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ARIA Opportunity Space: Future Proofing Our Climate and Weather
AI for Safe Climate Cooling
Active climate cooling interventions - such as solar radiation management - carry risks and uncertainties, relying on slow, expensive, and often opaque modelling approaches. Encode Fellow Philine Lou Bommer will develop an explainable AI framework that integrates expert-in-the-loop forecasting with foundation models to rigorously evaluate the safety, effectiveness, and broader system impacts of active climate cooling strategies. This project aims to contribute to a more trustworthy, open, and scientifically robust foundation for evaluating and governing active climate cooling approaches, helping policymakers and researchers navigate pathways to climate resilience while avoiding unintended harm.
Gabi Hegerl's Lab
University of Edinburgh
,
Edinburgh
Hegerl Lab
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Philine is completing a PhD in Explainable AI (XAI) for Climate Science from TU Berlin. She built QuantusXClimate, the first-ever tutorial on XAI evaluation, comparison, and selection for climate teams. She led a projects developing frontier XAI methods and building S2S weather forecasting models, submitting to top-tier ML conferences and interdisciplinary journals.
Gabi Hegerl
Professor of Climate System Science, School of GeoSciences, University of Edinburgh.
Professor Gabi Hegerl, CBE FRS FRSE, is a Professor of Climate System Science, School of GeoSciences, University of Edinburgh. Prof Hegerl's research focuses on the causes of climate change and the causes and consequences of extreme events. She has also been involved in IPCC reports on climate change and work with the world climate research programme on setting priorities for climate research. She is also a fellow of the Royal Society and Royal Society of Edinburgh.
