble member of CMIP5 models; blue box-whisker and number in the top right box\r\n - seasonality_enso_cmip6; Seasonality metric in each ensemble member of CMIP6 models; red dots, with their multimodal ensemble mean and percentiles for the red box-whisker and number in the top right box\r\n . ACCESS-CM2: ens_cmip6 = 1 - 3\r\n . ACCESS-ESM1-5: ens_cmip6 = 4 - 23\r\n . AWI-CM-1-1-MR: ens_cmip6 = 24 - 28\r\n . AWI-ESM-1-1-LR: ens_cmip6 = 29\r\n . BCC-CSM2-MR: ens_cmip6 = 30 - 32\r\n . BCC-ESM1: ens_cmip6 = 33 - 35\r\n . CAMS-CSM1-0: ens_cmip6 = 36-38\r\n . CanESM5-CanOE: ens_cmip6 = 39 - 41\r\n . CanESM5: ens_cmip6 = 42 - 106\r\n . CESM2-FV2: ens_cmip6 = 107 - 109\r\n . CESM2: ens_cmip6 = 110 - 120\r\n . CESM2-WACCM-FV2: ens_cmip6 = 121 - 123\r\n . CESM2-WACCM: ens_cmip6 = 124 - 126\r\n . CIESM: ens_cmip6 = 127 - 129\r\n . CMCC-CM2-HR4: ens_cmip6 = 130\r\n . CMCC-CM2-SR5: ens_cmip6 = 131\r\n . CMCC-ESM2: ens_cmip6 = 132\r\n . CNRM-CM6-1-HR: ens_cmip6 = 133\r\n . CNRM-CM6-1: ens_cmip6 = 134 - 162\r\n . CNRM-ESM2-1: ens_cmip6 = 163 - 172\r\n . E3SM-1-0: ens_cmip6 = 173 - 177\r\n . E3SM-1-1-ECA: ens_cmip6 = 178\r\n . E3SM-1-1: ens_cmip6 = 179\r\n . EC-Earth3-AerChem: ens_cmip6 = 180, 181\r\n . EC-Earth3-CC: ens_cmip6 = 182\r\n . EC-Earth3: ens_cmip6 = 183 - 204\r\n . EC-Earth3-Veg-LR: ens_cmip6 = 205 - 207\r\n . EC-Earth3-Veg: ens_cmip6 = 208 - 215\r\n . FGOALS-f3-L: ens_cmip6 = 216 - 218\r\n . FGOALS-g3: ens_cmip6 = 219 - 224\r\n . FIO-ESM-2-0: ens_cmip6 = 225 - 227\r\n . GFDL-CM4: ens_cmip6 = 228\r\n . GFDL-ESM4: ens_cmip6 = 229 - 231\r\n . GISS-E2-1-G-CC: ens_cmip6 = 232\r\n . GISS-E2-1-G: ens_cmip6 = 233 - 278\r\n . GISS-E2-1-H: ens_cmip6 = 279 - 302\r\n . HadGEM3-GC31-LL: ens_cmip6 = 303 - 306\r\n . HadGEM3-GC31-MM: ens_cmip6 = 307 - 310\r\n . IITM-ESM: ens_cmip6 = 311\r\n . INM-CM4-8: ens_cmip6 = 312\r\n . INM-CM5-0: ens_cmip6 = 313 - 322\r\n . IPSL-CM5A2-INCA: ens_cmip6 = 323\r\n . IPSL-CM6A-LR: ens_cmip6 = 324 - 355\r\n . KACE-1-0-G: ens_cmip6 = 356-358\r\n . KIOST-ESM: ens_cmip6 = 359\r\n . MCM-UA-1-0: ens_cmip6 = 360, 361\r\n . MIROC6: ens_cmip6 = 362 - 411\r\n . MIROC-ES2L: ens_cmip6 = 412 - 421\r\n . MPI-ESM-1-2-HAM: ens_cmip6 = 422 - 424\r\n . MPI-ESM1-2-HR: ens_cmip6 = 425 - 434\r\n . MPI-ESM1-2-LR: ens_cmip6 = 435 - 444\r\n . MRI-ESM2-0: ens_cmip6 = 445 - 450\r\n . NESM3: ens_cmip6 = 451 - 455\r\n . NorCPM1: ens_cmip6 = 456 - 485\r\n . NorESM2-LM: ens_cmip6 = 486 - 488\r\n . NorESM2-MM: ens_cmip6 = 489 - 490\r\n . SAM0-UNICON: ens_cmip6 = 491\r\n . TaiESM1: ens_cmip6 = 492\r\n . UKESM1-0-LL: ens_cmip6 = 493 - 510\r\n\r\n\r\nAcronyms - ENSO - El Niño–Southern Oscillation, CMIP - Coupled Model Intercomparison Project, RCP - Representative Concentration Pathway, ERSST - Extended Reconstructed Sea Surface Temperature, HadISST - Hadley Centre Sea Ice and Sea Surface Temperature, ACCESS- CM2 – Australian Community Climate and Earth System Simulator coupled climate model, ACCESS- ESM – Australian Community Climate and Earth System Simulator Earth system model, AWI - Alfred Wegener Institute, BCC-CSM - Beijing Climate Center Climate System Model, CAMS - Chinese Academy of Meteorological Sciences, CanOE - Canadian Ocean Ecosystem, CESM2 - Community Earth System Model, WACCM - Whole Atmosphere Community Climate Model, CIESM - Community Integrated Earth System Model, CNCC - Centro Euro-Mediterraneo per I Cambiamenti Climatici, CNRM - Centre National de Recherches Météorologiques, E3SM - Energy Exascale Earth System Model, FGOALS - Flexible Global Ocean-Atmosphere-Land System Model, FIO-ESM - First Institute of Oceanography Earth System Model, GFDL - Geophysical Fluid Dynamics Laboratory, GISS - Goddard Institute for Space Studies, IITM - Indian Institute of Tropical Meteorology, INM - Institute for Numerical Mathematics, IPSL - Institut Pierre-Simon Laplace, KIOST-ESM - Korea Institute of Ocean Science & Technology Earth System, MIROC - Model for Interdisciplinary Research on Climate, MPI - Max-Planck-Institut für Meteorologie, NESM - Nanjing University of Information Science and Technology Earth System Model, NorCPM - Norwegian Climate Prediction Model, SAM0-UNICON - Seoul National University Atmosphere Model version 0 with a Unified Convection Scheme (SAM0-UNICON), TaiESM1 - Taiwan Earth System Model version 1, UKESM - The UK Earth System Modelling project.\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. The weight is provided as the weight attribute of ens_cmip5 and ens_cmip6.\r\n \r\n If X(i) is the array, and w(i) the corresponding weight.\r\n\r\n- Mean shoud be suｍ_i(X(i) * w(i)) / sum_i(w(i))\r\n\r\n- For percentile values, \r\n\r\n1. Sort X and w so that X is in the ascending order\r\n\r\n2. 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\r\n3. Use X(j) or (X(j) + X(j - 1))/2 as the percentile value\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": 37587, "uuid": "46f6427ae2e54aa0bec818dac4857e0b", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/netherlands/amsterdam-ap-schiphol/knmi-lufft-chm15k_A", "numberOfFiles": 1324, "volume": 3508309762, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37588, "uuid": "10af126c9dcf40e2aff7c3cf835d7e6b", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from KNMI's Lufft CHM15k \"Nimbus\" instrument A deployed at Amsterdam Ap Schiphol, Netherlands", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Royal Netherlands Meteorological Institute (KNMI)'s Lufft CHM15k \"Nimbus\" deployed at Amsterdam Ap Schiphol, Netherlands.\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: 0-20000-0-06240.\r\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool. Note: this WIGOS ID is shared by 4 instruments located at the site. Data from the 4 instruments use one shared value for latitude and longitude:\r\n\r\nLatitude: 52.317008972168 N\r\nLongitude: 4.80366992950439 E\r\n \r\nThe actual instrument deployments are as follows:\r\n\r\nInstrument: Amsterdam AP Schiphol A\r\nLatitude: 52.317010 N\r\nLongitude: 4.803670 E\r\nAltitude: -4\r\nLocation: Amsterdam AP Schiphol end of runway 27\r\n\r\nInstrument: Amsterdam AP Schiphol B\r\nLatitude: 52.286140 N\r\nLongitude: 4.729310 E\r\n-Altitude: -4\r\nLocation: Amsterdam AP Schiphol end of runway 06\r\n \r\nInstrument: Amsterdam AP Schiphol C\r\nLatitude: 52.368290 N\r\nLongitude: 4.712660 E\r\nAltitude: --4\r\nLocation: Amsterdam AP Schiphol end of runway 18R\r\n \r\nInstrument: Amsterdam AP Schiphol D\r\nLatitude: 52.3395500183105 N\r\nLongitude: 4.7407398223877 E\r\nAltitude: --4\r\nLocation: Amsterdam AP Schiphol end of runway 18C \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": 37590, "uuid": "25a1ca99b3a148f6b45c2cad518f5a03", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/netherlands/amsterdam-ap-schiphol/knmi-lufft-chm15k_B", "numberOfFiles": 1323, "volume": 3515475778, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37591, "uuid": "32dcaf1485de444c8ba273afde964f46", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from KNMI's Lufft CHM15k \"Nimbus\" instrument B deployed at Amsterdam Ap Schiphol, Netherlands", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Royal Netherlands Meteorological Institute (KNMI)'s Lufft CHM15k \"Nimbus\" deployed at Amsterdam Ap Schiphol, Netherlands.\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: 0-20000-0-06240.\r\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool. Note: this WIGOS ID is shared by 4 instruments located at the site. Data from the 4 instruments use one shared value for latitude and longitude:\r\n\r\nLatitude: 52.317008972168 N\r\nLongitude: 4.80366992950439 E\r\n \r\nThe actual instrument deployments are as follows:\r\n\r\nInstrument: Amsterdam AP Schiphol A\r\nLatitude: 52.317010 N\r\nLongitude: 4.803670 E\r\nAltitude: -4\r\nLocation: Amsterdam AP Schiphol end of runway 27\r\n\r\nInstrument: Amsterdam AP Schiphol B\r\nLatitude: 52.286140 N\r\nLongitude: 4.729310 E\r\n-Altitude: -4\r\nLocation: Amsterdam AP Schiphol end of runway 06\r\n \r\nInstrument: Amsterdam AP Schiphol C\r\nLatitude: 52.368290 N\r\nLongitude: 4.712660 E\r\nAltitude: --4\r\nLocation: Amsterdam AP Schiphol end of runway 18R\r\n \r\nInstrument: Amsterdam AP Schiphol D\r\nLatitude: 52.3395500183105 N\r\nLongitude: 4.7407398223877 E\r\nAltitude: --4\r\nLocation: Amsterdam AP Schiphol end of runway 18C \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": 37593, "uuid": "de24cf0b770849be9b803a9614865daa", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/netherlands/amsterdam-ap-schiphol/knmi-lufft-chm15k_C", "numberOfFiles": 1327, "volume": 3528637031, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37594, "uuid": "af83232f73bf42a88a1df88d1067825b", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from KNMI's Lufft CHM15k \"Nimbus\" instrument C deployed at Amsterdam Ap Schiphol, Netherlands", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Royal Netherlands Meteorological Institute (KNMI)'s Lufft CHM15k \"Nimbus\" deployed at Amsterdam Ap Schiphol, Netherlands.\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: 0-20000-0-06240.\r\n See online documentation for link to station details in the Observing Systems Capability Analysis and Review (OSCAR) Tool. Note: this WIGOS ID is shared by 4 instruments located at the site. Data from the 4 instruments use one shared value for latitude and longitude:\r\n\r\nLatitude: 52.317008972168 N\r\nLongitude: 4.80366992950439 E\r\n \r\nThe actual instrument deployments are as follows:\r\n\r\nInstrument: Amsterdam AP Schiphol A\r\nLatitude: 52.317010 N\r\nLongitude: 4.803670 E\r\nAltitude: -4\r\nLocation: Amsterdam AP Schiphol end of runway 27\r\n\r\nInstrument: Amsterdam AP Schiphol B\r\nLatitude: 52.286140 N\r\nLongitude: 4.729310 E\r\n-Altitude: -4\r\nLocation: Amsterdam AP Schiphol end of runway 06\r\n \r\nInstrument: Amsterdam AP Schiphol C\r\nLatitude: 52.368290 N\r\nLongitude: 4.712660 E\r\nAltitude: --4\r\nLocation: Amsterdam AP Schiphol end of runway 18R\r\n \r\nInstrument: Amsterdam AP Schiphol D\r\nLatitude: 52.3395500183105 N\r\nLongitude: 4.7407398223877 E\r\nAltitude: --4\r\nLocation: Amsterdam AP Schiphol end of runway 18C \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": 37596, "uuid": "62b85ff60a6245009be2652c4e593033", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/czech-republic/karlovy-vary/chmi-vaisala-cl31_A", "numberOfFiles": 279, "volume": 706829958, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37597, "uuid": "f18c0d83e3f44ea29fa38c8cf380537f", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from CHMI's Vaisala CL31 instrument deployed at Karlovy Vary, Czech Republic", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Czech Hydrometeorological Institute (CHMI)'s Vaisala CL31 deployed at Karlovy Vary, Czech Republic.\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: 0-20000-0-11414.\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": 37600, "uuid": "7d85b03a3a474319a8a27d0e39d4ff1f", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/sweden/ljungby/smhi-vaisala-cl31_A", "numberOfFiles": 1352, "volume": 1851341028, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37601, "uuid": "1a734ef4a341448e9875735449db8c05", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from SMHI's Vaisala CL31 instrument deployed at Ljungby, Sweden", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Swedish Meteorological and Hydrological Institute (SMHI)'s Vaisala CL31 deployed at Ljungby, Sweden.\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: 0-20000-0-02622. 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": 37605, "uuid": "b32b595e4ea54006a7bdf36a7b0fa4e3", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig11/v20220620", "numberOfFiles": 5, "volume": 23029, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37604, "uuid": "f38913d950694e3e8f0a19d0dc7f378e", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.11 (v20220620)", "abstract": "Data for Figure 3.11 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 3.11 shows a comparison between simulated annual precipitation changes and pollen-based reconstructions at the mid-Holocene (6,000 years ago).\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 List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n \r\n - area-averaged precipitation changes over five regions (Northern Europe, Western and Central Europe, Mediterranean, Sahara/Sahel, West Africa) as simulated by CMIP6 models\r\n - area-averaged precipitation changes over five regions (Northern Europe, Western and Central Europe, Mediterranean, Sahara/Sahel, West Africa) as simulated by CMIP5 models.\r\n - pollen-based MAP reconstructions points within the region (Northern Europe, Western and Central Europe, Mediterranean, Sahara/Sahel, West Africa)\r\n\r\n\r\nThese data are also available from a pre-existing GitHub repository which can be found under 'Sources of additional information' and the related documents.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n map_midHolocene_reconstructions.csv shows the data for bars in each region in the figure.\r\n map_midHolocene_models.csv shows the data for the multicolored circles in each region in the figure. The colors represent different models.\r\n Additional data about data provided in relation to figure can be found in the files headers.\r\n\r\n CMIP5 is the fifth phase of the Coupled Model Intercomparison Project.\r\n CMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\n\r\n---------------------------------------------------\r\nTemporal Range of Paleoclimate Data\r\n---------------------------------------------------\r\nThis dataset covers a paleoclimate timespan, starting and ending at 6000 years ago. \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 external GitHub repository also containing the figure data.\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": 37606, "uuid": "97ab7f84649d46aebd2cf8562b31f004", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/inputdata_ch3_fig27/v20220621", "numberOfFiles": 4, "volume": 40251095, "fileFormat": "netCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 33333, "uuid": "38bac9051d064d4da183fff2361f5de8", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 3.27 (v20220621)", "abstract": "Input data for figure 3.27 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 3.27 shows maps of multi-decadal salinity trends for the near-surface ocean.\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 two subpanels, with input data provided for the upper panel.\r\n\r\n ---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains the global ocean salinity estimates from Durack & Wijffels (2010) based on observations from 01-01-1950 to 12-31-2019:\r\n \r\n - Mean salinity (for the Jan/1950 to Dec/2019 period, units in PSS).\r\n - Salinity change (for the same period, PSS/70-years).\r\n - Salinity change error (same period, PSS/70-years).\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nThe observational data from here (top panel) is taken from the file:\r\nDurackandWijffels_GlobalOceanChanges_19500101-20191231__210122-205355_beta.nc. The fields of interest are salinity_mean (shown as black contours) and salinity_change (shown in colourscale). DurackandWijffels_GlobalOceanChanges_19500101-20191231__210122-205355_beta.nc is an updated file from Durack & Wijffels (2010).\r\n\r\nThe data file DurackandWijffels_GlobalOceanChanges_19500101-20191231__210122-205355_beta.nc is an intermediate file used in 3.27, please refer to the code to generate the figure using the corresponding tools (see the link to the code in the 'Related document' section README_AR6_WG1_Chap3_Figure3_27_GlobalSeaSurfaceSalinitytrends.md at main ESMValGroup/ESMValTool-AR6-OriginalCode-FinalFigures).\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 code for the figure, archived on Zenodo.\r\n - Link to input data figure 2.27.\r\n - Link to the figure on the IPCC AR6 website." }, "onlineresource_set": [] }, { "ob_id": 37607, "uuid": "9b388153354f4d0db5b50b6c6c2e12d9", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/fiduceo/data/fcdr/hirs/v2.00/", "numberOfFiles": 728665, "volume": 1786452362336, "fileFormat": "HIRS- NOAA Native Binary format: Data formats for HIRS/2 (NOAA-14 and before) are documented in the NOAA POD User's Guide. available online in PDF linked to in the documentation section", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34607, "uuid": "41d0dfd6d2064b158f244c0123c83972", "short_code": "ob", "title": "FIDUCEO: Fundamental Climate Data Record of brightness temperatures for High-resolution Infrared Radiation Sounder (HIRS) 1978 - 2016, V2.0", "abstract": "The FIDelity and Uncertainty in Climate data records from Earth Observations (FIDUCEO) project Fundamental Climate Data Record of brightness temperatures for the High-resolution Infrared Radiation Sounder (HIRS) contains brightness temperatures for HIRS for all editions of HIRS/2, HIRS/2I, HIRS/3, and HIRS/4 satellite instruments. It contains HIRS l1b data as available from the NOAA Comprehensive Large Array-Data Stewardship System (CLASS). Geolocation and calibration information is available in the files. For more information and relevant product guides please see the documentation section. This data set was used as input to the Fundamental Climate Data Record of recalibrated brightness temperatures for the High-resolution Infrared Radiation Sounder (HIRS) with uncertainties, 1978 - 2016, v1.0 dataset." }, "onlineresource_set": [] }, { "ob_id": 37609, "uuid": "77eee22019db47708dfb427bd4c6f8ef", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_05/ch5_fig33/v20220623", "numberOfFiles": 4, "volume": 5816, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37608, "uuid": "85409987ce6a4976b0845b512baa2843", "short_code": "ob", "title": "Chapter 5 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 5.33 (v20220623)", "abstract": "Data for Figure 5.33 from Chapter 5 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 5.33 shows carbon sink response in a scenario with net carbon dioxide (CO2) removal from the atmosphere. \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\nCanadell, J.G., P.M.S. Monteiro, M.H. Costa, L. Cotrim da Cunha, P.M. Cox, A.V. Eliseev, S. Henson, M. Ishii, S. Jaccard, C. Koven, A. Lohila, P.K. Patra, S. Piao, J. Rogelj, S. Syampungani, S. Zaehle, and K. Zickfeld, 2021: Global Carbon and other Biogeochemical Cycles and Feedbacks. 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. 673–816, doi:10.1017/9781009157896.007.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains data for 50-year periods during 2000-2300 for:\r\n \r\n - Atmospheric CO2 concentration\r\n - Net CO2 emissions (accumulated over 50 year periods)\r\n - Net land flux (accumulated over 50 year periods)\r\n - Net ocean flux (accumulated over 50 year periods)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data file: Data_Figure_5_33.csv:\r\n \r\n - row 1: x-axis values.\r\n - row 2: light blue bars.\r\n - row 3: orange bars.\r\n - row 4: green bars.\r\n - row 5: blue bars\r\n - row 6: relates with the values written in black over the corresponding arrows (row 2 values plus values written in black)\r\n - row 7: Standard deviation over orange bars.\r\n - row 8: Standard deviation over green bars.\r\n - row 9: Standard deviation over blue bars.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n This figure was created in Excel and the error bars (standard deviation) were added in Adobe \r\n Illustrator.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 5)\r\n - Link to the Supplementary Material for Chapter 5, which contains details on the input data used in Table 5.SM.6" }, "onlineresource_set": [] }, { "ob_id": 37613, "uuid": "ab2f644fe36b4f87ab735363dac798a4", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_12/ch12_fig04/v20220623", "numberOfFiles": 36, "volume": 49171239, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37615, "uuid": "eceae60685ef4a42a0ca0967013d4416", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig34/v20220404", "numberOfFiles": 4, "volume": 53398, "fileFormat": "txt, netCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34559, "uuid": "678ee967fe114a34a6d1f7d50e4aa7ee", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.34 (v20220104)", "abstract": "Data for Figure 3.34 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 3.34 shows attribution of observed seasonal trends in the annular modes to forcings. \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 3 panels, and all the data are provided in a single file named NAM_SAM_detection_attribution.nc.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains\r\n \r\n - Observed and simulated DJF NAM trends for 1958-2019\r\n - Observed and simulated JJA NAM trends for 1958-2019\r\n - Observed and simulated DJF SAM trends for 1979-2019\r\n - Observed and simulated JJA SAM trends for 1979-2019\r\n - Observed and simulated DJF SAM trends for 2000-2019\r\n - Observed and simulated JJA SAM trends for 2000-2019\r\n Simulations are from CMIP6 historical, hist-GHG, hist-aer, hist-nat, and hist-stratO3 simulations, and from equivalent time segments from CMIP6 piControl simulations (one segment from one model).\r\n\r\nNAM: Northern Annular Mode \r\nSAM: Southern Annular Mode\r\nGHG: greenhouse gas\r\nJJA: June, July, August\r\nDJF: December, January, February\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel a:\r\n - NAM_obs_DJF_1958_2019: grey horizontal lines in the left\r\n -->ERA5: obs_dataset = 0\\n\r\n -->JRA-55: obs_dataset = 1\\n\r\n - NAM_piControl_DJF_62yrs: multimodel ensemble mean and percentiles for blue open box-whisker in the left\r\n - NAM_hist_DJF_1958_2019: multimodel ensemble mean and percentiles for red open box-whisker in the left, and multimodel ensemble mean and confidence interval for red filled box, with ensemble means of individual models for black dots, in the left\r\n - NAM_GHG_DJF_1958_2019: multimodel ensemble mean and confidence interval for brown filled box, with ensemble means of individual models for black dots, in the left\r\n - NAM_aer_DJF_1958_2019: multimodel ensemble mean and confidence interval for light blue filled box, with ensemble means of individual models for black dots, in the left\r\n - NAM_stratO3_DJF_1958_2019: multimodel ensemble mean and confidence interval for purple filled box, with ensemble means of individual models for black dots, in the left\r\n - NAM_nat_DJF_1958_2019: multimodel ensemble mean and confidence interval for green filled box, with ensemble means of individual models for black dots, in the left\r\n - NAM_obs_JJA_1958_2019: grey horizontal lines in the right\r\n -->ERA5: obs_dataset = 0\\n\r\n -->JRA-55: obs_dataset = 1\\n\r\n - NAM_piControl_JJA_62yrs: multimodel ensemble mean and percentiles for blue open box-whisker in the right\r\n - NAM_hist_JJA_1958_2019: multimodel ensemble mean and percentiles for red open box-whisker in the right, and multimodel ensemble mean and confidence interval for red filled box, with ensemble means of individual models for black dots, in the right\r\n - NAM_GHG_JJA_1958_2019: multimodel ensemble mean and confidence interval for brown filled box, with ensemble means of individual models for black dots, in the right\r\n - NAM_aer_JJA_1958_2019: multimodel ensemble mean and confidence interval for light blue filled box, with ensemble means of individual models for black dots, in the right\r\n - NAM_stratO3_JJA_1958_2019: multimodel ensemble mean and confidence interval for purple filled box, with ensemble means of individual models for black dots, in the right\r\n - NAM_nat_JJA_1958_2019: multimodel ensemble mean and confidence interval for green filled box, with ensemble means of individual models for black dots, in the right\r\n \r\n Panel b:\r\n - SAM_obs_DJF_1979_2019: grey horizontal lines in the left\r\n -->ERA5: obs_dataset = 0\\n\r\n -->JRA-55: obs_dataset = 1\\n\r\n - SAM_piControl_DJF_41yrs: multimodel ensemble mean and percentiles for blue open box-whisker in the left\r\n - SAM_hist_DJF_1979_2019: multimodel ensemble mean and percentiles for red open box-whisker in the left, and multimodel ensemble mean and confidence interval for red filled box, with ensemble means of individual models for black dots, in the left\r\n - SAM_GHG_DJF_1979_2019: multimodel ensemble mean and confidence interval for brown filled box, with ensemble means of individual models for black dots, in the left\r\n - SAM_aer_DJF_1979_2019: multimodel ensemble mean and confidence interval for light blue filled box, with ensemble means of individual models for black dots, in the left\r\n - SAM_stratO3_DJF_1979_2019: multimodel ensemble mean and confidence interval for purple filled box, with ensemble means of individual models for black dots, in the left\r\n - SAM_nat_DJF_1979_2019: multimodel ensemble mean and confidence interval for green filled box, with ensemble means of individual models for black dots, in the left\r\n - SAM_obs_JJA_1979_2019: grey horizontal lines in the right\r\n -->ERA5: obs_dataset = 0\\n\r\n -->JRA-55: obs_dataset = 1\\n\r\n - SAM_piControl_JJA_41yrs: multimodel ensemble mean and percentiles for blue open box-whisker in the right\r\n - SAM_hist_JJA_1979_2019: multimodel ensemble mean and percentiles for red open box-whisker in the right, and multimodel ensemble mean and confidence interval for red filled box, with ensemble means of individual models for black dots, in the right\r\n - SAM_GHG_JJA_1979_2019: multimodel ensemble mean and confidence interval for brown filled box, with ensemble means of individual models for black dots, in the right\r\n - SAM_aer_JJA_1979_2019: multimodel ensemble mean and confidence interval for light blue filled box, with ensemble means of individual models for black dots, in the right\r\n - SAM_stratO3_JJA_1979_2019: multimodel ensemble mean and confidence interval for purple filled box, with ensemble means of individual models for black dots, in the right\r\n - SAM_nat_JJA_1979_2019: multimodel ensemble mean and confidence interval for green filled box, with ensemble means of individual models for black dots, in the right\r\n \r\n Panel c:\r\n - SAM_obs_DJF_2000_2019: grey horizontal lines in the left\r\n -->ERA5: obs_dataset = 0\\n\r\n -->JRA-55: obs_dataset = 1\\n\r\n - SAM_piControl_DJF_20yrs: multimodel ensemble mean and percentiles for blue open box-whisker in the left\r\n - SAM_hist_DJF_2000_2019: multimodel ensemble mean and percentiles for red open box-whisker in the left, and multimodel ensemble mean and confidence interval for red filled box, with ensemble means of individual models for black dots, in the left\r\n - SAM_GHG_DJF_2000_2019: multimodel ensemble mean and confidence interval for brown filled box, with ensemble means of individual models for black dots, in the left\r\n - SAM_aer_DJF_2000_2019: multimodel ensemble mean and confidence interval for light blue filled box, with ensemble means of individual models for black dots, in the left\r\n - SAM_stratO3_DJF_2000_2019: multimodel ensemble mean and confidence interval for purple filled box, with ensemble means of individual models for black dots, in the left\r\n - SAM_nat_DJF_2000_2019: multimodel ensemble mean and confidence interval for green filled box, with ensemble means of individual models for black dots, in the left\r\n - SAM_obs_JJA_2000_2019: grey horizontal lines in the right\r\n -->ERA5: obs_dataset = 0\\n\r\n -->JRA-55: obs_dataset = 1\\n\r\n - SAM_piControl_JJA_20yrs: multimodel ensemble mean and percentiles for blue open box-whisker in the right\r\n - SAM_hist_JJA_2000_2019: multimodel ensemble mean and percentiles for red open box-whisker in the right, and multimodel ensemble mean and confidence interval for red filled box, with ensemble means of individual models for black dots, in the right\r\n - SAM_GHG_JJA_2000_2019: multimodel ensemble mean and confidence interval for brown filled box, with ensemble means of individual models for black dots, in the right\r\n - SAM_aer_JJA_2000_2019: multimodel ensemble mean and confidence interval for light blue filled box, with ensemble means of individual models for black dots, in the right\r\n - SAM_stratO3_JJA_2000_2019: multimodel ensemble mean and confidence interval for purple filled box, with ensemble means of individual models for black dots, in the right\r\n - SAM_nat_JJA_2000_2019: multimodel ensemble mean and confidence interval for green filled box, with ensemble means of individual models for black dots, in the right\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nMultimodel ensemble means, interquartile ranges and 5th and 95th percentiles of historical and hist-* simulations are calculated after weighting individual members with the inverse of the ensemble size of the same model. The weight is given as the weight attribute of each variable. The weighting is not applied to piControl simulations.