Using AI to predict the weather

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.

•[10:47] Qiang Sun explains how he and his colleagues tested the ability of AI to predict gray swans.

•[12:28] Final thoughts and conclusion.