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Predicting regime changes and durations in Lorenz's atmospheric convection model
Eduardo L Brugnago1, Jason A C Gallas2, Marcus W Beims1
1Departamento de Física, Universidade Federal do Paraná, 81531-980 Curitiba, Brazil.
Chaos (Woodbury, N.Y.)
|November 3, 2020
Summary
Characteristic alignment of Lyapunov vectors predicts regime changes and duration in the Lorenz model. Combining this with bred vector expansion improves prediction accuracy for atmospheric convection models.
Area of Science:
- * Atmospheric science and dynamical systems.
- * Nonlinear dynamics and chaos theory.
Background:
- * The Lorenz model is a fundamental simplified model for atmospheric convection.
- * Predicting regime changes and their durations is crucial for weather forecasting.
- * Traditional methods face challenges in accurately forecasting these transitions.
Purpose of the Study:
- * To investigate the predictive power of Lyapunov vector alignment for regime shifts.
- * To develop an improved method for predicting regime durations in the Lorenz model.
- * To assess the effectiveness of combining Lyapunov vector alignment with bred vector expansion.
Main Methods:
- * Analysis of characteristic alignment patterns within Lyapunov vectors.
- * Utilizing maxima in the local expansion of bred vectors.
- * Application to the classical Lorenz model of atmospheric convection.
Main Results:
- * A distinct alignment of Lyapunov vectors effectively predicts regime changes.
- * The alignment also provides insights into the duration of atmospheric convection regimes.
- * The combined method significantly reduces prediction errors for regime durations.
Conclusions:
- * Lyapunov vector alignment offers a robust tool for predicting regime dynamics.
- * The integration with bred vector expansion enhances predictive accuracy.
- * This approach presents a competitive and effective strategy for improving weather model predictions.
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