Assessing large-scale climate influences on U.S. tornado outbreaks and potential insurance industry applications
Elizondo, Antonio M
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https://hdl.handle.net/2142/121548
Description
Title
Assessing large-scale climate influences on U.S. tornado outbreaks and potential insurance industry applications
Author(s)
Elizondo, Antonio M
Issue Date
2023-07-21
Director of Research (if dissertation) or Advisor (if thesis)
Sriver, Ryan L
Committee Member(s)
Trapp, Robert J
Sime, Laura
Department of Study
Atmospheric Sciences
Discipline
Atmospheric Sciences
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Enso
Nao
Climate
Tornado Outbreak Events/days/months/risks
Insurance Loss/risk/applications
Language
eng
Abstract
Devastating tornado outbreak events are a serious risk for substantial insurance losses in the United States. Improved assessments of these event risks are vital for mitigating future losses. Here, we aim to improve these risk assessments by exploring the influences of two large- scale climate signals, consisting of ENSO (Niño 3.4 region) and NAO, on tornado outbreaks in the conterminous United States. Tornado outbreak event probabilities were derived from both climate signals via multiple statistical analyses and a machine learning predictive model. A combination of negative ENSO and positive NAO conditions generated the largest event probabilities. Additional kernel density estimate maps created from tornado outbreak events found the highest concentration of tornado records over the Southeastern United States. We then utilize our research results to explore practical insurance risk applications such as hazard model integration, exposure visualization, and reinsurance purchasing. These risk applications show real promise of making meaningful contributions toward solving this major insurance industry issue.
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