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A new paper published in the Journal of Advances in Modeling Earth Systems proposes a method to use machine learning to improve the efficiency and accuracy of climate models, allowing for more detailed predictions on smaller scales. This approach challenges traditional methods of downscaling, which rely on physics-based models, by incorporating data-driven techniques.
