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.
@article{arxiv.2509.18994,
title = {An update to ECMWF's machine-learned weather forecast model AIFS},
author = {Gabriel Moldovan and Ewan Pinnington and Ana Prieto Nemesio and Simon Lang and Zied Ben Bouallègue and Jesper Dramsch and Mihai Alexe and Mario Santa Cruz and Sara Hahner and Harrison Cook and Helen Theissen and Mariana Clare and Cathal O'Brien and Jan Polster and Linus Magnusson and Gert Mertes and Florian Pinault and Baudouin Raoult and Patricia de Rosnay and Richard Forbes and Matthew Chantry},
journal= {arXiv preprint arXiv:2509.18994},
year = {2025}
}