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Spatiotemporal Characteristics and Propagation of Summer Extreme Precipitation Events Over United States: A Complex Network Analysis
Author(s) -
Mondal Somnath,
Mishra Ashok Kumar,
Leung L. Ruby
Publication year - 2020
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2020gl088185
Subject(s) - complex network , betweenness centrality , burstiness , clustering coefficient , environmental science , extreme value theory , precipitation , topology (electrical circuits) , centrality , statistical physics , meteorology , cluster analysis , computer science , geography , mathematics , physics , statistics , artificial intelligence , computer network , combinatorics , network packet , world wide web
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.