DOI: 10.1175/JCLI-D-15-0910.1
Scopus记录号: 2-s2.0-85012273892
论文题名: A dynamical and statistical characterization of U.S. extreme precipitation events and their associated large-scale meteorological patterns
作者: Zhao S. ; Deng Y. ; Black R.X.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2017
卷: 30, 期: 4 起始页码: 1307
结束页码: 1326
语种: 英语
Scopus关键词: Classification (of information)
; Cluster analysis
; Hierarchical systems
; Precipitation (meteorology)
; Rain
; Atmospheric circulation
; Community climate system model
; Extreme precipitation events
; Hierarchical cluster analysis
; Meteorological patterns
; North America
; Precipitation extremes
; Statistical characterization
; Climate models
; atmospheric circulation
; classification
; climate modeling
; cluster analysis
; extreme event
; precipitation (climatology)
; rainfall
; regional climate
; United States
英文摘要: Regional patterns of extreme precipitation events occurring over the continental United States are identified via hierarchical cluster analysis of observed daily precipitation for the period 1950-2005. Six canonical extreme precipitation patterns (EPPs) are isolated for the boreal warm season and five for the cool season. The large-scale meteorological pattern (LMP) inducing each EPP is identified and used to create a "base function" for evaluating a climate model's potential for accurately representing the different patterns of precipitation extremes. A parallel analysis of the Community Climate System Model, version 4 (CCSM4), reveals that the CCSM4 successfully captures the main U.S. EPPs for both the warm and cool seasons, albeit with varying degrees of accuracy. The model's skill in simulating each EPP tends to be positively correlated with its capability in representing the associated LMP. Model bias in the occurrence frequency of a governing LMP is directly related to the frequency bias in the corresponding EPP. In addition, however, discrepancies are found between the CCSM4's representation of LMPs and EPPs over regions such as the western United States and Midwest, where topographic precipitation influences and organized convection are prominent, respectively. In these cases, the model representation of finer-scale physical processes appears to be at least equally important compared to the LMPs in driving the occurrence of extreme precipitation. © 2017 American Meteorological Society. 资助项目: DOE, U.S. Department of Energy
; NSF, National Science Foundation
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/49883
Appears in Collections: 气候变化事实与影响
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作者单位: School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, United States
Recommended Citation:
Zhao S.,Deng Y.,Black R.X.. A dynamical and statistical characterization of U.S. extreme precipitation events and their associated large-scale meteorological patterns[J]. Journal of Climate,2017-01-01,30(4)