عنوان مقاله [English]
Providing accurate weather forecasts can help society better prepare. Regional climate models have been widely applied locally as a robust forecast and monitoring tool for extreme weather events. This study assesses the performance of the Weather Research and Forecasting (WRF) model in simulating different heavy precipitation events across Isfahan province. For this, WRF parametrisation was established considering different versions of the microphysics, planetary boundary layer (PBL), Short and long wavelength radiation, surface layer and convection scheme. The model was implemented in two nests of 12 and 4 km, using the GDAS-FNL reanalysis data as initial and boundary conditions for 17 extreme rainfall events in 2011-2018 and with different combinations of the schemes as mentioned. The observations of daily precipitation records from 77 rain gauge stations were applied to validate the WRF output. Finally, several statistical goodness-of-fit measures and spatial and temporal precipitation distributions were used for evaluating WRF performance. The result showed that the appropriate physical scheme for the parameterisation of short and long-wavelength radiation and surface layer could increase the performance of precipitation forecasts in the 4 km grid (high resolution), Although microphysics was more crucial than other parameterisations. In Isfahan province, Revised Monin-Obokhov, Dudhia, RRTMG, NSSL, TiedTKE, and BouLac schemes for parametrisation of surface layer, short and long wavelength radiation, microphysics, convection, and planetary boundary layer, respectively, performed better in simulating precipitation. Therefore, This optimal combination of parameterisations is suggested for further studies with the aim of precipitation forecasting and using them in flood forecast systems.