Increasing the fraction of the globe they cover by just 4% would cool Earth by 2 to 3 ☌-and less cloud cover would have the opposite effect. Low-level clouds, for example, cool the climate by reflecting sunlight, so representing their net effect accurately in the model is critical. Representing the net impact of small-scale processes is crucial to improving the fidelity of climate projections. These simulations can be used to train algorithms that reproduce the net impact of clouds in each cell of the model. But it’s possible to run high-resolution simulations of individual clouds in small regions, verify the simulations against field studies, and then use them to simulate a range of situations that could occur around the world. Simulating every cloud would require too much computing power. “Obviously there can be more than four clouds in the state of Massachusetts,” says Ferrari. Massachusetts, for example, would roughly equal four cells, and the model would have the capacity to represent only a single cloud in each one. But their resolution is so coarse they can account for only limited features. Current models calculate climate futures in a grid of cells that approximate processes on land, water, and air.
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