Heterogeneity of the Attractor of the Lorenz '96 Model: Lyapunov Analysis, Unstable Periodic Orbits, and Shadowing Properties
Chiara Cecilia Maiocchi, Valerio Lucarini, Andrey Gritsun and, Yuzuru Sato

TL;DR
This paper investigates the heterogeneity of the Lorenz '96 model's attractor, revealing how dynamical variability affects predictability, stability, and the connection between microscopic chaos and thermodynamics.
Contribution
It provides an extensive numerical analysis of unstable periodic orbits and shadowing properties, highlighting the impact of unstable dimension variability in high-dimensional chaotic systems.
Findings
Variability in unstable dimensions correlates with fluctuations in finite-time Lyapunov exponents.
Regions with different instability levels show significant differences in shadowing quality.
High and low energy states are linked to regions of high and low instability, respectively.
Abstract
The predictability of weather and climate is strongly state-dependent: special and extremely relevant atmospheric states like blockings are associated with anomalous instability. Indeed, typically, the instability of a chaotic dynamical system can vary considerably across its attractor. Such an attractor is in general densely populated by unstable periodic orbits that can be used to approximate any forward trajectory through the so-called shadowing. Dynamical heterogeneity can lead to the presence of unstable periodic orbits with different number of unstable dimensions. This phenomenon - unstable dimensions variability - implies a serious breakdown of hyperbolicity and has considerable implications in terms of the structural stability of the system and of the possibility to describe accurately its behaviour through numerical models. As a step in the direction of better understanding the…
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Taxonomy
TopicsQuantum chaos and dynamical systems · Nonlinear Dynamics and Pattern Formation · Chaos control and synchronization
