Precipitation of Weak Tropical Cyclone Mulan (2022): Sensitivity to Cumulus and Microphysics Parameterization Schemes

Abstract

Previous studies on precipitation caused by tropical cyclones (TCs) have largely focused on strong TCs while systematic research on weak systems remains limited. This study utilized the high-resolution (3 km) weather research and forecasting (WRF) model to investigate the sensitivity of heavy precipitation generated by weak TC Mulan (2022) over the South China Sea to cumulus and microphysics parameterization schemes. Six cumulus parameterizations and five microphysics schemes were configured with simulations validated against gauge observations. Results indicated that cumulus parameterizations had a significant influence on precipitation simulation while the microphysics schemes exhibited a relatively minor impact in this case. The combination of the New Tiedtke cumulus scheme and the WRF Single-Moment 6-class (WSM6) microphysics scheme yielded the best simulation of precipitation compared with the observations. Further investigation revealed that cumulus parameterizations modulated simulated large-scale circulation, moisture transportation, and vertical velocities. The New Tiedtke scheme reproduced a more northward TC track and an intensified southeast jet along the coast of Southeast China, aligning with the observed heavy precipitation zones and providing favorable dynamic and thermodynamic conditions for precipitation. In contrast, the Betts-Miller-Janjić (BMJ) scheme resolved cloud-environment interactions inadequately, resulting in excessive convection and latent heating, which amplified cumulus precipitation compared to the New Tiedtke scheme. Among the cumulus parameterization schemes, the Kain-Fritsch (KF) and BMJ schemes underperformed due to their overestimation of deep convection while the New Tiedtke and Multi-scale KF (MSKF) schemes showed better performance. This study provides a valuable reference for further precipitation prediction research in the study region and adjacent areas.