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Physics > Atmospheric and Oceanic Physics

arXiv:2509.18994 (physics)
[Submitted on 23 Sep 2025 ]

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

Title: 对ECMWF机器学习天气预报模型AIFS的更新

Authors:Gabriel Moldovan, Ewan Pinnington, Ana Prieto Nemesio, Simon Lang, Zied Ben Bouallègue, Jesper Dramsch, Mihai Alexe, Mario Santa Cruz, Sara Hahner, Harrison Cook, Helen Theissen, Mariana Clare, Cathal O'Brien, Jan Polster, Linus Magnusson, Gert Mertes, Florian Pinault, Baudouin Raoult, Patricia de Rosnay, Richard Forbes, Matthew Chantry
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.
Abstract: 我们介绍了ECMWF的机器学习天气预报模型AIFS Single的更新,包含多项关键改进。该模型现在通过边界层引入了物理一致性约束、更新了训练计划,并扩展了变量集。物理约束显著提高了降水预报,新变量表现出高水平的技能。高空头条评分也比之前的AIFS版本有所提高。AIFS自2025年2月25日起已在ECMWF全面投入运行。
Subjects: Atmospheric and Oceanic Physics (physics.ao-ph)
Cite as: arXiv:2509.18994 [physics.ao-ph]
  (or arXiv:2509.18994v1 [physics.ao-ph] for this version)
  https://doi.org/10.48550/arXiv.2509.18994
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Gabriel Moldovan [view email]
[v1] Tue, 23 Sep 2025 13:43:20 UTC (29,575 KB)
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