\r\n\r\nFilled boxes and black dots are evaluated based on the models with minimum 3 ensemble members. ensemble_assign attribute in each variable provides the model number to which each ensemble member belongs. 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 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": 37616, "uuid": "18b57fc255fb40df8aa159774664b3d7", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_02/inputdata_ch2_fig27/v20211112", "numberOfFiles": 3, "volume": 39000, "fileFormat": "txt, netCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37618, "uuid": "2d89bb68eb6f4a3e9a58eff58d7f6fa8", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_02/inputdata_ch2_fig29/v20220624", "numberOfFiles": 0, "volume": 0, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37620, "uuid": "2fc87a70d16f42719d5f87a163cd3046", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_02/ch2_fig29/v20220624", "numberOfFiles": 7, "volume": 400000, "fileFormat": "txt", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37621, "uuid": "85680abc3b364a058c7fefb952d4baf5", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_02/inputdata_ch2_fig29/v20220624", "numberOfFiles": 4, "volume": 4884, "fileFormat": "Data provided in .txt format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37617, "uuid": "81f53dc4487b4260b92d4dd8000a8b09", "short_code": "ob", "title": "Chapter 2 of the Working Group I Contribution to the IPCC Sixth Assessment Report - input data for Figure 2.29 (v20220624)", "abstract": "Input data for Figure 2.29 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\n\r\nFigure 2.29 shows the surface ocean pH evolution over time from the last 65 million years onwards up to modern times. \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\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---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has four panels, with input data provided for panel d Ocean-SODA (the remaining datasets used for this figure are publicly available and reference is provided in Supplementary Material for chapter 2, Table 2.SM.1) \r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains global mean surface ocean pH from 1981-2018 for reconstructed global ocean acidification change.\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel d (time series plot)\r\n \r\n - Data file: SODA_pH.txt (yearly data, 1981-2018); relates to purple line\r\n\r\nSODA stands for Satellite Oceanographic Datasets for Acidification.\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n Use program Chapter2_Fig.29_code_in_R to reproduce the figure (programming in R). \r\n\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 figure on the IPCC AR6 website\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": 37623, "uuid": "c8d0183ca03f4efaa2a6450f9de758a9", "short_code": "result", "curationCategory": "A", "dataPath": "/bodc/UOX220077/WINDS-C", "numberOfFiles": 52, "volume": 5388787900564, "fileFormat": "Data are CF-Compliant NetCDF formatted data files", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37622, "uuid": "b2b9bfe408f14ea7a79d9ff7aee0d0b8", "short_code": "ob", "title": "WINDS-C: A 1/50° decadal regional simulation of the Southwestern Indian Ocean with high frequency surface currents for Lagrangian applications (climatological forcing based on 1993-2018)", "abstract": "WINDS-C (Western Indian Ocean Simulation, Climatological) is a high-resolution (1/50° in the horizontal) regional ocean simulation spanning the SW Indian Ocean under climatological forcing (1993-2018), using the Coastal and Regional Ocean Community model (CROCO). WINDS-C is forced at the lateral boundaries by a monthly climatology from the 1/12° CMEMS (Copernicus Marine Environment Monitoring Service) GLORYS12V1 global ocean reanalysis and barotropic tides from TPXO9, at the surface by a monthly climatology from ERA5, and also includes climatological riverine fluxes. High frequency (0.5h) surface currents are provided for Lagrangian analyses, and other surface fields are provided at a daily frequency. Full 3D zonal velocity, meridional velocity, temperature, and salinity (U/V/T/S) fields are provided every 5 days." }, "onlineresource_set": [] }, { "ob_id": 37627, "uuid": "098d2853d1bd4fc790d0280e9f8acb1d", "short_code": "result", "curationCategory": "A", "dataPath": "/bodc/UOX220077/WINDS-M", "numberOfFiles": 129, "volume": 16066951759705, "fileFormat": "Data are CF-Compliant NetCDF formatted data files", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37626, "uuid": "bf6f0cfbd09e47498572f21081376702", "short_code": "ob", "title": "WINDS-M: A 1/50° multidecadal regional simulation of the Southwestern Indian Ocean with high frequency surface currents for Lagrangian applications (realistic forcing, 1993-2020)", "abstract": "WINDS-M (Western Indian Ocean Simulation, Multidecadal) is a high-resolution (1/50° in the horizontal) regional ocean simulation spanning the SW Indian Ocean from 1993-2020, using the Coastal and Regional Ocean Community model (CROCO). WINDS-M is forced at the lateral boundaries by daily output from the 1/12° CMEMS (Copernicus Marine Environment Monitoring Service) GLORYS12V1 global ocean reanalysis and barotropic tides from TPXO9, at the surface hourly output from ERA5, and also includes climatological riverine fluxes. High frequency (0.5h) surface currents are provided for Lagrangian analyses, and other surface fields are provided at a daily frequency. Full 3D zonal velocity, meridional velocity, temperature, and salinity (U/V/T/S) fields are provided every 5 days." }, "onlineresource_set": [] }, { "ob_id": 37630, "uuid": "72f9eadbc0b84367bd17b68d4d76cbd3", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_11/ch11_fig11/v20220622", "numberOfFiles": 9, "volume": 1161294, "fileFormat": "txt, netCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34643, "uuid": "3f415b44b4334725bfcc572c9246aa60", "short_code": "ob", "title": "Chapter 11 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 11.11 (v20220117)", "abstract": "Data for Figure 11.11 from Chapter 11 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nProjected changes in annual maximum temperature (TXx) and annual minimum temperature (TNn) at 1.5°C, 2°C, and 4°C of global warming compared to the 1850-1900 baseline.\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\nSeneviratne, S.I., X. Zhang, M. Adnan, W. Badi, C. Dereczynski, A. Di Luca, S. Ghosh, I. Iskandar, J. Kossin, S. Lewis, F. Otto, I. Pinto, M. Satoh, S.M. Vicente-Serrano, M. Wehner, and B. Zhou, 2021: Weather and Climate Extreme Events in a Changing Climate. 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. 1513–1766, doi:10.1017/9781009157896.013.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has three panels, with data provided for all panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n \r\n - Annual maximum temperature (°C) change (relative to 1850-1900)\r\n - Annual minimum temperature (°C) change (relative to 1850-1900)\r\n The data is given for global warming levels (GWLs), namely +1.5°C, 2.0°C, and +4.0°C.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel a:\r\n - Figure_11.11a_cmip6_TXx_change_at_1.5C.nc: simulated annual maximum temperature change (°C) at 1.5°C global warming relative to 1850-1900\r\n \r\n Panel b:\r\n - Figure_11.11b_cmip6_TXx_change_at_2.0C.nc: simulated annual maximum temperature change (°C) at 2.0°C global warming relative to 1850-1900\r\n \r\n Panel c:\r\n - Figure_11.11c_cmip6_TXx_change_at_4.0C.nc: simulated annual maximum temperature change (°C) at 4.0°C global warming relative to 1850-1900\r\n Panel d:\r\n - Figure_11.11d_cmip6_TNn_change_at_1.5C.nc: simulated annual minimum temperature change (°C) at 1.5°C global warming relative to 1850-1900\r\n Panel e:\r\n - Figure_11.11e_cmip6_TNn_change_at_2.0C.nc: simulated annual minimum temperature change (°C) at 2.0°C global warming relative to 1850-1900\r\n Panel f:\r\n - Figure_11.11f_cmip6_TNn_change_at_4.0C.nc: simulated annual minimum temperature change (°C) at 4.0°C global warming relative to 1850-1900\r\n\r\nAcronyms: CMIP - Coupled Model Intercomparison Project\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 11)\r\n - Link to the Supplementary Material for Chapter 11, which contains details on the input data used in Table 11.SM.9\r\n - Link to the Ch11 GitHub repository containing scripts for generating figures\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37631, "uuid": "5c3db00571c547a59b5652f52e7d5759", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_11/ch11_fig16/v20220622", "numberOfFiles": 6, "volume": 596816, "fileFormat": "txt, netCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34640, "uuid": "e7c78370837d4f85be6a1f0cbe288a92", "short_code": "ob", "title": "Chapter 11 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 11.16 (v20220117)", "abstract": "Data for Figure 11.16 from Chapter 11 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nProjected changes in annual maximum daily precipitation at 1.5°C, 2°C, and 4°C of global warming compared to the 1850-1900 baseline.\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\nSeneviratne, S.I., X. Zhang, M. Adnan, W. Badi, C. Dereczynski, A. Di Luca, S. Ghosh, I. Iskandar, J. Kossin, S. Lewis, F. Otto, I. Pinto, M. Satoh, S.M. Vicente-Serrano, M. Wehner, and B. Zhou, 2021: Weather and Climate Extreme Events in a Changing Climate. 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. 1513–1766, doi:10.1017/9781009157896.013.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has three panels, with data provided for all panels.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n \r\n - Annual maximum daily precipitation change (%) (relative to 1850-1900)\r\n The data is given for global warming levels (GWLs), namely +1.5°C, 2.0°C, and +4.0°C.\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel a:\r\n - Figure_11_16a_cmip6_Rx1day_change_at_1_5C.nc: simulated annual maximum daily precipitation change (%) at 1.5°C global warming relative to 1850-1900\r\n \r\n Panel b:\r\n - Figure_11_16b_cmip6_Rx1day_change_at_2_0C.nc: simulated annual maximum daily precipitation change (%) at 2.0°C global warming relative to 1850-1900\r\n \r\n Panel c:\r\n - Figure_11_16c_cmip6_Rx1day_change_at_4_0C.nc: simulated annual maximum daily precipitation change (%) at 4.0°C global warming relative to 1850-1900\r\n\r\n\r\nAcronyms: CMIP - Coupled Model Intercomparison Project, SSP - Shared Socioeconomic Pathways\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 11)\r\n - Link to the Supplementary Material for Chapter 11, which contains details on the input data used in Table 11.SM.9\r\n - Link to the Ch11 GitHub repository containing scripts for generating figures\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37632, "uuid": "79b225f4c6a74d71bb35a04aa368a7ec", "short_code": "result", "curationCategory": "B", "dataPath": "/badc/fund/data/hatpro", "numberOfFiles": 131, "volume": 1493077378, "fileFormat": "Data are NetCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37633, "uuid": "eb1af2fa81c24fdea94d00c183a1ed1b", "short_code": "ob", "title": "Met Office FUND: Radiometer 1", "abstract": "Met Office FUND: Radiometer 1" }, "onlineresource_set": [] }, { "ob_id": 37634, "uuid": "d1f360adc0f04e8fb583483d93440265", "short_code": "result", "curationCategory": "B", "dataPath": "/badc/fund/data/hatpro1", "numberOfFiles": 220, "volume": 1346098800, "fileFormat": "Data are NetCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37636, "uuid": "dfc926bce78c4ffb9637299650ac578c", "short_code": "ob", "title": "Met Office FUND: Radiometer 2", "abstract": "Met Office FUND: Radiometer 2" }, "onlineresource_set": [] }, { "ob_id": 37635, "uuid": "2619acce8cfb4d74a637b40635277940", "short_code": "result", "curationCategory": "B", "dataPath": "/badc/fund/data/hatpro2", "numberOfFiles": 132, "volume": 649855190, "fileFormat": "Data are NetCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37637, "uuid": "403aedb5171a46be83dbe321dbccfcae", "short_code": "ob", "title": "Met Office FUND: Radiometer 3", "abstract": "Met Office FUND: Radiometer 3" }, "onlineresource_set": [] }, { "ob_id": 37638, "uuid": "737f235b123547c5b9758b9e87d6eac9", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_10/ch10_ccb4_fig1/v20220622", "numberOfFiles": 12, "volume": 399724, "fileFormat": "txt, netCDF, csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34635, "uuid": "e4416a7d02ed4eeb9a971a7d3c2f4e42", "short_code": "ob", "title": "Chapter 10 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for CCB 10.4 Figure 1 (v20220622)", "abstract": "Data for CCB 10.4 Figure 1 from Chapter 10 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nCCB10.4 Figure 1 shows historical annual-mean surface air temperature linear trend (°C per decade) and its attribution over the Hindu Kush Himalaya (HKH) region.\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\nDoblas-Reyes, F.J., A.A. Sörensson, M. Almazroui, A. Dosio, W.J. Gutowski, R. Haarsma, R. Hamdi, B. Hewitson, W.-T. Kwon, B.L. Lamptey, D. Maraun, T.S. Stephenson, I. Takayabu, L. Terray, A. Turner, and Z. Zuo, 2021: Linking Global to Regional Climate Change. 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. 1363–1512, doi:10.1017/9781009157896.012.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has four subpanels. Data for all subpanels is provided.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n The data is annual means for:\r\n \r\n - Observed and modelled trends over 1961-2014\r\n - Anomalies 1961-2014 with respect to 1961-1980 average for the HKH region mean\r\n - Trends 1961-2014 for the HKH region mean\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel (a):\r\n - Data files: \r\nFig_10_CCB-4_1_panel-a_mapplot_tas_trend_BerkeleyEarth_single_trend.nc, \r\nFig_10_CCB-4_1_panel-a_mapplot_tas_trend_CRU_single_trend.nc, \r\nFig_10_CCB-4_1_panel-a_mapplot_tas_trend_APHRO-MA_single_trend.nc, \r\nFig_10_CCB-4_1_panel-a_mapplot_tas_trend_JRA-55_single_trend.nc; \r\nObserved and reanalysis surface air temperature OLS linear trends over 1961-2014 over the HKH region, from left to right Berkeley Earth, CRU TS, APHRO-MA, JRA-55\r\n \r\n Panel (b):\r\n - Data files: \r\nFig_10_CCB-4_1_panel-b_mapplot_tas_trend_cmip6_CMIP6_min_single-MultiModelMean_trend-min-median-max.nc, \r\nFig_10_CCB-4_1_panel-b_mapplot_tas_trend_cmip6_CMIP6_MultiModelMedian_single-MultiModelMean_trend-min-median-max.nc, \r\nFig_10_CCB-4_1_panel-b_mapplot_tas_trend_cmip6_CMIP6_max_single-MultiModelMean_trend-min-median-max.nc; \r\nModelled surface air temperature OLS linear trends over 1961-2014 over the Hindu Kush Himalaya region, from left to right (CMIP6 models with min (coldest), median and max (warmest) trends)\r\n \r\n Panel (c):\r\n - Data file: Fig_10_CCB-4_1_panel-c_timeseries.csv; \r\nSurface air temperature anomalies 1961-2014 in respect to 1961-1980 average for the Hindu Kush Himalaya (HKH) region mean: means of CMIP6 hist all-forcings (red), and the CMIP6 hist all-forcings sample corresponding to DAMIP experiments (pink), for hist-aer (grey) and hist-GHG (pale blue), Berkeley Earth (dark blue), CRU TS (brown), APHRO-MA (light green) and JRA-55 (dark green).\r\n \r\n Panel (d):\r\n - Data file: Fig_10_CCB-4_1_panel-d_trends.csv; \r\nSurface air temperature OLS linear trends 1961-2014 for the Hindu Kush Himalaya (HKH) region mean: observed and reanalysis data (Berkeley Earth, CRU TS, APHRO-MA, JRA-55: black crosses), individual members of CMIP6 hist all-forcings (red circles), CMIP6 hist all-forcings sample corresponding to DAMIP experiments (pink circles), CMIP6 hist-GHG (blue triangles), CMIP6 hist-aer (grey triangles), and box-and-whisker plots for the SMILEs: MIROC6, CSIRO-Mk3-6-0, MPI-ESM, d4PDF (grey shading)\r\n\r\n\r\nAcronyms: \r\nCRU TS- Climatic Research Unit Time Series, \r\nCMIP - Coupled Model Intercomparison Project, \r\nJRA - Japanese 55year Reanalysis, \r\nDAMIP - Detection and Attribution Model Intercomparison Project, \r\nGHG - Greenhouse Gas, \r\nSMILEs - Single model initial-condition large ensembles, \r\nMIROC - Model for Interdisciplinary Research on Climate, \r\nCSIRO -Commonwealth Scientific and Industrial Research Organisation, \r\nMPI - Max-Planck-Institut für Meteorologie, \r\nESM - Earth System Model, d4PDF - database for policy decision-making for future climate changes, \r\nOLS - ordinary least squares regression. \r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The code for ESMValTool is provided.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 10)\r\n - Link to the Supplementary Material for Chapter 10, which contains details on the input data used in Table 10.SM.11\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37639, "uuid": "4ed29ab08f774393867aca52c7a30f06", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_10/ch10_fig06/v20220622", "numberOfFiles": 17, "volume": 633503, "fileFormat": "txt, netCDF, csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34632, "uuid": "2dc808195d984efe8de7b52942796924", "short_code": "ob", "title": "Chapter 10 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 10.6 (v20220113)", "abstract": "Data for Figure 10.6 from Chapter 10 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 10.6 is an illustration of some model biases in simulations performed with dynamical models.\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\nDoblas-Reyes, F.J., A.A. Sörensson, M. Almazroui, A. Dosio, W.J. Gutowski, R. Haarsma, R. Hamdi, B. Hewitson, W.-T. Kwon, B.L. Lamptey, D. Maraun, T.S. Stephenson, I. Takayabu, L. Terray, A. Turner, and Z. Zuo, 2021: Linking Global to Regional Climate Change. 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. 1363–1512, doi:10.1017/9781009157896.012.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has two panels ((a) and (b)), which are further divided into 6 maps and 1 boxplot. Data is provided for all subpanels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n Boxplot data point is annual summer mean (JJA) surface air temperature (panel (a)) and precipitation (panel (b)) for western Mediterranean mean (lon: 10°W-10°E, lat: 33°N-45°N) between 1986 and 2005 for:\r\n \r\n - Observational datasets\r\n - Each model of CMIP5, CMIP6, HighResMIP, EURO-CORDEX 11 and EURO-CORDEX 44\r\n \r\nMapplot data is mean (1986-2005) annual summer mean (JJA) surface air temperature (panel (a)) and precipitation (panel (b)) for the western Mediterranean (lon: 15°W-15°E, lat: 28°N-50°N) regrided on a 1°x1° regular grid for:\r\n - Absolute values for reference observational dataset (BerkeleyEarth (a), CRU TS (b))\r\n - Ensemble biases of CMIP5, CMIP6, HighResMIP, EURO-CORDEX 11 and EURO-CORDEX 44\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel (a):\r\n - Data file: \r\nObserved (Berkeley Earth) mean (1986-2005) annual summer mean (JJA) surface air temperature over the western Mediterranean (top left):\r\nFig_10_6_panel-a_mapplot_tas_obs_single_single_mean.nc\r\n\r\n - Data files: \r\nEnsemble mean (1986-2005) annual summer mean (JJA) surface air temperature bias over the western Mediterranean (top right):\r\nFig_10_6_panel-a_mapplot_tas_bias_cmip5_tas_cmip5_map_MultiModelMean_bias.nc, \r\nFig_10_6_panel-a_mapplot_tas_bias_cmip6_tas_cmip6_map_MultiModelMean_bias.nc, \r\nFig_10_6_panel-a_mapplot_tas_bias_hrmip_tas_hrmip_map_MultiModelMean_bias.nc, \r\nFig_10_6_panel-a_mapplot_tas_bias_cdx44_tas_cdx44_map_MultiModelMean_bias.nc, \r\nFig_10_6_panel-a_mapplot_tas_bias_cdx11_tas_cdx11_map_MultiModelMean_bias.nc\r\n\r\n - Data file: \r\nObserved (black boxplots), reanalysis (black boxplots) and modelled (CMIP5: blue boxplots, CMIP6: red boxplots, HighResMIP: orange boxplots, CORDEX EUR-44: light blue boxplots, CORDEX EUR-11: green boxplots) annual summer mean (JJA) surface air temperature values (i.e. underlying data points of the boxplot) over the western Mediterranean (bottom part):\r\nFig_10_6_panel-a_boxplot.csv \r\n\r\n\r\n Panel (b):\r\n - Data file: \r\nObserved (CRU TS) mean (1986-2005) annual summer mean (JJA) precipitation rate over the western Mediterranean (top left):\r\nFig_10_6_panel-b_mapplot_pr_obs_single_masked_cru_single_mean.nc\r\n\r\n - Data files: \r\nEnsemble mean (1986-2005) annual summer mean (JJA) precipitation rate bias over the western Mediterranean (top right):\r\nFig_10_6_panel-b_mapplot_pr_bias_cmip5_pr_cmip5_map_MultiModelMean_bias.nc, \r\nFig_10_6_panel-b_mapplot_pr_bias_cmip6_pr_cmip6_map_MultiModelMean_bias.nc, \r\nFig_10_6_panel-b_mapplot_pr_bias_hrmip_pr_hrmip_map_MultiModelMean_bias.nc, \r\nFig_10_6_panel-b_mapplot_pr_bias_cdx44_pr_cdx44_map_MultiModelMean_bias.nc, \r\nFig_10_6_panel-b_mapplot_pr_bias_cdx11_pr_cdx11_map_MultiModelMean_bias.nc\r\n\r\n - Data file: \r\nobserved (black boxplots), reanalysis (black boxplots) and modelled (CMIP5: blue boxplots, CMIP6: red boxplots, HighResMIP: orange boxplots, CORDEX EUR-44: light blue boxplots, CORDEX EUR-11: green boxplots) annual summer mean (JJA) precipitation rate values (i.e. underlying data points of the boxplot) over the western Mediterranean (bottom part):\r\nFig_10_6_panel-b_boxplot.csv\r\n\r\n\r\nAcronyms: \r\nCMIP - Coupled Model Intercomparison Project, \r\nHighResMIP - High Resolution Model Intercomparison Project, \r\nCordex – Coordinated Regional Climate Downscaling Experiment, \r\nOLS - ordinary least squares regression.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The code for ESMValTool is provided.