EGU24-1675, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-1675
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

ML for weather prediction at Météo-France : current status and future plans

Laure Raynaud, Clément Brochet, and Gabriel Moldovan
Laure Raynaud et al.
  • Centre National de Recherche Météorologique, GMAP, France (laure.raynaud@meteo.fr)

Applications of Machine Learning (ML) in the different stages of weather forecasting have considerably developed recently. Such progress is likely to change the landscape and offer new perspectives to speed up and improve forecast performances, at different spatio-temporal scales. In this context, Météo-France engaged more actively in this new area of research, with the objective to further explore the capabilities and opportunities of ML for operational forecasting. Major ongoing projects include ML to significantly enhance the size of convective-scale ensemble forecasts, high-resolution statistical downscaling and the development of data-driven kilometre-scale forecasting systems. Early results will be presented and our short-term roadmap will be discussed.

How to cite: Raynaud, L., Brochet, C., and Moldovan, G.: ML for weather prediction at Météo-France : current status and future plans, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1675, https://doi.org/10.5194/egusphere-egu24-1675, 2024.