Using AI to predict the weather
About this episode
This episode discusses advances in AI-enabled weather forecasting with insights from various researchers.
Using AI to predict the weather Science Sessions are brief conversations with cutting-edge researchers, National Academy members, and policymakers as they discuss topics relevant to today's scientific community. Learn the behind-the-scenes story of work published in the Proceedings of the National Academy of Sciences (PNAS), plus a broad range of scientific news about discoveries that affect the world around us. In this episode, researchers discuss advances in AI-enabled weather forecasting. In this episode, we cover: •[00:00] Introduction •[01:12] Jeffrey Shrader explains what 48 expert forecasters had to say about how weather predictions might further improve through 2100, including the potential role of AI. •[03:43] Ignacio Lopez-Gomez explains how he used generative AI to downscale large-scale earth system models into finer-scale regional climate projections. •[05:35] Xiaofeng Li explains how he used a machine learning model to forecast whether tropical cyclones will rapidly intensify. •[07:40] Hui Su explains what nowcasting is and how her deep diffusion model works. •[09:52] Pedram Hassanzadeh explains what grey swans are and why they may be challenging for AI to predict…
People in this episode
Guests: Jeffrey Shrader, Ignacio Lopez-Gomez, Xiaofeng Li, Hui Su, Pedram Hassanzadeh, Qiang Sun
Topics covered
- AI in weather forecasting
- climate projections
- machine learning
- tropical cyclones
- nowcasting
- grey swans
Keywords
- AI
- weather forecasting
- climate models
- machine learning
- tropical cyclones
- nowcasting
- grey swans
Mentioned in this episode
Organizations: Columbia University, Google
Books & works: Proceedings of the National Academy of Sciences
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