(Sparse) Attention to the Details: Preserving Spectral Fidelity in ML-based Weather Forecasting Models

In three linesMosaic, a probabilistic weather forecasting model, addresses three spectral degradation failures in ML-based prediction: spectral damping, high-frequency aliasing, and residual leakage. With 214M parameters at 1.5° resolution, it matches models trained 6× finer and generates well-calibrated ensembles in 12s for 10-day forecasts on H100.

Summary generated by Claude — human-verified