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Windborne Systems launched WeatherMesh 6, an AI weather forecasting model that claims to outperform the European Centre for Medium-Range Weather Forecasting (ECMWF) in accuracy and frequency, thanks to direct ingestion of sensor data from its balloons.
This paper proposes using the Ensemble Score Filter (EnSF), a score-based diffusion data assimilation method, to correct forecasts from a pretrained spatio-temporal energy consumption model using noisy partial observations. Numerical experiments show EnSF significantly improves state estimation over open-loop propagation and outperforms the Ensemble Kalman Filter under nonlinear observations.