INSTITUTE OF ATMOSPHERIC PHYSICS, CHINESE ACADEMY OF SCIENCES
Clouds can cool or warm the planet’s surface, a radiative effect that contributes significantly to the global energy budget and can be altered by human-caused pollution. The world’s southernmost ocean, aptly named the Southern Ocean and far from human pollution but subject to abundant marine gases and aerosols, is about 80% covered by clouds. How does this body of water and relationship with clouds contribute to the world’s changing climate?
Researchers are still working to figure it out, and they’re 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 on September 20 in Advances in Atmospheric Sciences.
“Cloud and radiation biases over the Southern Ocean have been a long-lasting problem in the past generations of global climate models,” said corresponding author Yuan Wang, 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 anxious to see how they performed and whether the old problems were still there.”
CMIP6, a project of the World Climate Research Programme, allows for the systematic assessment of climate models to illuminate how they compare to each other and 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 that point to the Southern Ocean’s cloud coverage as a contributing factor to some CMIP6 models’ high sensitivity, when the simulations predict a surface temperature that rises too quickly for the rate of increased radiation. In other words, if improperly simulated, the Southern Ocean clouds may cast a shadow of doubt on the projection of future climate change.
“This paper emphasizes compensating errors in the cloud physical properties in spite of overall improvement of radiation simulation over the Southern Ocean,” Wang said. “With space satellite observations, we are able to quantify those errors in the simulated cloud microphysical properties, including cloud fraction, cloud water content, cloud droplet size and more, and further reveal how each contributes to the total bias in the cloud radiative effect.”
The cloud radiative effect — how clouds interfere radiation to warm or cool the surface — is largely determined by the physical properties of the cloud. “Cloud radiative effects in CMIP6 are comparable with satellite observations, but we found there are large compensating biases in cloud fraction liquid water path and droplet effective radius,” Wang said. “The major implication is that, even though 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 of large uncertainty.”
According to Wang, this discrepancy also partially explains why the model climate sensitivity assessments do not perform as well, since those assessments rely on model detailed physics — rather than the mean state performance — to evaluate the overall effect on the climate.
“Our future work will aim to pin down individual parameterizations that are responsible for these biases,” Wang said. “Hopefully, we can work closely with model developers to get them solved. After all, the ultimate goal of any model evaluation study is to help improve those models.”
Other contributors include Lijun Zhao and Yuk L. Yung, Division of Geology and Planetary Science, 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.
JOURNAL
Advances in Atmospheric Sciences
DOI
ARTICLE TITLE
Compensating Errors in Cloud Radiative and Physical Properties over the Southern Ocean in the CMIP6 Climate Models
ARTICLE PUBLICATION DATE
20-Sep-2022
“…clouds may cast a shadow of doubt on the projection of future climate change.”
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That’s right, clouds cast a shadow. Clouds form because of more evaporation causing more water vapor resulting in more precipitation. Says so right in the IPCC assessment reports. The IPCC doesn’t say more clouds, but it doesn’t take a genius to figure that part out. Here’s my favorite link for that:
IPCC FAR Chapter 10 Page 750
Mean Precipitation
For a future warmer climate, the current generation of models indicates that precipitation generally increases in the areas of regional tropical precipitation maxima (such as the monsoon regimes) and over the tropical Pacific in particular, with general decreases in the subtropics, and increases at high latitudes as a consequence of a general intensification of the global hydrological cycle. Globally averaged mean water vapour, evaporation and precipitation are projected to increase.
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And it doesn’t take much more head scratching to figure out that more clouds reflect more of the sun’s radiation back out to space and constitutes negative feed back. Willis E. Has banged on about that in more detail many times on these WUWT pages. If you still don’t understand the concept, it rains every afternoon in the tropics. There’s a reason Hawaii has a rainbow on its license plates.
These so called scientists won’t get very far unless they include the fact that at evaporation Water absorbs the energy of radiation and converts it to Latent Heat in the Vapor produced.
This takes place at CONSTANT TEMPERATURE which means that the sensitivity is virtually ZERO.
Evaporation and Condensation occurs continuously in the climate so the above fact has a considerable influence on the global SENSITIVITY value.
One can but ask here whether any of the CMIP6 models include the above in their calculations
Updated Climate Models Clouded by UNSCIENTIFIC Biases, Researchers Find
Always trust compooter models from people with letters after their name-
A VNI West puzzle: What is it about this modelling that looks a bit odd? | RenewEconomy
Lest doubts and impure thoughts creep in and …gulp!…that way leads to the dark side and the dooming.
The floods are slowly inundating everything, yet some scientists still don’t know what is causing the warming. In fact, it doesn’t matter at the moment because now only geoengineering can provide a temporary solution.
Clouds also have extraterrestrial influences.
Not fashionable, but maybe worth considering them
So, they are saying the previous models were wrong?
Quick! Somebody tell the politicians before they screw up the World’s economy.
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Oops! Too late.
Oh. Completely off topic I know but couldn’t resist. Jacob Rees-Mogg has now officially lifted the pause on fracking and the UK government is now looking at a round of oil and gas leases (including fracking) in October. The usual suspects, along with some Tory MP’s, have been screaming since the announcements.
Climate “models”…’nuff said.
I am not familiar enough with these advanced climate models to say what they can do, or not do, but I wrote heat transfer codes for geothermal work forty years ago and I know about errors that reside in code. For at least thirty years I have been brow-beaten by the wide-eyed modeling fanatics about how good the models are and how we need to believe. For these same thirty years I keep reading about improvements to the models. Some of these sound rather substantial. This press release about improving things as fundamental as getting surface warming and top of the atmosphere to balance better corroborates my suspicion that these models are not suitable for the uses they are being put to.
This is a lot like the advertising for commercial products. The new and improved version hyped to the skies, suggesting inadvertently that the old product must have been pretty bad.
But why do we give the Nobel Prize for the worst climate model? https://www.youtube.com/watch?v=98zl8SlObLE
this is off-topic, but related somewhat…
I believe that the models are at least mathematically chaotic (butterfly-effect chaotic) and I wonder if any of them have been run multiple times with slightly varying input values to see how much variation is in the end results and how long in projected time the results start to vary significantly.
It is possible that one or more of my assumptions are incorrect, ie, models are not chaotic, the results are terminated before the resulting values vary, But I have wondered about this.
So parameters are wrong but we will work on getting them right.
This is all you need to know about climate models. THEY ARE UNRELATED TO OBSERVABLE PHYSICS. They rely on fiddles.
The whole concept of GHE only occurs in climate phiisics. Laws written by politicians.
The cloud persistence in the Southern Ocean is simply related to the surface temperature never getting above 15C. They is no convective instability. It is all condensing cloud that slows the rate of cooling because the atmosphere is often fully saturated. Meaning no surface evaporation so primary heat loss through convection to cloud tops.
Once above 15C, an LFC can form and that reduces the average relatively humidity as instability sets in. See attached showing variation of RH with ocean surface temperature.
The cloud works both ways because it makes the surface slow to respond to sunshine. It takes 192W/m^2 change in solar EMR to shift the Southern Ocean temperature one degree centigrade.
The reason the Southern Ocean is cooling is because it is has been getting less solar EMR for a long time. The peak December sunlight was 3.5kys ago. It is dropping at 0.5W/m^2 per century.
Cloud error alone is enough to make CMIP5 simulations about 1000× too coarse to resolve the tiny perturbation of CO₂ emissions, and the CMIP6 models are no better.
The whole of consensus climatology is no more than pseudoscience. A subjectivist narrative decorated with mathematics.