DOI: 10.1175/JCLI-D-12-00452.1
Scopus记录号: 2-s2.0-84881226318
论文题名: Evaluation of the surface climatology over the conterminous united states in the north american regional climate change assessment program hindcast experiment using a regional climate model evaluation system
作者: Kim J. ; Waliser D.E. ; Mattmann C.A. ; Mearns L.O. ; Goodale C.E. ; Hart A.F. ; Crichton D.J. ; Mcginnis S. ; Lee H. ; Loikith P.C. ; Boustani M.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2013
卷: 26, 期: 15 起始页码: 5698
结束页码: 5715
语种: 英语
Scopus关键词: Jet Propulsion Laboratory
; Model errors
; Model evaluation/performance
; North America
; Regional climate changes
; Regional climate models
; Regional effects
; Surface air temperatures
; Climatology
; Incident solar radiation
; Precipitation (meteorology)
; Public policy
; Climate models
; air temperature
; climate change
; climate modeling
; climate prediction
; climatology
; ensemble forecasting
; error analysis
; hindcasting
; precipitation (climatology)
; regional climate
; spatial variation
; surface temperature
; Arizona
; Atlantic Ocean
; Gulf of Mexico
; New Mexico
; Pacific Northwest
; United States
英文摘要: Surface air temperature, precipitation, and insolation over the conterminous United States region from the North American Regional Climate Change Assessment Program (NARCCAP) regional climate model (RCM) hindcast study are evaluated using the Jet Propulsion Laboratory (JPL) Regional Climate Model Evaluation System (RCMES). All RCMs reasonably simulate the observed climatology of these variables. RCM skill varies more widely for the magnitude of spatial variability than the pattern. The multimodel ensemble is among the best performers for all these variables. Systematic biases occur across these RCMs for the annual means, with warm biases over the Great Plains (GP) and cold biases in the Atlantic and the Gulf of Mexico (GM) coastal regions. Wet biases in the Pacific Northwest and dry biases in the GM/southern Great Plains also occur inmost RCMs. All RCMs suffer problems in simulating summer rainfallin the Arizona-New Mexico region. RCMs generally overestimate surface insolation, especially in the eastern United States. Negative correlation between the biases in insolation and precipitation suggest that these two fields are related, likely via clouds. Systematic variations in biases for regions, seasons, variables, and metrics suggest that the bias correction in applying climate model data to assess the climate impact on various sectors must be performed accordingly. Precipitation evaluation with multiple observations reveals that observational data can be an important source of uncertainties in model evaluation; thus, cross examination of observational data is important for model evaluation. © 2013 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51729
Appears in Collections: 气候变化事实与影响
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作者单位: Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, Los Angeles, CA, United States; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States; Institute for Mathematical Applications to the Geosciences, National Center for Atmospheric Research, Boulder, CO, United States
Recommended Citation:
Kim J.,Waliser D.E.,Mattmann C.A.,et al. Evaluation of the surface climatology over the conterminous united states in the north american regional climate change assessment program hindcast experiment using a regional climate model evaluation system[J]. Journal of Climate,2013-01-01,26(15)