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 10)\r\n - Link to the Supplementary Material for Chapter 10, which contains details on the input data used in Table 10.SM.11\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37640, "uuid": "e70bdcd6fe214330b4c4288718148ae7", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_10/ch10_fig10/v20220622", "numberOfFiles": 13, "volume": 652574, "fileFormat": "txt, netCDF, csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34626, "uuid": "d4eccbbd51db4ab7a8ad05a6f2f6a98a", "short_code": "ob", "title": "Chapter 10 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 10.10 (v20220622)", "abstract": "Data for Figure 10.10 from Chapter 10 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 10.10 shows observed and projected changes in austral summer (December to February) mean precipitation in Global Precipitation Climatology Centre (GPCC), Climatic Research Unit Time-Series (CRU TS) and 100 members of the Max-Planck-Institut für Meteorologie Earth-System Model (MPI-ESM).\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\nDoblas-Reyes, F.J., A.A. Sörensson, M. Almazroui, A. Dosio, W.J. Gutowski, R. Haarsma, R. Hamdi, B. Hewitson, W.-T. Kwon, B.L. Lamptey, D. Maraun, T.S. Stephenson, I. Takayabu, L. Terray, A. Turner, and Z. Zuo, 2021: Linking Global to Regional Climate Change. 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. 1363–1512, doi:10.1017/9781009157896.012.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has two panels, with data provided for both panels. Panel (a) consists of two maps, panel (b) shows multiple timeseries and boxplots.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n The dataset contains data of relative precipitation anomalies over 1950-2100 with respect to 1995-2014 average for global, S.E.South-America, Sao Paulo and Buenos Aires for:\r\n \r\n - Observational data (GPCC and CRU TS)\r\n - Model data (100 runs of MPI-ESM)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel (a):\r\n - Data files: \r\nModelled precipitation rate OLS linear trends between 2015-2070 with respect to 1995-2014 average over S.E. South America region, from left to right (MPI-ESM member with min (driest) and max (wettest) trends):\r\nFig_10_10_panel-a_mapplot_trend_SES_DJF_MPI-GE_min_single-MultiModelMean_trend-min-median-max.nc, \r\nFig_10_10_panel-a_mapplot_trend_SES_DJF_MPI-GE_max_single-MultiModelMean_trend-min-median-max.nc\r\n \r\n Panel (b):\r\n - Data files: \r\nPrecipitation rate anomalies 1950-2100 with respect to 1995-2014 average for the global mean, S.E.South-America mean, Sao Paulo mean and Buenos Aires mean of GPCC (dark blue), CRU (dark brown), members of the MPI-ESM (grey), the MPI-ESM member with the driest (brown) and wettest (green) trend:\r\nFig_10_10_panel-b_timeseries_global.csv, \r\nFig_10_10_panel-b_timeseries_SES.csv, \r\nFig_10_10_panel-b_timeseries_SaoPaulo.csv, \r\nFig_10_10_panel-b_timeseries_BuenosAires.csv\r\n\r\n - Data files: \r\nUnderlying data points of the boxplot showing MPI-ESM modelled precipitation rate OLS linear trends over all members between 2015-2070 with respect to 1995-2014 average for the global mean, S.E.South-America mean, Sao Paulo mean and Buenos Aires mean:\r\nFig_10_10_panel-b_boxplot_BuenosAires.csv, \r\nFig_10_10_panel-b_boxplot_global.csv, \r\nFig_10_10_panel-b_boxplot_SaoPaulo.csv, \r\nFig_10_10_panel-b_boxplot_SES.csv; \r\n\r\nOLS - ordinary least squares regression.\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The code for ESMValTool is provided.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 10)\r\n - Link to the Supplementary Material for Chapter 10, which contains details on the input data used in Table 10.SM.11\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37641, "uuid": "8d8eeb00a90e4a6da722e8a8a3aefb90", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_10/ch10_fig11/v20220622", "numberOfFiles": 8, "volume": 298024, "fileFormat": "txt, netCDF, csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34623, "uuid": "970847e5690c4f9e8c4ad455641bd558", "short_code": "ob", "title": "Chapter 10 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 10.11 (v20220622)", "abstract": "Data for Figure 10.11 from Chapter 10 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. 10.11 shows attribution of historic precipitation change in the Sahelian West African monsoon during June to September.\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\nDoblas-Reyes, F.J., A.A. Sörensson, M. Almazroui, A. Dosio, W.J. Gutowski, R. Haarsma, R. Hamdi, B. Hewitson, W.-T. Kwon, B.L. Lamptey, D. Maraun, T.S. Stephenson, I. Takayabu, L. Terray, A. Turner, and Z. Zuo, 2021: Linking Global to Regional Climate Change. 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. 1363–1512, doi:10.1017/9781009157896.012.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 5 subpanels. Data for all subpanels is provided.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n The data is annual June-September (JJAS) precipitation means for:\r\n \r\n - Observed anomalies over 1920-2018 respect to 1955-1984 average over the Sahel (lon: 20°W-30°E, lat: 10°N-20°N)\r\n - Model anomalies over 1920-2018 respect to 1955-1984 average over the Sahel (lon: 20°W-30°E, lat: 10°N-20°N)\r\n - Observed precipitation difference 1980-1990 mean - 1950-1960 mean\r\n - Model differences between 1.5x and 0.2x aerosol scalings over 1955-1984\r\n - Trends in relative precipitation anomalies (baseline 1955-1984) over decline (1955-1984) and recovery (1985-2014) period over the Sahel (lon: 20°W-30°E, lat: 10°N-20°N)\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel (a):\r\nObserved (CRU TS) timeseries anomalies over 1920-2018 in respect to 1955-1984 average over the Sahel (lon: 20°W-30°E, lat: 10°N-20°N):\r\n - Data file: \r\nFig_10_11_panel-a_timeseries_obs.csv\r\n \r\n Panel (b):\r\nObserved (CRU TS) precipitation difference 1980-1990 mean - 1950-1960 mean:\r\n - Data file: \r\nFig_10_11_panel-b_mapplot_pr_change_CRU_single_mean.nc\r\n \r\n Panel (c):\r\nModel differences between 1.5x and 0.2x aerosol scalings over 1955-1984:\r\n - Data file: \r\nFig_10_11_panel-c_mapplot_pr_diff_SMURPHS_single_mean.nc\r\n \r\n Panel (d):\r\nModel timeseries anomalies over 1920-2018 respect to 1955-1984 average over the Sahel (lon: 20°W-30°E, lat: 10°N-20°N) for CMIP6 hist all-forcings (red), CMIP6 hist all-forcings sample corresponding to DAMIP experiments (pink), CMIP6 hist-aer (grey) and CMIP6 hist-GHG (pale blue):\r\n - Data file: \r\nFig_10_11_panel-d_timeseries_cmip6.csv\r\n \r\n Panel (e):\r\nObserved and modelled OLS linear trends in relative precipitation anomalies (baseline 1955-1984) over decline (1955-1984) and recovery (1985-2014) period over the Sahel (lon: 20°W-30°E, lat: 10°N-20°N): observed data (GPCC, CRU TS: black crosses), 34 CMIP5 models (dark blue circles), individual members of CMIP6 hist all-forcings (red circles), CMIP6 hist all-forcings sample corresponding to DAMIP experiments (pink circles), CMIP6 hist-GHG (blue triangles), CMIP6 hist-aer (grey triangles), and box-and-whisker plots for the SMILEs: MIROC6, CSIRO-Mk3-6-0, MPI-ESM, d4PDF (grey shading):\r\n - Data file: \r\nFig_10_11_panel-e_trends.csv;\r\n\r\nAcronyms: \r\nCMIP - Coupled Model Intercomparison Project, \r\nCRU TS- Climatic Research Unit Time Series, \r\nSMURPHS - Securing Multidisciplinary UndeRstanding and Prediction of Hiatus and Surge events, \r\nDAMIP - Detection and Attribution Model Intercomparison Project, \r\nGHG - Greenhouse Gases, \r\nGPCC - GLOBAL PRECIPITATION CLIMATOLOGY CENTRE, \r\nSMILEs -single model initial-condition large ensembles, \r\nCSIRO - Commonwealth Scientific and Industrial Research Organisation, \r\nMIROC - Model for Interdisciplinary Research on Climate, \r\nMPI - Max-Planck-Institut für Meteorologie, \r\nd4PDF - Database for Policy Decision-Making for Future Climate Change, \r\nOLS - ordinary least squares regression. \r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The code for ESMValTool is provided.\r\n\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 10)\r\n - Link to the Supplementary Material for Chapter 10, which contains details on the input data used in Table 10.SM.11\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37642, "uuid": "2f303317bf744b8a98ecf893a3287c67", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_10/ch10_fig12/v20220622", "numberOfFiles": 7, "volume": 124224, "fileFormat": "txt, netCDF, csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34620, "uuid": "b981b3f983df4aa48a16ddbe3d8bf38d", "short_code": "ob", "title": "Chapter 10 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 10.12 (v20220622)", "abstract": "Data for Figure 10.12 from Chapter 10 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 10.12 shows Southeastern South America positive mean precipitation trend and its drivers during 1951-2014.\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\nDoblas-Reyes, F.J., A.A. Sörensson, M. Almazroui, A. Dosio, W.J. Gutowski, R. Haarsma, R. Hamdi, B. Hewitson, W.-T. Kwon, B.L. Lamptey, D. Maraun, T.S. Stephenson, I. Takayabu, L. Terray, A. Turner, and Z. Zuo, 2021: Linking Global to Regional Climate Change. 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. 1363–1512, doi:10.1017/9781009157896.012.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 4 subpanels. Data for 3 subpanels (b-d) is provided. Subpanel (a) is a schematic.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n The data is annual December-Jannuary (DJF) precipitation means for:\r\n \r\n - Observed and model relative anomalies over 1951-2014 with respect to 1995-2014 average over south-eastern South America (26.25°S–38.75°S, 56.25°W–66.25°W)\r\n - Observed precipitation trends 1951-2014 South America\r\n - Trends in precipitation over 1951-2014 over south-eastern South America (26.25°S–38.75°S, 56.25°W–66.25°W)\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel (b):\r\nObserved (CRU TS, black line, and CRU TS no-running mean (bars)) and Model (MPI-ESM runs with min (brown) and max (green) trends) precipitation rate relative anomalies over 1951-2014 with respect to 1995-2014 average over south-eastern South America (26.25°S–38.75°S, 56.25°W–66.25°W):\r\n - Data file: \r\nFig_10_12_panel-b_timeseries.csv\r\n \r\n Panel (c):\r\nObserved precipitation OLS linear trends 1951-2014 over South America:\r\n - Data files: \r\nFig_10_12_panel-c_mapplot_pr_trend_CRU_single_trend.nc, \r\nFig_10_12_panel-c_mapplot_pr_trend_GPCC_single_trend.nc \r\n \r\n Panel (d):\r\nOLS linear trends in precipitation over 1951-2014 over south-eastern South America (26.25°S–38.75°S, 56.25°W–66.25°W): observed data (GPCC, CRU TS: black crosses), individual members of CMIP6 historical (red circles), and box-and-whisker plots for the SMILEs: MIROC6, CSIRO-Mk3-6-0, MPI-ESM, d4PDF (grey shading):\r\n - Data file: \r\nFig_10_12_panel-d_trends.csv\r\n\r\n\r\nAcronyms: \r\nCRU TS- Climatic Research Unit Time Series, \r\nCMIP - Coupled Model Intercomparison Project, \r\nSMILEs -single model initial-condition large ensembles, \r\nMIROC - Model for Interdisciplinary Research on Climate, \r\nCSIRO - Commonwealth Scientific and Industrial Research Organisation, \r\nMPI - Max-Planck-Institut für Meteorologie, \r\nESM - Earth System Model, \r\nd4PDF - Database for Policy Decision-Making for Future Climate Change, OLS - ordinary least squares regression. \r\n\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The code for ESMValTool is provided.\r\n\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 10)\r\n - Link to the Supplementary Material for Chapter 10, which contains details on the input data used in Table 10.SM.11\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37643, "uuid": "772c4f0d3d0c486cbd6b759025b641ad", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_10/ch10_fig13/v20220622", "numberOfFiles": 15, "volume": 693122, "fileFormat": "txt, netCDF, csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34617, "uuid": "5d64c2103c534f83b8ec11a2a4cab10d", "short_code": "ob", "title": "Chapter 10 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 10.13 (v20220622)", "abstract": "Data for Figure 10.13 from Chapter 10 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 10.13 shows attribution of the southwestern North America precipitation decline during the 1983-2014 period.\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\nDoblas-Reyes, F.J., A.A. Sörensson, M. Almazroui, A. Dosio, W.J. Gutowski, R. Haarsma, R. Hamdi, B. Hewitson, W.-T. Kwon, B.L. Lamptey, D. Maraun, T.S. Stephenson, I. Takayabu, L. Terray, A. Turner, and Z. Zuo, 2021: Linking Global to Regional Climate Change. 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. 1363–1512, doi:10.1017/9781009157896.012.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 3 subpanels. Data for all subpanels is provided.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n The data is annual October-September (water year) precipitation means for:\r\n \r\n - Observed and modelled trends over 1983-2014\r\n - Observed and modelled relative anomalies with respect to 1971-2000 averages over southwestern North America (lon: 240°E-255°E, lat: 28°N-40°N)\r\n - Trends in relative precipitation anomalies between 1983-2014 (baseline 1983-2014) over southwestern North America (lon: 240°E-255°E, lat: 28°N-40°N)\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel (a):\r\nObserved and Model (MPI-ESM and d4PDF runs with min and max trends as well as mean trends) OLS linear trends in precipitation between 1983 and 2014 over North America:\r\n - Data files: \r\nFig_10_13_panel-a_mapplot_pr_trend_CRU_single_trend.nc, \r\nFig_10_13_panel-a_mapplot_pr_trend_REGEN_single_trend.nc, \r\nFig_10_13_panel-a_mapplot_pr_trend_GPCC_single_trend.nc, \r\nFig_10_13_panel-a_mapplot_pr_trend_GPCP_single_trend.nc, \r\nFig_10_13_panel-a_mapplot_pr_trend_d4pdf_d4PDF_max_single-MultiModelMean_trend-min-mean-max.nc, \r\nFig_10_13_panel-a_mapplot_pr_trend_d4pdf_d4PDF_min_single-MultiModelMean_trend-min-mean-max.nc, \r\nFig_10_13_panel-a_mapplot_pr_trend_d4pdf_d4PDF_MultiModelMean_single-MultiModelMean_trend-min-mean-max.nc, \r\nFig_10_13_panel-a_mapplot_pr_trend_mpige_MPI-GE_max_single-MultiModelMean_trend-min-mean-max.nc, \r\nFig_10_13_panel-a_mapplot_pr_trend_mpige_MPI-GE_min_single-MultiModelMean_trend-min-mean-max.nc, F\r\nig_10_13_panel-a_mapplot_pr_trend_mpige_MPI-GE_MultiModelMean_single-MultiModelMean_trend-min-mean-max.nc\r\n \r\n Panel (b):\r\nObserved (CRU TS, black) and Model (d4PDF runs with min (brown) and max (green) trends) timeseries relative precipitation anomalies in respect to 1971-2000 averages over southwestern North America (lon: 240°E-255°E, lat: 28°N-40°N):\r\n - Data file: \r\nFig_10_13_panel-b_timeseries.csv\r\n \r\n Panel (c):\r\nOLS linear trends in relative precipitation anomalies between 1983-2014 (baseline 1983-2014) over southwestern North America (lon: 240°E-255°E, lat: 28°N-40°N): observed data (CRU TS, REGEN, GPCC and GPCP, black crosses), individual members of CMIP6 historical (red circles), and box-and-whisker plots for the SMILEs: MIROC6, CSIRO-Mk3-6-0, MPI-ESM, d4PDF (grey shading):\r\n - Data file: \r\nFig_10_13_panel-c_trends.csv\r\n\r\n\r\nAcronyms: \r\nCMIP - Coupled Model Intercomparison Project, \r\nHighResMIP - High Resolution Model Intercomparison Project, \r\nCordex – Coordinated Regional Climate Downscaling Experiment, \r\nCRU TS- Climatic Research Unit Time Series, \r\nGPCC - GLOBAL PRECIPITATION CLIMATOLOGY CENTRE, \r\nGPCP - Global Precipitation Climatology Project, \r\nd4PDF - Database for Policy Decision-Making for Future Climate Change, \r\nMPI GE - Max-Planck-Institut für Meteorologie Grand Ensemble, \r\nESM - Earth System Model, \r\nSMILEs -single model initial-condition large ensembles, \r\nMIROC - Model for Interdisciplinary Research on Climate, \r\nCSIRO - Commonwealth Scientific and Industrial Research Organisation, \r\nREGEN -Rainfall Estimates on a Gridded Network, \r\nOLS - ordinary least squares regression. \r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The code for ESMValTool is provided.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 10)\r\n - Link to the Supplementary Material for Chapter 10, which contains details on the input data used in Table 10.SM.11\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37644, "uuid": "a55e3f47fff34f7f86a054b10ab707bf", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_10/ch10_fig19/v20220622", "numberOfFiles": 12, "volume": 535900, "fileFormat": "txt, netCDF, csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34614, "uuid": "e79aab21bf644e61bf5dacd02199daa3", "short_code": "ob", "title": "Chapter 10 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 10.19 (v20220622)", "abstract": "Data for Figure 10.19 from Chapter 10 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 10.19 shows changes in the Indian summer monsoon in the historical and future periods.\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\nDoblas-Reyes, F.J., A.A. Sörensson, M. Almazroui, A. Dosio, W.J. Gutowski, R. Haarsma, R. Hamdi, B. Hewitson, W.-T. Kwon, B.L. Lamptey, D. Maraun, T.S. Stephenson, I. Takayabu, L. Terray, A. Turner, and Z. Zuo, 2021: Linking Global to Regional Climate Change. 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. 1363–1512, doi:10.1017/9781009157896.012.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 6 subpanels. Data for all subpanels is provided.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n The dataset contains:\r\n APHRODITE station density for June-September (JJAS) 1956\r\n Precipitation June-September (JJAS):\r\n \r\n - Model mean bias 1985-2010\r\n - Observed and modelled trends: CRU TS 1950-2000, CMIP6 hist-GHG & hist-aer 1950-2000, and CMIP6 SSP5-8.5 2015-2100 trends\r\n - Observed and model relative anomalies over 1950-2100 with respect to 1995-2014 averages over central India (lon: 76°E-87°E, lat: 20°N-28°N)\r\n - Modelled change until 2081‒2100 with respect to 1995-2014 averages over central India (lon: 76°E-87°E, lat: 20°N-28°N)\r\n - Trends in relative precipitation anomalies (baseline 1995-2014) over past (1950-2000) and future (2015-2100) period over central India (lon: 76°E-87°E, lat: 20°N-28°N).\r\n - Trend difference between the 3 MPI-ESM runs with the lowest and the 3 MPI-ESM runs with the highest trend\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel (a):\r\nAPHRODITE station density for JJAS 1956:\r\n - Data file: \r\nFig_10_19_panel-a_mapplot_APHRODITE_stationdensity_single_mean.nc\r\n \r\n Panel (b):\r\nCMIP6 mean precipitation bias June-September mean 1985-2010 mean with respect to CRU TS:\r\n - Data file: \r\nFig_10_19_panel-b_mapplot_pr_cmip6_bias_pr_cmip6_maps_past_bias_MultiModelMean_bias.nc\r\n \r\n Panel (c):\r\nOLS linear precipitation for June-September mean trend of CRU TS 1950-2000 (top left), CMIP6 hist-GHG (bottom left) & hist-aer (bottom right) 1950-2000, and CMIP6 SSP5-8.5 2015-2100 (top right):\r\n - Data files: \r\nFig_10_19_panel-c_mapplot_pr_cmip6_mean_trend_future_pr_cmip6_maps_trend_future_MultiModelMean_trend.nc,\r\nFig_10_19_panel-c_mapplot_pr_histaer_mean_trend_past_pr_aer_maps_trend_past_MultiModelMean_trend.nc, \r\nFig_10_19_panel-c_mapplot_pr_histghg_mean_trend_past_pr_ghg_maps_trend_past_MultiModelMean_trend.nc, \r\nFig_10_19_panel-c_mapplot_pr_obs_mean_trend_past_CRU_single_trend.nc;\r\n \r\n Panel (d):\r\nObserved and model relative precipitation June-September mean anomalies over 1950-2100 in respect to 1995-2014 averages over central India (lon: 76°E-87°E, lat: 20°N-28°N) (CRU TS (brown), GPCC (dark blue), REGEN (green), APHRO-MA (light brown), IITM all-India rainfall (light blue), CMIP6 hist all-forcings sample corresponding to DAMIP experiments (pink), CMIP6 hist-aer (grey), hist-GHG (light blue) CMIP6 historical/SSP5-8.5 (dark red) and CMIP5 historical/RCP8.5 (dark blue) and Modelled change until 2081‒2100 in respect to 1995-2014 averages over central India (CMIP6 SSP5-8.5 (dark red) and CMIP5 historical/RCP8.5 (dark blue)):\r\n - Data files: \r\nFig_10_19_panel-d_timeseries.csv, \r\nFig_10_19_panel-d_boxplot.csv\r\n \r\n Panel (e):\r\nOLS linear trends in relative precipitation June-September mean anomalies (baseline 1995-2014) over past (1950-2000) and future (2015-2100) period over central India (lon: 76°E-87°E, lat: 20°N-28°N) of observations (GPCC, CRU TS, REGEN and APRHO-MA: black crosses) and models (individual members of CMIP5 historical-RCP8.5 (blue), CMIP6 historical-SSP5-8.5 (dark red), CMIP6 hist all-forcings sample corresponding to DAMIP experiments (pink circles), CMIP6 hist-GHG (blue triangles), CMIP6 hist-aer (grey triangles)), and box-and-whisker plots for the SMILEs: MIROC6, CSIRO-Mk3-6-0, MPI-ESM, d4PDF (grey shading):\r\n - Data file: \r\nFig_10_19_panel-e_trends.csv\r\n \r\n Panel (f):\r\nJune-September mean 2016-2045 OLS linear trend difference in precipitation between the 3 MPI-ESM runs with the lowest and the 3 MPI-ESM runs with the highest trend:\r\n - Data file: \r\nFig_10_19_panel-f_mapplot_pr_mpige_mean_trend_future_spread_single_trend-difference-min3-max3.nc\r\n\r\nAcronyms: \r\nCMIP - Coupled Model Intercomparison Project, \r\nAPHRODITE - ASIAN PRECIPITATION - HIGHLY-RESOLVED OBSERVATIONAL DATA INTEGRATION TOWARDS EVALUATION OF WATER RESOURCES, \r\nCRU TS- Climatic Research Unit Time Series, \r\nGHG - Greenhouse gas, \r\nIITM - Indian Institute of Technology Madras, \r\nRCP - Representative Concentration Pathway, \r\nDAIMP - Detection and Attribution Model Intercomparison Project, \r\nSSP - Shared Socioeconomic Pathways, \r\nGPCC - GLOBAL PRECIPITATION CLIMATOLOGY CENTRE, \r\nREGEN - Rainfall Estimates on a Gridded Network, S\r\nMILEs -single model initial-condition large ensembles, \r\nd4PDF - Database for Policy Decision-Making for Future Climate Change, \r\nMIROC - Model for Interdisciplinary Research on Climate, \r\nMPI - Max-Planck-Institut für Meteorologie, \r\nESM - Earth System Model, \r\nCordex – Coordinated Regional Climate Downscaling Experiment, \r\nOLS - ordinary least squares regression. \r\n\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The code for ESMValTool is provided.\r\n\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 10)\r\n - Link to the Supplementary Material for Chapter 10, which contains details on the input data used in Table 10.SM.11\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37645, "uuid": "b446aa6d7b344c93b7c48f55de72bc99", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_10/ch10_fig20/v20220622", "numberOfFiles": 11, "volume": 270651, "fileFormat": "txt, netCDF, csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34611, "uuid": "19ec340e6f2d47479ddb483961b0c1bb", "short_code": "ob", "title": "Chapter 10 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 10.20 (v20220113)", "abstract": "Data for Figure 10.20 from Chapter 10 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 10.20 shows aspects of Mediterranean summer warming.\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\nDoblas-Reyes, F.J., A.A. Sörensson, M. Almazroui, A. Dosio, W.J. Gutowski, R. Haarsma, R. Hamdi, B. Hewitson, W.-T. Kwon, B.L. Lamptey, D. Maraun, T.S. Stephenson, I. Takayabu, L. Terray, A. Turner, and Z. Zuo, 2021: Linking Global to Regional Climate Change. 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. 1363–1512, doi:10.1017/9781009157896.012.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 7 subpanels. Data for subpanels d, e, f and g is provided.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n The data is annual summer (JJA) means for:\r\n \r\n - Observed trends over 1960-2014\r\n - Anomalies 1960-2014 with respect to 1995-2014 average for the Mediterranean mean (lon: 10°W-40°E, lat: 25°N-50°N)\r\n - Trends 1960-2014 for the Mediterranean mean (lon: 10°W-40°E, lat: 25°N-50°N)\r\n - Modelled trend differences to the observed over 1960-2014\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel (d):\r\n - Data file: Fig_10_20_panel-d_mapplot_tas_obs_trend_single_single_trend.nc; \r\nJJA Berkeley Earth surface air temperature OLS linear trends over 1960-2014 over the Mediterranean (lon: 10°W-40°E, lat: 25°N-50°N)\r\n \r\n Panel (e):\r\n - Data file: Fig_10_20_panel-e_timeseries.csv; \r\nObserved and modelled JJA surface air temperature anomalies 1960-2014 (baseline 1995-2014) for the Mediterranean mean (lon: 10°W-40°E, lat: 25°N-50°N): CMIP5 (blue), CMIP6 (red), HighResMIP (orange), CORDEX EUR-44 (light blue), CORDEX EUR-11 (green), Berkeley Earth (dark blue), CRU TS (brown), HadCRUT5 (cyan)\r\n \r\n Panel (f):\r\n - Data file: Fig_10_20_panel-f_trends.csv; \r\nJJA OLS linear trends in surface air temperature 1960-2014 for the Mediterranean mean (lon: 10°W-40°E, lat: 25°N-50°N) of observations (Berkeley Earth, CRU TS, HadCRUT5: black crosses) and models (CMIP5 (blue circles), CMIP6 (red circles), HighResMIP (orange circles), CORDEX EUR-44 (light blue circles), CORDEX EUR-11 (green circles)) and box-and-whisker plots for the SMILEs: MIROC6, CSIRO-Mk3-6-0, MPI-ESM, d4PDF (grey shading)\r\n \r\n Panel (g):\r\n - Data files: \r\nFig_10_20_panel-g_mapplot_tas_cmip5_mean_trend_bias_tas_cmip5_maps_trend_MultiModelMean_trend-bias.nc, \r\nFig_10_20_panel-g_mapplot_tas_cmip6_mean_trend_bias_tas_cmip6_maps_trend_MultiModelMean_trend-bias.nc, \r\nFig_10_20_panel-g_mapplot_tas_cordex_11_mean_trend_bias_tas_cordex_11_maps_trend_MultiModelMean_trend-bias.nc, \r\nFig_10_20_panel-g_mapplot_tas_cordex_44_mean_trend_bias_tas_cordex_44_maps_trend_MultiModelMean_trend-bias.nc, \r\nFig_10_20_panel-g_mapplot_tas_hrmip_mean_trend_bias_tas_hrmip_maps_trend_MultiModelMean_trend-bias.nc; \r\nModelled OLS linear surface air temperature trend differences to the observed trend (Berkeley Earth) over 1960-2014 of CMIP5, CMIP6, HighResMIP, CORDEX EUR-44, and CORDEX EUR-11 ensemble means\r\n\r\n\r\nAcronyms: \r\nCMIP - Coupled Model Intercomparison Project, \r\nCordex – Coordinated Regional Climate Downscaling Experiment, \r\nCRU TS- Climatic Research Unit Time Series, \r\nCSIRO - Commonwealth Scientific and Industrial Research Organisation, \r\nMIROC - Model for Interdisciplinary Research on Climate, \r\nSMILEs - single model initial-condition large ensembles, \r\nd4PDF - Database for Policy Decision-Making for Future Climate Change, \r\nOLS - ordinary least squares regression. \r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The code for ESMValTool is provided.