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October 19, 20254 citationsOpen Access

AIFS 1.1.0: An update to ECMWF's machine-learned weather forecast model AIFS

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GMG. MoldovanEPEwan PinningtonANAna Prieto Nemesio

Key Points

  • Improvements to precipitation forecasts are achieved through the addition of physical consistency constraints.
  • The updated training schedule and expanded variables contribute to enhanced model performance metrics.
  • Upper-air headline scores demonstrate improvement over earlier AIFS versions, indicating better predictive capabilities.
  • The AIFS 1.1.0 model has been operational at ECMWF since February 25, 2025, marking a significant upgrade.

Abstract

Abstract. We present an update to ECMWF's machine-learned weather forecasting model AIFS Single with several key improvements. The model now incorporates physical consistency constraints through bounding layers, an updated training schedule, and an expanded set of variables. The physical constraints substantially improve precipitation forecasts and the new variables show a high level of skill. Upper-air headline scores also show improvement over the previous AIFS version. The AIFS has been fully operational at ECMWF since the 25th of February 2025.

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Cite This Study

Moldovan et al. (2025) studied this question.

synapsesocial.com/papers/68f43f03854d1061a58ac41ahttps://doi.org/10.5194/egusphere-2025-4716
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