A Stochastic Statistical Model for U.S. Outbreak-Level Tornado Occurrence Based on the Large-Scale Environment

Tornado outbreaks — when multiple tornadoes occur within a short period of time — are rare yet impactful events. Here we developed a two-part U.S. tornado outbreak index. The first component produces a probability map for outbreak tornado occurrence based on spatially-resolved values of convective precipitation, storm relative helicity (SRH), and convective available potential energy. The second part of the index provides a probability distribution for the total number of tornadoes across the U.S. given the outbreak tornado probability map. Storm report data from the Storm Prediction Center is used to train the model and evaluate its performance. In the first component, the probability of an outbreak-level tornado is most sensitive to SRH changes. In the second component, the total number of CONUS tornadoes depends on the sum and grid point maximum of the probability map. Overall, this tornado outbreak index represents the climatology, seasonal cycle, and interannual variability of tornado outbreak activity well, particularly over regions and seasons when tornado outbreaks occur most often (e.g., during spring, over the Tennessee River Valley). We found that the El Niño-Southern Oscillation (ENSO) modulates the tornado outbreak index such that La Niña is associated with enhanced U.S. tornado outbreak activity over the Ohio River Valley and Tennessee River Valley regions during January through March, similar to the behavior seen in storm report data.