Complex network (CN) is a graph theory‐based depiction of relation shared by various elements of a complex dynamical system such as the atmosphere. Here we apply the concept of CN to understand the directionality and topological structure of summer extreme precipitation events (SEPEs) over the conterminous United States (CONUS). The SEPEs are calculated based on the 95th percentile daily rainfall at 0.5° × 0.5° spatial resolution for CONUS to investigate the multidimensional characteristics of precipitation extremes. The derived CN coefficients (e.g., betweenness centrality, clustering coefficient, orientation, and network divergence) reveal important structural and dynamical information about the topology of the SEPEs and improve understanding of the dominant meteorological patterns. The initiation and propagation of SEPEs from the source zones to the sink zones are identified. The SEPEs are influenced by topography, dominant wind patterns, and moisture sources in terms of their topological structure and spatial dynamics.

中文翻译：

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美国夏季极端降水事件的时空特征和传播：复杂网络分析

复杂网络（CN）是基于图论的关系描述，它由复杂动力系统的各种元素（如大气）共享。在这里，我们使用CN的概念来了解美国本土（CONUS）上夏季极端降水事件（SEPE）的方向性和拓扑结构。SEPE是根据空间分辨率为0.5°×0.5°的第95个百分位日降水量计算得出的，以调查CONUS极端降水的多维特征。导出的CN系数（例如，中间度，聚类系数，方向和网络差异）揭示了关于SEPE拓扑的重要结构和动态信息，并增强了对主要气象模式的理解。识别SEPE从源区到汇区的启动和传播。SEPE受其拓扑结构和空间动力学的影响，受地形，主导风型和湿气源的影响。