EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Control Simulation Experiments with the Lorenz-96 Model

Qiwen Sun1,4, Takemasa Miyoshi1,2,3, and Serge Richard1,4
Qiwen Sun et al.
  • 1Data Assimilation Research Team, RIKEN Center for Computational Science (R-CCS), Kobe, Japan
  • 2Prediction Science Laboratory , RIKEN Cluster for Pioneering Research (CPR), Kobe, Japan
  • 3RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS), Wako, Japan
  • 4Graduate School of Mathematics, Nagoya University, Nagoya, Japan

The successful development of numerical weather prediction (NWP) helps better preparedness for extreme weather events. Weather modifications have also been explored, for example, when enhancing rainfalls by cloud seeding. However, it is generally believed that the tremendous energy involved in extreme events prevents any attempt of human interventions to avoid or to control their occurrences.

In this study, we investigate the controllability of a chaotic dynamical system by adding small perturbations to generate amplified effects and to prevent extreme events. The high sensitivity to initial conditions would ultimately lead to modifications of extreme events with infinitesimal perturbations. Based on this idea, we extend the well-known observing systems simulation experiment (OSSE) and design the control simulation experiment (CSE) with the Lorenz-96 model, a widely-used toy system in data assimilation studies. We also study the sensitivity of the control to the amplitude of the perturbation, the forecast length, the localized perturbation and the partial observations. The CSE would be applicable to other chaotic dynamical systems including realistic numerical weather prediction models.

How to cite: Sun, Q., Miyoshi, T., and Richard, S.: Control Simulation Experiments with the Lorenz-96 Model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3313,, 2022.

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