DOI: 10.1175/JCLI-D-15-0404.1
Scopus记录号: 2-s2.0-84960874549
论文题名: Predicting the climatology of tornado occurrences in North America with a Bayesian hierarchical modeling framework
作者: Cheng V.Y.S. ; Arhonditsis G.B. ; Sills D.M.L. ; Gough W.A. ; Auld H.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2016
卷: 29, 期: 5 起始页码: 1899
结束页码: 1917
语种: 英语
Scopus关键词: Bayesian networks
; Error analysis
; Forecasting
; Molecular physics
; Potential energy
; Regression analysis
; Risk analysis
; Risk assessment
; Storms
; Bayesian hierarchical model
; Bayesian methods
; Convective available potential energies
; Geographic variability
; Model evaluation/performance
; Spatiotemporal variability
; Statistical forecasting
; Statistical techniques
; Tornadoes
; atmospheric modeling
; Bayesian analysis
; climate prediction
; climatology
; error analysis
; hierarchical system
; regression analysis
; risk assessment
; statistical analysis
; tornado
; weather forecasting
; North America
英文摘要: Destruction and fatalities from recent tornado outbreaks in North America have raised considerable concerns regarding their climatic and geographic variability. However, regional characterization of tornado activity in relation to large-scale climatic processes remains highly uncertain. Here, a novel Bayesian hierarchical framework is developed for elucidating the spatiotemporal variability of the factors underlying tornado occurrence in North America. It is demonstrated that regional variability of tornado activity can be characterized using a hierarchical parameterization of convective available potential energy, storm relative helicity, and vertical wind shear quantities. It is shown that the spatial variability of tornado occurrence during the warm summer season can be explained by convective available potential energy and storm relative helicity alone, while vertical wind shear is clearly better at capturing the spatial variability of the cool season tornado activity. The results suggest that the Bayesian hierarchical modeling approach is effective for understanding the regional tornadic environment and in forming the basis for establishing tornado prognostic tools in North America. © 2016 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/50102
Appears in Collections: 气候变化事实与影响
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作者单位: Ecological Modeling Laboratory, Department of Physical and Environmental Sciences, University of Toronto, Toronto, ON, Canada; Risk Sciences International, Ottawa, ON, Canada; Cloud Physics and Severe Weather Research Section, Atmospheric Science and Technology Directorate, Science and Technology Branch, Environment and Climate Change Canada, Toronto, ON, Canada; Climate Laboratory, Department of Physical and Environmental Sciences, University of Toronto, Toronto, ON, Canada
Recommended Citation:
Cheng V.Y.S.,Arhonditsis G.B.,Sills D.M.L.,et al. Predicting the climatology of tornado occurrences in North America with a Bayesian hierarchical modeling framework[J]. Journal of Climate,2016-01-01,29(5)