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Statistical Models for Tornado Climatology: Long and Short-Term Views.

James B Elsner1, Thomas H Jagger1, Tyler Fricker1

  • 1Department of Geography, Florida State University, Tallahassee, Florida, United States of America.

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Summary
This summary is machine-generated.

This study models tornado risk using historical data, identifying key U.S. tornado corridors and how risk shifts with climate factors like El Niño. It provides updated tornado risk assessments for various users.

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Area of Science:

  • Atmospheric Science and Meteorology
  • Statistical Modeling
  • Geospatial Analysis

Background:

  • Accurate estimation of regional tornado risk is crucial for public safety and disaster preparedness.
  • Previous risk assessments may not fully account for historical data biases or dynamic climate influences.

Purpose of the Study:

  • To estimate long-term and short-term regional tornado risk using statistical models and historical event data.
  • To identify major U.S. tornado corridors and assess the impact of climate variability on tornado activity.
  • To provide updated tornado risk insights for government agencies, insurers, and the public.

Main Methods:

  • A spatial statistical model was applied to county-aggregated tornado counts, adjusting for observational changes over time.
  • A space-time statistical model was used with raster-aggregated tornado counts, incorporating climate factors.
  • Model validation involved predicting tornado rates by excluding the target year from the training data.

Main Results:

  • Identified U.S. tornado corridors with expected annual rates exceeding two tornadoes per 10,000 sq km, with some areas in Texas and Kansas exceeding four.
  • Analysis revealed a southward and eastward shift in high-risk areas when weaker tornadoes (EF0) were excluded.
  • Short-term risk assessment showed shifts in tornado activity away from the Ohio Valley during El Niño and the Southeast during positive North Atlantic Oscillation conditions.

Conclusions:

  • The developed statistical models offer state-of-the-art, dynamic views of regional tornado risk.
  • Findings highlight the importance of considering both long-term trends and climate-driven short-term variations in tornado risk assessment.
  • The results are valuable for informing policy, insurance decisions, and public awareness regarding tornado hazards.