A Dynamical and Statistical Characterization of United States Extreme Precipitation Events and their Associated Large-Scale Meteorological Patterns

TitleA Dynamical and Statistical Characterization of United States Extreme Precipitation Events and their Associated Large-Scale Meteorological Patterns
Publication TypeJournal Article
Year of Publication2017
AuthorsZhao, Siyu, Deng Yi, and Black Robert X.
JournalJournal of Climate
Volume30
Pages1307-1326
Date Published02/2017
Abstract / Summary

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 US 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 US 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.

URLhttp://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-15-0910.1
DOI10.1175/JCLI-D-15-0910.1
Journal: Journal of Climate
Year of Publication: 2017
Volume: 30
Pages: 1307-1326
Date Published: 02/2017

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 US 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 US 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
Citation:
Zhao, S, Y Deng, and RX Black.  2017.  "A Dynamical and Statistical Characterization of United States Extreme Precipitation Events and their Associated Large-Scale Meteorological Patterns."  Journal of Climate 30: 1307-1326.  https://doi.org/10.1175/JCLI-D-15-0910.1.