The Institut Pierre-Simon Laplace (IPSL) is a federation of research laboratories devoted to study the climate system and the global environment. Since 1995, the IPSL Climate Modelling Centre (IPSL-CMC) develops and uses climate models in order to improve our understanding and knowledge of the climate system, its current characteristics and its past and future changes.

Many aspects of the climate system are studied at IPSL and IPSL-CMC is one of the few climate modelling centres worldwide that develop most aspects of its Earth System Model (ESM). Such a model represent the different components of the climate system and their interactions. The IPSL Earth System Model comprises of the LMDz model for the atmosphere, the INCA and REPROBUS models for atmospheric composition, the NEMO model for the ocean, including ocean dynamics (NEMO-OCE), sea-ice (NEMO-LIM) and ocean biogeochemistry (NEMO-PISCES), and the ORCHIDEE model for terrestrial surfaces. The IPSL climate model uses the OASIS coupler and the powerful XIOS input/output server. A new dynamical core for the atmosphere, known as DYNAMICO, is now coupled to the atmospheric physics and forms our next generation model.

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2023 ORCHIDEE model training

The ORCHIDEE project group organises a training session for new users of the model. The training covers two days of lectures and hands on session. It will take place on the 6-7 of February 2023 on the Pierre and Marie Curie campus in Paris, but an option to follow the training online will also be […]

2023 libIGCM training

The next training on how to use the IPSL climate model will take place on 19 & 20 and 26 & 27 January 2023. The deadline for registration is December 14, 2022 but the number of attendees in each session is limited. This course is for beginners and advanced users. It will be mostly hands-on […]

IPSL CMC seminar

IPSL CMC has a two-day residential seminar on November 17-18th to discuss their future climate modelling roadmap. Among the many subjects discussed: Water and energy cycle, Biogeochemical couplings, Model tuning and evaluation, Ice sheet modelling, Use of model hierarchy and spinup, AI contribution to modelling, Training for and by our models, Data stewardship.