Causal Inference for Earth System Sciences - Jakob Runge

Explore causal inference techniques for Earth system sciences in this 45-minute conference talk by Jakob Runge, recorded as part of the Machine Learning for Climate KITP conference. Delve into the challenges of informing society about future climate changes at regional and local scales, and discover how big data and machine learning algorithms can provide new opportunities for descriptive and causal inference in climate systems. Examine the potential for data-driven approaches to answer complex questions when combined with modeling experiments and research in model parameterizations. Gain insights into the interdisciplinary efforts to address climate change through collaborative research, combining expertise from earth system and computational sciences. Learn about the conference's role in summarizing current understanding, identifying open questions, and setting the stage for future advancements in climate science research.