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DTSTAMP:20260421T090514Z
LOCATION:Bldg. 8 - Room B 101
DTSTART;TZID=Europe/Stockholm:20260630T141500
DTEND;TZID=Europe/Stockholm:20260630T144500
UID:submissions.pasc-conference.org_PASC26_sess147_msa203@linklings.com
SUMMARY:Anemoi: A New Collaborative Framework for Data-driven Weather Fore
 casting
DESCRIPTION:Cathal O Brien (ECMWF)\n\nAnemoi is an open source python-base
 d framework for building data-driven weather forecasting models. It is dev
 eloped in collaboration by many weather forecasting centres across Europe.
  The goal of Anemoi is to provide the key building blocks to train state‑o
 f-the‑art data-driven models and run them in an operational context.\n\nAn
 emoi users have many different use cases (e.g. global, local or ensemble w
 eather models). Additionally, Anemoi is run on diverse hardware; from loca
 l clusters to the largest  EuroHPC supercomputers. A key challenge when de
 veloping Anemoi is how to ensure all these different use cases and hardwar
 e are supported in tandem. Furthermore, one must balance the ease of addin
 g new scientific features with the requirement to maintain high-performanc
 e across diverse hardware.\n\nThis talk describes how the Anemoi developme
 nt process addresses these challenges. It will outline the project’s colla
 borative workflows, automated testing infrastructure, and performance vali
 dation strategies, and discuss how open-source development practices enabl
 e rapid scientific innovation while maintaining operational robustness.\n\
 nDomain: Climate, Weather, and Earth Sciences, Applied Social Sciences and
  Humanities\n\nSession Chair: Jan Frederik Engels (German Climate Computin
 g Centre)\n\n
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