November 27, 2023 Dataset Restricted Access

Böhner, Jürgen; Dietrich, Helge; Wehberg, Jan

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{"@context":"https://schema.org/","@id":"http://doi.org/10.25592/uhhfdm.11449","@type":"Dataset","citation":[{"@id":"http://doi.org/10.1007/s13595-018-0788-5","@type":"CreativeWork"},{"@id":"http://doi.org/10.1002/joc.3915","@type":"CreativeWork"},{"@id":"http://doi.org/10.1007/s10113-013-0499-2","@type":"CreativeWork"}],"contributor":[{"@type":"Person","affiliation":"Integrated Climate Data Center (ICDC), Center for Earth System Research and Sustainability (CEN), University of Hamburg, Hamburg, Germany","name":"Sadikni, Remon"},{"@id":"https://orcid.org/0000-0001-7281-3746","@type":"Person","affiliation":"Integrated Climate Data Center (ICDC), Center for Earth System Research and Sustainability (CEN), University of Hamburg, Hamburg, Germany","name":"Kern, Stefan"}],"creator":[{"@type":"Person","affiliation":"Universit\u00e4t Hamburg, Center for Earth System Research and Sustainability, Institute of Geography, Bundesstra\u00dfe 55, 20146 Hamburg","name":"B\u00f6hner, J\u00fcrgen"},{"@type":"Person","affiliation":"Universit\u00e4t Hamburg, Center for Earth System Research and Sustainability, Institute of Geography, Bundesstra\u00dfe 55, 20146 Hamburg","name":"Dietrich, Helge"},{"@type":"Person","affiliation":"Universit\u00e4t Hamburg, Center for Earth System Research and Sustainability, Institute of Geography, Bundesstra\u00dfe 55, 20146 Hamburg","name":"Wehberg, Jan"}],"datePublished":"2023-11-27","description":"<p><strong>Abstract:</strong> Gridded climate time series for Germany derived through downscaling of EURO-CORDEX historical simulations and climate projections from following ensemble members (<a href=\"http://www.euro-cordex.net\">www.euro-cordex.net</a>)::</p>\n\n<p>MPI-M-MPI-ESM-LR(r1)_CLMcom-CCLM4-8-17: RCPs 8.5, 4.5, 2.6 and historical (MPI_CLM)</p>\n\n<p>ICHEC-EC-EARTH(r12)_KNMI-RACMO22E(v1): RCP 8.5 and historical (ECE_RAC)</p>\n\n<p>CCCmaCanESM2_r1i1p1_CLMcomCCLM4817_v1: RCP 8.5 and historical (CA2_CLM)</p>\n\n<p>All time series were consistently calculated at daily resolution and a grid cell spacing of 250 &times; 250 meter. Historical 1950&ndash;2005 data sets and 2006&ndash;2100 RCP projections comprise of mean temperature, minimum temperature, maximum temperature, precipitation, global radiation, air pressure, wind speed, specific humidity and delineated variables (relative humidity, potential evapotranspiration, water vapor pressure). All data sets except specific humidity and surface air pressure are available twice, as downscaled but non-bias corrected EURO-CORDEX data, and as bias corrected data sets. Correction terms for empirical adjustment of downscaling results were computed according to Sachindra et al. (2014) using gridded WP-KS-KW data as observational reference (Dietrich et al. 2019).</p>\n\n<p>Dietrich, H., Wolf, T., Kawohl, T., Wehberg, J., K&auml;ndler, G., Mette, T., R&ouml;der, A. &amp; B&ouml;hner, J. (2019): Temporal and spatial high-resolution climate data from 1961-2100 for the German National Forest Inventory (NFI). &ndash; Annals of Forest Science 76: 6, <a href=\"https://doi.org/10.1007/s13595-018-0788-5\">https://doi.org/10.1007/s13595-018-0788-5</a>.