Enforcing approximate hydrostatic balance as a soft training constraint improves RMSE in a global ML weather model, with gains most visible after 7-10 days.
Accurate medium-range global weather forecasting with 3D neural networks.Nature, 619(7970):533– 538, 2023
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Imposing the Fundamental Dynamical Constraint of Hydrostatic Balance to Improve Global ML Weather Prediction
Enforcing approximate hydrostatic balance as a soft training constraint improves RMSE in a global ML weather model, with gains most visible after 7-10 days.