With the increase in extreme precipitation events, the need for accurate and reliable extreme precipitation forecasting systems has become increasingly urgent. This study evaluates the performance of various physical parameterization schemes within the Weather Research and Forecasting (WRF) model for forecasting extreme precipitation in the Yangtze River Middle Reaches Urban Agglomeration (YRMRUA). Three assessment methods were employed: Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Method for Object-based Diagnostic Evaluation (MODE), and Structure-Amplitude-Location (SAL) to assess four microphysics (MP) schemes and three cumulus parameterization (CP) schemes. The results indicate that for large-scale weather system event, the Lin (KF + EC) scheme performs the best, while for small-scale weather system event, the WSM6 (MSKF+EC) scheme is more effective. For MP schemes, Single-moment MP schemes are generally superior to double-moment MP schemes. For CP schemes, when the inner domain is within the gray resolution range, explicit convection is more effective. In the outer domain, the KF scheme shows better simulation performance for large-scale event, while the MSKF scheme performs better for small-scale event. These findings contribute to better simulation of extreme precipitation in the YRMRUA and serve a reference for generating numerical precipitation forecast ensembles with the WRF model.

中文翻译：

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长江中游城市群极端降雨模拟的 WRF 物理参数化评价


随着极端降水事件的增加，对准确可靠的极端降水预报系统的需求变得越来越迫切。本研究评估了天气研究与预报 （WRF） 模型中各种物理参数化方案在预测长江中游城市群 （YRMRUA） 极端降水的性能。采用三种评估方法：按理想解相似性排序技术 （TOPSIS）、基于对象的诊断评估方法 （MODE） 和结构-振幅-位置 （SAL） 来评估四种微物理 （MP） 方案和三种积云参数化 （CP） 方案。结果表明，对于大尺度天气系统事件，Lin （KF + EC） 方案表现最好，而对于小尺度天气系统事件，WSM6 （MSKF+EC） 方案效果更好。对于 MP 方案，单矩 MP 方案通常优于双矩 MP 方案。对于 CP 方案，当内部域在灰度分辨率范围内时，显式对流更有效。在外域，KF 方案对大尺度事件表现出更好的模拟性能，而 MSKF 方案对小尺度事件表现出更好的模拟性能。这些发现有助于更好地模拟 YRMRUA 的极端降水，并为使用 WRF 模型生成数值降水预报集合提供参考。