Evaluation of Cumulus Parameterization of the Regional Climate Model in the São Francisco River Basin

Abstract

The use of climate models with emphasis on precipitation simulation is strategic for climate and water resources studies. The objective of this work was to evaluate the precipitation simulated by the RegCM regional climate model in the São Francisco River basin, according to the cumulus parameterization and the domain. Our evaluation, using several statistical indices and their combination, show that RegCM showed greater performance in simulating precipitation patterns when Emanuel or Tiedke parameterization was prescribed (activated). The other parameterizations evaluated, Kain-Fritsch and Grell, underestimated precipitation considerably. Emanuel stood out for the better representation of the temporal variability of precipitation, while Tiedke presented a higher correlation and lower mean errors. The Low São Francisco was the region in which RegCM showed the lower skill in simulating precipitation from May to July (rainy season), indicating the difficulty of the model in representing the moisture transport from the ocean to the continent and the occurrence of Easterly Waves disturbances. Finally, the model prescribed with a larger domain simulated better the precipitation patterns probably because it contemplates the region where the meteorological systems of larger scales act in the basin.

Keywords
cumulus parameterization; dynamic downscaling; regional atmospheric model; RegCM