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Making climate models relevant for local decision-makers

news.mit.edu Making climate models relevant for local decision-makers

A climate modeling downscaling method developed by MIT scientists leverages a machine-learning technique called adversarial learning to produce simulations faster and at finer resolutions, making them relevant to use on local levels for assessing risks of extreme weather.

Making climate models relevant for local decision-makers

Interesting application of machine learning to actually reduce computational intensity for once...

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