Quantifying nonergodicity in nonautonomous dissipative dynamical systems

An application to climate change

Gábor Drótos, Tamás Bódai, Tamás Tél

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In nonautonomous dynamical systems, like in climate dynamics, an ensemble of trajectories initiated in the remote past defines a unique probability distribution, the natural measure of a snapshot attractor, for any instant of time, but this distribution typically changes in time. In cases with an aperiodic driving, temporal averages taken along a single trajectory would differ from the corresponding ensemble averages even in the infinite-time limit: ergodicity does not hold. It is worth considering this difference, which we call the nonergodic mismatch, by taking time windows of finite length for temporal averaging. We point out that the probability distribution of the nonergodic mismatch is qualitatively different in ergodic and nonergodic cases: its average is zero and typically nonzero, respectively. A main conclusion is that the difference of the average from zero, which we call the bias, is a useful measure of nonergodicity, for any window length. In contrast, the standard deviation of the nonergodic mismatch, which characterizes the spread between different realizations, exhibits a power-law decrease with increasing window length in both ergodic and nonergodic cases, and this implies that temporal and ensemble averages differ in dynamical systems with finite window lengths. It is the average modulus of the nonergodic mismatch, which we call the ergodicity deficit, that represents the expected deviation from fulfilling the equality of temporal and ensemble averages. As an important finding, we demonstrate that the ergodicity deficit cannot be reduced arbitrarily in nonergodic systems. We illustrate via a conceptual climate model that the nonergodic framework may be useful in Earth system dynamics, within which we propose the measure of nonergodicity, i.e., the bias, as an order-parameter-like quantifier of climate change.

Original languageEnglish
Article number022214
JournalPhysical Review E - Statistical, Nonlinear, and Soft Matter Physics
Volume94
Issue number2
DOIs
Publication statusPublished - Aug 24 2016

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Dissipative Dynamical System
Nonautonomous Dynamical System
Climate Change
climate change
dynamical systems
Ensemble
Ergodicity
Probability Distribution
trajectories
Trajectory
Climate Models
climate models
Snapshot
Time Windows
Zero
Conceptual Model
Quantifiers
System Dynamics
Climate
Instant

ASJC Scopus subject areas

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Condensed Matter Physics

Cite this

Quantifying nonergodicity in nonautonomous dissipative dynamical systems : An application to climate change. / Drótos, Gábor; Bódai, Tamás; Tél, Tamás.

In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, Vol. 94, No. 2, 022214, 24.08.2016.

Research output: Contribution to journalArticle

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