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Linking hails and tornadoes to mesoscale convective systems: a long-term statistical study

Presentation Date
Friday, December 11, 2020 at 4:16pm
Location
Virtual
Authors

Author

Abstract

Hails and tornadoes are hazardous weather events that are responsible for significant property damage and economic loss in the United States. Previous studies show that these hazards are commonly produced by short-lived, intense convective storms (e.g., supercell, spatial coverage of tens km and temporal scale of 1-2 hours or sub-hourly). However, intense convective cells are often embedded in large mesoscale convective systems (MCSs). MCS has spatial scales of 100s km and lifespan of 10s hours and frequently occurs in the Great Plains. MCS is often associated with strong synoptic forcing which implies higher predictability in numerical weather predictions than isolate convective storms. Therefore, understanding the relationships between MCSs and hazardous weather events have an important implication to the predictability of hazardous weather events. In this study, we map the instantaneous high-resolution hazard reports to a recently developed MCS database over the contiguous U.S. based on 14 years of radar observations, and analyze the characteristics of hails and tornadoes associated with MCS vs. non-MCS convection, including the seasonality, regionality, and morphology of the convection. Key findings include (1) more than half of the hails and tornadoes are associated with MCSs and the percentage increases with the severity of the hazard; (2) MCS-associated hazards are more evenly distributed among convective morphologies of cellular, nonlinear, and linear modes, but the hazards associated with non-MCS convection are dominated by cellular mode; (3) Central U.S. has higher percentage of MCS-associated hazards than Eastern U.S.; and (4) The hails and tornadoes in the Central U.S. peak in early summer (Mar-Apr-May), but hails in the Eastern U.S. peak one month later and tornadoes are more evenly distributed throughout the warm season.

Category
Atmospheric Sciences