A new analysis based on simple equations has reduced uncertainty about how clouds will affect future climate change
Clouds have two main effects on global temperature: they cool the planet by reflecting sunlight, and they warm it by acting as insulators against Earth’s radiation. The impact of clouds is the area of greatest uncertainty in global warming predictions.
In a new study, researchers at the University of Exeter and the Laboratoire de Météorologie Dynamique in Paris have created a model that predicts how changes to the surface of cumulonimbus, anvil-shaped clouds (global storm clouds), will affect global warming. tropics).
By comparing their model with observations about the influence of clouds on today’s warming, they confirmed its effectiveness, thereby reducing uncertainty in climate predictions.
This is what the model shows the surface of cumulonimbus clouds have a much smaller impact on global warming than previously thought, meaning the extent they cover may not be as important. However, there is another factor that can have an influence: the shine of these clouds (determined by its thickness) remains poorly understood, making it one of the biggest obstacles to predicting future global warming.
“Climate change is complex, but sometimes we can answer important questions quite simply,” says lead author Brett McKim. “In this case, we simplify the clouds into basic properties: whether they are high or low, their size and temperature. “This allowed us to write equations and create a model that could be compared to the observed clouds.”
“Our results more than halve the uncertainty about the influence of the anvil cloud surface on warming.” “This is a big step, potentially meaning several years difference in the time by which we hope to reach thresholds like the 2 degrees set in the Paris Agreement “To reach the limit,” he continues. “Now we need to investigate how warming affects cloud brightness.” “That is the next phase of our investigation.”
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Weak feedback from the anvil cloud region, which is due to physical and observational limitations