Annual meeting 2026

The research grouping (GDR) "Theoretical challenges for climate sciences" was created in 2022. Its goal is to federate the community of theorists: climatologists, oceanographers, atmospheric scientists, physicists, mathematicians, computer scientists, numerical scientists, machine learning, who work on climate sciences.

The annual meeting of the GDR will take place from May 27-29, 2026 in Paris.  The event is open to all scientists interested in the topics of the GDR.  Like in the previous years we will also put forward a specific theme. The specific theme this year will be "Multi-scale processes for climate physics: convection, boundary layers, turbulence". The goal is to make the connection between idealized studies of small-scale phenomena and global modelling, by combining the understanding of physical mechanisms and parameterization development approaches.

Practical information

Dates: May 27-29, 2026

LocationAmphi Buffon, université Paris Cité

Deadline to apply for oral contributions: April 24, 2026

Deadline for registration: May 8, 2026

Registration is free but mandatory - (does not include dinners and overnight stays)

Oral constributions and posters :  in the registration form you may apply for a poster or oral presentation. Priority will be given to early-career colleagues and research close to this year's special theme, but all are encouraged to apply. Poster format: A0 vertical or smaller.

Contact : defi-theo-climat-request@listes.math.cnrs.fr

Register to GDR mailing list (independent of the annual meeting).

GDR Theoretical challenges for climate science

The Theoretical Challenges for Climate Science GDR brings together the community of theorists: physicists, climatologists, oceanographers, atmospheric scientists, mathematicians, computer scientists, numerical scientists, machine learning, who work on climate science. The goal of the GDR is to develop innovative theoretical and numerical tools to overcome current scientific limitations. The approaches of statistical physics, turbulence modeling, mathematics, machine learning, will allow to deepen the understanding of fundamental mechanisms, improve models, and better predict extreme events to reduce uncertainties on the impacts of climate change. This GDR has a strong interdisciplinary vocation and involves researchers from several CNRS institutes, many other French organizations and companies.

More information on the GDR website: https://defi-theo-climat.ipsl.fr

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