DOI: 10.1175/JCLI-D-11-00469.1
Scopus记录号: 2-s2.0-84859950845
论文题名: Exposing global cloud biases in the Community Atmosphere Model (CAM) using satellite observations and their corresponding instrument simulators
作者: Kay J.E. ; Hillman B.R. ; Klein S.A. ; Zhang Y. ; Medeiros B. ; Pincus R. ; Gettelman A. ; Eaton B. ; Boyle J. ; Marchand R. ; Ackerman T.P.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2012
卷: 25, 期: 15 起始页码: 5190
结束页码: 5207
语种: 英语
Scopus关键词: Climate sensitivity
; Cloud properties
; Cloud radiative forcing
; Community atmosphere model
; Global clouds
; Instrument Simulator
; Marine boundary layer clouds
; Model evaluation
; Optical depth
; Physical process
; Radiative effects
; Satellite observations
; Atmospheric radiation
; Cams
; Clouds
; Climate models
; boundary layer
; climate feedback
; climate modeling
; cloud radiative forcing
; computer simulation
; estimation method
; marine atmosphere
; performance assessment
; satellite imagery
英文摘要: Satellite observations and their corresponding instrument simulators are used to document global cloud biases in the Community Atmosphere Model (CAM) versions 4 and 5. The model-observation comparisons show that, despite having nearly identical cloud radiative forcing, CAM5 has a much more realistic representation of cloud properties than CAM4. In particular, CAM5 exhibits substantial improvement in three long-standing climate model cloud biases: 1) the underestimation of total cloud, 2) the overestimation of optically thick cloud, and 3) the underestimation of midlevel cloud. While the increased total cloud and decreased optically thick cloud in CAM5 result from improved physical process representation, the increased midlevel cloud in CAM5 results from the addition of radiatively active snow. Despite these improvements, both CAM versions have cloud deficiencies. Of particular concern, both models exhibit large but differing biases in the subtropical marine boundary layer cloud regimes that are known to explain intermodel differences in cloud feedbacks and climate sensitivity. More generally, this study demonstrates that simulatorfacilitated evaluation of cloud properties, such as amount by vertical level and optical depth, can robustly expose large and at times radiatively compensating climate model cloud biases. © 2012 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/52293
Appears in Collections: 气候变化事实与影响
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作者单位: Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO, United States; Department of Atmospheric Sciences, University of Washington, Seattle, WA, United States; Joint Institute for the Study of the Atmosphere and Ocean, University of Washington, Seattle, WA, United States; Program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore, CA, United States; NOAA/Earth System Research Lab, Physical Sciences Division, University of Colorado, Boulder, CO, United States
Recommended Citation:
Kay J.E.,Hillman B.R.,Klein S.A.,et al. Exposing global cloud biases in the Community Atmosphere Model (CAM) using satellite observations and their corresponding instrument simulators[J]. Journal of Climate,2012-01-01,25(15)