2026/06/24 by Q. Huang, Moyan Liu, Upmanu Lall · 1 voice
Earth and Planetary Sciences · Engineering · #Infrastructure Resilience and Vulnerability Analysis #Meteorological Phenomena and Simulations #Tropical and Extratropical Cyclones Research
paper · doi:10.1371/journal.pwat.0000562
openalex publication_date 2026/06/24 · openalex created_date 2026/06/25 · openalex updated_date 2026/06/26
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.