Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)

Abstract. Hail forecasting using numerical models remains a challenge due to the uncertainties and deficiencies in microphysics schemes. In this study, we assessed the hail simulation performance of the 2-moment Milbrandt-Yau (MY2) microphysics scheme within the Weather Research and Forecast (WRF) model by simulating three heavy rainfall events in Meiyu systems in which hail was rarely observed, rather than focusing on hail cases as done in previous researches. Simulation results showed that MY2 scheme produced noticeable hail in these rainstorms. Further analysis revealed that the overprediction of hail was caused by the imperfect graupel-to-hail conversion parameterization method adopted in the MY2 scheme. By incorporating the graupel spongy wet growth process, the modified scheme significantly mitigated the hail overforecasting. Moreover, the modified MY2 scheme kept the ability to simulate hail in real hail cases, demonstrating its ability to differentiate between heavy rainfall and hail events—a distinction the original scheme lacked. By comparing simulations of both rainstorms and hailstorms, it is concluded that the upward transport of large raindrops near the 0 °C level is critical for the graupel-to-hail conversion.