CGILS: Results from the first phase of an international project to understand the physical mechanisms of low cloud feedbacks in single column models

By Minghua Zhang, Chris Bretherton, Peter N. Blossey, Phillip H. Austin, Julio Bacmeister, Sandrine Bony, F. Brient, S. Cheedela, A. Cheng, A. D. Del Genio and 30 more. 2013

144 citations recorded by the source corpus.

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.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/c66c46eae68707a6885b79dc822b3b7bc3e56c43

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In Atmospheric Science

1. Shian‐Jiann Lin
2. Ming Zhao
3. I. Held
4. Yi Ming
5. J. Golaz
6. Paul Ginoux
7. Leo Donner
8. D. Paynter

In Global and Planetary Change

1. Shian‐Jiann Lin
2. Yi Ming
3. J. Golaz
4. V. Ramaswamy
5. Ming Zhao
6. Leo Donner
7. Paul Ginoux
8. D. Paynter

Citations in the corpus

• Uncertainty in Model Climate Sensitivity Traced to Representations of Cumulus Precipitation Microphysics (2016, background): “…and understanding many aspects of intermodel differences in cloud feedback and climate sensitivity between GCMs (e.g., Cess et al. 1990; Zhang et al. 1994; Cess et al. 1996; Soden et al. 2004;Wyant et al. 2006; Ringer et al. 2006; Bony et al. 2006; Medeiros et al. 2008; Wyant et al.…”
• Emergent Constraints for Cloud Feedbacks (2015, unknown): “[54] provide indirect evidence for the small-scale mixing component of the Sherwood mechanism.”