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Low-cloud optical depth feedback in climate models

delete2014-05-27
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OA
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N
Neil D. Gordon *
S
Stephen A. Klein
DOI:10.1002/2013JD021052delete
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摘要

摘要

En 中文
The relationship between low-level cloud optical depth and atmospheric and surface air temperature is examined in the control climate of 13 climate models to determine if cloud optical depth-temperature relationships found in observations are replicated in climate models and if climate model behavior found in control climate simulations provides information about the optical depth feedback in climate warming simulations forced by increasing carbon dioxide. A positive relationship between cloud optical depth and cloud temperature exists in all models for low clouds with relatively cold temperatures at middle and high latitudes, whereas a negative relationship exists for warmer low clouds in the tropics and subtropics. This relationship is qualitatively similar to that in an earlier analysis of satellite observations, although modeled regression slopes tend to be too positive and their intermodel spread is large. In the models, the cold cloud response comes from increases in cloud water content with increasing temperature, while the warm cloud response comes from decreases in physical thickness with increasing cloud temperature. The intermodel and interregional spread of low-cloud optical depth feedback in climate warming simulations is well predicted by the corresponding spread in the relationships between optical depth and temperature for the current climate, suggesting that this aspect of cloud feedback may be constrained by observations. Because models have a positive bias relative to observations in the optical depth-temperature relationship, shortwave cloud feedback for climate changes may be more positive than climate models currently simulate.
Keyword:
LIQUID WATER PATH
HADLEY-CENTER
TEMPERATURE-DEPENDENCE
THICKNESS
BUDGET
ECMWF
GCM
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期刊

J
Journal of Geophysical Research and Atmospheres
IF:
3.4
论文数:
2.2W
被引数:
7.7W

机构

U
united states department of energy (doe)
学者数:
11.3W
论文数: 9.6W
被引数: 246
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