DOI: 10.1002/2013JD019994
论文题名: Use of dynamical downscaling to improve the simulation of Central U.S. warm season precipitation in CMIP5 models
作者: Harding K.J. ; Snyder P.K. ; Liess S.
刊名: Journal of Geophysical Research Atmospheres
ISSN: 21698996
出版年: 2013
卷: 118, 期: 22 起始页码: 12522
结束页码: 12536
语种: 英语
英文关键词: CMIP5
; dynamical downscaling
; extreme rainfall events
; Great Plains
; model evaluation
; WRF
Scopus关键词: Climate change
; Climate models
; Flood control
; Forestry
; Rain
; Weather forecasting
; CMIP5
; Dynamical downscaling
; Extreme rainfall
; Great Plains
; Model evaluation
; WRF
; Computer simulation
; climate change
; climate modeling
; diurnal variation
; downscaling
; drought
; extreme event
; flood
; global climate
; parameterization
; precipitation (climatology)
; rainfall
; regional climate
; seasonality
; weather forecasting
; United States
英文摘要: Despite supporting exceptionally productive agricultural lands, the Central U.S. is susceptible to severe droughts and floods. Such precipitation extremes are expected to worsen with climate change. However, future projections are highly uncertain as global climate models (GCMs) generally fail to resolve precipitation extremes. In this study, we assess how well models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulate summer means, variability, extremes, and the diurnal cycle of Central U.S. summer rainfall. Output from a subset of historical CMIP5 simulations are used to drive the Weather Research and Forecasting model to determine whether dynamical downscaling improves the representation of Central U.S. rainfall. We investigate which boundary conditions influence dynamically downscaled precipitation estimates and identify GCMs that can reasonably simulate precipitation when downscaled. The CMIP5 models simulate the seasonal mean and variability of summer rainfall reasonably well but fail to resolve extremes, the diurnal cycle, and the dynamic forcing of precipitation. Downscaling to 30 km improves these characteristics of precipitation, with the greatest improvement in the representation of extremes. Additionally, sizeable diurnal cycle improvements occur with higher (10 km) resolution and convective parameterization disabled, as the daily rainfall peak shifts 4 h closer to observations than 30 km resolution simulations. This lends greater confidence that the mechanisms responsible for producing rainfall are better simulated. Because dynamical downscaling can more accurately simulate these aspects of Central U.S. summer rainfall, policymakers can have added confidence in dynamically downscaled rainfall projections, allowing for more targeted adaptation and mitigation. Key Points The simulation of Central U.S. summer rainfall in CMIP5 models is analyzed CMIP5 models fail to simulate extremes or the correct forcing of rainfall Downscaling in WRF improves simulation of rainfall characteristics ©2013. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/63164
Appears in Collections: 影响、适应和脆弱性 气候减缓与适应
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作者单位: Department of Soil, Water and Climate, University of Minnesota, 439 Borlaug Hall, 1991 Upper Buford Circle, Saint Paul, MN 55108, United States
Recommended Citation:
Harding K.J.,Snyder P.K.,Liess S.. Use of dynamical downscaling to improve the simulation of Central U.S. warm season precipitation in CMIP5 models[J]. Journal of Geophysical Research Atmospheres,2013-01-01,118(22)