High-resolution future climate data for species distribution models in Europe

<p><strong>Description</strong></p> <p>This dataset contains a set of 13 climatological variables (<code>Variable</code>, <code>VariableName</code>) at a spatial resolution of 1x1km for Europe (nx = 13147, ny = 6071) for historical (<code>ClimatePeriod</code>) and future climate conditions. These variables are a subset of the so-called bioclimatic variables that are often part of global gridded datasets (e.g. <a href="https://worldclim.org/data/bioclim.html">WorldClim</a>, <a href="http://chelsa-climate.org/bioclim/">CHELSA</a>) that have been specifically developed for species distribution modelling and ecological applications.</p> <p>The climatological data correspond to 35-year (<code>Startyear_Endyear</code> = <code>1971_2005</code>) and 30-year (<code>Startyear_Endyear</code> = <code>2041_2070</code>) mean values representing respectively historical and future climate conditions. To account for the future climate conditions, three possible emission scenarios of greenhouse gases as defined by the <a href="https://www.ipcc.ch/">Intergovernmental Panel on Climate Change (IPCC)</a> are used (<code>ClimatePeriod</code> = <code>rcp26</code>, <code>rcp45</code>, <code>rcp85</code>).</p> <p>The complete set of variables (var[1-13]) for which historical and future climate data layers are produced are given below.</p> <p>The source data for the climate layers were assembled from the <a href="https://cordex.org/data-access/">EURO-CORDEX archive</a> (Kotlarski et al., 2014). More specifically, we have used the regional climate model simulations for Europe at a spatial resolution of 12.5x12.5km on which a three-step statistical downscaling approach has been applied:</p> <ol> <li><strong>Processing</strong> (averaging, totals, &hellip;) of all available time series of the EURO-CORDEX model experiments (<code>ClimatePeriod</code> = evaluation, historical, rcp) for the climatological variables.</li> <li><strong>Interpolation</strong> of the data layers from the 12.5x12.5km EURO-CORDEX grid to a 1x1km spatial <a href="http://chelsa-climate.org/">CHELSA</a> (Karger et al., 2017) reference grid (see files <code>lat_1km.csv</code> and <code>lon_1km.csv</code>).</li> <li><strong>Calculate differences</strong> between the 1x1km-interpolated variables (<code>Variable</code> = only for var[1-9]) from the evaluation model experiments (or <code>ClimatePeriod</code>) and the corresponding reference bioclimatic CHELSA variables. In order to account for possible biases present in the EURO-CORDEX climate models, these differences (or biases) are then subtracted from the respective 1x1-km-interpolated variables for the historical and rcp model experiments (<code>ClimatePeriod</code>).</li> </ol> <p>The dimensions of the 1x1km grid (excl. the first row and column):</p> <ul> <li>y-dimension = number of columns = 6071</li> <li>x-dimension = number of rows = 13147</li> </ul> <p>The longitudes and latitudes of respectively the southwest and northeast corner of the grid are:</p> <ul> <li>longitude -44.592; latitude 21.991 (southwest corner)</li> <li>longitude 64.967; latitude 72.583 (northeast corner)</li> </ul> <p>The climatological variables are used as input data for the species distribution modelling of Invasive Alien Species for the <a href="https://osf.io/7dpgr/">Tracking Invasive Alien Species (TrIAS)</a> project.</p> <p><strong>Variables</strong></p> <ul> <li><strong>Variable</strong> (VariableName): Unit</li> <li><strong>var1</strong> (AnnualMeanTemperature): &deg;C</li> <li><strong>var2</strong> (AnnualAmountPrecipitation): mm year^-1</li> <li><strong>var3</strong> (AnnualVariationPrecipitation): coefficient of variation</li> <li><strong>var4</strong> (AnnualVariationTemperature): stdev</li> <li><strong>var5</strong> (MaximumTemperatureWarmestMonth): &deg;C</li> <li><strong>var6</strong> (MinimumTemperatureColdestMonth): &deg;C</li> <li><strong>var7</strong> (TemperatureAnnualRange): &deg;C</li> <li><strong>var8</strong> (PrecipitationWettestMonth): mm</li> <li><strong>var9</strong> (PrecipitationDriestMonth): mm</li> <li><strong>var10</strong> (30yrMeanAnnualCumulatedGDDAbove5degreesC): &deg;C days</li> <li><strong>var11</strong> (AnnualMeanPotentialEvapotranspiration): mm day^-1</li> <li><strong>var12</strong> (AnnualMeanSolarRadiation): W m^-2</li> <li><strong>var13</strong> (AnnualVariationSolarRadiation): stdev</li> </ul> <p><strong>Files</strong></p> <ul> <li><strong>varX_VariableName_ClimatePeriod_Startyear_Endyear.csv</strong>:&nbsp;climatological data layers for the 13 variables listed above</li> <li><strong>lon_1km.csv</strong>: longitudes for the&nbsp;1x1km grid</li> <li><strong>lat_1km.csv</strong>: latitudes for the&nbsp;1x1km grid</li> </ul>