Effect of rate of change of parameter on early warning signals for critical transitions

TL;DR

This study investigates how the rate of parameter change affects early warning signals for critical transitions in dynamical systems, demonstrating that faster rates shorten warning times and affect the reliability of indicators like autocorrelation and Hurst exponent.

Contribution

The paper introduces a theoretical model and experimental analysis showing the impact of parameter change rate on early warning signals in a thermoacoustic system with subcritical Hopf bifurcation.

Findings

Warning time decreases with increasing rate of parameter change following an inverse power law.

Lag-1 autocorrelation and Hurst exponent are effective early warning indicators.

Hyperexponential scaling relation observed between autocorrelation and variance during bifurcation.

Abstract

Many dynamical systems exhibit abrupt transitions or tipping as the control parameter is varied. In scenarios where the parameter is varied continuously, the rate of change of control parameter greatly affects the performance of early warning signals (EWS) for such critical transitions.We study the impact of variation of the control parameter with a finite rate on the performance of \textcolor{black}{EWS for critical transitions} in a thermoacoustic system (a horizontal Rijke tube) exhibiting subcritical Hopf bifurcation. There is a growing interest in developing early warning signals for tipping in real systems. Firstly, we explore the efficacy of early warning signals based on critical slowing down and fractal characteristics. From this study, lag-1 autocorrelation (AC) and Hurst exponent H are found to be good measures to predict the transition well-before the tipping point. The warning time, obtained using AC and $H$, reduces with an increase in the rate of change of the control parameter following an inverse power law relation. Hence, for very fast rates, the warning time may be too short to perform any control action. Furthermore, we report the observation of a hyperexponential scaling relation between the AC and the variance of fluctuations during such dynamic Hopf bifurcation. We construct a theoretical model for noisy Hopf bifurcation wherein the control parameter is continuously varied at different rates to study the effect of rate of change of parameter on EWS. Similar results, including the hyperexponential scaling, are observed in the model as well.