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Published on: July 19, 2016
Evidence for a fluctuation theorem in an atmospheric circulation model
Summary
Global circulation models show negative largest Lyapunov exponents, indicating predictable atmospheric behavior for up to 10 days. This finding aligns with entropy production theories.
Area of Science:
- Atmospheric science
- Climate modeling
- Dynamical systems theory
Background:
- Understanding atmospheric predictability is crucial for weather forecasting and climate science.
- Finite-time trajectory divergence in global circulation models (GCMs) is a key indicator of predictability.
- Lyapunov exponents quantify the rate of separation of infinitesimally close trajectories in a dynamical system.
Purpose of the Study:
- To investigate the distribution of finite-time trajectory divergence in a GCM.
- To analyze the behavior of the largest local Lyapunov exponent over various time scales and resolutions.
- To compare the findings with theoretical predictions, such as the fluctuation theorem for entropy production.
Main Methods:
- Utilized a hydrostatic atmospheric global circulation model.
- Performed simulations with variable vertical levels and different horizontal resolutions (up to wave number ℓ=42, approximately 250 km).
- Analyzed the distribution of the largest local Lyapunov exponent for finite time spans.
Main Results:
- A significant probability of negative values for the largest local Lyapunov exponent was observed over time spans up to 10 days.
- This negative exponent probability was present even at relatively high resolutions (up to ℓ=42).
- The probability of a negative largest local Lyapunov exponent decreased over time, consistent with fluctuation theorem predictions for entropy production.
Conclusions:
- The study demonstrates periods of enhanced predictability in atmospheric GCMs, evidenced by negative largest local Lyapunov exponents.
- Findings suggest that atmospheric dynamics may exhibit more order than typically assumed over certain time scales.
- The results support theoretical frameworks linking predictability to entropy production in complex systems.
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