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ARIA Opportunity Space: Scoping Our Planet
AI for Climate Interventions
Climate interventions like solar radiation management are risky and poorly evaluated, relying on slow, expensive, and often opaque modeling approaches. Encode fellow Philine Lou Bommer will work with Tipply AI to build an explainable AI framework that combines expert-in-the-loop forecasting and foundation models to assess the safety and effectiveness of climate interventions on a global scale. This research could enable transparent, trustworthy, and adaptive climate intervention planning, empowering policymakers and scientists to avoid dangerous climate thresholds while improving global climate resilience.
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.
