Explaining the trends and variability in the United States tornado records using climate teleconnections and shifts in observational practices

Abstract

The annual frequency of tornadoes during 1950–2018 across the major tornado-impacted states were examined and modeled using anthropogenic and large-scale climate covariates in a hierarchical Bayesian inference framework. Anthropogenic factors include increases in population density and better detection systems since the mid-1990s. Large-scale climate variables include El Niño Southern Oscillation (ENSO), Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), Arctic Oscillation (AO), and Atlantic Multi-decadal Oscillation (AMO). The model provides a robust way of estimating the response coefficients by considering pooling of information across groups of states that belong to Tornado Alley, Dixie Alley, and Other States, thereby reducing their uncertainty. The influence of the anthropogenic factors and the large-scale climate variables are modeled in a nested framework to unravel secular trend from cyclical variability. Population density explains the long-term trend in Dixie Alley. The step-increase induced due to the installation of the Doppler Radar systems explains the long-term trend in Tornado Alley. NAO and the interplay between NAO and ENSO explained the interannual to multi-decadal variability in Tornado Alley. PDO and AMO are also contributing to this multi-time scale variability. SOI and AO explain the cyclical variability in Dixie Alley. This improved understanding of the variability and trends in tornadoes should be of immense value to public planners, businesses, and insurance-based risk management agencies.

Predictability of a tornado environment index from El Niño–Southern Oscillation (ENSO) and the Arctic Oscillation

“…Brown and Nowotarski (2020) reported that daily values of the NOAA/Climate Prediction Center AO index were relevant to tornado outbreak likelihood in the southeastern US across all seasons. Nouri et al (2021) found a positive relation between annually averaged state tornado frequencies and the AO. While only suggestive, the tornado report numbers in early 2021 are not inconsistent with the concurrent values of the AO index: February −1.191, March 2.109, April −0.204, and May −0.161 (NOAA Climate Prediction Center, 2022b).…”

Examining the changes in the spatial manifestation and the rate of arrival of large tornado outbreaks

“…Moreover, Elsner et al [40] showed the connection between a positive phase of the North Atlantic Oscillation (NAO) and a lower tornado activity across southeastern states. Another recent study [41] also showed that NAO negatively influences annual tornado frequency. Knowing that the winter index of NAO (December to March) during mid-1970s to early-2000s was primarily in its positive phase [42], we can also associate less frequent LTOs with the positive phase of NAO.…”

Are Significant Tornadoes Occurring Later in the Year in Southern Ontario?

“…The reason for the shift in southern Ontario tornado frequency to later in the season is not clear, especially given no such shift is apparent for neighboring US states. One would assume that if the shift relates to global atmospheric teleconnections such as the El Niño–Southern Oscillation and the North Atlantic Oscillation (see Nouri et al., 2021, for further details on teleconnections and tornadoes), then the effect would be periodic and seen over a larger region than just southern Ontario. It is known that the Great Lakes have been gradually warming over at least the last several decades—since reliable buoy observations began (e.g., Dobiesz & Lester, 2009; O’Reilly et al., 2015).…”