globalchange  > 影响、适应和脆弱性
DOI: 10.1029/2012JD018575
论文题名:
Diagnosis of regime-dependent cloud simulation errors in CMIP5 models using "a-Train" satellite observations and reanalysis data
作者: Su H.; Jiang J.H.; Zhai C.; Perun V.S.; Shen J.T.; Del Genio A.; Nazarenko L.S.; Donner L.J.; Horowitz L.; Seman C.; Morcrette C.; Petch J.; Ringer M.; Cole J.; Von Salzen K.; Mesquita M.D.S.; Iversen T.; Kristjansson J.E.; Gettelman A.; Rotstayn L.; Jeffrey S.; Dufresne J.-L.; Watanabe M.; Kawai H.; Koshiro T.; Wu T.; Volodin E.M.; L'Ecuyer T.; Teixeira J.; Stephens G.L.
刊名: Journal of Geophysical Research Atmospheres
ISSN: 21698996
出版年: 2013
卷: 118, 期:7
起始页码: 2762
结束页码: 2780
语种: 英语
Scopus关键词: Atmospheric thermodynamics ; Climate models ; Clouds ; Errors ; Cloud top heights ; Coupled Model Intercomparison Project ; Deep convective clouds ; Lower troposphere ; Satellite observations ; Vertical distributions ; Vertical structures ; Vertical velocity ; Computer simulation ; CALIPSO ; climate modeling ; CloudSat ; condensate ; convective cloud ; data set ; error analysis ; moisture content ; satellite imagery ; troposphere
英文摘要: The vertical distributions of cloud water content (CWC) and cloud fraction (CF) over the tropical oceans, produced by 13 coupled atmosphere-ocean models submitted to the Phase 5 of Coupled Model Intercomparison Project (CMIP5), are evaluated against CloudSat/CALIPSO observations as a function of large-scale parameters. Available CALIPSO simulator CF outputs are also examined. A diagnostic framework is developed to decompose the cloud simulation errors into large-scale errors, cloud parameterization errors and covariation errors. We find that the cloud parameterization errors contribute predominantly to the total errors for allmodels. The errors associated with large-scale temperature and moisture structures are relatively greater than those associated with large-scale midtropospheric vertical velocity and lower-level divergence. All models capture the separation of deep and shallow clouds in distinct large-scale regimes; however, the vertical structures of high/low clouds and their variations with large-scale parameters differ significantly from the observations. The CWCs associated with deep convective clouds simulated in most models do not reach as high in altitude as observed, and their magnitudes are generally weaker than CloudSat total CWC, which includes the contribution of precipitating condensates, but are close to CloudSat nonprecipitating CWC. All models reproduce maximum CF associated with convective detrainment, but CALIPSO simulator CFs generally agree better with CloudSat/CALIPSO combined retrieval than the model CFs, especially in the midtroposphere. Model simulated low clouds tend to have little variation with large-scale parameters except lower-troposphere stability, while the observed low cloud CWC, CF, and cloud top height vary consistently in all large-scale regimes. © 2012. American Geophysical Union. All Rights Reserved.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/63846
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: Jet Propulsion Laboratory (JPL), California Institute of Technology, Pasadena, CA, United States; Goddard Institute for Space Studies (GISS), New York, NY, United States; Geophysical Fluid Dynamics Laboratory (GFDL), Princeton, NJ, United States; UK Met Office, Exeter, United Kingdom; UK Met Office Hadley Centre (MOHC), Exeter, United Kingdom; Canadian Centre for Climate Modeling and Analysis (CCCMA), Environment Canada, Victoria, BC, Canada; Bjerknes Centre for ClimateResearch (BCCR), Uni Research, Bergen, Norway; Norwegian Climate Centre (NCC), Meteorologisk Institutt, Oslo, Norway; University of Oslo, Oslo, Norway; National Center for Atmospheric Research (NCAR), Boulder, CO, United States; Commonwealth Scientific and Industrial Research Organisation (CSIRO), Aspendale, VIC, Australia; Queensland Climate Change Centre of Excellence (QCCCE), QLD, Australia; Laboratory of Dynamical Meteorology, Institute Pierre Simon Laplace (IPSL), France; Model for Interdisciplinary Research on Climate (MIROC), Atmospheric and Ocean Research Institute, University of Tokyo, Chiba, Japan; Meteorological Research Institute (MRI), Japan Meteorological Agency, Tsukuba, Japan; Beijing Climate Center (BCC), China Meteorological Administration, Beijing, China; Institute for Numerical Mathematics, Russian Academy of Sciences, Moscow, Russian Federation; University of Wisconsin-Madison, Madison, WI, United States; JPL, California Institute of Technology, Pasadena, CA, United States

Recommended Citation:
Su H.,Jiang J.H.,Zhai C.,et al. Diagnosis of regime-dependent cloud simulation errors in CMIP5 models using "a-Train" satellite observations and reanalysis data[J]. Journal of Geophysical Research Atmospheres,2013-01-01,118(7)
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