Abstract:

Regarding the forecasting errors of operational models for the high-impact extremely heavy rainfall event in Beijing on July 21, 2012, this work examines the impact of assimilating surface and rawinsonde observations using EnKF data assimilation system on the simulation of rainfall distribution and the surface features in the initiation period of the rainfall in Beijing, and reveals the possible reasons for the forecasting errors. Results show that data assimilation significantly improves the simulation of rainfall distribution, confirming that the cyclonic vortex is the key influencing system of the heavy rainfall event, which was proposed by previous researchers based on observations and sensitivity analyses. This work also reveals that the surface low and its associated inverted trough are the direct producers of the rainfall in Beijing. These results indicate that the reason of the failure of the operational models in this extremely heavy rainfall is the large forecasting errors in the strength and location of the cyclonic vortex and the associated inverted trough eastward of the surface low.

Key words: 7·21 heavy rainfall, cyclonic vortex, inverted trough, extremely heavy rainfall, Beijing

摘要：

针对2012年7月21日北京极端暴雨的业务预报误差, 详细地考察地面和探空资料的EnKF同化对7·21极端暴雨总体时空分布和暴雨触发地面特征模拟的影响, 进而揭示预报误差的可能原因。结果表明, 资料同化显著地改善了北京地区降水时空分布的模拟结果, 证实了前人基于观测和敏感性分析提出的“低涡是北京7·21暴雨的关键影响系统”的判断, 揭示出低涡对应的地面低压东侧倒槽对北京7·21暴雨的直接贡献。研究结果显示, 业务数值模式对此次极端暴雨预报失败的主要原因可能是对低涡和低涡对应的地面低压东侧倒槽强度和位置有较大的预报误差。

关键词: 7·21暴雨, 低涡, 倒槽, 极端暴雨, 北京