William E. Chapman, John Schreck, Yingkai Sha
Featured August 1, 2026
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AI weather models that force perfect conservation can secretly get worse because the "fixer" hides their mistakes; the paper shows how to make the model learn to be good on its own by checking its raw predictions and penalizing imbalances.
The paper shows that fixing model outputs to perfectly conserve things can hide problems, so they changed how the model learns to make it conserve better on its own.
They found that without their new training method, the model's raw guesses got much worse, but with it, the model learned to make good guesses from the start.