Opportunities for Skillful Weather Prediction

Today on the show we have Elizabeth Barnes, Associate Professor in the department of Atmospheric Science at Colorado State University, who joins us to talk about her work Identifying Opportunities for Skillful Weather Prediction with Interpretable Neural Networks. Find more from the Barnes Research Group on their site.

Weather is notoriously difficult to predict. Complex systems are demanding of computational power. Further, the chaotic nature of, well, nature, makes accurate forecasting especially difficult the longer into the future one wants to look. Yet all is not lost!

In this interview, we explore the use of machine learning to help identify certain conditions under which the weather system has entered an unusually predictable position in it’s normally chaotic state space.

Guest

Elizabeth Barnes: Dr. Elizabeth (Libby) Barnes' research focuses on understanding Earth system variability, predictability, and change across time and space, with an emphasis on developing and implementing artificial intelligence tools in a way that mimics scientific human reasoning to improve intrinsic interpretability. Her overarching research goal is to responsibly harness AI to anticipate human-Earth system futures in support of a thriving society in the decades ahead. She teaches graduate courses on statistical analysis, machine learning for the Earth sciences, and data-driven forecasting across timescales from days-to-decades.