Session

DescriptionIn recent years weather forecasting and to a lower extent climate modeling have been undergoing a revolution driven by the emergence of machine learning-based models. After having been successfully developed and used in the field of Large Language Model, the foundation model concept is being applied to machine learning-based weather-forecasting. The goal is to capture rich, multi-scale representations of the Earth system across space and time by training on diverse datasets. These models can then be applied to a wide range of tasks, much like traditional equation-based Earth system models. The first large foundation models are now emerging, and their potential applications are actively being explored. The talks in this minisymposium will define the concept of foundation models for weather and climate, discuss both their development and applications, and provide a comprehensive overview of the current state of the field.