Clouds can cool or warm the planet’s surface, a radiative forcing that contributes significantly to the global energy budget and can be altered by human-caused pollution. The world’s southern ocean, which is called the Southern Ocean far from human pollution but subject to abundant marine gases and aerosols, is covered by clouds of about 80%. How does this body of water and the relationship with clouds contribute to changing the world’s climate?
Researchers are still working on figuring this out, and are now one step closer, thanks to an international collaboration that identifies compensation errors in widely used climate modeling protocols known as CMIP6. The researchers published their findings on September 20 in Advances in atmospheric sciences.
“Cloud and radiation biases 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 introduction of the latest CMIP6 models, we were eager to see how they performed and whether the old issues remained.”
CMIP6, a project of the World Climate Research Program, allows for a systematic assessment of climate models to shed light on how they compare with each other and real-world data. In this study, Wang and researchers analyzed five CMIP6 models that are intended to serve as standard references.
Wang said the researchers were also motivated by other studies in the field that point to Southern Ocean cloud coverage as a contributing factor to the high sensitivity of some CMIP6 models, when simulations predict a surface temperature that rises too quickly for the increased rate of radiation. . In other words, if simulated incorrectly, the clouds of the Southern Ocean could cast doubt on projections of future climate change.
“This paper emphasizes compensating errors in the cloud’s physical properties despite comprehensive optimization of radiation simulations over the Southern Ocean,” said Wang. “Through space satellite observations, we can identify these errors in the exact physical properties of the simulated cloud, including cloud fraction, cloud water content, cloud droplet size, and more, and also reveal how each contributes to the overall bias in the cloud’s radiative forcing.”
A cloud’s radiative forcing – how clouds interfere with radiation to warm or cool the surface – is largely determined by the cloud’s physical properties. “Cloud radiative forcings in CMIP6 are comparable to satellite observations, but we found that there are significant compensating biases in the liquid water trajectory of the cloud portion and the effective radius of the droplets,” Wang said. “The main meaning is that although the latest CMIP models are improving simulations of their mean states, such as radiation fluxes in the upper atmosphere, the detailed clouds are still highly ambiguous.”
According to Wang, this discrepancy also partly explains why typical climate sensitivity assessments do not perform well, given that those assessments rely on a detailed physical model – rather than an average country performance – to assess the overall climate impact.
“Our future work will aim to identify the individual criteria responsible for these biases,” Wang said. “Hopefully we can work closely with model developers to solve it. After all, the ultimate goal of any model evaluation study is to help improve those models.”
Other contributors include Lejun Chau and Yuk Il-Young, Department of Geology and Planetary Science, Caltech; 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.
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Compensation for errors in radiative and physical properties of the cloud over the Southern Ocean in CMIP6 climate models, Advances in atmospheric sciences (2022). DOI: 10.1007/s00376-022-2036-z
Provided by the Chinese Academy of Sciences
the quoteResearchers (2022, September 20) find updated climate models tainted by science biases, retrieved September 21, 2022 from https://phys.org/news/2022-09-climate-clouded-scientific-biases.html
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