CGILS: Results from the First Phase of an International Project to Understand the Physical Mechanisms of Low Cloud Feedbacks in Single Column Models

Minghua Zhang, Stony Brook University
Christopher S. Bretherton, University of Washington
Peter N. Blossey, University of Washington
Phillip H. Austin, University of British Columbia
Julio T. Bacmeister, National Center for Atmospheric Research,
Sandrine Bony, Institute Pierre Simon Laplace (IPSL)
Florent Brient, Institute Pierre Simon Laplace (IPSL)
Suvarchal K. Cheedela, Max Planck Institute for Meteorology
Anning Cheng, NASA Langley Research Center
Anthony D. Del Genio, NASA Goddard Institute for Space Studies
Stephan R. De Roode, Delft University of Technology
Satoshi Endo, Brookhaven National Laboratory
Charmaine N. Franklin, Common- wealth Scientific and Industrial Research Organisation (CSIRO),
Jean-Christophe Golaz, NOAA Geophysical Fluid Dynamics Laboratory,
Cecile Hannay, National Center for Atmospheric Research
Thijs Heus, Cleveland State University


[1] CGILS—the CFMIP-GASS Intercomparison of Large Eddy Models (LESs) and single column models (SCMs)—investigates the mechanisms of cloud feedback in SCMs and LESs under idealized climate change perturbation. This paper describes the CGILS results from 15 SCMs and 8 LES models. Three cloud regimes over the subtropical oceans are studied: shallow cumulus, cumulus under stratocumulus, and well-mixed coastal stratus/stratocumulus. In the stratocumulus and coastal stratus regimes, SCMs without activated shallow convection generally simulated negative cloud feedbacks, while models with active shallow convection generally simulated positive cloud feedbacks. In the shallow cumulus alone regime, this relationship is less clear, likely due to the changes in cloud depth, lateral mixing, and precipitation or a combination of them. The majority of LES models simulated negative cloud feedback in the well-mixed coastal stratus/stratocumulus regime, and positive feedback in the shallow cumulus and stratocumulus regime. A general framework is provided to interpret SCM results: in a warmer climate, the moistening rate of the cloudy layer associated with the surface-based turbulence parameterization is enhanced; together with weaker large-scale subsidence, it causes negative cloud feedback. In contrast, in the warmer climate, the drying rate associated with the shallow convection scheme is enhanced. This causes positive cloud feedback. These mechanisms are summarized as the “NESTS” negative cloud feedback and the “SCOPE” positive cloud feedback (Negative feedback from Surface Turbulence under weaker Subsidence—Shallow Convection PositivE feedback) with the net cloud feedback depending on how the two opposing effects counteract each other. The LES results are consistent with these interpretations.