TY - JOUR
T1 - Diurnal cloud cycle biases in climate models
AU - Yin, Jun
AU - Porporato, Amilcare
N1 - Funding Information:
We acknowledge support from the USDA Agricultural Research Service cooperative agreement 58-6408-3-027; and the National Science Foundation (NSF) grants EAR-1331846, EAR-1316258, FESD EAR-1338694, and the Duke WISeNet Grant DGE-1068871.
Publisher Copyright:
© 2017 The Author(s).
PY - 2017/12/1
Y1 - 2017/12/1
N2 - Clouds' efficiency at reflecting solar radiation and trapping the terrestrial radiation is strongly modulated by the diurnal cycle of clouds (DCC). Much attention has been paid to mean cloud properties due to their critical role in climate projections; however, less research has been devoted to the DCC. Here we quantify the mean, amplitude, and phase of the DCC in climate models and compare them with satellite observations and reanalysis data. While the mean appears to be reliable, the amplitude and phase of the DCC show marked inconsistencies, inducing overestimation of radiation in most climate models. In some models, DCC appears slightly shifted over the ocean, likely as a result of tuning and fortuitously compensating the large DCC errors over the land. While this model tuning does not seem to invalidate climate projections because of the limited DCC response to global warming, it may potentially increase the uncertainty of climate predictions.
AB - Clouds' efficiency at reflecting solar radiation and trapping the terrestrial radiation is strongly modulated by the diurnal cycle of clouds (DCC). Much attention has been paid to mean cloud properties due to their critical role in climate projections; however, less research has been devoted to the DCC. Here we quantify the mean, amplitude, and phase of the DCC in climate models and compare them with satellite observations and reanalysis data. While the mean appears to be reliable, the amplitude and phase of the DCC show marked inconsistencies, inducing overestimation of radiation in most climate models. In some models, DCC appears slightly shifted over the ocean, likely as a result of tuning and fortuitously compensating the large DCC errors over the land. While this model tuning does not seem to invalidate climate projections because of the limited DCC response to global warming, it may potentially increase the uncertainty of climate predictions.
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U2 - 10.1038/s41467-017-02369-4
DO - 10.1038/s41467-017-02369-4
M3 - Article
C2 - 29273812
AN - SCOPUS:85039167773
SN - 2041-1723
VL - 8
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 2269
ER -