Impacts of Different Physical Parameterization Configurations on Widespread Heavy Rain Forecast over the Northern Area of Vietnam in WRF-ARW Model

Abstract

This study investigates the impacts of different physical parameterization schemes in the Weather Research and Forecasting model with the ARW dynamical core (WRF-ARW model) on the forecasts of heavy rainfall over the northern part of Vietnam (Bac Bo area). Various physical model configurations generated from different typical cumulus, shortwave radiation, and boundary layer and from simple to complex cloud microphysics schemes are examined and verified for the cases of extreme heavy rainfall during 2012–2016. It is found that the most skilled forecasts come from the Kain–Fritsch (KF) scheme. However, relating to the different causes of the heavy rainfall events, the forecast cycles using the Betts–Miller–Janjic (BMJ) scheme show better skills for tropical cyclones or slowly moving surface low-pressure system situations compared to KF scheme experiments. Most of the sensitivities to KF scheme experiments are related to boundary layer schemes. Both configurations using KF or BMJ schemes show that more complex cloud microphysics schemes can also improve the heavy rain forecast with the WRF-ARW model for the Bac Bo area of Vietnam.