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Regional climate models (RCMs) are expected to provide better representations of the climate dynamics because of their higher spatial resolutions. Here, we generated an ensemble of decadal (2006–36) RCM predictions for the area of Israel, which spans a considerable climatic gradient and comprises complex terrain. We used the WRF Model forced by the MIROC5 global climate model (GCM). The ensemble was generated by choosing different combinations of radiation, microphysics, surface layer, and planetary boundary layer parameterizations. The simulation results were compared with meteorological station data for the first simulated decade. For the minimum surface temperature, all the RCM configurations performed better than the driving GCM, while for the maximum surface temperature, only three out of eight configurations improved the predictions. The RCM configurations had higher errors in predicting the precipitation, but four configurations had comparable errors to the GCM. For the next two decades, the ensemble average predicts an increase of 0.51° and 0.40°C decade −1  for the average daily minimum and maximum surface temperatures, respectively. No significant change is predicted in the precipitation. We found that all the parameterizations affect the predictions of the surface temperatures and precipitation [e.g., the CAM radiation scheme simulates colder temperatures than the RRTM for GCMs (RRTMG)] but the PBL and surface layer scheme has the largest effect on the errors. Spectral nudging was found to have a considerable effect on the deviations of the precipitation predicted by the WRF configurations from the predictions of the GCM and a much smaller effect on the surface temperature predictions.

Regional Decadal Climate Predictions Using an Ensemble of WRF Parameterizations Driven by the MIROC5 GCM