A new machine learning framework called Probabilistic Bias Correction (PBC) has been developed to improve the accuracy of subseasonal weather forecasts, which typically degrade beyond two weeks. PBC works by learning to correct historical probabilistic forecasts, thereby reducing systematic errors. When tested on leading AI and dynamical models from the European Centre for Medium-Range Weather Forecasts (ECMWF), PBC doubled the skill of an AI Forecasting System and significantly improved the operational dynamical model's predictions for pressure, temperature, and precipitation. In a real-time forecasting competition, PBC-enhanced global forecasts outperformed those from six operational centers and 34 other teams. AI
IMPACT Enhances subseasonal weather prediction accuracy, potentially improving disaster preparedness and resource management.
RANK_REASON Academic paper detailing a new machine learning framework for weather forecasting. [lever_c_demoted from research: ic=1 ai=0.7]
- AI Forecasting System
- Dynamical Subseasonal Forecasts
- European Centre for Medium-Range Weather Forecasts
- Probabilistic Bias Correction
- Soukayna Mouatadid
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