most citedA Hybrid Deep-Learning Model for El Niño Southern Oscillation in the Low-Data Regime

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physics.ao-ph2026

AIFS-SUBS: Extending Data-Driven Forecasting to Sub-Seasonal Timescales

Jakob Schloer, Steffen Tietsche, Christopher D. Roberts +6

Data-driven models now rival numerical weather prediction in the medium range, but extending them to sub-seasonal lead times raises challenges absent at shorter horizons. Errors ac…

physics.ao-ph2026

Representing the Surface Ocean in ECMWF's data-driven forecasting system AIFS

Sara Hahner, Lorenzo Zampieri, Jean-Raymond Bidlot +22

Machine-learning (ML) models, such as the AIFS at the ECMWF, have revolutionised weather forecasting in recent years. We present an extension of the AIFS that jointly models the at…