\r\n\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 10)\r\n - Link to the Supplementary Material for Chapter 10, which contains details on the input data used in Table 10.SM.11\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37646, "uuid": "e424abd8ec144ba4933d406fb94dd0a1", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_10/ch10_fig21/v20220622", "numberOfFiles": 12, "volume": 9192977, "fileFormat": "txt, netCDF, csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34608, "uuid": "9f83afcc47ca49feb1d5702de9fa8869", "short_code": "ob", "title": "Chapter 10 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 10.21 (v20220622)", "abstract": "Data for Figure 10.21 from Chapter 10 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 10.21 shows projected Mediterranean summer warming.\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\nDoblas-Reyes, F.J., A.A. Sörensson, M. Almazroui, A. Dosio, W.J. Gutowski, R. Haarsma, R. Hamdi, B. Hewitson, W.-T. Kwon, B.L. Lamptey, D. Maraun, T.S. Stephenson, I. Takayabu, L. Terray, A. Turner, and Z. Zuo, 2021: Linking Global to Regional Climate Change. 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. 1363–1512, doi:10.1017/9781009157896.012.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 4 subpanels. Data for all subpanels is provided.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n The data is annual summer (JJA) surface air temperature means for:\r\n \r\n - Modelled anomalies 2015-2100 with respect to 1995-2014 average for the Mediterranean mean (lon: 10°W-40°E, lat: 25°N-50°N)\r\n - Modelled change until 2081‒2100 with respect to 1995-2014 averages over the Mediterranean (lon: 10°W-40°E, lat: 25°N-50°N)\r\n - Trends 2015-2050 for the Mediterranean mean (lon: 10°W-40°E, lat: 25°N-50°N)\r\n - Modelled trends over 2015-2050\r\n - Modelled Mediterranean summer vs global warming\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel (a):\r\n - Data files: \r\nFig_10_21_panel-a_timeseries.csv, \r\nFig_10_21_panel-a_boxplot.csv; \r\nModelled JJA surface air temperature anomalies 2015-2100 (baseline 1995-2014) for the Mediterranean mean (lon: 10°W-40°E, lat: 25°N-50°N, CMIP5 (blue), CMIP6 (dark red), HighResMIP (orange), CORDEX EUR-44 (light blue), CORDEX EUR-11 (green)) and change until 2081‒2100 in respect to 1995-2014 averages (SSP1-2.6 dark blue, SSP2-4.5 yellow, SSP3-7.0 red, SSP5-8.5 dark red)\r\n \r\n Panel (b):\r\n - Data file: Fig_10_21_panel-b_trends.csv; \r\nModelled JJA OLS linear trends in surface air temperature 2015-2050 for the Mediterranean mean (lon: 10°W-40°E, lat: 25°N-50°N) CMIP5 (blue circles), CMIP6 (dark red circles), HighResMIP (orange circles), CORDEX EUR-44 (light blue circles), CORDEX EUR-11 (green circles)) and box-and-whisker plots for the SMILEs: MIROC6, CSIRO-Mk3-6-0, MPI-ESM (grey shading)\r\n \r\n Panel (c):\r\n - Data files: \r\nFig_10_21_panel-c_mapplot_tas_cmip5_mean_trend_future_tas_cmip5_maps_trend_MultiModelMean_trend.nc, \r\nFig_10_21_panel-c_mapplot_tas_cmip6_mean_trend_future_tas_cmip6_maps_trend_MultiModelMean_trend.nc, \r\nFig_10_21_panel-c_mapplot_tas_cordex_11_mean_trend_future_tas_cordex_11_maps_trend_native_MultiModelMean_trend.nc, \r\nFig_10_21_panel-c_mapplot_tas_cordex_44_mean_trend_future_tas_cordex_44_maps_trend_native_MultiModelMean_trend.nc, \r\nFig_10_21_panel-c_mapplot_tas_hrmip_mean_trend_future_tas_hrmip_maps_trend_05_MultiModelMean_trend.nc; \r\nModelled OLS linear surface air temperature trends over 2015-2050 of CMIP5, CMIP6, HighResMIP, CORDEX EUR-44, and CORDEX EUR-11 ensemble means\r\n \r\n Panel (d):\r\n - Data file: Fig_10_21_panel-d_GWLRWL.csv; \r\nModelled Mediterranean summer (JJA) vs global warming under CMIP5 (RCP2.6 dark blue dashed line, RCP4.5 light blue dashed line, RCP6.0 orange dashed line and RCP8.5 red dashed line) and CMIP6 (SSP1-2.6 dark blue line, SSP2-4.5 yellow line, SSP3-7.0 red line, SSP5-8.5 dark red line) scenarios.\r\n\r\n\r\nAcronyms: \r\nCMIP - Coupled Model Intercomparison Project, \r\nCordex – Coordinated Regional Climate Downscaling Experiment, \r\nHighResMIP - High Resolution Model Intercomparison Project, \r\nSSP- Shared Socioeconomic Pathways, \r\nSMILEs -single model initial-condition large ensembles, \r\nMIROC - Model for Interdisciplinary Research on Climate, \r\nCSIRO - Commonwealth Scientific and Industrial Research Organisation, \r\nMPI - Max-Planck-Institut für Meteorologie, ESM - Earth System Model, \r\nRCP - Representative Concentration Pathway, \r\nOLS - ordinary least squares regression. \r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The code for ESMValTool is provided.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 10)\r\n - Link to the Supplementary Material for Chapter 10, which contains details on the input data used in Table 10.SM.11\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37648, "uuid": "2397138dc00b46bd8109621870fd269c", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_11/ch11_faq1_fig1/v20220629", "numberOfFiles": 7, "volume": 410091, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37647, "uuid": "f218301d1f4a46f1bf27023a77a58639", "short_code": "ob", "title": "Chapter 11 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for FAQ 11.1, figure 1 (v20220629)", "abstract": "Data for FAQ 11.1 , figure 1 from Chapter 11 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nFAQ 11.1, figure 1 shows global maps of future changes in surface temperature and precipitation for long-term average and extreme conditions.\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 Seneviratne, S.I., X. Zhang, M. Adnan, W. Badi, C. Dereczynski, A. Di Luca, S. Ghosh, I. Iskandar, J. Kossin, S. Lewis, F. Otto, I. Pinto, M. Satoh, S.M. Vicente-Serrano, M. Wehner, and B. Zhou, 2021: Weather and Climate Extreme Events in a Changing Climate. 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. 1513–1766, doi:10.1017/9781009157896.013.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has four panels, with data provided for all panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n - Summer mean temperature (days) change (relative to 1850-1900)\r\n - Annual maximum temperature (°C) change (relative to 1850-1900)\r\n - Summer mean precipitatioin (%) change (relative to 1850-1900)\r\n - Annual maximum daily precipitation (%) change (relative to 1850-1900)\r\n\r\n The data is given at a global warming levels (GWL) of +4.0°C.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel a:\r\n - FAQ_11_1_Figure_1a_cmip6_summer_temperature_change_at_4_0C.nc: simulated summer mean temperature change (°C) at 4.0°C global warming relative to 1850-1900\r\n \r\n Panel b:\r\n - FAQ_11_1_Figure_1b_cmip6_TXx_change_at_4_0C.nc: simulated annual maximum temperature change (°C) at 4.0°C global warming relative to 1850-1900\r\n \r\n Panel c:\r\n - FAQ_11_1_Figure_1c_cmip6_summer_prec_change_at_4_0C.nc: simulated summer mean precipitation change (%) at 4.0°C global warming relative to 1850-1900\r\n \r\n Panel d:\r\n - FAQ_11_1_Figure_1d_cmip6_Rx1day_change_at_4_0C.nc: simulated annual maximum daily precipitation change (%) at 4.0°C global warming relative to 1850-1900\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 11)\r\n - Link to the Supplementary Material for Chapter 11, which contains details on the input data used in Table 11.SM.9\r\n - Link to the Ch11 GitHub repository containing scripts for generating figures\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37651, "uuid": "3652d7b5899a45e4878768d03c167cc3", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_11/ch11_fig03/v20220629", "numberOfFiles": 4, "volume": 2420093, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37650, "uuid": "592748a417ab4efca4eb98e22c9dbec4", "short_code": "ob", "title": "Chapter 11 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 11.3 (v20220629)", "abstract": "Data for Figure 11.3 from Chapter 11 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 11.3 shows regional mean changes in annual hottest daily maximum temperature (TXx) for AR6 land regions and the global land, against changes in global mean surface air temperature (GSAT) as simulated by CMIP6 models under different forcing scenarios SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5\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 Seneviratne, S.I., X. Zhang, M. Adnan, W. Badi, C. Dereczynski, A. Di Luca, S. Ghosh, I. Iskandar, J. Kossin, S. Lewis, F. Otto, I. Pinto, M. Satoh, S.M. Vicente-Serrano, M. Wehner, and B. Zhou, 2021: Weather and Climate Extreme Events in a Changing Climate. 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. 1513–1766, doi:10.1017/9781009157896.013.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has twelve panels, with data provided for all panels in one single file.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n \r\n - Annual maximum temperature change (°C) as a function of global warming levels (GWLs) relative to 1850-1900 for the IPCC climate reference regions (Iturbide et al., 2020)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Figure_11_3_cmip6_TXx_scaling.nc: data for panels (a) through (l)\r\n\r\nSSP stands for Shared Socioeconomic Pathway and RCP stands for Representative Concentration Pathway.\r\nSSP1-1.9 and SSP1-2.6 are based on Shared Socioeconomic Pathway SSP1 with low climate change mitigation and adaptation challenges. SSP1-1.9 is based on RCP1.9, a future pathway with a radiative forcing of 1.9 W/m2 in the year 2100 and SSP1-2.6 is based on RPC2.6.\r\nSSP2-4.5 is based on Shared Socioeconomic Pathway SSP2 with medium challenges to climate change mitigation and adaptation and RCP4.5, a future pathway with a radiative forcing of 4.5 W/m2 in the year 2100.\r\nSSP3-7.0 is based on SSP3 which is characterized by high challenges to both mitigation and adaptation and RCP7.0, a future pathway with a radiative forcing of 7.0 W/m2 in the year 2100.\r\nSSP5-8.5 is based on SSP5 where climate change mitigation challenges dominate and RCP8.5, a future pathway with a radiative forcing of 8.5 W/m2 in the year 2100.\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n Panel (a): shows the individual ensemble members and the median of three SSPs. Other panels show the multi model median (over the 'mod_ens' dimension). The regions 'global', 'ocean', 'land', 'GIC', 'EAN', and 'WAN' are not shown in the figure.\r\n\r\n---------------------------------------------------\r\nSources of additional information\r\n---------------------------------------------------\r\nThe following weblinks are provided in the Related Documents section of this catalogue record:\r\n- Link to the figure on the IPCC AR6 website\r\n- Link to the report component containing the figure (Chapter 11)\r\n- Link to the Supplementary Material for Chapter 11, which contains details on the input data used in Table 11.SM.9\r\n- Link to the code for the figure, archived on Zenodo\r\n- Link to the Ch11 GitHub repository containing scripts for generating figures" }, "onlineresource_set": [] }, { "ob_id": 37654, "uuid": "b5c8a52fa50443d3800cad4d8d20208d", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_11/ch11_fig19/v20230203", "numberOfFiles": 15, "volume": 2377844, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37653, "uuid": "7be388b022e74926b0103125d22e6b06", "short_code": "ob", "title": "Chapter 11 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 11.19 (v20230203)", "abstract": "Data for Figure 11.19 from Chapter 11 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 11.19 shows projected changes in the number of consecutive dry days (CDD), annual mean soil moisture over the total column, and the frequency and intensity of one-in-ten year soil moisture (SM) drought for the June-to-August and December-to-February seasons at 1.5°C, 2°C, and 4°C of global warming compared to the 1851-1900 baseline.\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\n Seneviratne, S.I., X. Zhang, M. Adnan, W. Badi, C. Dereczynski, A. Di Luca, S. Ghosh, I. Iskandar, J. Kossin, S. Lewis, F. Otto, I. Pinto, M. Satoh, S.M. Vicente-Serrano, M. Wehner, and B. Zhou, 2021: Weather and Climate Extreme Events in a Changing Climate. 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. 1513–1766, doi:10.1017/9781009157896.013.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has twelve panels, with data provided for all panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n - Annual consecutive dry days change (days) (relative to 1850-1900)\r\n - Annual total column soil moisture (std) (relative to 1850-1900)\r\n - July-to-August frequency of 1-in-10 year soil moisture drought change (-) (relative to 1850-1900)\r\n - December-to-February frequency of 1-in-10 year soil moisture drought change (-) (relative to 1850-1900)\r\n\r\n\r\nThe data is given for global warming levels (GWLs), namely +1.5°C, 2.0°C, and +4.0°C.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel a:\r\n - Figure_11_19a_cmip6_CDD_change_at_1_5C.nc: simulated consecutive dry days change (days) at 1.5°C global warming relative to 1850-1900\r\n \r\n Panel b:\r\n - Figure_11_19b_cmip6_CDD_change_at_2_0C.nc: simulated consecutive dry days change (days) at 2.0°C global warming relative to 1850-1900\r\n \r\n Panel c:\r\n - Figure_11_19c_cmip6_CDD_change_at_4_0C.nc: simulated consecutive dry days change (days) at 4.0°C global warming relative to 1850-1900\r\n \r\n Panel d:\r\n - Figure 11_19d_cmip6_SM_total_change_at_1_5C.nc: simulated total column soil moisture change (std) at 1.5°C global warming relative to 1850-1900\r\n \r\n Panel e:\r\n - Figure 11_19e_cmip6_SM_total_change_at_2_0C.nc: simulated total column soil moisture change (std) at 2.0°C global warming relative to 1850-1900\r\n \r\n Panel f:\r\n - Figure 11_19f_cmip6_SM_total_change_at_4_0C.nc: simulated total column soil moisture change (std) at 4.0°C global warming relative to 1850-1900\r\n \r\n Panel g:\r\n - Figure_11_19g_JJA_cmip6_SM_drought_index_change_at_1_5C.nc: simulated July-to-August frequency of 1-in-10 year soil moisture drought change (-) at 1.5°C global warming relative to 1850-1900\r\n \r\n Panel h:\r\n - Figure_11_19h_JJA_cmip6_SM_drought_index_change_at_2_0C.nc: simulated July-to-August frequency of 1-in-10 year soil moisture drought change (-) at 2.0°C global warming relative to 1850-1900\r\n \r\n Panel i:\r\n - Figure_11_19i_JJA_cmip6_SM_drought_index_change_at_4_0C.nc: simulated July-to-August frequency of 1-in-10 year soil moisture drought (-) at 4.0°C global warming relative to 1850-1900\r\n \r\n Panel j:\r\n - Figure_11_19j_cmip6_DJF_SM_drought_index_change_at_1_5C.nc: simulated December-to-February frequency of 1-in-10 year soil moisture drought change (-) at 1.5°C global warming relative to 1850-1900\r\n \r\n Panel k:\r\n - Figure_11_19k_cmip6_DJF_SM_drought_index_change_at_2_0C.nc: simulated December-to-February frequency of 1-in-10 year soil moisture drought change (-) at 2.0°C global warming relative to 1850-1900\r\n \r\n Panel l:\r\n - Figure_11_19l_cmip6_DJF_SM_drought_index_change_at_4_0C.nc: simulated December-to-February frequency of 1-in-10 year soil moisture drought change (-) at 4.0°C global warming relative to 1850-1900\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project. \r\n\r\n---------------------------------------------------\r\nNotes on reproducing the figure\r\n---------------------------------------------------\r\nFor panels g to l the data should be plotted with a logarithmic colormap. Note that grid cells with no change (0) have been replaced by 10^-5 such that the logarithm is defined.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 11)\r\n - Link to the Supplementary Material for Chapter 11, which contains details on the input data used in Table 11.SM.9\r\n - Link to the Ch11 GitHub repository containing scripts for generating figures\r\n - Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37657, "uuid": "fa348ae3fca94b69b062c5cc9ed2a443", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_11/ch11_fig11_A_1/v20220629", "numberOfFiles": 4, "volume": 2480248, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37656, "uuid": "2f63e632dc3a494696b1b1315cbb531e", "short_code": "ob", "title": "Chapter 11 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 11.A.1 (v20220629)", "abstract": "Data for Figure 11.A.1 from Chapter 11 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 11.A.1 shows regional mean changes in annual minimum temperature (TNn) for AR6 land regions and the global land, against changes in global mean surface air temperature (GSAT) as simulated by CMIP6 models under different forcing scenarios SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5\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\n Seneviratne, S.I., X. Zhang, M. Adnan, W. Badi, C. Dereczynski, A. Di Luca, S. Ghosh, I. Iskandar, J. Kossin, S. Lewis, F. Otto, I. Pinto, M. Satoh, S.M. Vicente-Serrano, M. Wehner, and B. Zhou, 2021: Weather and Climate Extreme Events in a Changing Climate. 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. 1513–1766, doi:10.1017/9781009157896.013.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has twelve panels, with data provided for all panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n - Annual minimum temperature change (°C) as a function of global warming levels (GWLs) relative to 1850-1900 for the IPCC climate reference regions (Iturbide et al., 2020)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Figure_11_A_1_cmip6_TNn_scaling.nc: data for panels (a) through (l)\r\n\r\nSSP stands for Shared Socioeconomic Pathway.\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n Panel (a): shows the individual ensemble members and the median of three SSPs. Other panels show the multi model median (over the 'mod_ens' dimension). The regions 'global', 'ocean', 'land', 'GIC', 'EAN', and 'WAN' are not shown in the figure.\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 11)\r\n - Link to the Supplementary Material for Chapter 11, which contains details on the input data used in Table 11.SM.9\r\n - Link to the Ch11 GitHub repository containing scripts for generating figures\r\n - Link to the code for Chapter 11 figures, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37663, "uuid": "f2066422dfaa48fc8cd7ae6a6111696f", "short_code": "result", "curationCategory": "A", "dataPath": "/bodc/SOC220091/PRE-MELT_hindcasts", "numberOfFiles": 20, "volume": 511780457950, "fileFormat": "Data are CF-compliant NetCDF formatted data files", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37662, "uuid": "7668ea6b334841b0b7a06c0545664858", "short_code": "ob", "title": "Regional summaries from Arctic high-resolution sea ice-ocean modelling hindcasts (2008-2021)", "abstract": "Regional summaries from the high-resolution sea ice-ocean modelling ERA5JRA55-forced hindcasts (Japanese 55-year atmospheric analysis) were generated to analyse oceanic impacts on retreat of the Arctic sea-ice pack in the high Arctic and from areas of the Transpolar drift, north of Greenland and in the Fram Strait in the present climate. The model outputs span the Arctic Ocean proper and the sub-Arctic seas, covering the near-present climate period from 2008-2021 during which the largest sea ice changes have been observed.\r\n\r\nThe model configuration is Global Ocean and Sea Ice GO8p7, developed under the Joint Marine Modelling Programme (JMMP), a collaborative project between the National Oceanography Centre (NOC), British Antarctic Survey (BAS) and the Met Office. GO8p7 is based on NEMO v4.0 and the SI3 sea ice model and includes a package of modifications intending to address errors in the Southern Ocean, including a scale-dependent Gent & McWilliams parameterisation, partial slip lateral boundary conditions south of 50°S. and 4th-order horizontal tracer advection (Madec et al. 2019).\r\n\r\nThe present simulation was integrated with Japanese Reanalysis JRA55 v1.3-do from 1958 to 2021 (Tsujino et al., 2018). The model output has been validated against AMSR-E satellite sea-ice concentrations, as well as the CryoSat-2 and SMOS sea-ice thickness datasets. The monthly and 5-day averages of the key sea-ice and ocean fields for the pan-Arctic and Greenland regions were created and combined into 4-D files for easy data handling.\r\n\r\nThe model output has been validated against AMSR-E satellite sea-ice concentrations, as well as the CryoSat-2 and SMOS sea-ice thickness datasets. The monthly and 5-day averages of the key sea-ice and ocean fields for the pan-Arctic and Greenland regions were created and combined into 4-D files for easy data handling. \r\n\r\nThe model datasets were produced by National Oceanography Centre (NOC) scientists Dr Yevgeny Aksenov and Dr Stefanie Rynders, using the global model runs carried out by Dr Alex Megann. Dr Andrew Coward also assisted with data handling. The data were produced under Natural Environment Research Council (NERC) project PRE-MELT (grant references NE/T001399/1, NE/T000260/1, NE/T000546/1). The global model integrations were completed thanks to the funding from the National Environmental Research Council (NERC) national capability grant for the North Atlantic Climate System: Integrated study (ACSIS) NCLTS-M program (grant NE/N018044/1) (Megann et al., 2022a,b). Additional funding also came from NERC projects APEAR (grant reference NE/R012865/1) and CLASS (grant reference NE/R015953/1)." }, "onlineresource_set": [] }, { "ob_id": 37669, "uuid": "83bc3618cf304317b19493f2ba535650", "short_code": "result", "curationCategory": "A", "dataPath": "/bodc/SOC220091/PRE-MELT_projections", "numberOfFiles": 9, "volume": 19680668714, "fileFormat": "Data are CF-compliant NetCDF formatted data files", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37668, "uuid": "233fbf6df84547dda891d316da93885b", "short_code": "ob", "title": "Regional summaries from Arctic high-resolution sea ice-ocean forced modelling projections (2000-2050)", "abstract": "Regional summaries from the high-resolution sea ice-ocean-biogeochemical modelling UKESM1.1-forced projections were generated to analyse oceanic impacts on retreat of the Arctic sea-ice pack in the high Arctic and from areas of the Transpolar drift, north of Greenland and in the Fram Strait in the future climate up to the 2050s and subsequent impacts on the ocean biogeochemistry. The model datasets span the Arctic Ocean proper and the sub-Arctic seas, covering the near-present and future climate from 2000-2050. The model used was a NEMOv4.2-SI3 common NOC-UK MetOffice configuration (G8.7) coupled to the MEDUSA ecosystem model. The forcing fields were from the UK ESM1.1 model SSP370 integrations.\r\n\r\nThe sea ice model output has been validated against the AMSR-E satellite sea-ice concentrations, as well as the CryoSat-2 and SMOS sea-ice thickness datasets. Monthly averages of the key sea-ice and ocean fields for the pan-Arctic and Greenland regions for the end of each of the decades 2020, 2030, 2040, and 2050 were created and combined into 4-D files for easy data handling.