Climate models

Updated CMIP6 climate models darkened by scientific biases


The cloudy Southern Ocean shows an improved radiation budget in the latest IPCC climate models, but there are still significant biases in the physical properties of clouds simulated over the Southern Ocean. These biases are largely canceled out when they jointly influence the radiative effect of clouds. The image of the cloud is captured by the FY-3D satellite. Credit: China Meteorological Administration’s National Satellite Meteorological Center

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 human-made pollution. Appropriately named the Southern Ocean, the southernmost ocean in the world, is far from human pollution but subject to abundant marine gases and aerosols. It is about 80% cloud covered. How does this body of water and its relationship to clouds contribute to global climate change?

Scientists are still studying to figure it out, and they are now one step closer, thanks to an international collaboration identifying compensation errors in widely used climate model protocols known as CMIP6. They published their findings today (September 20) in the journal Advances in atmospheric science.

Radiative effect of clouds

Clouds can act as a greenhouse ingredient to warm the Earth by trapping the long wave infrared radiative flux exiting at the top of the atmosphere. Clouds can also enhance planetary albedo by reflecting shortwave solar radiative flux back into space to cool the Earth. The net effect of the two competing processes depends on cloud height, type, and optical properties. The cloud radiative effect (CRE) on the Earth’s current radiation budget can be inferred from satellite data by comparing the upward radiation in cloudy and cloudless regions.

“Cloud and radiation biases over the Southern Ocean have been a long-standing problem in recent generations of global climate models,” said corresponding author Yuan Wang. He is now an Associate Professor in the Department of Earth, Atmospheric and Planetary Sciences at Purdue University. “After the latest CMIP6 models were released, we were eager to see how they performed and if the old issues were still there.”

CMIP Phase 6 (CMIP6) is a project of the World Climate Research Program (WCRP). It enables the systematic evaluation of climate models to illuminate how they compare to each other and to real-world data. In this study, Wang and the researchers analyzed five of the CMIP6 models that aim to serve as standard references.

Wang said the researchers were also motivated by other studies in the field which indicate that cloud cover in the Southern Ocean is a contributing factor to the high sensitivity of some CMIP6 models, when the simulations predict a surface temperature that increases too rapidly for the increased radiation rate. . In other words, if simulated incorrectly, the clouds in the Southern Ocean can cast a shadow of doubt over the projection of future climate change.

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

The radiative effect of clouds – how clouds interfere with radiation to warm or cool the surface – is largely determined by the physical properties of the cloud. “The radiative effects of clouds in CMIP6 are comparable to satellite observations, but we found that there are large compensation biases in the path of liquid water in the cloud fraction and the effective radius of the clouds. droplets,” Wang said. “The major implication is that while the latest CMIP models improve the simulation of their mean states, such as radiation fluxes at the top of the atmosphere, the detailed cloud processes are still highly uncertain.”

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

“Our future work will aim to identify the individual parameterizations responsible for these biases,” Wang said. “Hopefully we can work closely with the model developers to resolve them. After all, the ultimate goal of any model evaluation study is to help improve those models. »

Reference: “Compensating Errors in Cloud Radiative and Physical Properties over the Southern Ocean in the CMIP6 Climate Models” by Lijun Zhao, Yuan Wang, Chuanfeng Zhao, Xiquan Dong and Yuk L. Yung, September 20, 2022, Advances in atmospheric science.
DOI: 10.1007/s00376-022-2036-z

Other contributors include Lijun Zhao and Yuk L. Yung, Division of Geology and Planetary Sciences, California Institute of Technology; Chuanfeng Zhao, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University; and Xiquan Dong, Department of Hydrology and Atmospheric Sciences, University of Arizona.