Targeted adaptive chaos control of regimes and eddy strength in two Lorenz models

Abstract. Extreme weather events present growing challenges as climate changes. "Weather Jiu-Jitsu" is a proposal to nudge atmospheric circulation to redirect or defuse these extreme events by leveraging the sensitivity of chaotic atmospheric dynamics to initial conditions. We demonstrate an optimal control strategy to stabilize two low-order models of atmospheric dynamics, the Lorenz 63 (L63) and Lorenz 84 (L84). Estimated local Lyapunov exponents (LLE) are used to decide when to apply control. In L63, regime transitions are treated as model analogs of persistent circulation states of concern, while in L84, large eddy amplitudes serve as conceptual surrogates for synoptic-scale moisture transport events such as atmospheric rivers. The timing and amplitude of nudges is solved over a forecast horizon to minimize the total energy applied, while ensuring that the trajectory remains within predefined bounds to avert undesirable consequences. We explicitly incorporate multiplicative noise, randomly selecting a trajectory from an ensemble forecast to apply control, thus reflecting the mismatch between model and reality that would arise in operational applications.