\r\n\r\nThe model datasets were produced by National Oceanography Centre (NOC) scientists Dr Yevgeny Aksenov and Dr Stefanie Rynders, using the global model runs carried out by Dr Andrew Coward. Dr Andrew Yool advised on the runs and assisted with data handling, and Dr Stephen Kelly also assisted with data extraction. The data were produced under Natural Environment Research Council (NERC) project PRE-MELT (grant references NE/T001399/1, NE/T000260/1, NE/T000546/1). Additional funding also came from NERC projects APEAR (grant reference NE/R012865/1), ARISE (grant reference NE/P006000/1), and Arctic PrIZE (grant reference NE/P006078/1), funded under the NERC/BMBF Changing Arctic Ocean Programme, from NERC NCLTS-M programme ESM (grant reference NE/N018036/1) and NCLTS-S programme CLASS (grant reference NE/R015953/1), from the European Commission grant CRESCENDO (grant no. 641816) and from the European Union’s Horizon 2020 research and innovation programme under grant agreement 820989 (Project COMFORT—Our common future ocean in the Earth system - quantifying coupled cycles of carbon, oxygen, and nutrients for determining and achieving safe operating spaces with respect to tipping points)." }, "onlineresource_set": [] }, { "ob_id": 37672, "uuid": "194a8061c81e41c39ad4b794371fcf3c", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_02/inputdata_ch2_fig27/v20211112", "numberOfFiles": 4, "volume": 40250893, "fileFormat": "txt, netCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 33307, "uuid": "78ad6999f2d743d2a7db16757c27b549", "short_code": "ob", "title": "Chapter 2 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 2.27 (v20211112)", "abstract": "Input data for Figure 2.27 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\n\r\nFigure 2.27 presents the ocean salinity trends during historical period (1950-2019) for the near surface (global map, panel a) and zonal mean sub-surface (panel b), with regions of non-significant changes masked by 'x' marks. \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\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---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has two panels, with data provided for all panels (DurackandWijffels_GlobalOceanChanges_19500101-20191231__210122-205355_beta.nc) and processed via the MATLAB script (Figure_2_27.m) linked in the Related Documens section.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains the global ocean salinity estimates from Durack & Wijffels (2010) based on observations from 01-01-1950 to 12-31-2019:\r\n \r\n - Mean salinity (for the Jan/1950 to Dec/2019 period, units in PSS).\r\n - Salinity change (for the same period, PSS/70-years).\r\n - Salinity change error (same period, PSS/70-years).\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n The processing of the salinity estimates from Durack & Wejffels (2010), is done in the MATLAB script (Figure_2_27.m).\r\n\r\n Panel a: \r\n - Ocean surface salinity change (1950-2019) and time mean (for isohalines).\r\n\r\n Panel b:\r\n - Zonal mean ocean subsurface salinity (0-2000m) change (1950-2019) and time mean (for isohalines).\r\n\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data.\r\n ---------------------------------------------------\r\n The salinity change from the dataset has unit PSS/70-years. Units for salinity change and salinity change error have been converted to PSS/decade.\r\n\r\n Salinity change error from the dataset must be multiplied by 1.09 (to account for the resolved error when a bootstrap resampling was undertaken) x 1.64485 (i.e., z-value for 90% confidence interval) in order to get the uncertainty for the stippling.\r\n\r\n The stippling in both panels is done for regions (either surface salinity, panel a, or zonal mean salinity, panel b) where the salinity uncertainties are larger than the salinity trend.\r\n\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 IPCC AR6 website\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": 37673, "uuid": "8d66c7dd695a4865a69ee4f4f480abea", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_02/inputdata_ch2_fig25/v20220119", "numberOfFiles": 4, "volume": 14457, "fileFormat": "txt, csv", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 34657, "uuid": "528c3543bc394134916aa792c4a2e700", "short_code": "ob", "title": "Chapter 2 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 2.25 (v20220119)", "abstract": "Input data for Figure 2.25 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\n\r\nFigure 2.25 shows changes in permafrost temperature for 4 Arctic regions over the period 1974-2019 shown as average departures from the International Polar Year (2007-2009) baseline.\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\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 List of data provided\r\n ---------------------------------------------------\r\n Annual mean permafrost temperatures(deg C) for sites in 4 regions at depths indicated based on Romanovsky et al. (2020) in State of the Climate in 2019 BAMS 101(8) p S265-S269 https://doi.org/10.1175/BAMS-D-20-0086.1\r\n Regions based on those in Romanovsky et al. (2017) Ch 4 in Snow, Water, Ice and Permafrost in the Arctic (SWIPA) 2017\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\nTime series for each site that was used to determine the regional anomalies shown in the figure\r\n\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 figure on the IPCC AR6 website\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" }, "onlineresource_set": [] }, { "ob_id": 37674, "uuid": "779ee63658f04adf94b521ee6a5b4b6e", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_02/inputdata_ch2_fig13/v20211022", "numberOfFiles": 5, "volume": 81050071, "fileFormat": "txt, netCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 33257, "uuid": "02fd1d886bad40f3bb2eef3271900823", "short_code": "ob", "title": "Chapter 2 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 2.13 (v20211022)", "abstract": "Input Data for Figure 2.13 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\n\r\nFigure 2.13 shows the global trends in surface specific humidity and surface relative humidity over 1973-2019\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\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 The figure has four panels, with input data provided for panels (a) HadISDH_blendq_1_0_0_2019f.nc and (c) HadISDH_blendRH_1_0_0_2019f.nc \r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains global maps of specific and relative humidity trends over 1973-2019\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n This dataset is the input data used in the code that generates panel (a) and panel (c) for figure 2.13 \r\n\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The following changes to filenames were made to archive the data (due to filenaming restrictions). To use the data with any associated figure code, the filenames should be reverted.\r\n\r\n HadISDH_blendq_1_0_0_2019f.nc -> HadISDH.blendq.1.0.0.2019f.nc \r\n HadISDH_blendRH_1_0_0_2019f.nc -> HadISDH.blendRH.1.0.0.2019f.nc \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 figure on the IPCC AR6 website" }, "onlineresource_set": [] }, { "ob_id": 37675, "uuid": "ed5121799c5e46db87d3b2c9cc02c207", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_02/inputdata_ch2_fig15/v20211022", "numberOfFiles": 6, "volume": 267591347, "fileFormat": "txt, netCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 33260, "uuid": "8ec2d4b94f8e4756ad31858ff8256464", "short_code": "ob", "title": "Chapter 2 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 2.15 (v20211022)", "abstract": "Input data for Figure 2.15 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\n\r\nFigure 2.15 provides global precipitation trend maps and time series for a variety of data sources\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\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 The figure has six panels, with input data provided for panel (a) (cru_masked_2019_2), panels (b) and (e) (gpcc_v2020_msk2.nc), panel (d) (cru_masked_2019_2.nc), and panel (f) (gpcp2019.nc)\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains observed global precipitation data from a variety of sources covering the period 1891-2019\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n This dataset is the input data used in the code that generates panels (a), (b), (d), (e) and (f) for figure 2.15. \r\n\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 figure on the IPCC AR6 website" }, "onlineresource_set": [] }, { "ob_id": 37677, "uuid": "7710a06621924b0682ccaa49e0bc3a04", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/acruise/data/NERC_ACRUISE_MODIS_shiptracks", "numberOfFiles": 1132857, "volume": 9771844028217, "fileFormat": "Data are NetCDF (.nc) formatted with additional geopackages files (.gpkg)", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37676, "uuid": "0d88dc06fd514e8199cdd653f00a7be0", "short_code": "ob", "title": "ACRUISE: deep-learning inferred shiptrack clouds from AQUA MODIS daylight satellite data for 2002-2021", "abstract": "Large dataset of emission induced \"shiptrack\" clouds, detected using deep-learning, from satellite based remote sensing data with global coverage, from 2002 to 2021 for the Atmospheric Composition and Radiative forcing changes due to UN International Ship Emissions regulations (ACRUISE) project. Shiptracks were inferred from every daylight granule captured by the MODerate Imaging Spectroradiometer (MODIS) instrument, onboard the NOAA-AQUA satellite from 2002-2021 inclusive and stored in a compressed netcdf file. In addition, polygons corresponding to contours of level 0.5 and 0.8 from the inference images are provided as a light-weight alternative. These are stored in annual geopackages in the geographic projection.\r\n\r\nThe model is a standard neural-network based segmentation model with a UNet architecture, a resnet-152 backbone and sigmoid activation on the final layer that was pre-trained on the 2012 ImageNet Large Scale Visual Recognition Challenge 2012 (ILSVRC2012) ImageNet dataset. This model was trained to segment clouds formed by ship exhausts, known as shiptracks, from MODIS level 1b, day microphysics composite granules enhanced through histogram stretching.\r\n\r\nThe purpose of these data is to measure the effect that shipping fuel regulation has on climate change and to reduce the uncertainty in the relationship between aerosols and cloud formation and properties. This allows the determination of where tracks are more likely to form and the sensitivity of clouds to such perturbations.The data indicate a sharp reduction in tracks due to the more stringent ship emission regulations since 2020.\r\n\r\nA small minority of granules (<0.5%) are missing due to a combination of missing or corrupt files and/or unexpected computational processing failures. These remained unresolved as they were judged insignificant compared to model uncertainties and and of negligible additional benefit to warrant the overheads to resolve each missing granule." }, "onlineresource_set": [] }, { "ob_id": 37682, "uuid": "20ecdc79782148a496e66ea2827f1022", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_02/ch3_fig12/v20220630", "numberOfFiles": 0, "volume": 0, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37685, "uuid": "b57f55a171bc483bb4b579874c4c4748", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_02/inputdata_ch2_fig16/v20220630", "numberOfFiles": 11, "volume": 41536648, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37684, "uuid": "2a1284ec9d564f679480ee013b733ae1", "short_code": "ob", "title": "Chapter 2 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 2.16 (v20220630)", "abstract": "Input data for Figure 2.16 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\n\r\nFigure 2.16 provides global precipitation minus evaporation trend maps and time series from a variety of data sources\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\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 The figure has four panels, with input data provided for all panels in the main directory\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n The datasets contains:\r\n \r\n - Global precipitation and evaporation data from ERA5 reanalysis\r\n - Time series of global, land-only and ocean-only average annual P–E (mm day–1) from the following reanalysis products: 20CRv3, ERA5, ERA20CM, MERRA, CFSR, ERA20C, JRA55 and MERRA2.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panel a:\r\n - Data files: IntermediateData_era5_evap_2.nc and era5_tp_2.nc\r\n \r\n Panel b:\r\n - Data file: GPME2.csv and GPME2.mat\r\n \r\n Panel c:\r\n - Data file: LPME2.csv and LPME2.mat\r\n \r\n Panel d:\r\n - Data file: OPME2.csv and OPME2.mat\r\n \r\n For panels b to d:\r\n I. Column 2: orange solid line\r\n II. Column 3: cyan solid line\r\n III. Column 4: black solid line\r\n IV. Column 5: grey solid line\r\n V. Column 6: blue solid line\r\n VI. Column 7: dark green solid line\r\n VII. Column 8: brown solid line\r\n VIII. Column 9: green solid line\r\n\r\n 20CRv3 is the NOAA-CIRES-DOE Twentieth Century Reanalysis Version 3.\r\n ERA5 is a reanalysis of the global climate from 1950 to present, developed by ECMWF.\r\n ERA20CM is a twentieth century atmospheric model ensemble developed by ECMWF.\r\n MERRA stands for Modern-Era Retrospective analysis for Research and Applications.\r\n CFSR stands for Climate Forecast System Reanalysis.\r\n ERA20C is the first atmospheric reanalysis of the 20th century, from 1900-2010, developed by ECMWF.\r\n JRA55 stands for Japanese 55-year Reanalysis.\r\n MERRA2 stands for Modern-Era Retrospective analysis for Research and Applications, version 2.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n Additional information to correctly reproduce the figure in the corresponding readme files for code archived on Zenodo (see the link to code provided in the Related Documents section of this catalogue record).\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 figure on the IPCC AR6 website\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": 37687, "uuid": "7b1e64b029a64515b17f8300dc527234", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_02/inputdata_ch2_fig12/v20220630", "numberOfFiles": 23, "volume": 675827, "fileFormat": "txt, netCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37681, "uuid": "c9397680d08442b9a1d21e7c50df4aba", "short_code": "ob", "title": "Chapter 2 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input Data for Figure 2.12 (v20220630)", "abstract": "Input Data for Figure 2.12 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\n\r\nFigure 2.12 shows changes in temperature through the troposphere and stratosphere, both on near-global scales and in the tropics.\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\n Gulev, 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---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has five subpanels, with intermediate data provided for panels b to e.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains trends in temperature at various atmospheric heights for 1980–2019 and 2002–2019\r\n \r\n - for the near-global (70°N–70°S) domain.\r\n - for the tropical (20°N–20°S) region.\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Panels b-e: each line shows the observed trend for the specified time period/region for a given data set as a function of height.\r\n \r\n - Data files: *ROM_SAF*.nc: Radio occultation RO (ROM SAF). Violet line\r\n - Data files: *UCAR*.nc: Radio occultation RO (UCAR/NOAA). Cyan line\r\n - Data files: *Wegener*.nc: Radio occultation RO (WEGC). Blue line\r\n - Data files: *ERA5*.nc: Modern reanalysis. Cyan dotted lines.\r\n - Data files: *RICH*.nc: Radiosonde. Orange line\r\n - Data files: *RAOBCORE*.nc: Radiosonde. Yellow line\r\n - Data files: *AIRS*.nc: Infrared satellite. Green line\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\nThere are notes guiding the user to reproduce the figure in the code associated to this dataset. Link to the code that reproduces the figure in the Related Documents section of this catalogue record.\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 figure on the IPCC AR6 website\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": 37689, "uuid": "1289951dba454d3e849372b67231fba6", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_02/inputdata_ch2_fig23/v20220630", "numberOfFiles": 5, "volume": 20900, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37688, "uuid": "b618062ee96a4d36b6010271e099a5c4", "short_code": "ob", "title": "Chapter 2 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 2.23 (v20220630)", "abstract": "Input data for Figure 2.23 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\n\r\nFigure 2.23(a) shows number of a finite selection of surveyed glaciers that advanced during the past 2000 years. Figure 2.23(b) shows the annual and decadal global glacier mass change from 1961 until 2018.\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\n Gulev, 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---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has two panels, with input data provided for panel b (green lines and shadow).\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n Global mean glacier mass balance between 2000 and 2010 and between 2010 and 2020 from Hugonnet et al. (2021).\r\n All values are in Gt yr-1.\r\n All uncertainties are 90% CI.\r\n\r\n Note: two thirds of the data (the rows 2000-2010, 2010-2020) are directly available online at https://doi.org/10.6096/13 under a CC-BY-4.0 license. The last row of 2006-2019 can be derived from the data in that same DOI using provided scripts, but is not directly available in a table.\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Figure 2.23 Panel b:\r\n \r\n - green line. table_hugonnet_regions_10yr_ar6period.xlsx. Decadal (2000-2010 and 2010-2020) global mass balance (Gt yr-1) from Hugonnet et al. (2021). The mean values are computed in the matlab script from the value of each region.\r\n - green area. table_hugonnet_regions_10yr_ar6period.xlsx. Decadal (2000-2010 and 2010-2020) global mass balance (Gt yr-1) uncertainty from Hugonnet et al. (2021). The mean values are computed in the matlab script from the value of each region.\r\n\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n Input datasets are provided and matlab scripts linked in the related Documents section to reproduce the figure.\r\n\r\nInput dataset: table_hugonnet_regions_10yr_ar6period.xlsx and 2.23b_Zemp_etal_results_global.csv (a table already available as supplementary material by Zemp et al. (2019)). The rest of the files are provided in the corresponding code on GitHub (matlab script). The link to the code archive on Zenodo is provided in the Related Documents section of this catalogue record.\r\n\r\n\r\nCode please be aware that you will need: \r\n - MB_figure_FGD_chapter2_jun_28_2021.m script \r\n - shadedplot.m matlab function \r\n - colorscheme.mat created by the TSU of WGI\r\n\r\n\r\n* black line. Zemp_etal_results_global.csv. Global mass change (Gt yr-1) based on spatial interpolation from 1961 to 2016; supplementary materials from Zemp et al. (2019) it is complemented with the mass change for years 2017 and 2018 from Table 1 of Zemp et al. (2020). Decadal means are computed by the matlab script.\r\n\r\n\r\n* grey area. Zemp_etal_results_global.csv. Total uncertainty of regional mass change (Gt yr-1) from 1961 to 2016; supplementary materials from Zemp et al. (2019) it is complemented with the uncertainty of mass change for years 2017 and 2018 from Table 1 of Zemp et al. (2020). Decadal uncertainties are computed by the matlab script.\r\n\r\n\r\n* blue line. Global mean glacier mass balance (Gt yr-1) between 2002 and 2016 from Wouters et al. (2019). Values are taken from Table 1 of Wouters et al. (2019) Global total of glacier mass budget. Values are declared in the matlab script.\r\n\r\n\r\n* light blue area. Global mean glacier mass balance uncertainty (Gt yr-1) between 2002 and 2016 from Wouters et al. (2019). Values are taken from Table 1 of Wouters et al. (2019) Global total of glacier mass budget uncertainty. Values are declared in the matlab script.\r\n\r\n\r\n* desert yellow line. Global mean glacier mass balance (Gt yr-1) between 2006 and 2015 from Hock et al. (2019) Values are taken from Table 2A.1 of Chapter 2 of SROCC Global values. Values are declared in the matlab script.\r\n\r\n\r\n* desert yellow area. Global mean glacier mass balance uncertainty (Gt yr-1) between 2006 and 2015 from Hock et al. (2019) Values are taken from Table 2A.1 of Chapter 2 of SROCC Global values. Values are declared in the matlab script.\r\n\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 figure on the IPCC AR6 website\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": 37691, "uuid": "cd4a0c8625934ee7973254fe8d6475bd", "short_code": "result", "curationCategory": "A", "dataPath": "/neodc/esacci/lakes/data/lake_products/L3S/v2.0.2/", "numberOfFiles": 10325, "volume": 519722961950, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37381, "uuid": "a07deacaffb8453e93d57ee214676304", "short_code": "ob", "title": "ESA Lakes Climate Change Initiative (Lakes_cci): Lake products, Version 2.0.2", "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 2.0.2 of the dataset. \r\n\r\nThe 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 and in Carrea, L., Crétaux, JF., Liu, X. et al. Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies. Sci Data 10, 30 (2023). https://doi.org/10.1038/s41597-022-01889-z" }, "onlineresource_set": [] }, { "ob_id": 37700, "uuid": "317c19af466b47ed907d396d5722c432", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/inputdata_ch3_fig28/v20220620", "numberOfFiles": 21, "volume": 574024475, "fileFormat": "txt, netCDF, cpg, dbf, prj, shp, shx", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 33394, "uuid": "f7c3f3cbf65447b9a43207dcc30219d9", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 3.28 (v20220621)", "abstract": "Input Data for Figure 3.28 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 3.28 shows long-term trends in halosteric and thermosteric sea level in CMIP6 models and observations. \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---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The data is used in left upper and left lower panels (scatter panels), as well as right upper panels (D&W, EN4, Ishii) \r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n 210127_DurackandWijffels_V1.0_70yr_steric_1950-2019_0-2000db_210122-205355_beta.nc is input data for D&W. The variables steric_height_halo_anom_depthInterp and steric_height_thermo_anom_depthInterp are used.\r\n 210201_EN4.2.1.g10_annual_steric_1950-2019_5-5350m.nc is input data for EN4\r\n 210201_Ishii17_v7.3_annual_steric_1955-2019_0-3000m.nc is input data for Ishii\r\n\r\n\r\n---------------------------------------------------\r\n Notes on reproducing the figure from the provided data.\r\n ---------------------------------------------------\r\n This data is an input observational data for the Figure 3.28. It is used for scatter plots and contour maps.\r\n In addition, shapefiles are required to calculate the regional boundaries: Pacific.shp, Atlantic.shp. These regions should be standarised throught AR6.\r\n\r\n\r\nThe following changes to filenames were made to archive the data (due to filenaming restrictions). To use the data with any associated figure code, the filenames should be reverted.\r\n\r\n 210127_DurackandWijffels_V1_0_70yr_steric_1950-2019_0-2000db_210122-205355_beta.nc -> 210127_DurackandWijffels_V1.0_70yr_steric_1950-2019_0-2000db_210122-205355_beta.nc \r\n 210201_EN4_2_1_g10_annual_steric_1950-2019_5-5350m.nc -> 210201_EN4.2.1.g10_annual_steric_1950-2019_5-5350m.nc \r\n 210201_Ishii17_v7_3_annual_steric_1955-2019_0-3000m.nc -> 210201_Ishii17_v7.3_annual_steric_1955-2019_0-3000m.nc \r\n\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\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": 37708, "uuid": "0975d78c703b4a7f992151af8fdb94f0", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_02/ch2_fig12/v20220701", "numberOfFiles": 4, "volume": 27571, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37707, "uuid": "e9f67cfb456845b3b406328c6ae43e2d", "short_code": "ob", "title": "Chapter 2 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 2.12 (v20220701)", "abstract": "Data for Figure 2.12 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\n\r\nFigure 2.12 shows changes in temperature through the troposphere and stratosphere, both on near-global scales and in the tropics.\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\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 The figure has 5 subpanels, with data provided for panel a.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains observed temperature anomaly trends for 2002-2019 from the ROM SAF dataset, plotted as a trend/height/latitude contour plot.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Data provided in relation to Figure 2.12:\r\n \r\n - Data file: Figure_2_12a_data_file.nc: tdry_trends filled contours plot\r\n - Data file: Figure_2_12a_data_file.nc: lrt_temprature_altitude grey line\r\n\r\nROM SAF stands for Radio Occultation Meteorology Satellite Application Facilities.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n Panel (a) is plotted using standard matplotlib software. \r\nThere are notes guiding the user to reproduce the figure in the code associated to this dataset. Link to the code that reproduces the figure in the Related Documents section of this catalogue record.\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 figure on the IPCC AR6 website\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 input data figure 2.12.