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• W2010058194 abstract "Tornadoes represent one of nature’s most hazardous phenomena that have been responsible for significant destruction and devastating fatalities. Here we present a Bayesian modelling approach for elucidating the spatiotemporal patterns of tornado activity in North America. Our analysis shows a significant increase in the Canadian Prairies and the Northern Great Plains during the summer, indicating a clear transition of tornado activity from the United States to Canada. The linkage between monthly-averaged atmospheric variables and likelihood of tornado events is characterized by distinct seasonality; the convective available potential energy is the predominant factor in the summer; vertical wind shear appears to have a strong signature primarily in the winter and secondarily in the summer; and storm relative environmental helicity is most influential in the spring. The present probabilistic mapping can be used to draw inference on the likelihood of tornado occurrence in any location in North America within a selected time period of the year. Tornadoes are one of nature’s most hazardous phenomena, yet prognostic tools for tornado occurrence are lacking. Here, the authors use Bayesian inference techniques to evaluate the spatiotemporal relationship between atmospheric variables and tornado activity in North America." @default.
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• W2010058194 date "2015-03-25" @default.
• W2010058194 modified "2023-10-14" @default.
• W2010058194 title "A Bayesian modelling framework for tornado occurrences in North America" @default.
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• W2010058194 doi "https://doi.org/10.1038/ncomms7599" @default.
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