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
 Elsner, J.B. & Widen, H.M., Predicting spring tornado activity in the central great plains by March 1st. Monthly Weather Review, 142, pp. 259–267, 2014. http://dx.doi.org/10.1175/MWR-D-13-00014.1
 Allen, J.T., Tippett, M.K. & Sobel, A.H., Influence of the El Nin˜o/Southern Oscillation on tornado and hail frequency in the United States. Nature Geosciences, 8, pp. 278–283, 2015. http://dx.doi.org/10.1038/ngeo2385
 King, P., On the absence of population bias in the tornado climatology of southwestern Ontario. Weather and Forecasting, 12, pp. 939–946, 1997.
 Ray, P.S., Bieringer, P., Niu, X. & Whissel, B., An improved estimate of tornado occurrence in the central plains of the United States. Monthly Weather Review, 131, pp. 1026–1031, 2003. http://dx.doi.org/10.1175/1520-0493(2003)131<1026:AIEOTO>2.0.CO;2
 Anderson, C.J., Wikle, C.K. & Zhou, Q., Population influences on tornado reports in the United States. Weather and Forecasting, 22, pp. 571–579, 2007.
 Brooks, H.E., Doswell, C.A. & Kay, M.P., Climatological estimates of local daily t ornado probability for the United States. Weather and Forecasting, 18, pp. 626–640, 2003.
 Dixon, P.G., Mercer, A.E., Choi, J. & Allen, J.S., Tornado risk analysis: is dixie alley an extension of tornado alley? Bulletin of the American Meteorological Society, 92, pp. 433–441, 2011. http://dx.doi.org/10.1175/2010BAMS3102.1
 Shafer, C.M. & Doswell, C.A., Using kernel density estimation to identify, rank, and classify severe weather outbreak events. Electronic Journal of Severe Storms Meteorology, 6, pp. 1–28, 2011.
 Doswell, C.A. & Burgess, D.W., On some issues of United States Tornado climatology.
Monthly Weather Review, 116, pp. 495–501, 1988. http://dx.doi.org/10.1175/1520-0493(1988)116<0495:OSIOUS>2.0.CO;2  Elsner, J.B., Michaels, L.E., Scheitlin, K.N. & Elsner, I.J., The decreasing population bias in tornado reports. Weather, Climate, and Society, 5, pp. 221–232, 2013.
 Doswell, C.A., Brooks, H.E. & Kay, M.P., Climatological estimates of daily local nontornadic severe thunderstorm probability for the United States. Weather and Forecasting, 20, pp. 577–595, 2005.
 Verbout, S.M., Brooks, H.E., Leslie, L.M. & Schultz, D.M., Evolution of the U.S.
tornado database: 1954-2003. Weather and Forecasting, 21, pp. 86–93, 2006. http://dx.doi.org/10.1175/WAF910.1
 Jagger, T.H., Elsner, J.B. & Widen, H.M., A statistical model for regional tornado climate studies. PLoS ONE, 10(8), p. e0131876, 2015.
 Elsner, J.B., Jagger, T.H. & Elsner, I.J., Tornado intensity estimated from damage path dimensions. PLoS ONE, 9(9), p. e107571, 2014.
 Besag, J., Statistical analysis of non-lattice data. Journal of the Royal Statistical Society:
Series D (The Statistician), 24, pp. 179–195, 1975. http://dx.doi.org/10.2307/2987782
 Rue, H., Martino, S. & Chopin, N., Approximate bayesian inference for latent G aussian models by using integrated nested Laplace approximations. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 71, pp. 319–392, 2009. http://dx.doi.org/10.1111/j.1467-9868.2008.00700.x
 Rue, H., Martino, S., Lindgren, F., Simpson, D., Riebler, A. & Krainski, E.T., INLA: Functions which allow to perform full Bayesian analysis of latent Gaussian models using Integrated Nested Laplace Approximaxion, 2014 + 0100). R package version 0.01417182342.
 Marzban, C. & Schaefer, J.T., The correlation between US tornadoes and Pacific sea surface temperatures. Monthly Weather Review, 129(4), pp. 884–895, 2001.
 Cook, A.R. & Schaefer, J.T., The relation of El Nin˜o-Southern Oscillation (ENSO) to winter tornado outbreaks. Monthly Weather Review, 136, pp. 3121–3137, 2008. http://dx.doi.org/10.1175/2007MWR2171.1
 Mun˜oz, E. & Enfield, D., The boreal spring variability of the Intra-Americas low-level jet and its relation with precipitation and tornadoes in the eastern United States. Climate Dynamics, 36(1–2), pp. 247–259, 2011.
 Lee, S.K., Atlas, R., Enfield, D., Wang, C. & Liu, H., Is there an optimal ENSO pattern that enhances large-scale atmospheric processes conducive to tornado outbreaks in the United States? Journal of Climate, 26, pp. 1626–1642, 2013. http://dx.doi.org/10.1175/JCLI-D-12-00128.1
 Hijmans, R.J., raster: Geographic Data Analysis and Modeling, 2015. R package version 2, pp. 4–18.
 Krishnamurthy, L., Vecchi, G.A., Msadek, R., Wittenberg, A., Delworth, T.L. & Zeng, F., The seasonality of the great plains low-level jet and ENSO relationship. Journal of Climate, 28, pp. 4525–4544, 2015. http://dx.doi.org/10.1175/JCLI-D-14-00590.1