\r\n- Link to the code for the figure, archived on Zenodo." }, "onlineresource_set": [] }, { "ob_id": 37716, "uuid": "131fb7a52fdc4b4396e9240809635350", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/land_surface_temperature/data/MULTISENSOR_IRMGP/L3S/0.05/v1.00/monthly/", "numberOfFiles": 1153, "volume": 97564821985, "fileFormat": "Data are in NetCDF format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37611, "uuid": "98ca52a0bcf94fc98155b7e914aa22a0", "short_code": "ob", "title": "ESA Land Surface Temperature Climate Change Initiative (LST_cci): Monthly multisensor Infra-Red (IR) Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) land surface temperature (LST) level 3 supercollated (L3S) global product (2009-2020), version 1.00", "abstract": "This dataset contains monthly-averaged land surface temperatures (LSTs) and their uncertainty estimates from multiple Infra-Red (IR) instruments on satellites in Geostationary Earth Orbit (GEO) and Low Earth Orbiting (LEO) sun-synchronous (a.k.a. polar orbiting) satellites. Satellite land surface temperatures are skin temperatures, which means, for example, the temperature of the ground surface in bare soil areas, the temperature of the canopy over forests, and a mix of the soil and leaf temperature over sparse vegetation. The skin temperature is an important variable when considering surface fluxes of, for instance, heat and water.\r\n\r\nLST fields are provided at 3 hourly intervals each day (00:00 UTC, 03:00 UTC, 06:00 UTC, 09:00 UTC, 12:00 UTC, 15:00 UTC, 18:00 UTC and 21:00 UTC). Per pixel uncertainty estimates are given in two forms, first, an estimate of the total uncertainty for the pixel and second, a breakdown of the uncertainty into components by correlation length. Also provided in the files, on a per pixel basis, are the observation time, the satellite viewing and the solar geometry angles.\r\n\r\nThe product is based on merging of available GEO data and infilling with available LEO data outside of the GEO discs. Inter-instrument biases are accounted for by cross-calibration with the IASI instruments on METOP and LSTs are retrieved using a Generalised Split Window algorithm from all instruments. As data towards the edge of the GEO disc is known to have greater uncertainty, any datum with a satellite zenith angle of more than 60 degrees is discarded. All LSTs included have an observation time that lies within +/- 30 minutes of the file nominal Universal Time.\r\n\r\nData from the following instruments is included in the dataset: geostationary, Imagers on Geostationary Operational Environmental Satellite (GOES) 12 and GOES 13, Advanced Baseline Imager (ABI) on GOES 16, Spinning Enhanced Visible Infra-Red Imager (SEVIRI) on Meteosat Second Generation (MSG) 1, MSG 2, MSG 3, and MSG 4, Japanese Advanced Meteorological Imager (JAMI) on Multifunctional Transport Satellite MTSAT) 1, and MTSAT 2; and polar, Advanced Along-Track Scanning Radiometer (AATSR) on Environmental Satellite (Envisat), Moderate-resolution Imaging Spectroradiometer (MODIS) on Earth Observation System (EOS) - Aqua and EOS - Terra, Sea and Land Surface Temperature Radiometer SLSTR on Sentinel-3A and Sentinel-3B. However, it should be noted that which instruments contribute to a particular product file depends on depends on mission start and end dates and instrument downtimes.\r\n\r\nDataset coverage starts on 1st January 2009 and ends on 31st December 2020. \r\n\r\nLSTs are provided on a global equal angle grid at a resolution of 0.05° longitude and 0.05° latitude. The dataset coverage is nominally global over the land surface but varies depending on satellite and instrument availability and coverage. Furthermore, LSTs are not produced where clouds are present since under these circumstances the IR radiometer observes the cloud top which is usually much colder than the surface.\r\n\r\nThe dataset was produced by the University of Leicester (UoL) and data were processed in the UoL processing chain. The Geostationary data were produced by the Instituto Português do Mar e da Atmosfera (IPMA) before being merged into the final dataset.\r\n\r\nThe dataset was produced as part of the ESA Land Surface Temperature Climate Change Initiative which strives to improve satellite datasets to Global Climate Observing System (GCOS) standards." }, "onlineresource_set": [] }, { "ob_id": 37740, "uuid": "909ee9a27b824593ba6df638e21bb3a6", "short_code": "result", "curationCategory": "A", "dataPath": "/bodc/SOC220065/GO8p7_JRA55_eORCA25", "numberOfFiles": 18982, "volume": 2160870689459, "fileFormat": "Data are CF-Compliant NetCDF data files", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37739, "uuid": "e02c8424657846468c1ff3a5acd0b1ab", "short_code": "ob", "title": "Model output from 1/4° global JRA55-forced integration of GO8p7 global ocean-sea ice model from 1958 to 2021", "abstract": "Annual, monthly and 5-day ocean and ice output from an integration of the UK Global Ocean GO8p7 configuration, based on version 4.0.4 of the NEMO (Nucleus for European Modelling of the Ocean) ocean and sea-ice model, forced by the JRA-55 (Japanese 55-year atmospheric analysis, Tsujino et al., 2018) surface field dataset. The present integration is on the 1/4° eORCA025 global grid. The complete dataset includes: full monthly and annual mean ocean fields; monthly mean sea ice fields; monthly and annual mean global mean scalar quantities; and 5-day mean values of a subset of 2-dimensional fields, including surface fields and bottom pressure. The model is initialised from an average of years 1995-2014 of the EN4 climatology (Good et al., 2013), and is integrated from 1958 to 2021. The model was run on the Archer2 HPC platform. The integrations were funded by the Natural Environment Research Council (NERC) under the Atlantic Climate System Integrated Study (ACSIS) project (NE/N018044/1)." }, "onlineresource_set": [] }, { "ob_id": 37745, "uuid": "2dfb1e4472054d5ca9360fe5e2a2f356", "short_code": "result", "curationCategory": "A", "dataPath": "/bodc/SOC220065/GO8p7_JRA55_eORCA12", "numberOfFiles": 18993, "volume": 18019485068801, "fileFormat": "Data are CF-Compliant NetCDF data files", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37744, "uuid": "399b0f762a004657a411a9ea7203493a", "short_code": "ob", "title": "Model output from 1/12° global JRA55-forced integration of GO8p7 global ocean-sea ice model from 1958 to 2021", "abstract": "Annual, monthly and 5-day ocean and ice output from an integration of the UK Global Ocean GO8p7 configuration, based on version 4.0.4 of the NEMO (Nucleus for European Modelling of the Ocean) ocean and sea-ice model, forced by the JRA-55 (Japanese 55-year atmospheric analysis, Tsujino et al., 2018) surface field dataset. The complete dataset includes: full monthly and annual mean ocean fields; monthly mean sea ice fields; monthly and annual mean global mean scalar quantities; and 5-day mean values of a subset of 2-dimensional fields, including surface fields and bottom pressure. The present integration is on the 1/12° eORCA12 global grid. The model is initialised from an average of years 1995-2014 of the EN4 climatology (Good et al., 2013), and is integrated from 1958 to 2021. The model was run on the Archer2 HPC platform. The integrations were funded by the Natural Environment Research Council (NERC) under the Atlantic Climate System Integrated Study (ACSIS) project (NE/N018044/1)." }, "onlineresource_set": [] }, { "ob_id": 37753, "uuid": "aa241574a64f4597b8a5a84ed3491b54", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/moya/data/aircraft/Boliva_BAS-Flights_and_Model", "numberOfFiles": 9, "volume": 372672338, "fileFormat": "Data are BADC-CSV and NetCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37752, "uuid": "26b934d2731944dd945bc05406e40bee", "short_code": "ob", "title": "MOYA: In flight Methane samples, Llanos de Moxos, Bolivia 2019 with supporting GEOS-Chem and NAME model output", "abstract": "This dataset contains isotopic sampling of methane taken on board the British Antarctic Survey (BAS) twin-otter aircraft during a flight campaign over the Llanos de Moxos wetland near Trinidad, Bolivia in 2019 and supporting model simulations for the Methane Observations and Yearly Assessments (MOYA) project. Air samples were collected in tedlar bags during flights over the region and subsequently analysed at the Greenhouse Gas Laboratory, Royal Holloway University (RHUL). These are supported with data from a nested GEOS-Chem model simulation at 0.25° x 0.3125° which was used to map the relationship between emissions and aircraft measurements in a regional domain bounded by 24 - 0 °S and 75 – 55 °W. In addition, a footprint of the air source was simulated for each minute of aircraft sampling to capture using the Met Office NAME model at of 0.14° × 0.09° and temporal resolution of 3 hourly." }, "onlineresource_set": [] }, { "ob_id": 37759, "uuid": "be63c6c1b716403bbc1f93a183527075", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_08/ch8_box8_2_fig1/v20220718", "numberOfFiles": 10, "volume": 2046842, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37758, "uuid": "8d769bddaddc4e10bdd6f5428a3a0af5", "short_code": "ob", "title": "Chapter 8 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Box 8.2, Figure 1 (v20220718)", "abstract": "Data for Box 8.2, figure 1 from Chapter 8 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\n\r\nBox 8.2, figure 1 shows projected long-term changes in precipitation seasonality. \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\n Douville, H., K. Raghavan, J. Renwick, R.P. Allan, P.A. Arias, M. Barlow, R. Cerezo-Mota, A. Cherchi, T.Y. Gan, J. Gergis, D. Jiang, A. Khan, W. Pokam Mba, D. Rosenfeld, J. Tierney, and O. Zolina, 2021: Water Cycle Changes. 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. 1055–1210, doi:10.1017/9781009157896.010.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has multiple panels. Data is provided in panel-specific sub-directories.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n - Global simulated 1995–2014 precipitation climatology\r\n - Global maps of projected changes in precipitation seasonality averaged across 31 to 33 CMIP6 models in the SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios\r\n \r\n All changes are estimated in 2081–2100 relative to 1995–2014.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n There are two NetCDF files per panel, except for panel a which has only the first one :\r\n - one for the main field, which is represented with colors and has 'rchange' or 'rmeans' or 'mean' in the filename\r\n - the other for the confidence information, based on fraction of models which agree about signal change sign, which is represented in figures by diagonal lines as specified by the so called AR6 simple hatching scheme; it has 'agreemeent' or 'slashes' in the filename\r\n \r\n Each datafile has NetCDF attributes which clearly describe the data.\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nSSP stands for Shared Socioeconomic Pathway.\r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\nSSP245 is the Shared Socioeconomic Pathway which represents the median of radiative forcing and development scenarios, consistent with RCP4.5.\r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 8)\r\n - Link to the Supplementary Material for Chapter 8, which contains details on the input data used in Table 8.SM.1\r\n - Link to the code for all figures in Chapter 8, archived on Zenodo.\r\n - Link to the documentation for CAMMAC, the tool used for AR6 analysis." }, "onlineresource_set": [] }, { "ob_id": 37762, "uuid": "9263d28778d74a64a21015773b8c6cce", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_08/ch8_fig14/v20220718", "numberOfFiles": 11, "volume": 2328856, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37761, "uuid": "bbf5ae3b78c44bf28ccb17b487d58a94", "short_code": "ob", "title": "Chapter 8 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 8.14 (v20220718)", "abstract": "Data for Figure 8.14 from Chapter 8 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 8.14 shows projected long-term relative changes in seasonal mean precipitation. \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\n Douville, H., K. Raghavan, J. Renwick, R.P. Allan, P.A. Arias, M. Barlow, R. Cerezo-Mota, A. Cherchi, T.Y. Gan, J. Gergis, D. Jiang, A. Khan, W. Pokam Mba, D. Rosenfeld, J. Tierney, and O. Zolina, 2021: Water Cycle Changes. 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. 1055–1210, doi:10.1017/9781009157896.010.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has multiple panels. Data is provided in panel-specific sub-directories.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n \r\n - Global maps of projected relative changes (%) in seasonal mean of precipitation averaged across 29 CMIP6 models in the SSP2-4.5 scenario (2081–2100 relative to the 1995–2014).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n There are two NetCDF files per panel: one for the main field (*pr_means*.nc), which is represented with colors, the other for the confidence information (*pr_agreement-fraction-on-sign*.nc), based on agreement fraction of models about signal change sign, which is represented by diagonal lines as specified by the so called AR6 simple hatching scheme.\r\n \r\n Each datafile has NetCDF attributes which clearly describe the data.\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\n SSP245 is the Shared Socioeconomic Pathway which represents the median of radiative forcing and development scenarios, consistent with RCP4.5.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 8)\r\n - Link to the Supplementary Material for Chapter 8, which contains details on the input data used in Table 8.SM.1\r\n - Link to the code for all figures in Chapter 8, archived on Zenodo.\r\n - Link to the documentation for CAMMAC, the tool used for AR6 analysis." }, "onlineresource_set": [] }, { "ob_id": 37765, "uuid": "7a2eafa8c9414c13928b10dbf7212afb", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_08/ch8_fig15/v20220718", "numberOfFiles": 15, "volume": 3455876, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37764, "uuid": "2d67a9f7631247d7bb6130ddc033ba7a", "short_code": "ob", "title": "Chapter 8 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 8.15 (v20220718)", "abstract": "Data for Figure 8.15 from Chapter 8 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 8.15 shows projected long-term relative changes in daily precipitation statistics.\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\n Douville, H., K. Raghavan, J. Renwick, R.P. Allan, P.A. Arias, M. Barlow, R. Cerezo-Mota, A. Cherchi, T.Y. Gan, J. Gergis, D. Jiang, A. Khan, W. Pokam Mba, D. Rosenfeld, J. Tierney, and O. Zolina, 2021: Water Cycle Changes. 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. 1055–1210, doi:10.1017/9781009157896.010.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has multiple panels. Data is provided in panel-specific sub-directories.\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains global data of projected seasonal mean relative changes (%) averaged across CMIP6 models in the SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios, in:\r\n \r\n - Number of dry days (e.g. days with less than 1 mm of rain)\r\n - Daily precipitation intensity (in mm/ day–1, estimated as the mean daily precipitation amount on wet days – e.g. days with intensity above 1 mm/ day–1)\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n There are two NetCDF files per panel :\r\n - One for the main field, which is represented with colors and has 'rchange' or 'rmeans' in the filename\r\n - The other for the confidence information, based on fraction of models which agree about signal change sign, which is represented in figures by diagonal lines as specified by the so called AR6 simple hatching scheme; it has 'agreement' or 'slashes' in the filename\r\n Each datafile has NetCDF attributes which clearly describe the data.\r\n\r\n CMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\n SSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\n SSP245 is the Shared Socioeconomic Pathway which represents the median of radiative forcing and development scenarios, consistent with RCP4.5.\r\n SSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\r\n\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 8)\r\n - Link to the Supplementary Material for Chapter 8, which contains details on the input data used in Table 8.SM.1\r\n - Link to the code for all figures in Chapter 8, archived on Zenodo.\r\n - Link to the documentation for CAMMAC, the tool used for AR6 analysis." }, "onlineresource_set": [] }, { "ob_id": 37768, "uuid": "7111762781a544bfa56911dcbe5cafcb", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_08/inputdata_ch8_fig16/v20220718", "numberOfFiles": 4, "volume": 360894, "fileFormat": "Data are json formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37767, "uuid": "92dc7ae089d84a43a28099ae49633383", "short_code": "ob", "title": "Chapter 8 of the Working Group I Contribution to the IPCC Sixth Assessment Report - Input data for Figure 8.16 (v20220718)", "abstract": "Input Data for Figure 8.16 from Chapter 8 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 8.16 shows rate of change in mean and variability across increasing global warming levels. \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\n Douville, H., K. Raghavan, J. Renwick, R.P. Allan, P.A. Arias, M. Barlow, R. Cerezo-Mota, A. Cherchi, T.Y. Gan, J. Gergis, D. Jiang, A. Khan, W. Pokam Mba, D. Rosenfeld, J. Tierney, and O. Zolina, 2021: Water Cycle Changes. 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. 1055–1210, doi:10.1017/9781009157896.010.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has multiple panels. Input data is provided in one single file. \r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n A single json file provides in a structured way the data for each graph point. Details are provided under 'notes on reproducing the figure'.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n Datafile : 'Fig8-16_data.json'\r\n\r\n The relation between provided data and figure elements is essentially described in field 'List of data' above, 'Notes on reproducing the figure' below, and in caption.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The figure can be reproduced using the software linked in the Related Documents section of this catalogue record\r\n \r\n For additional details about data description, please refer to 'Fig8-16_input_data.README.txt'\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 8)\r\n - Link to the Supplementary Material for Chapter 8, which contains details on the input data used in Table 8.SM.1\r\n - Link to the code for all figures in Chapter 8, archived on Zenodo.\r\n - Link to the the script for generating figure on GitHub\r\n - Link to the documentation for CAMMAC, the tool used for AR6 analysis." }, "onlineresource_set": [] }, { "ob_id": 37771, "uuid": "ec0509cafff944cc891edc748efd3b79", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_08/ch8_fig17/v20220718", "numberOfFiles": 15, "volume": 3494963, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37770, "uuid": "7da00222bbb345c99ce14e358cde9f6d", "short_code": "ob", "title": "Chapter 8 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 8.17 (v20220718)", "abstract": "Data for Figure 8.17 from Chapter 8 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 8.17 shows projected long-term relative changes in seasonal mean evapotranspiration.\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\n Douville, H., K. Raghavan, J. Renwick, R.P. Allan, P.A. Arias, M. Barlow, R. Cerezo-Mota, A. Cherchi, T.Y. Gan, J. Gergis, D. Jiang, A. Khan, W. Pokam Mba, D. Rosenfeld, J. Tierney, and O. Zolina, 2021: Water Cycle Changes. 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. 1055–1210, doi:10.1017/9781009157896.010.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has multiple panels. Data is provided in panel-specific sub-directories.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains global data of projected relative changes (%) in seasonal mean of surface evapotranspiration for\r\n - December–January–February (DJF; left panels)\r\n - June–July–August (JJA; right panels)\r\n \r\n The data are averaged across 29 or 30 CMIP6 models for SSP1.2-6, SSP2-4.5, and SSP5-8.5 scenarios. All changes are estimated in 2081–2100 relative to 1995–2014.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n There are two NetCDF files per panel :\r\n - one for the main field, which is represented with colors and has 'rchange' or 'rmeans' in the filename\r\n - the other for the confidence information, based on fraction of models which agree about signal change sign, which is represented in figures by diagonal lines as specified by the so called AR6 simple hatching scheme; it has 'agreemeent' or 'slashes' in the filename\r\n Each datafile has NetCDF attributes which clearly describe the data.\r\n\r\n CMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\n SSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\n SSP245 is the Shared Socioeconomic Pathway which represents the median of radiative forcing and development scenarios, consistent with RCP4.5.\r\n SSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 8)\r\n - Link to the Supplementary Material for Chapter 8, which contains details on the input data used in Table 8.SM.1\r\n - Link to the code for all figures in Chapter 8, archived on Zenodo.\r\n - Link to the documentation for CAMMAC, the tool used for AR6 analysis." }, "onlineresource_set": [] }, { "ob_id": 37774, "uuid": "45291f72ae7542ee8469b86681079791", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_08/ch8_fig13/v20220718", "numberOfFiles": 12, "volume": 409873, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37773, "uuid": "6ed1539e8fe84caea089a0d6a7ffcdbd", "short_code": "ob", "title": "Chapter 8 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 8.13 (v20220718)", "abstract": "Data for Figure 8.13 from Chapter 8 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 8.13 shows zonal and annual mean projected long-term changes in the atmospheric water budget.\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 Douville, H., K. Raghavan, J. Renwick, R.P. Allan, P.A. Arias, M. Barlow, R. Cerezo-Mota, A. Cherchi, T.Y. Gan, J. Gergis, D. Jiang, A. Khan, W. Pokam Mba, D. Rosenfeld, J. Tierney, and O. Zolina, 2021: Water Cycle Changes. 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. 1055–1210, doi:10.1017/9781009157896.010.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n There are 9 sub-panels, with data provided for all panels in one single directory.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains zonal and annual-mean projected long-term changes in the atmospheric water budget in:\r\n \r\n - Modelled global precipitation (CMIP6 simulations, ssp126, ssp245 and ssp585 scenarios, 1650 -2100)\r\n - Modelled global evaporation (CMIP6 simulations, ssp126, ssp245 and ssp585 scenarios, 1650 -2100)\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n There is one NetCDF file per sub-panel, named by the scenario and variable of the sub-panels: 3 variables (precipitation : 'pr', evaporation : 'evspsbl' and their difference : 'P-E') times 3 scenarios (ssp126, ssp245 and ssp585).\r\n\r\n Each sub-panel NetCDF file has 6 variables. The variable names have suffix:\r\n - mean for multi-model change mean (thick coloured line)\r\n - land_mean for multi-model change mean over land (thick black line),\r\n - pctl5 and pctl95 for multi-model 5 and 95 percentiles (coloured shaded area),\r\n - variab5 and variab95 for 5 and 95 percentiles of the internal variability (grey shaded area).\r\n\r\n As an example Fig8-13_pr_ssp126.nc (precipitation, scenario SSP1-2.6), relates to the upper panel (left).\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\n SSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\n SSP245 is the Shared Socioeconomic Pathway which represents the median of radiative forcing and development scenarios, consistent with RCP4.5.\r\n SSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 8)\r\n - Link to the Supplementary Material for Chapter 8, which contains details on the input data used in Table 8.SM.1\r\n - Link to the code for all figures in Chapter 8, archived on Zenodo.\r\n - Link to the documentation for CAMMAC, the tool used for AR6 analysis." }, "onlineresource_set": [] }, { "ob_id": 37777, "uuid": "114e281266064c59b52b7fd80e34d273", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_08/ch8_fig18/v20220718", "numberOfFiles": 15, "volume": 3487819, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37776, "uuid": "caf598e54c674d219f2e245df32dbc1a", "short_code": "ob", "title": "Chapter 8 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 8.18 (v20220718)", "abstract": "Data for Figure 8.18 from Chapter 8 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 8.18 shows projected long-term relative changes in seasonal mean runoff.\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 Douville, H., K. Raghavan, J. Renwick, R.P. Allan, P.A. Arias, M. Barlow, R. Cerezo-Mota, A. Cherchi, T.Y. Gan, J. Gergis, D. Jiang, A. Khan, W. Pokam Mba, D. Rosenfeld, J. Tierney, and O. Zolina, 2021: Water Cycle Changes. 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. 1055–1210, doi:10.1017/9781009157896.010.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has multiple panels. Data is provided in panel-specific sub-directories.