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Influence of cloud phase composition on climate feedbacks
Author(s) -
Choi YongSang,
Ho ChangHoi,
Park ChangEui,
Storelvmo Trude,
Tan Ivy
Publication year - 2014
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2013jd020582
Subject(s) - cloud fraction , atmospheric sciences , cloud feedback , albedo (alchemy) , environmental science , liquid water content , climate change , climate model , positive feedback , cloud computing , water vapor , atmosphere (unit) , climatology , climate sensitivity , meteorology , cloud cover , physics , geology , art , oceanography , electrical engineering , engineering , performance art , computer science , art history , operating system
The ratio of liquid water to ice in a cloud, largely controlled by the presence of ice nuclei and cloud temperature, alters cloud radiative effects. This study quantitatively examines how the liquid fraction of clouds influences various climate feedbacks using the NCAR Community Atmosphere Model (CAM). Climate feedback parameters were calculated using equilibrated temperature changes in response to increases in the atmospheric concentration of carbon dioxide in CAM Version 3.0 with a slab ocean model. Two sets of model experiments are designed such that cloud liquid fraction linearly decreases with a decrease in temperature down to −20°C (Experiment “C20”) and −40°C (Experiment “C40”). Thus, at the same subzero temperature, C20 yields fewer liquid droplets (and more ice crystals) than C40. Comparison of the results of experiments C20 and C40 reveals that experiment C20 is characterized by stronger cloud and temperature feedbacks in the tropics (30°N–30°S) (by 0.25 and −0.28 W m −2 K −1 , respectively) but weaker cloud, temperature, and albedo feedbacks (by −0.20, 0.11, and −0.07 W m −2 K −1 ) in the extratropics. Compensation of these climate feedback changes leads to a net climate feedback change of ~7.28% of that of C40 in the model. These results suggest that adjustment of the cloud phase function affects all types of feedbacks (with the smallest effect on water vapor feedback). Although the net change in total climate feedback is small due to the cancellation of positive and negative individual feedback changes, some of the individual changes are relatively large. This illustrates the importance of the influence of cloud phase partitioning for all major climate feedbacks, and by extension, for future climate change predictions.