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Abstract A statistical‐dynamical downscaling method is presented to estimate 10 m wind speed and direction distributions at high spatial resolutions using a weather type based approach combined with a mesoscale model. Daily 850 hPa wind fields (predictors) from ERA40 reanalysis and daily 10 m wind speeds and directions (predictands) measured at 78 meteorological stations over France are used to build and validate the downscaling algorithm over the period 1974–2002. First of all, the daily 850 hPa wind fields are classified into a large number of wind classes and one day is randomly chosen inside each wind class. Simulations with a non‐hydrostatic mesoscale atmospheric model are then performed for the selected days over three interactively nested domains over France, with finest horizontal mesh size of 3 km over the Mediterranean area. The initial and coupling fields are derived from the ERA40 reanalysis. Finally, the 10 m wind distributions are reconstructed by weighting each simulation by the corresponding wind class frequency. Evaluation and uncertainty assessment of each step of the procedure is performed. This method is then applied for a climate change impact study: daily 850 hPa wind fields from 14 general circulation models of the CMIP3 multimodel dataset are used to determine evolutions in the frequency of occurrence of the wind classes and to assess the potential evolution of the wind resources in France. Two time periods are focused on: a historical period (1971–2000) from the climate of the twentieth century experiment and a future period (2046–2065) from the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) experiment. Evolution of the 10 m winds in France and associated uncertainties are discussed. Significant changes are depicted, in particular a decrease of the wind speed in the Mediterranean area. Copyright © 2010 Royal Meteorological Society
Najac et al. (Fri,) studied this question.