Abstract

This paper evaluates the Weather Research and Forecasting model (WRF) sensitivity to eight different combinations of cumulus, microphysics, and planetary boundary layer (PBL) parameterization schemes over a topographically complex region in southern Spain (Andalusia) for the period 1990-99. The W... Show moreThis paper evaluates the Weather Research and Forecasting model (WRF) sensitivity to eight different combinations of cumulus, microphysics, and planetary boundary layer (PBL) parameterization schemes over a topographically complex region in southern Spain (Andalusia) for the period 1990-99. The WRF configuration consisted of a 10-km-resolution domain nested in a coarser domain driven by 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40) data, with spectral nudging above the PBL employed over the latter domain. The model outputs have been compared at different time scales with an observational dataset that comprises 438 rain gauges and 152 temperature stations with records of both daily maximum and minimum temperatures. To reduce the "representation error" the validation with observations has been performed using a multistep regionalization that distinguishes five precipitation regions and four temperature regions. The analysis proves that both cumulus and PBL schemes have a crucial impact on the description of precipitation in Andalusia, whereas no noticeable differences between microphysics options were appreciated. Temperature is described similarly by all the configurations, except for the PBL choice affecting minimum values. WRF provides a definite improvement over ERA-40 in the climate description in terms of frequency, spatial distribution, and intensity of extreme events. It also captures more accurately the annual cycle and reduces the biases and the RMSE for monthly precipitation, whereas only a minor enhancement of these features was obtained for monthly-mean maximum and minimum temperatures. The results indicate that WRF is able to correctly reproduce Andalusian climate and produces useful added-value information for climate studies. Show less