Updated climate models are clouded by scientific biases, researchers find

Clouds can cool or warm the planet’s surface, a radiative effect that contributes significantly to the global energy balance and can be altered by man-made pollution. The world’s southernmost ocean, aptly named the Southern Ocean and far from human pollution but exposed to abundant sea gases and aerosols, is about 80% covered by clouds. How does this body of water and its relationship to clouds contribute to the changing world climate?

Researchers are still working to find out, and they’re now one step closer thanks to an international collaboration identifying compensation errors in widely used climate modeling protocols, known as CMIP6. The researchers published their findings on September 20 in Advances in atmospheric science.

“Cloud and radiative distortions over the Southern Ocean have been a long-standing problem in past generations of global climate models,” said corresponding author Yuan Wang, now an associate professor in Purdue University’s Department of Earth, Atmospheric and Planetary Sciences. “After the latest CMIP6 models were released, we were curious to see how they perform and if the old issues are still there.”

CMIP6, a project of the World Climate Research Programme, enables the systematic assessment of climate models to show how they compare to each other and to real-world data. In this study, Wang and the researchers analyzed five of the CMIP6 models to serve as standard references.

Wang said the researchers are also motivated by other studies in the field, which point to Southern Ocean cloud cover as a factor contributing to the high sensitivity of some CMIP6 models when the simulations predict a surface temperature that is responsible for the rate of increased Radiation increases too quickly. In other words, if improperly simulated, Southern Ocean clouds can cast a shadow of doubt on projections of future climate change.

“This paper emphasizes compensating for errors in the physical properties of clouds despite the overall improvement in radiative simulation over the Southern Ocean,” Wang said. “With space satellite observations, we are able to quantify these errors in the simulated microphysical cloud properties, including cloud fraction, cloud water content, cloud droplet size and more, and further show how each contributes to the overall distortion of the cloud radiative effect.” “

The radiative effect of clouds – how clouds interfere with radiation to heat or cool the surface – is largely determined by the cloud’s physical properties. “Cloud radiative effects in CMIP6 are comparable to satellite observations, but we found that there are large compensating distortions in the cloud fraction liquid path and effective droplet radius,” Wang said. “The main implication is that although the latest CMIP models improve the simulation of their mean states, such as B. Radiant fluxes at the top of the atmosphere, the detailed cloud processes are still of great uncertainty.”

According to Wang, this discrepancy also partly explains why the model’s climate sensitivity ratings don’t fare so well, since those ratings rely on the model’s detailed physics — rather than mean state performance — to assess the overall effect on climate.

“Our future work will aim to identify individual parameterizations responsible for these distortions,” Wang said. “Hopefully we can work closely with model developers to solve them. Finally, the ultimate goal of any model validation study is to help improve those models.”

Additional contributors are Lijun Zhao and Yuk L. Yung, Division of Geology and Planetary Science, California Institute of Technology; Chuanfeng Zhao, Institute of Atmospheric and Ocean Sciences, Faculty of Physics, Peking University; and Xiquan Dong, Department of Hydrology and Atmospheric Sciences, University of Arizona.