Spatial Coherence Patterns of Extreme Winter Precipitation In The United States

Abstract

Extreme precipitation events have a significant impact on life and property. The United States experiences huge economic losses due to severe floods caused by extreme precipitation. With the varied terrain, it becomes increasingly important to understand the spatial variability of extreme precipitation to conduct a proper risk assessment of natural hazards such as floods. In this work, we use a complex network based approach to identify distinct regions exhibiting spatially coherent precipitation patterns due to various underlying climate mechanisms. To quantify interactions between event series of different locations, we use a nonlinear similarity measure, called the edit-distance method, which considers not only the occurrence of the extreme events but also their intensity while measuring similarity. Using network measures, namely, degree and betweenness centrality, we are able to identify the specific regions affected by landfall of atmospheric rivers in addition to those regions where the extreme precipitation due to storm track activity is modulated by different mountain ranges such as the Rockies and the Appalachians. Our approach provides a comprehensive picture of the spatial patterns of extreme winter precipitation in the United States due to various climate processes despite its vast complex topography