J16B.3 AIFS – ECMWF’s Data-Driven Probabilistic Forecasting System

Thursday, 1 February 2024: 4:45 PM
336 (The Baltimore Convention Center)
Matthew Chantry, ECMWF, Reading, OXF, United kingdom; and M. Alexe, S. Lang, B. Raoult, J. Dramsch, F. Pinault, Z. Ben Bouallegue, M. Clare, C. Lessig, L. Magnusson, P. DUEBEN, A. Brown, F. Pappenberger, and F. Rabier

In just two years, the idea of an operational data-driven system for medium-range weather forecasting has been transformed from dream to very real possibility. This has occurred through a series of publications from innovators, which have rapidly improved deterministic forecast skill. Our own evaluation confirms that these forecasts have comparable deterministic skill to NWP models across a range of variables. However, on medium-range timescales probabilistic forecasting, typically achieved through ensembles, is key for providing actionable insights to users. ECMWF is building on top of these recent works to develop a probabilistic forecasting system, AIFS. We will showcase results from our progress towards this system and outline our roadmap to operationalisation.
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