ClimSim: An open large-scale dataset for training high-resolution physics emulators

CAOS Professor Laure Zanna served as a co-author of "ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation" which won an Outstanding Paper Award at the NeurIPS 2023 Conference in New Orleans. ClimSim comprises multi-scale climate simulations, developed by a consortium of climate scientists and ML researchers. The project aims to create more accurate climate projections; you can read more about their progress here.