Diurnal cloud cycle biases in climate models

Jun Yin and Amilcare Porporato ()
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Jun Yin: Princeton University
Amilcare Porporato: Princeton University

Nature Communications, 2017, vol. 8, issue 1, 1-8

Abstract: Abstract 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.

Date: 2017
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DOI: 10.1038/s41467-017-02369-4

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