Temperature and Precipitation Bias Patterns in a Dynamical Downscaling Procedure over Europe during the Period 1951–2010

The Weather Research and Forecasting (WRF) mesoscale meteorological model is used to dynamically downscale data from the Goddard Institute for Space Studies (GISS) atmospheric general circulation (GCM) CMIP5 version (Model E2-R) over Europe at a 0.25° grid size resolution, period of 1951 2010. configuration single nested with resolutions 0.75° 0.25°. Two 30-year datasets are produced periods 1951–1980 1981–2010, representing historic current periods, respectively. Simulated changes in climate normals estimated compared against change derived E-OBS gridded dataset spatial analysis. Results indicate that consistently underpredicts temperature fluctuations observed across all subregions, indicative colder climatology. Winter has strongest bias seasons, northeastern part domain having highest. This largely due land–atmosphere interactions. Conversely, spring summer have lowest regional biases, owing combination low snow cover (relative winter) milder radiation effects (as opposed summer). Precipitation negative most cases, regardless subregion analyzed, physical mechanism employed topographic features each region. Both number days when exceeds 25 °C precipitation 5 mm/day captured by reasonably well, exhibiting similar characteristics their counterpart means.