Characterizing severe weather potential in synoptically weakly forced thunderstorm environments

Authors: Paul Miller*, University of Georgia
Topics: Climatology and Meteorology, Hazards, Risks, and Disasters, Physical Geography
Keywords: weakly forced thunderstorms, pulse thunderstorms, storm environments, severe weather
Session Type: Paper
Day: 4/12/2018
Start / End Time: 10:00 AM / 11:40 AM
Room: Galerie 6, Marriott, 2nd Floor
Presentation File: No File Uploaded


Weakly forced thunderstorms (WFTs), short-lived convection forming in synoptically quiescent regimes, are a contemporary forecasting challenge. The convective environments that support severe WFTs are often similar to those that yield only nonsevere WFTs, and additionally, only a small proportion individual WFTs will ultimately produce severe weather. The purpose of this study is to better characterize the relative severe weather potential in these settings as a function of the convective environment. Thirty near-storm convective parameters for >200,000 WFTs in the Southeast United States are calculated from a high-resolution numerical forecasting model, the Rapid Refresh (RAP). For each parameter, the relative likelihood of WFT days with at least one severe weather event is assessed along a moving threshold. Parameters (and the values of them) that reliably separate severe-weather-supporting from nonsevere WFT days are highlighted. Only two convective parameters, vertical totals (VT) and total totals (TT), appreciably differentiate severe-wind-supporting and severe-hail-supporting days from nonsevere WFT days. When VTs exceeded values between 24.6–25.1°C or TTs between 46.5–47.3°C, severe-wind days were roughly 5x more likely. Meanwhile, severe-hail days became roughly 10x more likely when VTs exceeded 24.4–26.0°C or TTs exceeded 46.3–49.2°C. The stronger performance of VT and TT is partly attributed to the more accurate representation of these parameters in the numerical model. Under-reporting of severe weather and model error are posited to exacerbate the forecasting challenge by obscuring the subtle convective environmental differences enhancing storm severity.

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