2025 Gordon Research Conference on Machine Learning for Actionable Climate Science

The Machine Learning for Actionable Climate Science GRC is a premier, international scientific conference focused on advancing the frontiers of science through the presentation of cutting-edge and unpublished research, prioritizing time for discussion after each talk and fostering informal interactions among scientists of all career stages. The conference program includes a diverse range of speakers and discussion leaders from institutions and organizations worldwide, concentrating on the latest developments in the field. The conference is five days long and held in a remote location to increase the sense of camaraderie and create scientific communities, with lasting collaborations and friendships. In addition to premier talks, the conference has designated time for poster sessions from individuals of all career stages, and afternoon free time and communal meals allow for informal networking opportunities with leaders in the field.

Machine Learning (ML) in Climate Science represents a promising and growing path of research that could contribute to substantially enhancing our understanding of the Earth system and reducing uncertainty in climate projections. ML has already started to make a tremendous contribution to Earth system science and is rapidly evolving to include new methodologies and applications. Climate modeling and analysis are facing new demands to enhance projections and climate information. This GRC conference will explore how to best push the frontiers of ML beyond state-of-the-art approaches, in particular in the fields of (1) developing hybrid (physics+ML) Earth system models with greater fidelity, (2) providing capabilities for climate extremes through large ensembles with emulators as well as enhancing detection and attribution methods, and (3) advancing climate model analysis and benchmarking. Utilizing this potential requires addressing (4) key ML challenges, in particular generalization, uncertainty quantification, explainable artificial intelligence, and causality that will be discussed as well. This interdisciplinary conference brings together ML and climate scientists, as well as the private sector, to accelerate progress towards actionable climate science.