Control simulation experiments of extreme events with the Lorenz-96 model

The control simulation experiment (CSE) is a recently developed approach to investigate the controllability of dynamical systems, extending the well-known observing system simulation experiment (OSSE) in meteorology. For effective control of chaotic dynamical systems, it is essential to exploit the high sensitivity to initial conditions for dragging a system away from an undesired regime by applying minimal perturbations. In this study, we design a CSE for reducing the number of extreme events in the Lorenz-96 model. The 40 variables of this model represent idealized meteorological quantities evenly distributed on a latitude circle. The reduction of occurrence of extreme events over 100-year runs of the model is discussed as a function of the parameters of the CSE: the ensemble forecast length for detecting extreme events in advance, the magnitude and localization of the perturbations, and the quality and coverage of the observations. The design of the CSE is aimed at reducing weather extremes when applied to more realistic weather prediction models.

Automated summary

The control simulation experiment (CSE) is a newly developed approach for studying the controllability of dynamical systems, based on the well-known observing system simulation experiment (OSSE) in meteorology. The CSE aims to reduce extreme weather events in the Lorenz-96 model by exploiting the system's sensitivity to initial conditions and applying minimal perturbations. The study discusses the impact of various parameters of the CSE on the reduction of extreme events over a 100-year simulation.