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Modeling and Forecasting

A Brief Overview
George Pararas-Carayannis

Tornadoes strike usually in areas known to have sustained damage in the past. However, over long periods of time there is significant variability in their climatology (McCormick, 2000). Tornado forecasts and warnings are usually issued on a short-term basis since they involve rapidly developing weather subsystems which are difficult to forecast.

Mathematical modeling has become essential in understanding the dynamics of storm formation and other associated hazards. However, forecasting the precise locations where tornadoes may touch down is a very difficult task.

Recurrence period for F2 or greater tornadoes in thousands of years based on Monte Carlo simulations (After Meyer et al. 2005).

The use of tornado modeling has become essential in risk analysis and hazard mitigation (Schaefer et al, 1986). Knowing where approximately the tornado may strike and its probable intensity, individuals and businesses can be better prepared for significant events - tornadoes with a designation of F2 or greater on the internationally adopted Fujita intensity scale (Brooks and Doswell, 2001). Officials in areas with large populations can develop better plans for preparedness. With advance forecasts provided by tornado models, damages, injuries and deaths can be reduced significantly.

Thus, mathematical techniques are integral part in weather prediction and a prerequisite in tracking the creation of severe storms that can generate tornadoes. Fortunately, the advent of new computer technology, Doppler radar imagery and synoptic observations - made possible by remote sensing and satellite imagery - have greatly facilitated the use of numerical tornado models and the understanding of the physics of the hazard and its potential long and short term risks (Brooks and Kay, 2001). Also, a statistically significant historical database of about 10,000 tornadoes has been compiled for a 75-year period from 1921 to 1995 (Grazulis, 1993). This database has been augmented and has helped establish good climatology for this hazard (Doswell and Burgess, 1988; Kelly et al., 1978).

The database includes, path lengths and widths and Fujita intensity scale designations ranging from F0 to F5. Violent tornadoes are those classified F2 and greater. Through the use of numerical models, tornado occurrence, location, path length, path width, and Fujita scale of intensity can be determined (Concannon et al., 2000). In fact, using the historical database, models were developed to determine specific patterns of recurrence and spatial variability of intensity for different regions in the United States (Schaefer et al., 1986). Similar models - extrapolated statistically from the known historical data – have helped to establish long-term patterns and to analyze for variability between different time periods and thus establish overall risks and future impacts. The model used for this purpose has been the Monte Carlo Model, which essentially provides a statistical approach to the long-term, risk analysis of the tornado hazard (Meyer et al. 2005)(See figure on tornado recurrence periods).

Reliability of Tornado Numerical Modeling: As mentioned, numerical models can help forecast in advance the overall timing and structure of storms that can generate tornadoes. Such modeling has become an indispensable tool in assessing the overall risk from tornadoes. However, since tornadoes are rapidly and ever-changing dynamic systems, it is difficult to model them in real time and forecast exactly when or where they will touch down. To this day no mathematical model has been capable of forecasting a specific tornado or where it is more likely to strike.


Brooks, H. E., and C. A. Doswell III, 2001. “Some aspects of the international climatology of tornadoes by damage classification”. Atmos. Res., 56, 191-201.
Concannon, P.R., H.E. Brooks, C.A. Doswell III, 2000. “Climatological risk of strong and violent tornadoes in the United States”. Preprints, 2nd Conf. On Environmental Applications , Amer. Meteor. Soc., Long Beach, California. American Meteorological Society, 212-219.
Doswell, C.A. III, and D.W. Burgess, 1988. “On some issues of the United States tornado climatology”. Mon. Wea. Rev., 116, 495-501.
Grazulis, T.P., 1993. “Significant Tornadoes, 1680-1995”. Environmental Films, St. Johnsbury, VT, 1326 pp.
IPCC, 2001. “Climate Change 2001: The Scientific Basis- Contribution of Working Group I to the IPCC Third Assessment Report”. Cambridge Univ. Press, 881 pp.
Kelly, D.L., J.T. Schaefer, R.P. McNulty, C.A. Doswell III, 1978. “An augmented tornado climatology”. Mon. Wea. Rev., 106, 1172-1183.
McCormick, T.L., 2000. “Variability of significant tornado climatology in the United States. Research Experience for Undergraduates” (Available from NSSL).
Meyer Cathryn L., Brooks, Harold E. and Michael P. Kay, 2005. “A HAZARD MODEL FOR TORNADO OCCURRENCE IN THE UNITED STATES 2005” Internet publication.
Schaefer, J.T., D.L. Kelly, R.F. Abbey, 1986. “A minimum assumption tornado-hazard probability model”. Journal of Climate and Applied Meteorology, 25, 1934-1945.

Wilks, D.S., 1995: “Statistical Methods in the Atmospheric Sciences”. Academic Press, Inc., 467 pp.





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Web Design by Dr. Carolyn Carayannis Copyright 2008 / all rights reserved. © Copyright 1963-2007 George Pararas-Carayannis / all rights reserved / Information on this site is for viewing and personal information only - protected by copyright. Any unauthorized use or reproduction of material from this site without written permission is prohibited. Material included at the website links above is for informative and educational purposes and for disaster preparedness only. Any predictions of large earthquakes, destructive tsunamis, or any other natural disasters presented in these pages are based primarily on statistical determinations of the historical recurrence frequencies of such events. Such historical/statistical approaches are used only for long-term predictions. There is no intent by the author to predict or forecast any type of natural disaster or to frighten people.