Climate Dynamics

, Volume 27, Issue 2–3, pp 261–279 | Cite as

A comparison of low-latitude cloud properties and their response to climate change in three AGCMs sorted into regimes using mid-tropospheric vertical velocity

  • Matthew C. WyantEmail author
  • Christopher S. Bretherton
  • Julio T. Bacmeister
  • Jeffrey T. Kiehl
  • Isaac M. Held
  • Ming Zhao
  • Stephen A. Klein
  • Brian J. Soden


Low-latitude cloud distributions and cloud responses to climate perturbations are compared in near-current versions of three leading U.S. AGCMs, the NCAR CAM 3.0, the GFDL AM2.12b, and the NASA GMAO NSIPP-2 model. The analysis technique of Bony et al. (Clim Dyn 22:71–86, 2004) is used to sort cloud variables by dynamical regime using the monthly mean pressure velocity ω at 500 hPa from 30S to 30N. All models simulate the climatological monthly mean top-of-atmosphere longwave and shortwave cloud radiative forcing (CRF) adequately in all ω-regimes. However, they disagree with each other and with ISCCP satellite observations in regime-sorted cloud fraction, condensate amount, and cloud-top height. All models have too little cloud with tops in the middle troposphere and too much thin cirrus in ascent regimes. In subsidence regimes one model simulates cloud condensate to be too near the surface, while another generates condensate over an excessively deep layer of the lower troposphere. Standardized climate perturbation experiments of the three models are also compared, including uniform SST increase, patterned SST increase, and doubled CO2 over a mixed layer ocean. The regime-sorted cloud and CRF perturbations are very different between models, and show lesser, but still significant, differences between the same model simulating different types of imposed climate perturbation. There is a negative correlation across all general circulation models (GCMs) and climate perturbations between changes in tropical low cloud cover and changes in net CRF, suggesting a dominant role for boundary layer cloud in these changes. For some of the cases presented, upper-level clouds in deep convection regimes are also important, and changes in such regimes can either reinforce or partially cancel the net CRF response from the boundary layer cloud in subsidence regimes. This study highlights the continuing uncertainty in both low and high cloud feedbacks simulated by GCMs.


Cloud Fraction Geophysical Fluid Dynamics Laboratory Cloud Radiative Force Liquid Water Path TRMM Microwave Imager 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This paper grew out of a multi-institution Climate Process Team whose goal is to reduce the uncertainty in representing low-latitude cloud feedbacks on climate change by improving the representation of cloud processes in GCMs (Bretherton et al. 2004). The authors would like to thank Cecile Hannay, Jim Mccaa, Christine Shields at NCAR for their assistance with CAM and the CAM simulations, Paul Kushner, Rich Gudgel, and Tom Knutson for producing some of the GFDL simulations. Also thanks to Mark Stevens at NCAR for gridding the NCEP, SSMI, and ERBE data. Thanks to Rob Wood for the providing processed monthly TMI data, Peter Blossey for helpful discussions, and Marc Michelson for computer support. The authors thank Edwin Schneider and several anonymous reviewers who helped improve this paper. SSMI data are produced by Remote Sensing Systems and sponsored by the NASA Earth Science REASoN DISCOVER Project. Data are available at ERA-40 data were provided by ECMWF. Funding for this work was provided by NSF grant 0336703 and NOAA by the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement No. NA17RJ1232, Contribution, #1153.


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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Matthew C. Wyant
    • 1
    Email author
  • Christopher S. Bretherton
    • 1
  • Julio T. Bacmeister
    • 2
  • Jeffrey T. Kiehl
    • 3
  • Isaac M. Held
    • 4
  • Ming Zhao
    • 4
  • Stephen A. Klein
    • 4
    • 5
  • Brian J. Soden
    • 4
    • 6
  1. 1.Department of Atmospheric SciencesUniversity of WashingtonSeattleUSA
  2. 2.NASA Global Modeling and Assimilation OfficeGoddard Spaceflight CenterGreenbeltUSA
  3. 3.National Center for Atmospheric ResearchBoulderUSA
  4. 4.NOAA Geophysical Fluid Dynamics LaboratoryPrincetonUSA
  5. 5.The Atmospheric Science DivisionLawrence Livermore National LaboratoryLivermoreUSA
  6. 6.Division of Meteorology and Physical Oceanography, Rosenstiel School of Marine and Atmospheric ScienceUniversity of MiamiMiamiUSA

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