Weather Jiu-Jitsu: Prospects for atmospheric nudging to defuse the impact of catastrophic weather extremes

Qin Huang, Moyan Liu and Upmanu Lall

PLOS Water, 2026, vol. 5, issue 6, 1-11

Abstract: 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. We propose supplementing disaster management with Weather Jiu-Jitsu: a strategy that exploits the chaotic sensitivity of mid-latitude atmospheric dynamics to redirect destructive weather trajectories through small, precisely timed perturbations guided by Finite-Time Lyapunov Exponent (FTLE) diagnostics and deep learning forecast models. Proof-of-concept experiments using the Aurora deep-learning Earth system model show that FTLE-guided nudges applied days before peak impact can shift a hurricane track to avoid landfall on a major city, weaken the peak intensity of a blocking-driven cold extreme, and reduce atmospheric river moisture transport under favorable upstream conditions. Control inputs remain below 2% of total system energy in idealized models, though real-world implementation will require advances in monitoring, attribution, and international governance. This nature-assisted approach could form a transformative complement to conventional disaster management in the 21st century.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pwat00:0000562

DOI: 10.1371/journal.pwat.0000562

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