</p>\n\n<p>Sachindra, D.A., Huang, F., Bartona, A. &amp; Pereraa, B.J.C. (2014): Statistical downscaling of general circulation model outputs to precipitation &ndash; part 2: bias-correction and future projections. &ndash; Int. J. Climatol. 34: 3282&ndash;3303, <a href=\"https://doi.org/10.1002/joc.3915\">https://doi.org/10.1002/joc.3915</a>.</p>\n\n<p><strong>TableOfContents:</strong> daily mean 2m-air temperature (tav); daily minimum 2m-air temperature (tmn), daily maximum 2m-air temperature (tmx); daily sum of precipitation (prz); daily sum of global radiation (sgz); daily surface air pressure (psz); daily mean 10m wind speed (wsp); daily mean specific humidity (hus); daily mean relative humidity (rhm); potential evapotranspiration (pet); daily mean water vapor pressure (vap)</p>\n\n<p><strong>TechnicalInfo:</strong> dimension: 2578 columns x 3476 rows; temporalExtent_startDate_Historlcal: 1950-01-01 00:00:00; temporalExtent_endDate_Historical: 2005-12-31 23:59:59; temporalDuration_Historical: 56; temporalDurationUnit_Historical: a; temporalExtent_startDate_RCPs: 2006-01-01 00:00:00; temporalExtent_endDate_RCPs: 2100-12-31 23:59:59; temporalDuration_RCPs: 95; temporalDurationUnit_RCPs: a; temporalResolution: 1; temporalResolutionUnit: d; spatialResolution: 250; spatialResolutionUnit: m; horizontalResolutionXdirection: 250; horizontalResolutionXdirectionUnit: m; horizontalResolutionYdirection: 250; horizontalResolutionYdirectionUnit: m; verticalResolution: none; verticalResolutionUnit: none</p>\n\n<p><strong>Methods:</strong> Statistical downscaling of EURO-CORDEX data is performed, merging MOS (Model Output Statistics) downscaling with surface parameterization techniques (B&ouml;hner &amp; Antonic 2009; B&ouml;hner &amp; Bechtel 2018) to account for terrain-forced fine-scale topoclimatic variations. For a comprehensive description of the methods, see Wehberg &amp; B&ouml;hner (2023).</p>\n\n<p>B&ouml;hner, J. &amp; Antonic, O. (2009): Land-Surface Parameters Specific to Topo-Climatology. &ndash; In: Hengl, T &amp; Reuter, H.I. [Eds.]: Geomorphometry: Concepts, Software, Applications. &ndash; Developments in Soil Science, Elsevier, Volume 33, 195-226, <a href=\"https://doi.org/10.1016/S0166-2481(08)00008-1\">https://doi.org/10.1016/S0166-2481(08)00008-1</a>.</p>\n\n<p>B&ouml;hner, J. &amp; Bechtel, B. (2018): GIS in Climatology and Meteorology. &ndash; In: Huang, B. [Ed.]: Comprehensive Geographic Information Systems. &ndash; Vol. 2, pp. 196&ndash;235. Oxford: Elsevier. <a href=\"http://dx.doi.org/10.1016/B978-0-12-409548-9.09633-0\">http://dx.doi.org/10.1016/B978-0-12-409548-9.09633-0</a>.</p>\n\n<p>B&ouml;hner, J. &amp; Wehberg, J.-A. (2022): Schlussbericht zum Verbundvorhaben Standortsfaktor Wasserhaushalt im Klimawandel (WHH-KW); Teilvorhaben 4: Klimadaten. Universit&auml;t Hamburg/Centrum f&uuml;r Erdsystemforschung und Nachhaltigkeit (CEN)/Institut f&uuml;r Geographie/Abt. Physische Geographie. Waldklimafonds, Bundesministerium f&uuml;r Ern&auml;hrung und Landwirtschaft, Bundesministerium f&uuml;r Umwelt, Naturschutz und nukleare Sicherheit. 