Forecasts of the Warm-Sector Heavy Rainfall With a Warm Shear Pattern Over Coastal Areas of the Yangtze–Huaihe River in a Regional Business Forecast Model - Zhang, Ling; Song, Liuxian; Zhu, Shoupeng; Guo, Zhun; Wang, Hongbin; Zhou, Linyi; Chen, Chaohui; Zhi, Xiefei (Frontiers in Earth Science, 2022)
Based on the observational hourly precipitation data and the ERA5 reanalysis datasets, the short-term forecasts of the Warm-sector heavy Rainfall with Warm type Shear line (WRWS) events over the coastal areas of Yangtze-Huaihe River (YHR) are investigated in the regional business model Precision Weather Analysis and Forecasting System (PWAFS). Evaluations and diagnoses are carried out via objective estimations and composition analyses for the rainy season of 2017. Results show that the short-term forecasts of PWAFS are characterized by considerable skills for WRWS events in the coastal areas of YHR in view of the object-based diagnostic evaluation, which, however, tend to generate the rain belts with northeast shift phases and weaker intensities. Meanwhile, the threat score results for WRWS associated processes show that the model forecasting skill declines sharply as the precipitation intensity increases. Besides, composition differences of the synoptic-scale thermodynamic characteristics between observations and forecast results are diagnosed to reveal the possible mechanisms of the short-term forecast biases towards WRWS. The zonal westerlies are overestimated in the model, while the southerlies are underestimated in the lower troposphere over coastal areas of YHR, leading to the northeastward shifted shear line and the absent moisture channel associated with East China Sea at the boundary layer. Attributed to these atmospheric circulation biases, the accumulated warm and moist energy is weaker at the boundary layer, and hence, the short-term forecasts of the rain-belt location for WRWS over the YHR coastal area have northeast shifting phases with weaker intensities of precipitation in forecasts of the regional business model PWAFS.