Source: Earth and Space Sciences
The clouds play a important role in the Earth’s climate and can warm or cool the atmosphere depending on their particular characteristics and when and where they form. Computer models of Earth’s future climate suffer from uncertainties related to the challenge of predicting cloud cover and how the effects of clouds might evolve as the planet warms.
To help meet these challenges, Vignesh et al. immersed in cloud cover predictions from climate models that are part of the Coupled Model Intercomparison Project (CMIP). CMIP is a periodically updated climate modeling framework used by scientists around the world so that the different models they develop can be systematically analyzed and compared.
Researchers compared cloud cover predictions from models developed under the current phase of CMIP, CMIP6, with predictions from models from the previous phase, CMIP5. They found differences in cloud cover simulation between the CMIP5 and CMIP6 models over a historical period from 1861 to 2005.
Specifically, the CMIP6 models showed greater spread, or variation, among their predictions of historical changes in the fraction of sky covered with clouds than the CMIP5 models. In addition, the CMIP6 models predicted a global average cloud fraction about 4.5% higher than that predicted by the CMIP5 models.
The scientists also used real-world cloud observations from NASA CALIPSO and CloudSat satellites to evaluate the CMIP6 predictions of recent years. Overall, the predictions matched the observations well, but the team found inconsistencies at certain altitudes and latitudes. But by applying a simple statistical technique, researchers could improve the agreement between CMIP6 predictions and satellite observations.
These results highlight specific areas of progress in cloud cover simulation and could help inform future improvements in climate models. (Earth and Space Sciences, https://doi.org/10.1029/2019EA000975, 2020)
—Sarah Stanley, science writer
Stanley, S. (2020), Assessing cloud cover predictions in climate models, Eos, 101, https://doi.org/10.1029/2020EO141682. Posted March 23, 2020.
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