{"accessLevel": "public", "bureauCode": ["010:12"], "contactPoint": {"@type": "vcard:Contact", "fn": "Sarah Shafer", "hasEmail": "mailto:sshafer@usgs.gov"}, "description": "This data set consists of monthly long-term mean temperature data (degrees C) for the last glacial maximum (21 ka) downscaled to a 10-km grid of North America.  The 10-km data were derived using simulated temperature data from 10 general circulation models (GCMs; CCSM4, CNRM-CM5, COSMOS-ASO, FGOALS-g2, GISS-E2-R, IPSL-CM5A-LR, MIROC-ESM, MPI-ESM-P-OA, MPI-ESM-P-OAC, and MRI-CGCM3) run under the PMIP3/CMIP5 (Paleoclimate Modelling Intercomparison Project phase 3 / Coupled Model Intercomparison Project phase 5) \u201clgm\u201d and \u201cpiControl\u201d experiments.  The lgm and piControl data are available from the Earth System Grid - Center for Enabling Technologies (ESG-CET; https://esgf-node.llnl.gov/projects/esgf-llnl/).  Additional information about the data is available from the CMIP5 (https://pcmdi.llnl.gov/mips/cmip5/) and PMIP3 (https://pmip3.lsce.ipsl.fr/) web sites.  The names of the lgm and piControl files we used are listed in the \u201csource_file\u201d global attribute of each GCM temperature netCDF file in this data release.  For each GCM, the PMIP3/CMIP5 lgm temperature data were bias corrected using long-term mean differences calculated as the lgm long-term mean minus the piControl long-term mean.  These long-term mean differences were regridded to a North America 10-km Lambert azimuthal equal-area grid using the CDO (Climate Data Operators, https://code.mpimet.mpg.de/projects/cdo) bilinear interpolation function \u201cremapbil\u201d.  We used ICE-5G (VM2) data (Peltier, 2004, https://doi.org/10.1146/annurev.earth.32.082503.144359) to identify grid cells with ice cover at 21 ka.  The interpolated long-term mean differences were applied to CRU CL 2.0 (1961-1990 30-year mean) climate data (New et al., 2002, https://doi.org/10.3354/cr021001).  The CRU CL 2.0 data were also regridded to the 10-km grid using local lapse-rate adjusted interpolation (Praskievicz and Bartlein, 2014, https://doi.org/10.1016/j.jhydrol.2014.06.017).  The ensemble mean data were calculated using the bias corrected temperature data from each of the 10 GCM simulations.", "distribution": [{"@type": "dcat:Distribution", "accessURL": "https://doi.org/10.5066/P9KC0L47", "description": "Landing page for access to the data", "format": "XML", "mediaType": "application/http", "title": "Digital Data"}, {"@type": "dcat:Distribution", "description": "The metadata original format", "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.5fc9b489d34e4b9faad8ac7a.xml", "format": "XML", "mediaType": "text/xml", "title": "Original Metadata"}], "identifier": "http://datainventory.doi.gov/id/dataset/USGS_5fc9b489d34e4b9faad8ac7a", "keyword": ["CMIP5", "PMIP3", "USGS:5fc9b489d34e4b9faad8ac7a", "climate change", "mathematical simulation"], "modified": "2021-01-26T00:00:00Z", "publisher": {"@type": "org:Organization", "name": "U.S. Geological Survey"}, "spatial": "84.117325, -6.454998, 80.000000, 89.981037", "theme": ["geospatial"], "title": "PMIP3/CMIP5 lgm simulated temperature data for North America downscaled to a 10-km grid"}