STATISTICAL MODELS FOR PREDICTING TORNADO RATES: CASE STUDIES FROM OKLAHOMA AND THE MID SOUTH USA
Free (open access)
Volume 6 (2016), Issue 1
1 - 9
JAMES B. ELSNER, TYLER FRICKER, THOMAS H. JAGGER, & VICTOR MESEV
The destructive impact tornadoes have on communities has sparked interest in predicting the risk of impacts on seasonal time scales. Here, the authors demonstrate how to build statistical models for predicting tornado rates. They test the models with tornado counts accumulated over a 45-year period aggregated to counties in the State of Oklahoma and to cells in a latitude/longitude grid across a large portion of south central United States. The spatial model provides a fit to the counts, which includes terms for the spatial correlation and the population effect. A space-time model not only provides a similar fit to annual counts but also includes a term for a time-varying climate factor. This work contributes to methods for forecasting severe convective storms on the seasonal time scale.
climate, risk prediction, space-time model, statistical model, tornadoes