Séminaire
Le groupe IA et Climat (
AI4climate.lip6.fr
) réunit des chercheurs de l’IPSL et le LIP6 impliqués dans la recherche pluridisciplinaire concernant l’utilisation des méthodes d’intelligence Artificielle dans les sciences de l’environnement et du climat. Cette initiative est soutenue par le groupe de travail SAMA (Statistiques pour l’analyse, la modélisation et l’assimilation) de l’IPSL.
Climate indices show large variability in CMIP climate predictions. In this presentation, we propose to weight multi-model climate simulations to reduce the uncertainty in climate predictions, and better estimate the future evolution of climate indices. The proposed methodology is based on advanced data science tools (i.e, data assimilation, analog forecasting, model evidence metrics), to accurately compute distances between current observations and simulated climate indices. This low-cost procedure is tested on a simplified climate model. The results show that the methods can be applied locally and is able to identify relevant parameterizations.
Short bio
Pierre Tandeo an associate professor at IMT Atlantique (Brest, France) and an associate researcher at the Data Assimilation Research Team, RIKEN Center for Computational Science (Kobe, Japan). M
ore information :
https://tandeo.wordpress.com/
.
julien.brajard@locean.ipsl.fr