Spatial extreme value analysis to project extremes of large-scale indicators for severe weather

Concurrently high values of the maximum potential wind speed of updrafts (Wmax) and 0–6 km wind shear (Shear) have been found to represent conducive environments for severe weather, which subsequently provides a way to study severe weather in future climates. Here, we employ a model for the product of these variables (WmSh) from the National Center for Atmospheric Research/United States National Center for Environmental Prediction reanalysis over North America conditioned on their having extreme energy in the spatial field in order to project the predominant spatial patterns of WmSh. The approach is based on the Heffernan and Tawn conditional extreme value model. Results suggest that this technique estimates the spatial behavior of WmSh well, which allows for exploring possible changes in the patterns over time. While the model enables a method for inferring the uncertainty in the patterns, such analysis is difficult with the currently available inference approach. A variation of the method is also explored to investigate how this type of model might be used to qualitatively understand how the spatial patterns of WmSh correspond to extreme river flow events. A case study for river flows from three rivers in northwestern Tennessee is studied, and it is found that advection of WmSh from the Gulf of Mexico prevails while elsewhere, WmSh is generally very low during such extreme events.

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Copyright 2013 The Authors. Environmetrics published by JohnWiley & Sons, Ltd.


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Author Gilleland, Eric
Brown, Barbara G.
Ammann, Caspar
Publisher UCAR/NCAR - Library
Publication Date 2013-09-01T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2025-07-12T01:16:47.804579
Metadata Record Identifier edu.ucar.opensky::articles:18211
Metadata Language eng; USA
Suggested Citation Gilleland, Eric, Brown, Barbara G., Ammann, Caspar. (2013). Spatial extreme value analysis to project extremes of large-scale indicators for severe weather. UCAR/NCAR - Library. https://n2t.org/ark:/85065/d7765gwq. Accessed 01 August 2025.

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