Space-Time Extremes of Severe U.S. Thunderstorm Environments

Severe thunderstorms cause substantial economic and human losses in the United States. Simultaneous high values of convective available potential energy (CAPE) and storm relative helicity (SRH) are favorable to severe weather, and both they and the composite variable (Formula presented.) can be used as indicators of severe thunderstorm activity. Their extremal spatial dependence exhibits temporal non-stationarity due to seasonality and large-scale atmospheric signals such as El Niño-Southern Oscillation (ENSO). In order to investigate this, we introduce a space-time model based on a max-stable, Brown–Resnick, field whose range depends on ENSO and on time through a tensor product spline. We also propose a max-stability test based on empirical likelihood and the bootstrap. The marginal and dependence parameters must be estimated separately owing to the complexity of the model, and we develop a bootstrap-based model selection criterion that accounts for the marginal uncertainty when choosing the dependence model. In the case study, the out-sample performance of our model is good. We find that extremes of PROD, CAPE, and SRH are generally more localized in summer and, in some regions, less localized during El Niño and La Niña events, and give meteorological interpretations of these phenomena. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.

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Publication Details

Journal
Journal of the American Statistical Association
Published
2024-11-04
DOI
https://doi.org/10.1080/01621459.2024.2421582
Citations
2
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
0.75
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article

Space-Time Extremes of Severe U.S. Thunderstorm Environments

Erwan Koch, Jonathan Koh, A. C. Davison
2 citations
Journal of the American Statistical Association
Meteorological Phenomena and Simulations
0.75
article

Space-Time Extremes of Severe U.S. Thunderstorm Environments

Erwan Koch, Jonathan Koh, A. C. Davison
article en
2 citations

Abstract

Severe thunderstorms cause substantial economic and human losses in the United States. Simultaneous high values of convective available potential energy (CAPE) and storm relative helicity (SRH) are favorable to severe weather, and both they and the composite variable (Formula presented.) can be used as indicators of severe thunderstorm activity. Their extremal spatial dependence exhibits temporal non-stationarity due to seasonality and large-scale atmospheric signals such as El Niño-Southern Oscillation (ENSO). In order to investigate this, we introduce a space-time model based on a max-stable, Brown–Resnick, field whose range depends on ENSO and on time through a tensor product spline. We also propose a max-stability test based on empirical likelihood and the bootstrap. The marginal and dependence parameters must be estimated separately owing to the complexity of the model, and we develop a bootstrap-based model selection criterion that accounts for the marginal uncertainty when choosing the dependence model. In the case study, the out-sample performance of our model is good. We find that extremes of PROD, CAPE, and SRH are generally more localized in summer and, in some regions, less localized during El Niño and La Niña events, and give meteorological interpretations of these phenomena. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work.

Journal of the American Statistical AssociationVol. 120(550)
University of Bern (CH), Oeschger Centre for Climate Change Research (CH), Institute of Mathematics and Informatics (BG), Czech Academy of Sciences, Institute of Mathematics (CZ), Institute of Mathematical Statistics (US), École Polytechnique Fédérale de Lausanne (CH), University of Lausanne (CH)
Climate action
Openalex Percentile: Top 30%
Meteorological Phenomena and Simulations
0.75
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Space-Time Extremes of Severe U.S. Thunderstorm Environments — Erwan Koch, Jonathan Koh, et al. · Journal of the American Statistical Association (2024) | TGRS Research Map | TGRS