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

• Published in: Scientific Reports
• Main Authors: Nouri, Niloufar, Devineni, Naresh, Were, Valerie, Khanbilvardi, Reza
• Other Authors: U.S. Department of Energy Early CAREER Award, The National Oceanic and Atmospheric Administration – Cooperative Science Center for Earth System Sciences and Remote Sensing Technologies
• Format: Article in Journal/Newspaper
• Language: English
• Published: Springer Science and Business Media LLC 2021
• Subjects: Multidisciplinary; Arctic; Pacific; Soi; North Atlantic; North Atlantic oscillation
• Online Access: http://dx.doi.org/10.1038/s41598-021-81143-5; http://www.nature.com/articles/s41598-021-81143-5.pdf; http://www.nature.com/articles/s41598-021-81143-5

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.