The study of clouds is difficult, sometimes clouds have a warming effect on the local climate and sometimes they have a cooling effect, depending on the type of clouds, the local climate, and a variety of other conditions.
One of the fundamental questions about climate change is: How long will the Earth continue to warm in response to greenhouse gas emissions in the future?
The answer lies in the clouds
Scientists say that the answer lies in the sky, as clouds are the protective shield for climate change, and play a crucial role in the rapid rise in global temperature, but recent studies indicate that cloud cover changes with changing global temperatures, which may accelerate global warming, and this means that the Earth may They are slightly more sensitive to greenhouse gases than some older estimates might suggest.
Paulo Seppi, a climate scientist at Imperial College London and one of the authors of one of the new studies in a report He posted on the Scientific American website, on July 26, that “clouds represent a state of uncertainty, and this was the main motivation for research. We want to understand how clouds will change and how cloud change will affect global warming.” “.
Studying clouds is difficult, sometimes clouds have a warming effect on the local climate and sometimes they have a cooling effect, depending on the type of clouds, the local climate and a variety of other conditions, and climate change complicates the matter even more, it is expected that global warming will lead to an increase in certain types of clouds in certain places and reduced in others.
Scientists have struggled for years to determine how clouds will change with future warming, but this question has been difficult to answer. Scientists usually use modeling to predict future climate changes, but it is known that simulating clouds is difficult, especially on a global scale.
Varying estimates of climate sensitivity
The question of doubling carbon dioxide – a measure known to scientists as “equilibrium climate sensitivity” – has been a central question among climate researchers for decades, and in 1979 he proposed a report According to the National Academy of Sciences, the planet would likely warm 1.5 to 4.5 degrees Celsius in response.
And last year, with improvements in cloud research, a new study found that a doubling of carbon dioxide would likely raise the temperature by an average of 2.6 degrees to just 3.9 degrees Celsius, a much lower rate. The most recent research on climate sensitivity, taking into account different directions of evidence, including recent advances in cloud science.
I have suggested study It was published last February in the journal Nature Climate Change that the potential sensitivity is about 3.5 degrees Celsius, and stated Another study It was published last May in the same journal that the potential sensitivity is 3 degrees Celsius, and both studies suggest that clouds on a global scale may have a ripple effect on the rate of global warming.
Traditional methods and machine learning
These studies used observations from the real world to draw their conclusions, as researchers collected large amounts of data on cloud behavior, such as how clouds interact with changes in temperature, humidity and other weather variables, and then performed statistical analyzes of those observations to predict how clouds will respond to climate change in the future. .
“It’s a fairly traditional way of tackling the problem,” says Mark Zelinka, a climatologist and cloud expert at Lawrence Livermore National Laboratory and co-author of both the May study and the study from last year.
On the other hand, taken Latest study Published in the Proceedings of the National Academy of Sciences a less conventional approach, the study used machine learning to see how clouds respond to changes in their environments.
Machine learning is a branch of artificial intelligence in which computers examine large amounts of data, identify patterns, and then use those patterns to build algorithms that predict how future data will behave under different conditions. In this case, the researchers used real-world observations of the way clouds respond to environmental change. .
The machine learning approach came to a similar conclusion: a narrower climate sensitivity, which excludes most of the milder climate scenarios, and the study found almost no chance of climate sensitivity below 2°C.
Dr Sebi, who authored the study with fellow climate scientist and machine learning expert Pierre Nowak, said: ‘I’ve thought for a while that the cloud problem was particularly well suited to machine learning methods. The individual effects of each of these environmental variables.
A combination of study methods
Machine learning has a promising future in other types of cloud science as well, as some research groups are experimenting with incorporating machine learning components into global climate models as a way to overcome the difficulties of simulating clouds.
Designers typically do not force their models to actually simulate the formation of clouds, but instead manually enter information about how clouds are formed and respond to changes in their environments, a tactic known as parameters.
And machine learning can be a proxy for parameters, so instead of introducing a rule of how a drag should behave within a model, a machine learning component can create algorithms that predict how a drag should respond.
It’s reassuring, Zlinka says, that different strategies have come to similar conclusions. “If it’s just one study you might question its findings, but if you have more and more evidence from researchers using different techniques, and they all come to a similar conclusion, that’s hard to question.” .
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