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.
Highlights
Tornadoes represent one of nature’s most hazardous phenomena that have been responsible for significant destruction and devastating fatalities
Canada has experienced significant losses caused by tornado activity, with significant tornado events occurring in recent years[2]
We use Bayesian inference techniques to dissect the problem of tornado occurrence into a two step-process, in which we first consider the causal linkages between atmospheric variables and tornado activity in space and time, and we postulate that the likelihood to observe a tornado is closely related to the population density
Summary
Tornadoes represent one of nature’s most hazardous phenomena that have been responsible for significant destruction and devastating fatalities. Canada has experienced significant losses caused by tornado activity, with significant tornado events occurring in recent years (for example, 14 tornadoes on 2 August 2006; 18 tornadoes on 20 August 2009)[2] These events have brought the study of tornado activity to the forefront of climatological research, raising questions regarding the relative influence of large-scale climatic signals and the importance of delineating the role of the underlying atmospheric processes at the appropriate spatiotemporal scale. Characterization of the interplay between large-scale atmospheric processes and local conditions leading to tornado formation has been examined in the severe storm research community[7,8,9] Atmospheric variables such as convective available potential energy and vertical wind shear have been shown to be most relevant to mechanisms related to severe thunderstorm and tornado formation[7]. Our ultimate goal is to develop an empirical modelling tool that can be used for drawing inference on the frequency of tornado occurrence or exceedance of a threshold number of tornadoes in any location in North America within a selected time period of the year
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