Nashville-basin tornadoes: using storm types to elucidate the local climatology and forecasting challenges

Abstract

Early 3 March 2020 was a devastating night for many middle Tennessee residents. A strong EF-3 tornado tore through Nashville at 65 mph, and another EF-4 killed 18 in Baxter and Cookeville alone. Residents of the Southeastern United States are particularly vulnerable to tornadoes. This study aims to better understand local forecasting challenges by looking at the types of storms that produce tornadoes. Storm types, also known as convective modes, divide tornado-producing storms into categories by length, shape, multiplicity, and intensity. Distinguishing storms by these modes allows for a broader understanding of their occurrences and impacts. This study specifically evaluates three forecasting success metrics for the Nashville county warning area from 2012–2018. This includes probability of detection (POD), false alarm ratio (FAR), and average lead time for four convective modes: cell in line, cell in cluster, discrete supercell, and quasi-linear convective system (QLCS). Three models were created to predict warnings, false alarms, and lead time with convective mode, nocturnality, and multiple-tornado days as predictors. The results affirm current literature findings that QLCSs are far more common to the Nashville basin than its surrounding areas, and QLCSs tend to occur at night as outbreaks. For this study period, QLCSs also have the best POD, FAR, and lead time, compared to other convective modes, which creates a unique climatological tornado profile that centers around QLCSs.

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