The effects of the initial cloud condensation nuclei (CCN) concentrations (100-3000 mg-1) on hail properties were investigated in an idealized non-severe hail storm experiment using the Weather Research and Forecasting (WRF) model, with the National Severe Storms Laboratory 2-moment microphysics scheme. The initial CCN concentration (CCNC) had obvious non-monotonic effects on the mixing ratio, number concentrations, and radius of hail, both in clouds and at the surface, with a CCNC threshold between 300 and 500 mg-1. An increasing CCNC is conducive (suppressive) to the amount of surface hail precipitation below (above) the CCNC threshold. The non-monotonic effects were due to both the thermodynamics and microphysics. Below the CCNC threshold, the mixing ratios with the increasing CCNC, resulting in more latent heat released of cloud droplets and ice crystals increased dramatically from condensation and frozen between 4 and 8 km and intensified updraft volume. The extent of the riming process, which is the primary process for hail production, increased dramatically. Above the CCNC threshold, the mixing ratio of cloud droplets and ice crystals increased continuously, but the maximum updraft volume was weakened because of reduced frozen latent heating at low level. The smaller ice crystals reduced the formation of hail and smaller clouds, with decreased rain water reducing riming efficiency so that graupel and hail also decreased with increasing CCNC, which is unfavorable for hail growth.
This study explores for the first time the impact of assimilating radial velocity(Vr)observations from a single or multiple Taiwan's coastal radars on tropical cyclone(TC)forecasting after landfall in the Chinese mainland by using a Weather Research and Forecasting model(WRF)-based ensemble Kalman filter(EnKF)data assimilation system.Typhoon Morakot(2009),which caused widespread damage in the southeastern coastal regions of the mainland after devastating Taiwan,was chosen as a case study.The results showed that assimilating Taiwan's radar Vr data improved environmental field and steering flow and produced a more realistic TC position and structure in the final EnKF cycling analysis.Thus,the subsequent TC track and rainfall forecasts in southeastern China were improved.In addition,better observations of the TC inner core by Taiwan's radar was a primary factor in improving TC rainfall forecast in the Chinese mainland.