The influence of model convection on the global cloud feedback: An observational constraint derived from the climatological distribution of clouds.
Abstract
Despite the increasing sophistication of climate models, equilibrium climate sensitivity remains stubbornly uncertain, with model estimates ranging from 2-5 K. Much of this uncertainty has been attributed to differences in how models simulate changes in planetary albedo due to clouds (the shortwave cloud feedback). Here we show that model differences in the shortwave cloud feedback are closely related to the climatological pattern of cloud albedo in simulations of the current climate: high-feedback models exhibit lower (higher) cloud albedo in regions of warm (cool) sea-surface temperatures, and therefore predict a larger reduction in global cloud albedo as temperatures rise and warm regions expand. Through partial-least-squares regression, we find that the climatological pattern of cloud albedo is strongly predictive (r=0.84) of a model's global cloud feedback, with satellite observations indicating a most-likely value of 0.58 +/-0.31 W/m2/K (90% confidence). This estimate is higher than the model-average cloud feedback of 0.43 W/m2/K, and with half the range of uncertainty. The observational constraint on climate sensitivity is weak but still significant, suggesting a likely value of 3.68 +/- 1.30 K, which also favors the upper range of model estimates. These results suggest that uncertainty in model estimates of the global cloud feedback may be substantially reduced by ensuring a realistic distribution of clouds in simulations of the current climate.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.A33B0211S
- Keywords:
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- 3305 Climate change and variability;
- ATMOSPHERIC PROCESSESDE: 3310 Clouds and cloud feedbacks;
- ATMOSPHERIC PROCESSESDE: 1626 Global climate models;
- GLOBAL CHANGEDE: 1627 Coupled models of the climate system;
- GLOBAL CHANGE