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Diagnosis of regime-dependent cloud simulation errors in CMIP5 models using "a-Train" satellite observations and reanalysis data

  • Hui Su
  • , Jonathan H. Jiang
  • , Chengxing Zhai
  • , Vince S. Perun
  • , Janice T. Shen
  • , Anthony Del Genio
  • , Larissa S. Nazarenko
  • , Leo J. Donner
  • , Larry Horowitz
  • , Charles Seman
  • , Cyril Morcrette
  • , Jon Petch
  • , Mark Ringer
  • , Jason Cole
  • , Knut Von Salzen
  • , Michel D.S. Mesquita
  • , Trond Iversen
  • , Jon Egill Kristjansson
  • , Andrew Gettelman
  • , Leon Rotstayn
  • Stephen Jeffrey, Jean Louis Dufresne, Masahiro Watanabe, Hideaki Kawai, Tsuyoshi Koshiro, Tongwen Wu, Evgeny M. Volodin, Tristan L'Ecuyer, Joao Teixeira, Graeme L. Stephens
  • California Institute of Technology
  • NASA Goddard Institute for Space Studies
  • National Oceanic and Atmospheric Administration
  • Now at Met Office Hadley Centre
  • Meteorological Research Branch
  • Bjerknes Centre for Climate Research
  • Norwegian Meteorological Institute
  • University of Oslo
  • National Center for Atmospheric Research
  • Commonwealth Scientific and Industrial Research Organization
  • Department of Science, Information Technology, Innovation and the Arts
  • University of Tokyo
  • Japan Meteorological Agency
  • China Meteorological Administration
  • RAS
  • University of Wisconsin-Madison

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)2762-2780
Number of pages19
JournalJournal of Geophysical Research: Atmospheres
Volume118
Issue number7
DOIs
Publication statusPublished - 16 Apr 2013

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