Abstract
This paper estimates regional tornado risk from records of past events using statistical models. First, a spatial model is fit to the tornado counts aggregated in counties with terms that control for changes in observational practices over time. Results provide a long-term view of risk that delineates the main tornado corridors in the United States where the expected annual rate exceeds two tornadoes per 10,000 square km. A few counties in the Texas Panhandle and central Kansas have annual rates that exceed four tornadoes per 10,000 square km. Refitting the model after removing the least damaging tornadoes from the data (EF0) produces a similar map but with the greatest tornado risk shifted south and eastward. Second, a space-time model is fit to the counts aggregated in raster cells with terms that control for changes in climate factors. Results provide a short-term view of risk. The short-term view identifies a shift of tornado activity away from the Ohio Valley under El Niño conditions and away from the Southeast under positive North Atlantic oscillation conditions. The combined predictor effects on the local rates is quantified by fitting the model after leaving out the year to be predicted from the data. The models provide state-of-the-art views of tornado risk that can be used by government agencies, the insurance industry, and the general public.
Highlights
The purpose of this paper is to describe a strategy for the development of a comprehensive seasonal tornado risk assessment system
By specifying a ‘future’ year the long-term model predicts a distribution for the counts in each county
The color ramp is on a logarithmic scale so that each level of color saturation indicates a doubling of the occurrence rate
Summary
There remains no regularly issued forecasts of tornado activity months in advance despite demonstrated useful skill (accuracy above random guess) at predicting tornado activity prior to the start of the season [1] and initial forays into public dissemination of a forecast system [2]. The absence of routine seasonal tornado forecasts is due to large gaps in the understanding of how climate affects severe weather and to the limited methods to forecast activity on this time scale. Dynamical models are used as guidance to make seasonal forecasts of temperature and precipitation anomalies but tornadoes are too small to be resolved in them. Dynamical guidance on environmental conditions favorable for tornadoes is available out to about two weeks [3] though there is a high false alarm rate on the predictions with increasing lead time.
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