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Title: A Dynamical and Statistical Characterization of U.S. Extreme Precipitation Events and Their Associated Large-Scale Meteorological Patterns

Abstract

Abstract 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 tomore » be at least equally important compared to the LMPs in driving the occurrence of extreme precipitation.« less

Authors:
 [1];  [1];  [1]
  1. School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia
Publication Date:
Research Org.:
Georgia Inst. of Technology, Atlanta, GA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1342286
Alternate Identifier(s):
OSTI ID: 1537002
Grant/Contract Number:  
SC0012554
Resource Type:
Published Article
Journal Name:
Journal of Climate
Additional Journal Information:
Journal Name: Journal of Climate Journal Volume: 30 Journal Issue: 4; Journal ID: ISSN 0894-8755
Publisher:
American Meteorological Society
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Meteorology & Atmospheric Sciences

Citation Formats

Zhao, Siyu, Deng, Yi, and Black, Robert X. A Dynamical and Statistical Characterization of U.S. Extreme Precipitation Events and Their Associated Large-Scale Meteorological Patterns. United States: N. p., 2017. Web. doi:10.1175/JCLI-D-15-0910.1.
Zhao, Siyu, Deng, Yi, & Black, Robert X. A Dynamical and Statistical Characterization of U.S. Extreme Precipitation Events and Their Associated Large-Scale Meteorological Patterns. United States. doi:10.1175/JCLI-D-15-0910.1.
Zhao, Siyu, Deng, Yi, and Black, Robert X. Thu . "A Dynamical and Statistical Characterization of U.S. Extreme Precipitation Events and Their Associated Large-Scale Meteorological Patterns". United States. doi:10.1175/JCLI-D-15-0910.1.
@article{osti_1342286,
title = {A Dynamical and Statistical Characterization of U.S. Extreme Precipitation Events and Their Associated Large-Scale Meteorological Patterns},
author = {Zhao, Siyu and Deng, Yi and Black, Robert X.},
abstractNote = {Abstract 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.},
doi = {10.1175/JCLI-D-15-0910.1},
journal = {Journal of Climate},
number = 4,
volume = 30,
place = {United States},
year = {2017},
month = {2}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1175/JCLI-D-15-0910.1

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Cited by: 2 works
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Works referencing / citing this record:

Intraseasonal variation and future projection of atmospheric diffusion conditions conducive to extreme haze formation over eastern China
journal, April 2020