Comparison of Simulated Warm-Rain Microphysical Processes in a Record-Breaking Rainfall Event Using Polarimetric Radar Observations

During 6-7 May 2017, a record-breaking nocturnal rainfall event occurred in Guangzhou, China, and it was a typical warm-sector heavy rainfall event under weak synoptic forcing. A prior observational study by the authors revealed that warm-rain microphysical processes were dominant and responsible for the record-breaking precipitation. In this study, the double-moment Morrison, Thompson and NSSL microphysics schemes in WRF are evaluated against polarimetric radar observations in their ability of reproducing observed microphysical characteristics. The Thompson scheme shows the greatest fidelity to the observed raindrop size distribution (RSD) median value, corresponding to the most amount of precipitation forecast. While the Morrison and NSSL simulations overestimate (underestimate) the raindrop size (number concentration), exhibiting continental-type convective precipitation. The three experiments slightly overestimate differential reflectivity (ZDR), but significantly underestimate specific differential phase (KDP) and liquid water content by about 30%-50%, implying the undervaluation of number of medium-sized raindrops. Examinations of the occurrence frequencies of ZDR, KDP, mass-weighted diameter, and logarithmic normalized intercept parameter for rain suggest that all three schemes fail to reproduce the full variability of observed RSD for the extreme rainfall. The vertical variations of RSD parameters and the Kumjian-Ryzhkov parameter space suggest that the collision-coalescence is the dominant warm-rain microphysical process but the simulated process is too weak. This may be attributed to the misrepresented RSD near the melting layer, where the raindrops with lower number concentration and larger sizes cannot grow through the collision-coalescence process as actively. Extreme rainfall is of great concern due to its potential to cause major disasters. Cloud microphysics has been considered one of the main sources of uncertainty in predicting rainfall at cloud-resolving resolutions. This study investigates the performances of three commonly used schemes representing cloud precipitation processes in an extreme rainfall case that occurred in the warm and moist environment of South China. The Thompson scheme is found to perform better in simulating raindrop sizes and surface precipitation. None of the three schemes reproduces the full variation of observed raindrops, and all of them underestimate raindrop size growth through collision processes. These results suggest areas needing improvement in microphysics schemes for predicting extreme precipitation in sub-tropical regions. Thompson scheme better reproduces raindrop median size and number concentration than two other schemes in a Guangzhou extreme rain eventNone of the three schemes examined adequately predicts the full variability of raindrop size distribution important for extreme rainfallLow raindrop concentration and excessively large sizes in simulations jointly cause the too weak collision-coalescence processes