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WIREs Clim Change
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Cloud feedback mechanisms and their representation in global climate models

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Cloud feedback—the change in top‐of‐atmosphere radiative flux resulting from the cloud response to warming—constitutes by far the largest source of uncertainty in the climate response to CO2 forcing simulated by global climate models (GCMs). We review the main mechanisms for cloud feedbacks, and discuss their representation in climate models and the sources of intermodel spread. Global‐mean cloud feedback in GCMs results from three main effects: (1) rising free‐tropospheric clouds (a positive longwave effect); (2) decreasing tropical low cloud amount (a positive shortwave [SW] effect); (3) increasing high‐latitude low cloud optical depth (a negative SW effect). These cloud responses simulated by GCMs are qualitatively supported by theory, high‐resolution modeling, and observations. Rising high clouds are consistent with the fixed anvil temperature (FAT) hypothesis, whereby enhanced upper‐tropospheric radiative cooling causes anvil cloud tops to remain at a nearly fixed temperature as the atmosphere warms. Tropical low cloud amount decreases are driven by a delicate balance between the effects of vertical turbulent fluxes, radiative cooling, large‐scale subsidence, and lower‐tropospheric stability on the boundary‐layer moisture budget. High‐latitude low cloud optical depth increases are dominated by phase changes in mixed‐phase clouds. The causes of intermodel spread in cloud feedback are discussed, focusing particularly on the role of unresolved parameterized processes such as cloud microphysics, turbulence, and convection. WIREs Clim Change 2017, 8:e465. doi: 10.1002/wcc.465

Strengths of individual global‐mean feedbacks and equilibrium climate sensitivity (ECS) for CMIP5 models, derived from coupled experiments with abrupt quadrupling of CO2 concentration. Model names and feedback values are listed in the Table S1, Supporting information. Feedback parameter results are from Caldwell et al., with additional cloud feedback values from Vial et al. and Zelinka et al. ECS values are taken from Andrews et al., Forster et al., and Flato et al. Feedback parameters are calculated as in Soden et al. but accounting for rapid adjustments; the cloud feedback from Zelinka et al. is calculated using cloud‐radiative kernels (Box ). Circles are colored according to the total feedback parameter. The Planck feedback (mean value of −3.15 W m−2 K−1) is excluded from the total feedback parameter shown here.
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Schematic of the relationship between clear‐sky radiative cooling, subsidence warming, radiatively‐driven convergence, and altitude of anvil clouds in the tropics in a control and warm climate, as articulated in the fixed anvil temperature hypothesis. Upon warming, radiative cooling by water vapor increases in the upper troposphere, which must be balanced by enhanced subsidence in clear‐sky regions. This implies that the level of peak radiatively‐driven convergence and the attendant anvil cloud coverage must shift upward. TC denotes the anvil cloud top temperature isotherm.
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Zonal‐, annual‐, and multimodel‐mean net cloud feedbacks in a set of 11 CMIP3 and 7 CMIP5 models (Table S2), plotted against the sine of latitude, and partitioned into components due to the change in cloud amount, altitude, and optical depth. Curves are solid where 75% or more of the models agree on the sign of the feedback, dashed otherwise. (Reprinted with permission from Ref . Copyright 2016 John Wiley and Sons)
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Spatial distribution of the multimodel‐mean net cloud feedback (in W m−2 per K surface warming) in a set of 11 CMIP3 and 7 CMIP5 models subjected to an abrupt increase in CO2 (Table S2). (Reprinted with permission from Ref . Copyright 2016 John Wiley and Sons)
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Global‐mean longwave (red), shortwave (blue), and net (black) cloud feedbacks decomposed into amount, altitude, optical depth, and residual components for (a) all clouds, (b) free‐tropospheric clouds only, and (c) low clouds only, defined by cloud top pressure. Multimodel‐mean feedbacks are shown as horizontal lines. Results are based on an analysis of 11 CMIP3 and 7 CMIP5 models; the CMIP3 values do not account for rapid adjustments. Model names and total feedback values are listed in Table S2. (Reprinted with permission from Ref . Copyright 2016 John Wiley and Sons)
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