华北、黄淮极端雨强多尺度过程和物理模型

Multi-scale process and physical model of extreme rainfall intensity in North China-Huanghuai region

  • 摘要: 近些年华北、黄淮地区极端强降水事件频繁发生,如具有代表性的“21·7”河南暴雨与“23·7”京津冀暴雨事件。回顾业务预报和机理分析研究,暴露出当前对极端雨强多尺度成因机制认知的不足,亟需开展系统研究。本文总结了近几年对华北、黄淮极端雨强的机理研究,系统梳理了极端雨强的时空分布特征、典型天气形势、中尺度对流系统演变以及微物理结构;通过结合多源观测与数值模拟数据补充既有研究,解析了涵盖天气尺度、中尺度至云微物理层面的多尺度物理过程。文中强调了不同尺度间的协同耦合作用,提出一种多尺度天气型识别方法,通过匹配从大尺度环流到中小尺度扰动的形势特征,显著提高了极端降水的识别;合成归纳出暖性型和深对流型两类典型极端雨强中尺度系统类型,明确其在雨滴谱特征与水凝物相态分布等微物理结构的主要差异。针对华北、黄淮地区的极端雨强构建了一个多尺度物理模型,深化了对极端雨强形成机制的认识,为提升极端雨强的天气分析、预报能力以及数值模式的物理过程表达提供了重要参考。

     

    Abstract: In recent years, extreme rainfall events such as the "21·7" Henan and "23·7" Beijing–Tianjin–Hebei storms have frequently impacted North China and the Huanghuai region. These events exposed significant gaps in our understanding of their physical mechanisms. This article summarizes recent researches on spatial-temporal features, synoptic patterns, mesoscale convective systems (MCSs), and microphysical structures of extreme rainfall. By combining multi-source observations and model simulations, the study highlights the multiscale processes—from large-scale circulation to microphysics—that jointly shape rainfall intensity. A multiscale pattern recognition method is proposed to improve the identification of extreme events. Two distinct MCS types—warm-type and deep-convective-type—are characterized, especially in terms of raindrop spectra and hydrometeor composition. A multiscale conceptual model tailored to North China is presented, offering insights to improve forecasting and model representation of extreme rainfall processes.

     

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