Turning chaotic sensitivity from a bug into a feature: Using physical modeling and deep learning to alter the paths of storms and mitigate extreme weather events

Statistical Modeling, Causal Inference, and Social Science 2026-07-06

Summary:

Qin Huang, Moyan Liu, and Upmanu Lall write: Extreme weather events, e.g., droughts, floods, heatwaves, and freezes, are increasing in frequency and intensity, posing severe socio-economic impacts as growing populations heighten exposure to risks that conventional infrastructure cannot fully address. … Continue reading

Link:

https://statmodeling.stat.columbia.edu/2026/07/06/turning-chaotic-sensitivity-from-a-bug-into-a-feature-using-physical-modeling-and-deep-learning-to-alter-the-paths-of-storms-and-mitigate-extreme-weather-events/

From feeds:

Statistics and Visualization » Statistical Modeling, Causal Inference, and Social Science

Tags:

miscellaneous

Authors:

Andrew

Date tagged:

07/06/2026, 15:14

Date published:

07/06/2026, 09:36