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.
The era5 global reanalysis.Quarterly journal of the royal meteorological society, 146(730):1999–2049, 2020
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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.