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains global maps of projected relative change (%) in runoff seasonal mean for:\r\n \r\n - December–January–February (DJF; left panels)\r\n - June–July–August (JJA; right panels)\r\n\r\n The data are averaged across CMIP6 models for the SSP1.2-6, SSP2-4.5 and SSP5-8.5 scenarios. All changes are estimated in 2081–2100 relative to 1995–2014.\r\n\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n There are two NetCDF files per panel :\r\n - one for the main field, which is represented with colors and has 'rchange' or 'rmeans' in the filename\r\n - the other for the confidence information, based on fraction of models which agree about signal change sign, which is represented in figures by diagonal lines as specified by the so called AR6 simple hatching scheme; it has 'agreemeent' or 'slashes' in the filename\r\n\r\n Each datafile has NetCDF attributes which clearly describe the data.\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\n SSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\n SSP245 is the Shared Socioeconomic Pathway which represents the median of radiative forcing and development scenarios, consistent with RCP4.5.\r\n SSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 8)\r\n - Link to the Supplementary Material for Chapter 8, which contains details on the input data used in Table 8.SM.1\r\n - Link to the code for all figures in Chapter 8, archived on Zenodo.\r\n - Link to the documentation for CAMMAC, the tool used for AR6 analysis." }, "onlineresource_set": [] }, { "ob_id": 37780, "uuid": "ad11d0a8bd504cdf8e10e65b8252c6a3", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_08/ch8_fig21/v20220718", "numberOfFiles": 7, "volume": 1092598, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37779, "uuid": "b03a4577108545c2a05bbae2d9759f9d", "short_code": "ob", "title": "Chapter 8 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 8.21 (v20220718)", "abstract": "Data for Figure 8.21 from Chapter 8 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 8.21 is a schematic depicting understanding of large-scale circulation changes and effects of the regional water cycle.\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 Douville, H., K. Raghavan, J. Renwick, R.P. Allan, P.A. Arias, M. Barlow, R. Cerezo-Mota, A. Cherchi, T.Y. Gan, J. Gergis, D. Jiang, A. Khan, W. Pokam Mba, D. Rosenfeld, J. Tierney, and O. Zolina, 2021: Water Cycle Changes. 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. 1055–1210, doi:10.1017/9781009157896.010.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The three maps subpanels in the middle of the figure have data provided in panel-specific sub-directories.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains:\r\n \r\n - Precipitation minus evaporation (P–E) changes at 3°C of global warming relative to an 1850–1900 base period (mean of 23 CMIP6 SSP5-8.5 simulations) for:\r\n . Annual mean changes\r\n . Seasonal mean changes (DJF, JJA)\r\n \r\n - Precipitation minus evaporation (P–E) climatology (annual mean, 1850-1900).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n The map for the annual case (subdir ANN) has two data files :\r\n 1. One for the colored , P-E change, field :\r\n - Fig8-21_ANN_P-E_mean-change_ssp585_ANN_1850-1900_plus3K.nc\r\n \r\n 2. One for the P-E climatology (for red isoline 0) :\r\n - Fig8-21_ANN_P-E_mean_piControl_ANN_1850-1900_.nc. The solid and dashed contours are isolines 0 of that data, masked out over continents. The decision between solid and dashed line is a manual one, based on the latitude of the line. \r\n\r\nThe seasonal panels (subdirs DJF and JJA) have a single file for the colored, P-E change, field.\r\npanel_DJF: Fig8-21_DJF_P-E_mean-change_ssp585_DJF_1850-1900_plus3K.nc\r\npanel_JJA: Fig8-21_JJA_P-E_mean-change_ssp585_JJA_1850-1900_plus3K.nc\r\n\r\nCLARIFICATION: The following file names have been changed from the original, for the purposes of conforming to the file naming standards for the CEDA catalogue. \r\n- panel_ANN: Fig8-21_ANN_P-E_mean-change_ssp585_ANN_1850-1900_+3K.nc -> Fig8-21_ANN_P-E_mean-change_ssp585_ANN_1850-1900_plus3K.nc\r\n- panel_DJF: Fig8-21_DJF_P-E_mean-change_ssp585_DJF_1850-1900_+3K.nc -> Fig8-21_DJF_P-E_mean-change_ssp585_DJF_1850-1900_plus3K.nc\r\n- panel_JJA: Fig8-21_JJA_P-E_mean-change_ssp585_JJA_1850-1900_+3K.nc -> Fig8-21_JJA_P-E_mean-change_ssp585_JJA_1850-1900_plus3K.nc\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 8)\r\n - Link to the Supplementary Material for Chapter 8, which contains details on the input data used in Table 8.SM.1\r\n - Link to the code for all figures in Chapter 8, archived on Zenodo.\r\n - Link to the documentation for CAMMAC, the tool used for AR6 analysis." }, "onlineresource_set": [] }, { "ob_id": 37783, "uuid": "00daa9623f8d40d1bbe04c09d2635002", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_08/ch8_fig25/v20220718", "numberOfFiles": 15, "volume": 3477999, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37782, "uuid": "47961b1927b8492990ed92f10a514b6b", "short_code": "ob", "title": "Chapter 8 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 8.25 (v20220718)", "abstract": "Data for Figure 8.25 from Chapter 8 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 8.25 shows the effect of first versus second 2°C of global warming relative to 1850-1900 on seasonal mean precipitation.\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 Douville, H., K. Raghavan, J. Renwick, R.P. Allan, P.A. Arias, M. Barlow, R. Cerezo-Mota, A. Cherchi, T.Y. Gan, J. Gergis, D. Jiang, A. Khan, W. Pokam Mba, D. Rosenfeld, J. Tierney, and O. Zolina, 2021: Water Cycle Changes. 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. 1055–1210, doi:10.1017/9781009157896.010.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has multiple panels. Data is provided in panel-specific sub-directories.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains CMIP6 multi-model ensemble mean December–January–February (left panels) and June–July–August (right panels) precipitation difference for:\r\n \r\n - SSP5-8.5 scenario at +2°C\r\n - SSP5-8.5 scenario at +4°C minus SSP5-8.5 at +2°C (second 2°C warming)\r\n - Second minus first 2°C fast warming.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n There are two NetCDF files per panel :\r\n - one for the main field, which is represented with colors and has 'rchange' or 'rmeans' in the filename\r\n - the other for the confidence information, based on fraction of models which agree about signal change sign, which is represented in figures by diagonal lines as specified by the so called AR6 simple hatching scheme; it has 'agreement' or 'slashes' in the filename\r\n \r\n Each datafile has NetCDF attributes which clearly describe the data.\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 8)\r\n - Link to the Supplementary Material for Chapter 8, which contains details on the input data used in Table 8.SM.1\r\n - Link to the code for all figures in Chapter 8, archived on Zenodo.\r\n - Link to the documentation for CAMMAC, the tool used for AR6 analysis." }, "onlineresource_set": [] }, { "ob_id": 37786, "uuid": "02bdd4d84f424e479285afc2ae31ce52", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_08/ch8_fig26/v20220718", "numberOfFiles": 4, "volume": 29728, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37785, "uuid": "ef3dd7efa4f442b2812c4ee905f794c2", "short_code": "ob", "title": "Chapter 8 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 8.26 (v20220718)", "abstract": "Data for Figure 8.26 from Chapter 8 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6).\r\n\r\nFigure 8.26 shows the rate of change in basin-scale annual mean runoff with increasing global warming levels.\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 Douville, H., K. Raghavan, J. Renwick, R.P. Allan, P.A. Arias, M. Barlow, R. Cerezo-Mota, A. Cherchi, T.Y. Gan, J. Gergis, D. Jiang, A. Khan, W. Pokam Mba, D. Rosenfeld, J. Tierney, and O. Zolina, 2021: Water Cycle Changes. 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. 1055–1210, doi:10.1017/9781009157896.010.\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n There is one single NetCDF file for data for all panels.\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains relative changes (%) in basin-averaged annual mean runoff estimated as multi-model ensemble median from a variable subset of CMIP6 models for each SSP over nine major river basins:\r\n \r\n - Mississippi (a),\r\n - Danube (b),\r\n - Lena (c),\r\n - Amazon (d),\r\n - Euphrates (e),\r\n - Yangtze (f),\r\n - Niger (f),\r\n - Indus (g),\r\n - Murray (h).\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n The NetCDF file contains a multi-dimensionnal variable 'mrro_mean' which matches the various curves showing in the figure. These are parametric curves, and the parameter is a period index. The file also contains a variable 'tas' for the value of global warming for the period, for each scenario.\r\n \r\n Dimension 'period' is a period index, which is the parameter for the parametric curves linking variables 'mrro_mean' and 'tas'. Period value 1 stands for 1901-1920, 2 for 1911-1920 ...,\r\n \r\n Dimension ssp is the SSP index, for that order : ssp585 , ssp245 , ssp126.\r\n \r\n Variable 'tas' is the change of globally averaged surface temperature w.r.t. 1850-1900 average, indexed by period.\r\n \r\n Variable mrro_mean provide statistics of relative changes (%) of runoff in basin-averaged annual mean runoff. The basin averages have been estimated after a first-order conservative remapping of the model outputs on the 0.5° by 0.5° river network of (Decharme et al., 2019). It is indexed by :\r\n - dimension 'stats' for statistics over a CMIP6 multi-model ensemble, in that order : percentile 5, mean, and percentile 95,\r\n - dimension 'basin' for this ordered list : Mississippi, Danube, Lena, Amazon, Euphrates, Yangtze, Niger, Indus, Murray\r\n \r\n Variable mrro_std is not used in the figure.\r\n\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\n SSP stands for Shared Socioeconomic Pathway.\r\n SSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\n SSP245 is the Shared Socioeconomic Pathway which represents the median of radiative forcing and development scenarios, consistent with RCP4.5.\r\n SSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n Curves are parametric curves. The parameter is the period index.\r\n\r\n So each curve for a given statistics 'stat', scenario 'ssp' and basin 'basin' is defined by varying period_index in:\r\n \r\n x=tas(ssp,period_index),\r\n \r\n y=mrro_mean(ssp, basin, stat, period_index)\r\n\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 8)\r\n - Link to the Supplementary Material for Chapter 8, which contains details on the input data used in Table 8.SM.1\r\n - Link to the code for all figures in Chapter 8, archived on Zenodo.\r\n - Link to the documentation for CAMMAC, the tool used for AR6 analysis." }, "onlineresource_set": [] }, { "ob_id": 37788, "uuid": "7e9b3b5f364e49d58b0a1f85beb8aecf", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/austria/kufstein/zamg-vaisala-cl51_A", "numberOfFiles": 401, "volume": 1000783409, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37789, "uuid": "a1247fe8044946d29b205d655f61c9dd", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from ZAMG's Vaisala CL51 instrument deployed at Kufstein, Austria", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from Zentralanstalt für Meteorologie und Geodynamik (ZAMG)'s Vaisala CL51 deployed at Kufstein, Austria.\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: 0-20000-0-11130.\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": 37792, "uuid": "b8d0c160a5db4ed58966c35064ff186e", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/hungary/szentes/omsz-lufft-chm15k_A", "numberOfFiles": 0, "volume": 0, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37802, "uuid": "731c1a062e5f4bb08bb9220765577268", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/eprofile/data/daily_files/uk/chilbolton-atmospheric-observatory/ncas-vaisala-cl51_A", "numberOfFiles": 1280, "volume": 3397591076, "fileFormat": "Data are netCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37803, "uuid": "818f746a3ea54210a232145d95e9c819", "short_code": "ob", "title": "EUMETNET E-PROFILE: ceilometer cloud base height and aerosol profile data from NCAS's vaisala-cl51 instrument deployed at the Chilbolton Atmospheric Observatory, UK", "abstract": "Daily concatenated files of ceilometer cloud base height and aerosol profile data from National Centre for Atmospheric Science (NCAS)'s vaisala-cl51 deployed at Chilbolton Alc, UK.\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: 0-826-300-3.\r\nSee 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": 37833, "uuid": "d321f16d219546bcb560305b4b109cc9", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/deposited2022/WACCM-X_2015-2070", "numberOfFiles": 2691, "volume": 436008541109, "fileFormat": "Data are NetCDF formatted.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37832, "uuid": "45283390b97c4a27861d74b3d915b0bd", "short_code": "ob", "title": "Monthly mean climate data from a transient simulation with the Whole Atmosphere Community Climate Model eXtension (WACCM-X) from 2015 to 2070", "abstract": "This dataset comprises monthly mean data from a global, transient simulation with the Whole Atmosphere Community Climate Model eXtension (WACCM-X) from 2015 to 2070. WACCM-X is a global atmosphere model covering altitudes from the surface up to ~500 km, i.e., including the troposphere, stratosphere, mesosphere and thermosphere. WACCM-X version 2.0 (Liu et al., 2018) was used, part of the Community Earth System Model (CESM) release 2.1.0 (http://www.cesm.ucar.edu/models/cesm2) made available by the National Center for Atmospheric Research. The model was run in free-running mode with a horizontal resolution of 1.9 degrees latitude and 2.5 degrees longitude (giving 96 latitude points and 144 longitude points) and 126 vertical levels. Further description of the model and simulation setup is provided by Cnossen (2022) and references therein. A large number of variables is included on standard monthly mean output files on the model grid, while selected variables are also offered interpolated to a constant height grid or vertically integrated in height (details below). Zonal mean and global mean output files are included as well.\r\n\r\nThe data are provided in NetCDF format and file names have the following structure: \r\n\r\nf.e210.FXHIST.f19_f19.h1a.cam.h0.[YYYY]-[MM][DFT].nc\r\n\r\nwhere [YYYY] gives the year with 4 digits, [MM] gives the month (2 digits) and [DFT] specifies the data file type. The following data file types are included:\r\n\r\n1)\tMonthly mean output on the full grid for the full set of variables; [DFT] = \r\n2)\tZonal mean monthly mean output for the full set of variables; [DFT] = _zm\t\r\n3)\tGlobal mean monthly mean output for the full set of variables; [DFT] = _gm\r\n4)\tHeight-interpolated/-integrated output on the full grid for selected variables; [DFT] = _ht\r\n\r\nA cos(latitude) weighting was used when calculating the global means.\r\n\r\nData were interpolated to a set of constant heights (61 levels in total) using the Z3GM variable (for variables output on midpoints, with 'lev' as the vertical coordinate) or the Z3GMI variable (for variables output on interfaces, with ilev as the vertical coordinate) stored on the original output files (type 1 above). Interpolation was done separately for each longitude, latitude and time. \r\n\r\nMass density (DEN [g/cm3]) was calculated from the M_dens, N2_vmr, O2, and O variables on the original data files before interpolation to constant height levels. \r\n\r\nThe Joule heating power QJ [W/m3] was calculated using \r\nQ_J = (sigma_P*B^2)*((u_i - U_n)^2 + (v_i-v_n)^2 + (w_i-w_n)^2) \r\nwith sigma_P = Pedersen conductivity[S], B = geomagnetic field strength [T], ui, vi, and wi = zonal, meridional, and vertical ion velocities [m/s] and un, vn, and wn = neutral wind velocities [m/s]. QJ was integrated vertically in height (using a 2.5 km height grid spacing rather than the 61 levels on output file type 4) to give the JHH variable on the type 4 data files. The QJOULE variable also given is the Joule heating rate [K/s] at each of the 61 height levels.\r\n\r\nAll data are provided as monthly mean files with one time record per file, giving 672 files for each data file type for the period 2015-2070 (56 years).\r\n\r\nReferences:\r\n\r\nCnossen, I. (2022), A realistic projection of climate change in the upper atmosphere into the 21st century, in preparation.\r\n\r\nLiu, H.-L., C.G. Bardeen, B.T. Foster, et al. (2018), Development and validation of the Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X 2.0), Journal of Advances in Modeling Earth Systems, 10(2), 381-402, doi:10.1002/2017ms001232." }, "onlineresource_set": [] }, { "ob_id": 37839, "uuid": "9ecee1b3835f42f28811f8c7125ca658", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/sentinel5p/data/L2_HCHO/", "numberOfFiles": 68691, "volume": 24321694294927, "fileFormat": "These data are in NetCDF format.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37838, "uuid": "300559d22d9549049017f06bf38db929", "short_code": "ob", "title": "Sentinel 5P: Formaldehyde (HCHO) Total Column level 2 data", "abstract": "This dataset contains total column Formaldehyde (HCHO) data from the TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel 5P satellite.\r\n\r\nSentinel 5 Precursor (S5P) was launched on the 13th of October 2017 carrying the TROPOspheric Monitoring Instrument (TROPOMI). The TROPOMI is a nadir-viewing, imaging spectrometer covering wavelength bands between the ultraviolet and the shortwave infrared. The instrument uses passive remote sensing techniques to attain its objective by measuring, at the Top Of Atmosphere (TOA), the solar radiation reflected by and radiated from the earth. In addition to the main product results, such as HCHO slant column, vertical column, and air mass factor, the level 2 (geolocated total columns) data files contain several additional parameters and diagnostic information.\r\n\r\nFormaldehyde is an intermediate gas in almost all oxidation chains of Non-Methane Volatile Organic Compounds (NMVOC), leading eventually to CO2. NMVOCs are, together with NOx, CO, and CH4, among the most important precursors of tropospheric O3. The major HCHO source in the remote atmosphere is CH4 oxidation. Over the continents, the oxidation of higher NMVOCs emitted from vegetation, fires, traffic and industrial sources results in important and localised enhancements of the HCHO levels." }, "onlineresource_set": [] }, { "ob_id": 37841, "uuid": "99d77a9ddac74a29b0ba2cd9b359c0bb", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/sentinel5p/data/L2_CLOUD/", "numberOfFiles": 77720, "volume": 17207119367685, "fileFormat": "These data are netCDF format.", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37840, "uuid": "ba5618b8ad6540c4b16df4877350464c", "short_code": "ob", "title": "Sentinel 5P: Cloud (CLOUD) level 2 data", "abstract": "This dataset contains data that can be used for cloud correction of satellite trace gas retrievals these include: cloud fraction, cloud optical thickness (albedo), and cloud-top pressure (height).\r\n\r\nSentinel 5 Precursor (S5P) was launched on the 13th of October 2017 carrying the TROPOspheric Monitoring Instrument (TROPOMI). Cloud parameters from TROPOMI are not only used for enhancing the accuracy of trace gas retrievals but also to extend the satellite data record of cloud information derived from oxygen A-band measurements initiated with the Global Ozone Monitoring Experiment (GOME).\r\n\r\nThe TROPOMI/S5P cloud properties retrieval is based on the Optical Cloud Recognition Algorithm (OCRA) and Retrieval of Cloud Information using Neural Networks (ROCINN) algorithms currently being used in the operational GOME and GOME-2 products. OCRA retrieves the cloud fraction using measurements in the UV/VIS spectral regions and ROCINN retrieves the cloud height (pressure) and optical thickness (albedo) using measurements in and around the oxygen A-band at 760 nm. For TROPOMI/S5P we use OCRA/ROCINN Version 3.0, which is based on a more realistic treatment of clouds as optically uniform layers of light-scattering particles. Additionally, the cloud parameters are also provided for a cloud model which assumes the cloud to be a Lambertian reflecting boundary." }, "onlineresource_set": [] }, { "ob_id": 37843, "uuid": "caa9f8a7773243449f8b1193a60af931", "short_code": "result", "curationCategory": "", "dataPath": "/neodc/esacci/ghg/data/cci_plus/CO2_TAN_OCFP/v1.2/", "numberOfFiles": 417, "volume": 3171872255, "fileFormat": "Data is in NetCDF", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37842, "uuid": "b0beb88af3b748b98afc4b35f77bebf8", "short_code": "ob", "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged carbon dioxide from TANSAT, generated with the OCFP algorithm, for global land areas, version 1.2", "abstract": "This dataset contains column-average dry-air mole fractions of atmospheric carbon dioxide (CO2), derived from the TANSAT satellite, using the University of Leicester Full-Physics Retrieval Algorithm (UoL-FP, also known as OCFP). This dataset is also referred to as CO2_TAN_OCFP. This version of the dataset provides data globally over land. For further information on the dataset, please see the linked documentation.\r\n\r\nInitially this dataset contains data from the period from March 2017 to May 2018, delivered as part of the GHG_cci Climate Research Data Package 7. Additional time periods may be delivered in the future.\r\n\r\nThis data has been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme, with support from the UK's National Centre for Earth Observation (NCEO)." }, "onlineresource_set": [] }, { "ob_id": 37850, "uuid": "4ebe3233e2fc42e1b18fde9f2d5f94b7", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_12/ch12_fig05/v20220804", "numberOfFiles": 0, "volume": 0, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37853, "uuid": "62fcbca7506f4a2aa056e718bb0e758a", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_12/ch12_fig07/v20220804", "numberOfFiles": 0, "volume": 0, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37856, "uuid": "b4a86f4bb18b49dea65a014ce41da4d8", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_12/ch12_fig09/v20220804", "numberOfFiles": 0, "volume": 0, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37859, "uuid": "f85710c6d46043818085ed7411cb94a5", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_12/ch12_fig10/v20220804", "numberOfFiles": 0, "volume": 0, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37862, "uuid": "4af748c3bbdd4ce0b14364cdd000e5a1", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_12/ch12_fig06/v20220804", "numberOfFiles": 0, "volume": 0, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37890, "uuid": "6d69a84a2750427ab346d8e2969dee9b", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_12/ch12_fig04/v20220623", "numberOfFiles": 36, "volume": 49171533, "fileFormat": "Data are netCDF formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37889, "uuid": "b96e2225918348e1ae47b1fedee881a6", "short_code": "ob", "title": "Chapter 12 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 12.4 (v20220623)", "abstract": "Data for Figure 12.4 from Chapter 12 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 12.4 shows median projected changes in selected climatic impact-driver indices based on CMIP6 models for ssp126 and ssp585 scenarios, and RCP4.5 and RCP8.5 scenarios (for extreme total water level), for mid-term and long-term (relative to recent past).\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\n Ranasinghe, R., A.C. Ruane, R. Vautard, N. Arnell, E. Coppola, F.A. Cruz, S. Dessai, A.S. Islam, M. Rahimi, D. Ruiz Carrascal, J. Sillmann, M.B. Sylla, C. Tebaldi, W. Wang, and R. Zaaboul, 2021: Climate Change Information for Regional Impact and for Risk Assessment. 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. 1767–1926, doi:10.1017/9781009157896.014.\r\n\r\n\r\n---------------------------------------------------\r\n Figure subpanels\r\n ---------------------------------------------------\r\n The figure has 18 panels (panel a to panel r), with data provided for all panels in the 12.4 figure directory; for each panel, the panel name is indicated in the file name with panel_X (with X being panel letter between a and r).\r\n\r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n This dataset contains median projected changes in selected climatic impact-driver indices based on CMIP6 models for ssp126 and ssp585 scenarios for mid-term (2041-2060) and long-term (2081-2100), relative to recent past (1995-2014), and their associated masks of model agreement (with values -1 where at least 80% of the models agree in the sign of change, 0 elsewhere) for:\r\n \r\n - the mean number of days per year with maximum temperature exceeding 35°C\r\n - the mean number of days per year with NOAA Heat Index over 41°C\r\n - the number of negative precipitation anomaly events per decade using the 6-month Standardised Precipitation Index\r\n - the mean soil moisture\r\n - the mean surface wind speed\r\n \r\n It also contains the files of global projected median extreme total water level for CMIP5 RCP4.5 and RCP8.5 scenarios covering both mid-term (2041-2060) and long-term (2081-2100) horizons, and one for the recent past. The data is organized as points with their associated lon/lat coordinates.