Spatial coherence patterns of extreme winter precipitation in the U.S.

Abstract

Extreme precipitation events have a significant impact on life and property. The U.S. experiences huge economic losses due to severe floods caused by extreme precipitation. With the complex terrain of the region, 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 between two event series. Using network measures, namely, degree and betweenness centrality, we are able to identify the specific regions affected by the landfall of atmospheric rivers in addition to those 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 U.S. due to various climate processes despite its vast, complex topography.

Explaining the Mechanism of Multiscale Groundwater Drought Events: A New Perspective From Interpretable Deep Learning Model

“…These inferences are evident from Figure 9, which shows that the fractions of contributions from precipitation characteristics of states are mostly below 0.5, and the fractions are mostly larger than 0.5 for catchments. At the same time, as most catchments are located in the coastal areas of the South Atlantic‐Gulf Region, their climate patterns exhibit characteristics of concurrent hot and rainy seasons (Banerjee et al., 2023; Portmann et al., 2009). Consequently, there are seasonal discrepancies in the causes of groundwater droughts at the catchment scale: as shown in Figure 10, although temperatures are high in summer, precipitation is also substantial.…”

Time persistence of climate and carbon flux networks

“…Numerous studies have explored climate networks. For instance, constructing climate networks based on extreme winter precipitation in the United States enabled to identify regions of extreme precipitation and the climatic conditions that lead to extreme precipitation [16]. In Ref.…”

“…In Ref. [16] climate variables have been used to study the critical thresholds of climate change and provide early warning signals [17][18][19][20]. Moreover, integrating climate network methods have been applied to identify and measure the optimal paths that yield the interaction between pairs of remote nodes, i.e., teleconnections [21].…”