Decadal BIOCLIM estimates based on ISIMIP3b climatic forcing data for the European continent

<p>This dataset contains BIOCLIM variables (plus huss, sfcwind, rsds) which have been prepared and calculated from the original ISIMIP3b bias-adjusted climate forcing data from 5 GCM models (obtained on 2023-08-07). <br><br>For more information on the original data and its properties, please see the ISIMIP3b modelling protocol and here specifically the climate forcing section <a href="https://protocol.isimip.org/#/ISIMIP3b/31-forcing-data" target="_blank" rel="noopener">https://protocol.isimip.org/#/ISIMIP3b/31-forcing-data</a> and <a href="https://doi.org/10.5194/gmd-17-1-2024">Frieler et al. (2024)</a>.</p> <p>The original climate forcing data (global extent, daily temporal grain) were cropped to the European extent and spatial-temporally aggregated. Here 10 year (decadal) steps were chosen as target climatology.<br><br>For each time slot (e.g. 10 years) and scenario (historical or ssps) the following 22 variables were calculated:</p> <p>bioclim01 = Annual Mean Temperature<br>bioclim02 = Mean Diurnal Range (Mean of monthly (max temp - min temp))<br>bioclim03 = Isothermality (BIO2/BIO7) (&times;100)<br>bioclim04 = Temperature Seasonality (standard deviation &times;100)<br>bioclim05 = Max Temperature of Warmest Month<br>bioclim06 = Min Temperature of Coldest Month<br>bioclim07 = Temperature Annual Range (BIO5-BIO6)<br>bioclim08 = Mean Temperature of Wettest Quarter<br>bioclim09 = Mean Temperature of Driest Quarter<br>bioclim10 = Mean Temperature of Warmest Quarter<br>bioclim11 = Mean Temperature of Coldest Quarter<br>bioclim12 = Annual Precipitation<br>bioclim13 = Precipitation of Wettest Month<br>bioclim14 = Precipitation of Driest Month<br>bioclim15 = Precipitation Seasonality (Coefficient of Variation)<br>bioclim16 = Precipitation of Wettest Quarter<br>bioclim17 = Precipitation of Driest Quarter<br>bioclim18 = Precipitation of Warmest Quarter<br>bioclim19 = Precipitation of Coldest Quarter<br>huss = Average (arithmetric mean) specific humidity<br>rsds = Average (arithmetric mean) Surface downwelling shortwave radiation<br>sfcwind = Average near-surface wind speed (arithmetric mean)<br><br>---<br><strong>Data properties:</strong></p> <table> <tbody> <tr> <td>Shared Socioeconomic Pathways (SSP)</td> <td>SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5</td> </tr> <tr> <td>General circulation models (GCMs)</td> <td>GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL</td> </tr> <tr> <td>Spatial grain</td> <td>0.5 degree (~50km&sup2;)</td> </tr> <tr> <td>Geographic projection</td> <td>WGS 84</td> </tr> <tr> <td>Temporal grain</td> <td>10 year steps</td> </tr> <tr> <td>Spatial extent</td> <td>Continental Europe including Turkey (see screenshot)</td> </tr> <tr> <td>Temporal extent</td> <td>1850 to 2010 (Historical), 2010 - 2100 (Future)</td> </tr> <tr> <td>Number of variables</td> <td>22</td> </tr> </tbody> </table> <p><br>All files are provided in netCDF (nc) format. The preprocessed datasets are provided as it and the author takes no responsibility for errors or misuse.&nbsp;</p>