An evaluation of the WRF physical parameterizations for extreme rainfall simulation in the Yangtze River Middle Reaches Urban Agglomeration

Abstract

With the increase in extreme precipitation events, the need for accurate and reliable extreme precipitation forecasting systems has become increasingly urgent. This study evaluates the performance of various physical parameterization schemes within the Weather Research and Forecasting (WRF) model for forecasting extreme precipitation in the Yangtze River Middle Reaches Urban Agglomeration (YRMRUA). Three assessment methods were employed: Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Method for Object-based Diagnostic Evaluation (MODE), and Structure-Amplitude-Location (SAL) to assess four microphysics (MP) schemes and three cumulus parameterization (CP) schemes. The results indicate that for large-scale weather system event, the Lin (KF + EC) scheme performs the best, while for small-scale weather system event, the WSM6 (MSKF+EC) scheme is more effective. For MP schemes, Single-moment MP schemes are generally superior to double-moment MP schemes. For CP schemes, when the inner domain is within the gray resolution range, explicit convection is more effective. In the outer domain, the KF scheme shows better simulation performance for large-scale event, while the MSKF scheme performs better for small-scale event. These findings contribute to better simulation of extreme precipitation in the YRMRUA and serve a reference for generating numerical precipitation forecast ensembles with the WRF model.