Forecasting U.S. Tornado Outbreak Activity and Associated Environments in the Global Ensemble Forecast System (GEFS) Weather and Forecasting

Tornado outbreaks are high-impact events, often causing significant loss of life and property. This study evaluated the forecast skill of U.S. tornado outbreak activity using the Global Ensemble Forecast System (GEFS), version 12, at lead times up to 2 weeks. Tornado outbreak activity is represented in GEFS using an outbreak index, which relates the likelihood of outbreak-level tornadoes to GEFS forecasts of convective precipitation (CP), storm-relative helicity (SRH), and convective available potential energy (CAPE). GEFS forecasts of the outbreak index are verified against smoothed Storm Prediction Center report data. Since the performance of the outbreak index depends on how well GEFS predicts the index constituents, we also evaluated the climatology and forecast skill of CP, SRH, and CAPE, as well as their covariability. We found that GEFS has a systematic low-CAPE bias and that the forecast skill of the outbreak index is most limited by GEFS forecast skill of CP. We corrected the low-CAPE bias and index seasonality errors via a seasonally and regionally dependent scaling of CAPE and the index, which improved the seasonal cycle and forecast skill of CAPE and tornado outbreak activity in GEFS. Overall, on average, GEFS has its highest forecast skill of tornado outbreak activity during winter and spring—in some cases, positive skill extends beyond week 1 forecast leads—and has its lowest forecast skill during summer. Grant no. NA19OAR4590159