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CGILS: Results from the first phase of an international project to understand...

Zhang, M. H., coauthors, and K. Xu (2013), CGILS: Results from the first phase of an international project to understand the physical mechanisms of low cloud feedbacks in single column models, J. Adv. Modeling Earth Syst., 5, 1-17, doi:10.1002/2013MS000246.
Abstract: 

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, 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 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 ‘‘NESTS-SCOPE’’ (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.

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Research Program: 
Modeling Analysis and Prediction Program (MAP)