PODCAST: What's the Real Definition of Public Service Education? With Fellows David Van Slyke and Susan Gooden Season 2 · Ep 47
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Future risk is often assessed inaccurately. And even when it is assessed well, it often goes un-acted upon. Why?
Check out our global webinar series for scholars, policymakers, and practitioners working on climate adaptation and extreme weather. The series builds essential knowledge in the fields that support good governance work — climate science, risk analysis, and applied data tools.
Leading voices in climate risk science join the governance community in direct conversation, creating a shared knowledge base across disciplines. We're all working to strengthen how risk science becomes real institutional and financing action.
This series is jointly sponsored by:
Climate risk and weather forecasting are often confused, but they answer very different questions, on very different timescales, with very different levels of uncertainty.
This opening session explored the fundamentals governance practitioners need to interpret climate risk information accurately: what risk and uncertainty mean in a climate context, how input assumptions shape model outputs, and how downscaling translates global climate data into local, decision-relevant information.
The session also introduced a new generation of AI-accelerated climate modeling — an approach that promises faster, higher-resolution risk information than traditional methods have allowed. Speakers discussed what this shift makes possible, and what governance practitioners should understand about its strengths and limits.
Speakers: Tapio Schneider, Theodore Y. Wu Professor of Environmental Science and Engineering, Caltech, and Lead, Climate Modeling Alliance (CliMA)
Ailie Gallant, Associate Professor, School of Earth, Atmosphere and Environment, Monash University
Moderator: Michael Spencer, Research Fellow, Impact Labs, Monash University
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