Severe thunderstorm modeling is becoming increasingly routine as insurers realize that using historical claims data alone is not sufficient for managing this complex risk. As with all catastrophe models, severe thunderstorm models are largely based on historical data, in this case, the frequency and intensity of the individual events (hailstorms, tornadoes, and straight-line winds) that comprise a severe thunderstorm outbreak.

The Storm Prediction Center (SPC) at NOAA has collected this data in the form of event reports called in by local authorities, trained weather spotters, and the general public dating back to the 1950s. However, the data contains reporting biases, i.e., underreporting of events in some locales and overreporting in others. A few culprits include non-uniform population distribution (events in sparsely populated regions are more likely to go unnoticed), better radar detection technology in more recent years, and even the increased interest in amateur storm chasing following the 1996 blockbuster hit, Twister.

These biases must be addressed in order to develop a severe thunderstorm model that provides full spatial coverage of simulated events throughout the United States. In other words, relying on data of where events have been known to occur in the past may not provide a complete picture of where they're likely to occur in the future.