Toward Understanding Climatic Influences on Cold-Season Tornado Events

Efforts to better understand and predict the occurrence, intensity, and distribution of USA tornadoes are ongoing in the climate science community. While many studies have investigated spring and early summer tornadoes, few have considered cold-season events. This study aims to identify potential links between climate signals and such cold-season events, defined here as tornadoes rated F1-F5 and occurring from November through February (NDJF). Tornado counts for the period 1979-2014 are assessed regionally, and the South region (30-40N, 85-95W) shows the greatest NDJF tornado density coupled with a substantial upward trend in counts over the period. Thermodynamic and kinematic variables from the Climate Forecast System Reanalysis (CFSR) dataset, as well as sea surface temperatures (SSTs) and the associated ENSO phase, are analyzed to assess their respective influence on tornadogenesis through a case study of most active versus least active cold seasons. Of the CFSR variables investigated, only CAPE in the South region is strongly correlated (r = 0.48) to tornado counts, whereas other well-known tornado ingredients such as vertical wind shear and storm-relative helicity show little to no correlation. It is also found that ENSO phase plays a role in the location of enhanced counts by altering atmospheric jets and height anomalies, although there is not sufficient evidence to claim a significant linkage to tornado frequency. For example, while NDJF tornado counts are higher during episodes of La Niņa, the three most active cold-seasons included Neutral (1992-93), La Niņa (2007-08), and El Niņo (1982-83) periods. However, mean sea surface temperatures and upper-level height anomalies for the most active seasons reveal some teleconnection patterns that are closely aligned with cold-season tornado frequency, such as a positive TransNiņo Index (TNI) and positive phase Arctic Oscillation (AO). This climate analysis of cold-season tornadoes can complement the current discussion of developing a seasonal outlook that aims to provide probabilistic forecasts for severe weather and tornadoes.