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A Statistical Model for Regional Tornado Climate Studies.

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A new statistical model smooths regional tornado climatology, revealing that increased population and terrain roughness correlate with higher tornado occurrences. Tornadoes are also increasing annually by 1.9% across Kansas.

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Area of Science:

  • Atmospheric Science
  • Climatology
  • Statistical Modeling

Background:

  • Tornado reports are often rare, clustered, and of variable quality, hindering accurate regional tornado climatology.
  • Directly using raw tornado data presents challenges for understanding large-scale tornado patterns.

Purpose of the Study:

  • To develop and demonstrate a statistical model for smoothed regional tornado climatology.
  • To investigate the relationship between terrain roughness, population, and tornado frequency.
  • To analyze tornado activity variations across different County Warning Areas (CWAs).

Main Methods:

  • Applied a statistical model to county-aggregated data, including annual population, tornado counts, and terrain roughness index.
  • Incorporated a term for smoothed frequency relative to state average.
  • Examined correlations between terrain roughness, population, and tornado occurrences, and differences by CWA.

Main Results:

  • Tornado reports increased by 13% for a two-fold population increase in Kansas, independent of rating improvements.
  • Tornadoes have been increasing annually by 1.9%.
  • Terrain roughness significantly impacts tornado frequency, with an 18% reduction in tornadoes per ten-meter increase in elevation standard deviation.
  • Counties served by DDC and GID CWAs showed a 51% higher likelihood of tornado occurrence.

Conclusions:

  • The statistical model effectively produces smoothed regional tornado climatology, overcoming limitations of raw data.
  • Terrain roughness and population are significant factors influencing tornado frequency.
  • Regional variations in tornado activity exist, potentially linked to factors like dryline climatology and specific CWAs.