Impact of Prognostic Graupel Density on Simulated Precipitating Convections

Ice particles in cloud microphysics schemes are traditionally categorized as ice crystals, snow, graupel, and/or hail. Each category is defined by static parameters that determine density, diameter-mass relationship, and diameter-fall speed relationship. Several previous studies have reported considerable sensitivity in simulated precipitation systems based on these fixed parameters. This study introduces a prognostic approach for graupel density in the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) microphysics scheme, based on the work of Milbrandt and Morrison (2013). This allows graupel density to vary from 100 to 900 [kg/m3]. The modified WDM6 is tested for idealized squall line and winter snowfall cases over the Korean Peninsula. In the idealized squall line case, simulation results reveal variant graupel density in time and space, according to the evolution of squall line. For winter snowfall cases, simulations using the modified WDM6 show improved statistical skill scores, such as the root mean square error and bias, compared to the original WDM6, mitigating the positive precipitation bias simulated in the original WDM6. The modified WDM6 increases surface graupel amounts and decreases graupel suspended in the atmosphere due to faster sedimentation of graupel. Therefore, the major microphysical processes that generate graupel are influenced, subsequently reducing surface snow and precipitation over mountainous regions. Importantly, the modified WDM6 adeptly captures the relationship between graupel density and fall velocity, as verified by 2D video disdrometer measurements. *This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (grant no. RS-2023-00272751).