\r\n\r\nNOAA stands for the US National Oceanic and Atmospheric Administration.\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\nPlease note the following filenames have been changed to ensure continuity with filenames on GitHub repository:\r\npanel p (ETWL):\r\n- panel_p_globalTWL_RCP45.nc -> globalTWL_RCP45.nc\r\n- panel_p_q_r_globalTWL_baseline.nc -> globalTWL_baseline.nc\r\npanel q (ETWL):\r\n- panel_q_globalTWL_RCP45.nc -> globalTWL_RCP85.nc\r\n- panel_p_q_r_globalTWL_baseline.nc -> globalTWL_baseline.nc\r\npanel r (ETWL):\r\n- panel_r_globalTWL_RCP45.nc -> globalTWL_RCP85.nc\r\n- panel_p_q_r_globalTWL_baseline.nc -> globalTWL_baseline.nc\r\n\r\nData provided in relation to Figure 12.4:\r\n\r\nPanels a-c (tx35) where X is replaced with a,b or c:\r\n- 'tx35_panel_X_ssp126_2081-2100_minus_baseline.nc' :\r\nglobal spatial field of changes in mean number of days per year with maximum temperature exceeding 35°C for CMIP6 ssp126 ensemble median, long-term (colors)\r\n- 'mask_80perc-agreement_tx35_panel_X_ssp126_2081-2100_minus_baseline.nc' : \r\nspatial mask (for hatching) showing where at least 80% of the models agree in terms of sign of change (negative change, positive change or zero change); values are: -1 where true, 0 where false\r\n\r\n\r\nPanels d-f (HI41) where X is replaced with d,e or f:\r\n- 'HI41_panel_X_ssp126_2081-2100_minus_baseline.nc' :\r\nglobal spatial field of changes in mean number of days per year with NOAA Heat Index over 41°C for CMIP6 ssp126 ensemble median, long-term (colors)\r\n- 'mask_80perc-agreement_HI41_panel_X_ssp126_2081-2100_minus_baseline.nc' : \r\nspatial mask (for hatching) showing where at least 80% of the models agree in terms of sign of change (negative change, positive change or zero change); values are: -1 where true, 0 where false\r\n\r\n\r\nPanel g-i (DF6) where X is replaced with g, h or i:\r\n- 'DF6_panel_X_ssp126_farch_minus_baseline.nc' : \r\nglobal spatial field of changes in number of negative precipitation anomaly events per decade using the 6-month Standardised Precipitation Index for CMIP6 ssp126 ensemble median, long-term (colors)\r\n- 'mask_80perc-agreement_DF6_panel_X_ssp126_farch_minus_baseline.nc' : \r\nspatial mask (for hatching) showing where at least :80% of the models agree in terms of sign of change (negative change, positive change or zero change); values are: -1 where true, 0 where false\r\n\r\n\r\nPanel j-l (SM) where X is replaced with j, k or l:\r\n- 'SM_panel_X_ssp126_2081-2100_minus_baseline.nc' : \r\nglobal spatial field of changes in mean soil moisture for CMIP6 ssp126 ensemble median, long-term (colors)\r\n- 'mask_80perc-agreement_SM_panel_X_ssp126_2081-2100_minus_baseline.nc': \r\nspatial mask (for hatching) showing where at least 80% of the models agree in terms of sign of change (negative change, positive change or zero change); values are: -1 where true, 0 where false\r\n\r\n\r\n\r\nPanels m-o (sfcWind) where X is replaced with m, n or o:\r\n- 'sfcWind_panel_X_ssp126_2081-2100_minus_baseline.nc': \r\nglobal spatial field of changes in mean surface wind speed for CMIP6 ssp126 ensemble median, long-term (colors)\r\n- 'mask_80perc-agreement_sfcWind_panel_X_ssp126_2081-2100_minus_baseline.nc': \r\nspatial mask (for hatching) showing where at least 80% of the models agree in terms of sign of change (negative change, positive change or zero change); values are: -1 where true, 0 where false\r\n\r\n\r\nPanel p (ETWL):\r\n- globalTWL_RCP45.nc; global spatial field of median extreme sea level for CMIP5 RCP4.5, long-term (colors); long-term corresponds to decades=2100 in the file\r\n\r\nPanels q and r (ETWL):\r\n- globalTWL_RCP85.nc; global spatial field of median extreme sea level for RCP8.5, mid-term and long-term (colors)\r\n\r\nPanels p, q and r (ETWL):\r\n- globalTWL_baseline.nc; global spatial field of median extreme sea level for baseline\r\n\r\nFor panels p, q and r:\r\n- the data shown on the plot is the difference between the future projections (globalTWL_RCP45.nc and globalTWL_RCP85.nc) and the baseline (globalTWL_baseline.nc)\r\n- the variable used is TWL; it is three dimensional: npoints, npercentiles (value given by variable percentile(npercentiles)), nsdec (value given by variable decades(nsdec))\r\n- we use percentile=50\r\n- mid-term corresponds to decades=2050\r\n- long-term corresponds to decades=2100\r\n- the baseline file has no time (decades) dimension\r\n\r\nCMIP5 is the fifth phase of the Coupled Model Intercomparison Project.\r\nCMIP6 is the sixth phase of the Coupled Model Intercomparison Project.\r\nSSP126 is the Shared Socioeconomic Pathway which represents the lower boundary of radiative forcing and development scenarios, consistent with RCP2.6.\r\nSSP585 is the Shared Socioeconomic Pathway which represents the upper boundary of radiative forcing and development scenarios, consistent with RCP8.5.\r\nRCP4.5 is the Representative Concentration Pathway for 4.5 Wm-2 global warming by 2100.\r\nRCP8.5 is the Representative Concentration Pathway for 8.5 Wm-2 global warming by 2100.\r\n\r\n---------------------------------------------------\r\nNotes on reproducing the figure\r\n---------------------------------------------------\r\nScripts for plotting figure panels can be found in the dedicated Chapter 12 GitHub repository which is linked in the Related Documents section of this catalogue record. Code used for the figure is archived on Zenodo.\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 figure on the IPCC AR6 website\r\n - Link to the report component containing the figure (Chapter 12)\r\n - Link to the Supplementary Material for Chapter 12, which contains details on the input data used in Table 12.SM.1\r\n - Link to the code for the figure, archived on Zenodo\r\n - Link to the Chapter 12 GitHub repository" }, "onlineresource_set": [] }, { "ob_id": 37895, "uuid": "3d0e1d1f24d441a9a1331560a8b0ce1f", "short_code": "result", "curationCategory": "A", "dataPath": "/bodc/UOX220127/WIO_coral_larval_dispersal", "numberOfFiles": 10106, "volume": 5658878197561, "fileFormat": "Data are CF-Compliant NetCDF formatted data files", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37894, "uuid": "2727525bf80c4798b7319116a0c15353", "short_code": "ob", "title": "Coral larval dispersal simulations for the southwestern Indian Ocean (1993-2020)", "abstract": "This dataset, contributing towards the Marine dispersal and retention in the western Indian Ocean project, contains raw coral larval connectivity data computed by the SECoW (Simulating Ecosystem Connectivity with WINDS) dispersal model. 1024 virtual coral larvae are generated every day from 1993-2020 at c. 8000 coral reef sites across the southwestern Indian Ocean, and advected for 120 days following surface-currents from the 1/50° WINDS-M simulation (http://dx.doi.org/10.5285/BF6F0CFBD09E47498572F21081376702) using OceanParcels. A larval settling ‘event’ is defined as a time interval during which a virtual coral larva is continuously within a 1/50° coral reef cell, between 1-120 days after spawning. SECoW records the arrival time, event duration, and cell index for every settling event (up to a maximum of 60). From these data, larval settling fluxes, incorporating larval mortality and competency, can be computed through post-processing with SECoW. These data can therefore be adapted to a variety of biological parameters at a fraction of the computational cost required to recompute larval trajectories. The resulting coral reef connectivity predictions will be useful for marine practitioners working on coral reef conservation across the southwestern Indian Ocean. The data were produced as part of the Marine Dispersal and Retention in the Western Indian Ocean project funded by the Natural Environment Research Council (NERC) grant NE/S007474/1. See linked online references on this record for cited items given above." }, "onlineresource_set": [] }, { "ob_id": 37900, "uuid": "994e3b417afc4d1e8e1f31e67b790a4a", "short_code": "result", "curationCategory": "A", "dataPath": "/bodc/UOX220126/WIO_marine_debris_accumulation", "numberOfFiles": 12001, "volume": 1039187221309, "fileFormat": "Data are CF-Compliant NetCDF formatted data files", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37899, "uuid": "fc001b104fe6458e92ab6a0be314e68e", "short_code": "ob", "title": "Model output for marine debris accumulating at Seychelles and other remote islands in the western Indian Ocean (1993-2019)", "abstract": "This dataset contains raw beaching data computed by marine debris simulations (run using OceanParcels) for a range of physical scenarios (surface currents from GLORYS12V1 (https://doi.org/10.3389/feart.2021.698876) Stokes drift from WAVERYS (https://doi.org/10.1007/s10236-020-01433-w) and surface winds from ERA5 (https://doi.org/10.1002/qj.3803)) as described in the accompanying manuscript. Through postprocessing, debris ‘connectivity’ matrices can be computed, providing predictions for the main terrestrial and marine source regions of plastic debris accumulating at remote islands in the western Indian Ocean. These simulations include beaching and sinking processes, and a set of example matrices is provided here (https://doi.org/10.5287/bodleian:DEdqwXZQw) However, these matrices can be recomputed for different sinking and beaching rates using the scripts archived here (https://doi.org/10.5281/zenodo.7351695) or see here (https://github.com/nvogtvincent/WIO_Marine_Debris/) for the live version with documentation. These predictions will be useful for environmental practitioners in the western Indian Ocean to assess source regions for marine debris accumulating at islands of interest, and when this debris is likely to beach. The data were produced as part of the Marine Dispersal and Retention in the Western Indian Ocean project funded by the Natural Environment Research Council (NERC) grant NE/S007474/1. See linked online references on this record for cited items given above." }, "onlineresource_set": [] }, { "ob_id": 37904, "uuid": "41ca930da28c4e2eb4e6c8a4fd7681fe", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_12/ch12_fig08/v20220804", "numberOfFiles": 0, "volume": 0, "fileFormat": "JSON, CSV, netCDF, txt", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37925, "uuid": "1d89a32cdadc49f4b76b49eb76db8971", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/osca/data/manchester/OSCA_Manc_FIDAS_Met", "numberOfFiles": 106, "volume": 248623645, "fileFormat": "NetCDF and CSV format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37924, "uuid": "62af3c6051044460aa0a716e2204bffc", "short_code": "ob", "title": "Meteorological Data from Palas FIDAS 200 Instrument at Manchester Air Quality Site, 2019 onwards", "abstract": "Meteorological data including Temperature, Pressure and Humidity from a Palas FIDAS 200 Instrument at Manchester Air Quality Site (MAQS) for the Integrated Research Observation System for Clean Air (OSCA) project from 2019-onwards." }, "onlineresource_set": [] }, { "ob_id": 37939, "uuid": "4cc7a3a2a6e5404cb0f4455753071aad", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/osca/data/manchester/OSCA_Manc_FIDAS_PM", "numberOfFiles": 111, "volume": 241876749, "fileFormat": "NetCDF and CSV format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37938, "uuid": "c5a629e1012b472c9b1fa130d2432fe1", "short_code": "ob", "title": "Particulate Matter Data from Palas FIDAS 200 Instrument at Manchester Air Quality Site, 2019 onwards", "abstract": "Particulate matter data measured at 7m above ground level by a Palas FIDAS 200 Instrument at Manchester Air Quality Site (MAQS) for the Integrated Research Observation System for Clean Air (OSCA) project.\r\nMeasurements include the abundance of mass concentration of PM1 ambient aerosol in air, mass concentration of PM2.5 ambient aerosol in air, mass concentration of PM10 ambient aerosol in Air, and the concentration of ambient aerosol particles." }, "onlineresource_set": [] }, { "ob_id": 37942, "uuid": "e24781d18d094ec796dcc482fb996b42", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/osca/data/manchester/OSCA_MAQS_CPC_aerosol_conc", "numberOfFiles": 119, "volume": 181804451, "fileFormat": "NetCDF and CSV format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37946, "uuid": "e0f62422d38d419ca9384e017d351acc", "short_code": "ob", "title": "Number Concentration of Ambient Aerosol Particles in Air Data from Cloud Particle Condenser Instrument at Manchester Air Quality Site, 2019 onwards.", "abstract": "Number concentration of ambient aerosol particles in air data measured at 7m above ground level by Cloud Particle Condenser (CPC) Instruments at at the Manchester Air Quality Site (MAQS) for the Integrated Research Observation System for Clean Air (OSCA) project.\r\n\r\nCloud Particle Condenser instrument 3750 was used (June 2019 - February 2021 and December 2021 - February 2022) and was switched over to Cloud Particle Condenser instrument 3772 (February - December 2021)" }, "onlineresource_set": [] }, { "ob_id": 37947, "uuid": "88d56df1a0294576b4e57ea7a20871b7", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/osca/data/manchester/OSCA_Manc_FIDAS_Distribution", "numberOfFiles": 92, "volume": 1372203765, "fileFormat": "NetCDF and CSV format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": null, "onlineresource_set": [] }, { "ob_id": 37952, "uuid": "a03458692f8346f3a36e3cba4169d20d", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/osca/data/manchester/OSCA_MAQS_Distro_Precipitation", "numberOfFiles": 218, "volume": 14185445457, "fileFormat": "NetCDF and CSV format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37951, "uuid": "0a948ff688f24a9f87aed71ae38a4fc0", "short_code": "ob", "title": "Number and Speed of Drops in Precipitation per Minute from Disdrometer at Manchester Air Quality Site 2019- onwards", "abstract": "Data from Laser Precipitation Monitor Model 5.4110.00.000 to measure the frequency, speed and other factors for Solid and Liquid Precipitation at Manchester Air Quality Site (MAQS), 2019 onwards." }, "onlineresource_set": [] }, { "ob_id": 37957, "uuid": "81df0f6bdc3041128c7e472500b97bde", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/osca/data/manchester/OSCA_MAQS_LGR_EAA-22_NH3", "numberOfFiles": 193, "volume": 404430833, "fileFormat": "NetCDF and CSV format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37956, "uuid": "5fc811f707f54415b129882a38889501", "short_code": "ob", "title": "Ammonia and Water Abundance Measurements from Los Gatos Research Ammonia Analyzer Instrument at Manchester Air Quality Site 2019 onwards.", "abstract": "Ammonia (NH3) and water (H20) abundance measurements made at 7 metres above ground level by a Los Gatos research ammonia analyzer instrument at Manchester air quality site (MAQS) for the Integrated Research Observation System for Clean Air (OSCA) project." }, "onlineresource_set": [] }, { "ob_id": 37962, "uuid": "d86b998fbf664148a2a82582c75198f3", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/osca/data/manchester/OSCA_MAQS_LGR_CH4_CO_CO2_H2O", "numberOfFiles": 191, "volume": 614325128, "fileFormat": "NetCDF and CSV format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37961, "uuid": "671628b8f4474599ba074607e65c4bcc", "short_code": "ob", "title": "Methane, Carbon Monoxide, Carbon Dioxide and Water Abundance Measurements from a Los Gatos Research Ammonia Analyzer Instrument at the Manchester Air Quality Site, 2019 onwards", "abstract": "Methane, carbon monoxide, carbon dioxide and water abundance measurements made at 7 metres above ground level by a Los Gatos Research Multi-Carbon Analyzer Instrument at the Manchester Air Quality Site (MAQS) for the Integrated Research Observation System for Clean Air (OSCA) project." }, "onlineresource_set": [] }, { "ob_id": 37968, "uuid": "dd4ada9043854c67926a011fb8ad1688", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/osca/data/manchester/OSCA_MAQS_SMPS-CPC_aerosol", "numberOfFiles": 99, "volume": 600775615, "fileFormat": "NetCDF and CSV format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37967, "uuid": "6f6366eb78c44875b2c92d3b8fe403c1", "short_code": "ob", "title": "Number concentration and size distribution of ambient aerosol particles in air measurements from a Cloud Particle Condenser instrument (SMPS) at the Manchester Air Quality Site, 2019 onwards", "abstract": "Number concentration and size distribution of ambient aerosol particles in air measurements made at 7m above ground level using a 3082 Scanning Mobility Particle Sizer (SMPS) in combination with a 3750 Cloud Particle Condenser (CPC) at the Manchester Air Quality Site (MAQS) for the Integrated Research Observation System for Clean Air (OSCA) project." }, "onlineresource_set": [] }, { "ob_id": 37973, "uuid": "8e358abce10f4f2fa318851c83c93433", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/osca/data/manchester/OSCA_MAQS_Sonic_Windmaster", "numberOfFiles": 189, "volume": 460630863, "fileFormat": "NetCDF and CSV format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37972, "uuid": "91625bdf73944c5e896eb56d1fec35ee", "short_code": "ob", "title": "Wind speed and direction data from Gill sonic windmaster instrument at the Manchester Air Quality Site, 2019 onwards", "abstract": "Quality tested wind speed and wind direction data at 7m above ground level from a Gill Sonic Windmaster instruments at the Manchester Air Quality Site (MAQS) for the Integrated Research Observation System for Clean Air (OSCA) project." }, "onlineresource_set": [] }, { "ob_id": 37978, "uuid": "50d16f162600454ca84b75e7b5dfa75b", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/osca/data/manchester/OSCA_MAQS_Teledyne_T500U_NO2", "numberOfFiles": 195, "volume": 308625426, "fileFormat": "Data are CSV formatted", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37977, "uuid": "f60761f3279042859e5c2902dfa0f2ef", "short_code": "ob", "title": "Nitrogen Dioxide Abundance Data from Teledyne Model T500U Instrument at the Manchester Air Quality Site, 2019 onwards", "abstract": "Mass fraction of Nitrogen Dioxide (NO2) in air measured at 7m above ground level by a Teledyne Model T500U Instrument at the Manchester Air Quality Site (MAQS) for the Integrated Research Observation System for Clean Air (OSCA) project." }, "onlineresource_set": [] }, { "ob_id": 37983, "uuid": "de4b427f2cce4fc5bb1ae45513b42da6", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/osca/data/manchester/OSCA_MAQS_Thermo_48i_CO", "numberOfFiles": 134, "volume": 200037229, "fileFormat": "NetCDF and CSV format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37982, "uuid": "dd3a958c68074e9fbad07e4922b7b011", "short_code": "ob", "title": "CO Abundance Data from Thermo 48i Carbon Monoxide Analyser Instrument at the Manchester Air Quality Site, 2019 onwards", "abstract": "Mass fraction of carbon monoxide (CO) in air measured at 7m above ground level by a Thermo 48i Carbon Monoxide Analyser Instrument at the Manchester Air Quality Site (MAQS) from 2019 onwards for the Integrated Research Observation System for Clean Air (OSCA) project." }, "onlineresource_set": [] }, { "ob_id": 37988, "uuid": "9f5039803cbb428bbe08e500e57e3bfa", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/osca/data/manchester/OSCA_MAQS_Thermo_49i_O3", "numberOfFiles": 195, "volume": 312610964, "fileFormat": "NetCDF and CSV format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37987, "uuid": "966423f87a304c8b99a80f66c1b8e6fd", "short_code": "ob", "title": "Ozone Abundance Data from Model 49i Ozone Analyzer Instrument at the Manchester Air Quality Site, 2019 onwards", "abstract": "Mass Fraction of Ozone (O3) in air measured at 7 metres above ground level by a Thermo Model 49i Ozone Analyzer Instrument at the Manchester Air Quality Site (MAQS) for the Integrated Research Observation System for Clean Air (OSCA) project." }, "onlineresource_set": [] }, { "ob_id": 37993, "uuid": "2efdbb3f9f134418bef47f91a95bb88b", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/osca/data/manchester/OSCA_MAQS_Thermo_49iY_NO-NOy", "numberOfFiles": 195, "volume": 492458331, "fileFormat": "NetCDF and CSV format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37992, "uuid": "1d58f2f5e7874e55a83ca57311dcfb9a", "short_code": "ob", "title": "NO and NOy Abundance Data from Thermo Model 42i-Y NOY Analyzer Instrument at the Manchester Air Quality Site, 2019 onwards", "abstract": "Oxides of nitrogen (NO and NOy) rates measured at 7 metres above ground level by a Thermo Model 42i-Y NOY Analyzer Instrument at the Manchester Air Quality Site (MAQS) for the Integrated Research Observation System for Clean Air (OSCA) project." }, "onlineresource_set": [] }, { "ob_id": 37998, "uuid": "545bd98c878742709eb9311c3fa87844", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/osca/data/manchester/OSCA_MAQS_XACT_elemental_comp", "numberOfFiles": 155, "volume": 71000701, "fileFormat": "NetCDF and CSV format", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37997, "uuid": "21723af1f2a640c6990ce9cb3b70aaef", "short_code": "ob", "title": "Elemental Composition Data of Ambient PM2.5 and PM10 Aerosol Particles in Air from a Cooper XACT 625i Instrument at the Manchester Air Quality Site, 2019 onwards", "abstract": "Elemental Composition of Ambient Aerosol Particles in Air Data measured at 7m above ground level using a Cooper XACT 625i Instrument at the Manchester Air Quality Site for the Integrated Research Observation System for Clean Air (OSCA) project. Only PM10 Aerosols are analysed prior to December 2020, and both PM2.5 and PM10 are analysed from December 2020 onwards." }, "onlineresource_set": [] }, { "ob_id": 38006, "uuid": "920678ab37ca413593d4ae8eb2ede3ce", "short_code": "result", "curationCategory": "A", "dataPath": "/badc/ar6_wg1/data/ch_03/ch3_fig44/v20220615", "numberOfFiles": 7, "volume": 29178, "fileFormat": "CSV, txt", "storageStatus": "online", "storageLocation": "internal", "oldDataPath": [], "observation": { "ob_id": 37564, "uuid": "d35ac1955c264deea9699d08dbc568f2", "short_code": "ob", "title": "Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.44 (v20220615)", "abstract": "Data for Figure 3.44 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 3.44 shows multivariate synopsis of paleoclimate model results compared to observational references. \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 Figure has three rows (a), (b) and (c). The data is on the DMS in the panel_a, panel_b, panel_c subdirectories. \r\n\r\n---------------------------------------------------\r\n List of data provided\r\n ---------------------------------------------------\r\n - GSAT anomalies in MidHolocene from CMIP6, PMIP3, non-CMIP6 PMIP4 models as well as Bertlein et al. (2011) reconstructions\r\n - GSAT anomalies in LIG, LGM and EECO from CMIP6, PMIP3, non-CMIP6 PMIP4 models as well as Tierney et al. (2020) reconstructions\r\n - Regional Mean Temperature of the Warmest month, Mean Annual Precipitation and Mean Temperature of the Coldest month from CMIP6, PMIP3, non-CMIP6 PMIP4 models as well as Bertlein et al. (2011) reconstructions\r\n - Regional Mean Temperature of the Warmest month, Mean Annual Precipitation and Mean Temperature of the Coldest month from CMIP6, PMIP3, non-CMIP6 PMIP4 models as well as Tierney et al. (2020) reconstructions\r\n\r\n---------------------------------------------------\r\n Data provided in relation to figure\r\n ---------------------------------------------------\r\n panel_a/gmst_anomalies_paleo_climate.csv has data for all the markers in all subpanels in panel a\r\n panel_a/gmst_anomalies_paleo_climate_reconstructions.csv: relates to the pale orange (navajowhite) shading in panel (a), column 2 contains the bottom values, column 3 are the top values.\r\n panel_b/temperature_and_precipitation_paleo_midHolocene.csv has data for all the markers in all subpanels in panel b\r\n panel_c/temperature_and_precipitation_paleo_lastGlacialMaximum.csv has data for all markers in all subpanels in panel c\r\n\r\nGSAT stands for Global Surface Air Temperature.\r\nCMIP6 is the sixth stage of the Coupled Model Intercomparison Project. \r\nPMIP3 is the Paleoclimate Modelling Intercomparison Project phase 3.\r\nPMIP4 is the Paleoclimate Modelling Intercomparison Project phase 4.\r\nLIG stands for Last Interglacial.\r\nLGM stands for the Last Glacial Maximum.\r\nEECO stands for Early Eocene Climatic Optimum.\r\n\r\n ---------------------------------------------------\r\n Temporal Range of Paleoclimate Data\r\n ---------------------------------------------------\r\n This dataset also covers a paleoclimate timespan from 55000000-5000 years BP (55000000-5000 years before present). \r\n\r\n ---------------------------------------------------\r\n Notes on reproducing the figure from the provided data\r\n ---------------------------------------------------\r\n The last column in each file is the color and/or shape of the marker.\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 figure on the IPCC AR6 website" }, "onlineresource_set": [] } ] }