Causality for Climate Science

This course explores the use of causal inference methods, which deal with understanding and quantifying cause-and-effect relationships from data and model assumptions, in the climate and Earth system sciences, covering both theoretical and practical challenges. The course begins with an introduction to causal inference and attribution in climate science before diving into specific adaptations of the methods for spatiotemporal dynamical systems (Block 1). Then, Block 2 focuses on the use of causal inference for tipping elements with applications to early-warning detection of tipping and causal representations of feedbacks. Block 3 introduces advanced topics including regime-oriented methods and helps students to formulate a project proposal. Throughout the blocks, students engage in hands-on implementation exercises to gain practical experience with state-of-the-art methods. After completing all three blocks, students work in groups to develop an independent research project on a topic of their choice from any of the covered areas. Projects are presented in a concluding session.