Impact of Predicted Graupel Density in Cloud Microphysics Schemes on Winter Precipitation Simulations

The Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) scheme was modified by incorporating a predicted graupel density approach to better represent graupel characteristics. This study assessed the impact of this modification on simulated winter precipitation during the International Collaborative Experiment for Pyeongchang Olympics and Paralympics (ICE-POP 2018). The graupel density was varied within a range of 100-900 kg m^-3, allowing the mass-diameter and fall velocity-diameter relationships of graupel to adjust accordingly. The revised WDM6 scheme resulted in increased surface graupel and a reduced atmospheric graupel mass mixing ratio due to enhanced sedimentation. These modifications mitigated the positive precipitation bias observed in the original WDM6, particularly over mountainous regions, and improved statistical skill scores for root mean square error (RMSE) and bias. Comparison with 2D video disdrometer data confirmed that the revised WDM6 more accurately simulates the graupel density-fall velocity relationship compared to the original scheme. Additionally, the simulated degree of riming was compared with observations from a multi-angle snowflake camera. The revised WDM6 successfully captured two distinct riming peaks at 06 UTC and 12 UTC on March 8, whereas the original WDM6 missed the latter peak. Further investigation into the effects of predicted graupel density on simulated winter precipitation was conducted using the Predicted Particle Properties (P3) and bin-type microphysics schemes. Overall, the cloud microphysics scheme with predicted graupel density effectively captured observed riming peaks during snowfall events.