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贝叶斯模型在北美的龙卷风发生频次中的应用

A Bayesian modelling framework for tornado occurrences in North America.

机构信息

1] Ecological Modeling Laboratory, Department of Physical &Environmental Sciences, University of Toronto, Toronto, Ontario, Canada M1C 1A4 [2] Climate Laboratory, Department of Physical &Environmental Sciences, University of Toronto, Toronto, Ontario, Canada M1C 1A4.

Ecological Modeling Laboratory, Department of Physical &Environmental Sciences, University of Toronto, Toronto, Ontario, Canada M1C 1A4.

出版信息

Nat Commun. 2015 Mar 25;6:6599. doi: 10.1038/ncomms7599.

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.

摘要

龙卷风是自然界最具危害性的现象之一,它曾造成巨大的破坏和毁灭性的人员伤亡。在这里,我们提出了一种贝叶斯建模方法,用于阐明北美的龙卷风活动的时空模式。我们的分析表明,加拿大草原和大北方平原在夏季的龙卷风活动显著增加,表明龙卷风活动从美国向加拿大的明显转移。逐月平均大气变量与龙卷风事件发生的可能性之间的联系具有明显的季节性;夏季时,对流可用位能是主要因素;垂直风切变在冬季表现出强烈的特征,夏季次之;而风暴相对环境螺旋度在春季的影响最大。目前的概率映射可用于推断在一年中选定的时间段内,北美的任何地点发生龙卷风的可能性。

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