Reducing manipulations in a control simulation experiment based on instability vectors with the Lorenz-63 model

Controlling weather is an outstanding and pioneering challenge for researchers around the world, due to the chaotic features of the complex atmosphere. A control simulation experiment (CSE) on the Lorenz-63 model, which consists of positive and negative regimes represented by the states of variable x, demonstrated that the variables can be controlled to stay in the target regime by adding perturbations with a constant magnitude to an independent model run . The current study tries to reduce the input manipulation of the CSE, including the total control times and magnitudes of perturbations, by investigating how controls affect the instability of systems. For that purpose, we first explored the instability properties of Lorenz-63 models without and under control. Experiments show that the maximum growth rate of the singular vector (SV) reduces when the variable x was controlled in the target regime. Subsequently, this research proposes to update the magnitude of perturbations adaptively based on the maximum growth rate of SV; consequently, the times to control will also change. The proposed method successfully reduces around 40 % of total control times and around 20 % of total magnitudes of perturbations compared to the case with a constant magnitude. Results of this research suggest that investigating the impacts of control on instability would be beneficial for designing methods to control the complex atmosphere with feasible manipulations.

Automated summary

Controlling weather is a challenging task due to the chaotic nature of the atmosphere. This study uses a control simulation experiment on the Lorenz-63 model to demonstrate that variables can be controlled by adding perturbations with a constant magnitude. By investigating the impact of controls on system instability, the researchers propose an adaptive method to update the magnitude of perturbations, leading to a reduction in control times and magnitudes. The results suggest that understanding the effects of control on instability is beneficial for designing feasible methods to control the complex atmosphere.