Can machine learning help predict extreme weather events and climate change? Christopher Bretherton, senior director of climate modeling at the Allen Institute for Artificial Intelligence, or AI2, explores the technology’s potential to enhance climate modeling with AI Podcast host Noah Kravitz in an episode recorded live at the NVIDIA GTC global AI conference. Bretherton explains how machine learning helps overcome the limitations of traditional climate models and underscores the role of localized predictions in empowering communities to prepare for climate-related risks. Through ongoing research and collaboration, Bretherton and his team aim to improve climate modeling and enable society to better mitigate and adapt to the impacts of climate change.
Stay tuned for more episodes recorded live from GTC, and watch the replay of Bretherton’s GTC session on using machine learning for climate modeling.
Time Stamps
2:03: What is climate modeling and how can it prepare us for climate change?
5:28: How can machine learning help enhance climate modeling?
7:21: What were the limitations of traditional climate models?
10:24: How does a climate model work?
12:11: What information can you get from a climate model?
13:26: What are the current climate models telling us about the future?
15:56: How does machine learning help enable localized climate modeling?
18:39: What, if anything, can individuals or small communities do to prepare for what climate change has in store for us?
25:59: How do you measure the accuracy or performance of an emulator that’s doing something like climate modeling out into the future?
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