Weak Tornadoes in the Ohio Valley: A Pre-Storm Environment Assessment (45)
Kristen Cassady, NOAA / NWS, Wilmington, OH
The Ohio Valley is susceptible to tornadoes and sits near the epicenter of the climatological maxima in quasi-linear convective system-driven tornado frequency in the U.S. (Smith et al. 2012, Thompson et al. 2012). These tornadoes are typically brief and on the ground for only a few minutes (Smith et al. 2012), yielding many instances of unwarned events (Brotzge and Erickson 2010). The short-lived nature of the tornadoes provides a notable challenge to forecasters in the warning decision process. Although research of the parent mesocyclones has been performed from both a radar (Trapp et al. 2005, Hatzos 2016) and an environmental parameters (Schaumann and Przybylinski 2012) perspective, this project serves to further and expand upon this prior research and demonstrate its applicability in the Ohio Valley. The objective of this study is to identify key environment changes in the near-storm environment before tornadoes develop.
Archived Rapid Refresh (RAP) analysis data was studied in weak tornado environments in the National Weather Service Wilmington, Ohio service area of southeastern Indiana, southwestern Ohio, and northern Kentucky from 2009 to 2017. Pre-storm environments were investigated utilizing 16 different RAP analyses stability, shear, and moisture parameters in the hours prior to tornado development. Time trends of each parameter were categorized by season and time of day and relationships were identified for each variable through time. The data collection methodology yielded over 6000 data points and parameters were assessed with regards to positive or negative correlations to tornado development time. Trends of individual stability and shear parameters were also compared to each other to assess degree of correlation - both with and without respect to time. The study identifies ingredient and parameter changes significant enough to support weak tornado formation, and concludes with subsequent recommendations for better real-time recognition of environments becoming increasingly favorable for such events.