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Journal Article

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

Authors

Banerjee,  Abhirup
External Organizations;

/persons/resource/mkemter

Kemter,  Matthias
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Goswami,  Bedartha
External Organizations;

/persons/resource/bmerz

Merz,  B.
4.4 Hydrology, 4.0 Geosystems, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Kurths,  Jürgen
External Organizations;

Marwan,  Norbert
External Organizations;

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Fulltext (public)

5015831.pdf
(Publisher version), 2MB

Supplementary Material (public)
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Citation

Banerjee, A., Kemter, M., Goswami, B., Merz, B., Kurths, J., Marwan, N. (2023): Spatial coherence patterns of extreme winter precipitation in the U.S. - Theoretical and Applied Climatology, 152, 385-395.
https://doi.org/10.1007/s00704-023-04393-5


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5015831
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.