Assessing the effects of Physical Parametrization of the WRF Model in Simulating Flood-Inducing Rainfall in Arid and Semi-Arid Areas (Case Study: Isfahan Province)

Extreme weather events are significantly more frequent in the past decades due to global warming. While preventing these events from happening is impossible, providing accurate weather forecasts can help the society to be better prepared for them. 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. The daily precipitation observational 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 to evaluate 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), the microphysics was nontheless more crucial than other parameterisations. In Isfahan province, the Revised Monin-Obokhov, Dudhia, RRTMG, NSSL, TiedTKE, and BouLac schemes performed better in simulating precipitation respectively for parametrisation of surface layer, short and long wavelength radiation, microphysics, convection, and planetary boundary layer. Therefore, This optimal combination of parameterisations is suggested for further studies with the aim of precipitation forecasting and using them in flood forecast systems.