14 Seiten.</p>\n\n<p>Wehberg, J.-A. &amp; B&ouml;hner, J. (2023): Hochaufgel&ouml;ste Klimaprojektionen f&uuml;r Deutschland. Forstliche Forschungsberichte M&uuml;nchen 224. Schriftenreihe des Zentrums Wald-Forst-Holz Weihenstephan, ISBN 3-933506-55-7, pp. 69-78.</p>\n\n<p><strong>Quality:</strong> --</p>\n\n<p><strong>Units:</strong> degC; degC; degC; mm; MJ/m2; hPa; m/s; kg/kg; percent; mm; hPa</p>\n\n<p><strong>ScaleFactors:</strong> 0.1; 0.1; 0.1; 0.1; 0.1; 0.1; 0.1; 1; 1; 0.1; 1</p>\n\n<p><strong>GeoLocation:</strong> westBoundCoordinate: 278750; westBoundCoordinateUnit: m; eastBoundCoordinate: 923000; eastBoundCoordinateUnit: m; southBoundCoordinate: 5234000; southBoundCoordinateUnit: m; northBoundCoordinate: 6102750; northBoundCoordinateUnit: m; ProjectCoordinateSystem: Transverse_Mercator; ProjectionCoordinateSystemParameters: [+proj=utm +datum=WGS84 +zone=32 +no_defs]. geoLocationPlace:Germany; UTMZone: 32</p>\n\n<p><strong>Size:</strong> Files are stored into one NetCDF-file per year and variable and uploaded as tar-archives - one per variable, model and run. The file size of the netCDF files differs between 36 and 206 GB per future scenario simulation and variable (95 years) and between 21 and 113 GB per historical run and variable (56 years).</p>\n\n<p><strong>Format:</strong> netCDF</p>\n\n<p><strong>DataSources:</strong> EURO-CORDEX data published via ESGF (<a href=\"https://cordex.org/data-access/esgf/\">https://cordex.org/data-access/esgf/</a>). Jacob, D., Petersen, J., Eggert, B. et al. EURO-CORDEX: new high-resolution climate change projections for European impact research. Reg Environ Change 14, 563&ndash;578 (2014). <a href=\"https://doi.org/10.1007/s10113-013-0499-2\">https://doi.org/10.1007/s10113-013-0499-2</a></p>\n\n<p><strong>Contact:</strong> Prof. Dr. J&uuml;rgen B&ouml;hner, Universit&auml;t Hamburg, Center for Earth System Research and Sustainability, Institute of Geography, Bundesstra&szlig;e 55, 20146 Hamburg, <a href=\"mailto:juergen.boehner@uni-hamburg.de\">juergen.boehner (at) uni-hamburg.de</a>; <a href=\"https://www.geo.uni-hamburg.de/en/geographie/mitarbeiterverzeichnis/boehner.html\">https://www.geo.uni-hamburg.de/en/geographie/mitarbeiterverzeichnis/boehner.html</a></p>\n\n<p>Webpage: <a href=\"https://www.waldklimafonds.de/\">https://www.waldklimafonds.de/</a> and <a href=\"https://www.lwf.bayern.de/boden-klima/wasserhaushalt/223446/index.php\">https://www.lwf.bayern.de/boden-klima/wasserhaushalt/223446/index.php</a></p>","identifier":"http://doi.org/10.25592/uhhfdm.11449","inLanguage":{"@type":"Language","alternateName":"eng","name":"English"},"keywords":["Climate Model Regionalisation","Historical simulations","Climate projections","Downscaling","Meteorology","Global radiation","2m-air temperature","Surface air pressure","Precipitation","Specific humidity","Relative humidity","Water vapor pressure","Potential evaporation","10m wind speed","Germany"],"name":"Temporal and spatial high-resolution climate data from regional and global climate models for the German National Forest Inventory for 1950-2100","url":"https://www.fdr.uni-hamburg.de/record/11449","version":"2023_fv0.01"}