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Satellite scatterometers can outperform traditional models in short-term offshore wind forecasting, achieving up to 23% lower error in just hours.
By fusing neural networks with physics-based models, NeuroDDAF achieves state-of-the-art air quality forecasting with calibrated uncertainty, outperforming purely data-driven approaches.
