Evaluation of the skill and added value of a reanalysis-driven regional simulation for Alpine temperature

To determine whether the use of regional climate models improves the representation of climate is a crucial topic in climate modelling. An improvement over coarser scale models is expected especially in areas with complex orography or along coastlines. However, some studies have shown no clear added value for regional climate models. In this study a high-resolution regional climate simulation performed with REMO 5.0 (regional model) over the whole of Europe over the period 1958-1998 is analysed for 2-m temperature over the European Alps and their surroundings called the Greater Alpine region (GAR). The simulation is driven by perfect boundary conditions at the lateral boundaries provided by the ERA40 reanalysis and spectral nudging of the large-scale wind fields towards ERA40 values for the upper layers inside the model domain. The added value of the regional simulation (1/6 degrees resolution) is analysed with respect to the driving reanalysis (1.125 degrees resolution). Both the REMO simulation and the ERA40 reanalysis are validated against different station datasets of monthly and daily mean 2-m temperature. Correlation analysis shows that the temporal variability of temperature is well represented by both REMO and ERA40. whereas both show considerable biases. The REMO bias reaches 3 K in summer in regions known to experience a problem with summer drying in a number of regional models. The comparison of REMO and ERA40 shows that an added value of the former exists for all regions in winter. For the regions surrounding the Alps, the added value is absent in summer, whereas in the inner Alpine subregions with most complex orography, REMO performs better than ERA40 during the whole year. The only moderate value added by REMO in this hindcast set-up may be partly explicable by the fact that meteorological measurements are assimilated in the ERA40 reanalysis but not in the REMO simulation. Copyright (C) 2009 Royal Meteorological Society