A new early warning indicator of abrupt climate change based on the changing normalized dynamic range

An abrupt change will occur when the system is forced to across a critical threshold. This study presents a novel early warning indicator—the changing normalized dynamic range. We use a one‐variable climate model and three simple folding models to test the performance of the new early warning indicator. The results show that the present indicator exhibits a statistically significant increase or decrease in all of tests at a significance level of α = .05 before a dynamical system with a folding bifurcation approaches a tipping point. Comparing the well‐known autocorrelation coefficient with the normalized dynamic range, it is found that autocorrelation coefficient performs well in most of tests, which shows an almost monotonous increasing or decreasing trend for an upcoming abrupt change. However, autocorrelation coefficient exhibits a diametrically opposite trend for a noise‐induced abrupt change in a two‐dimensional vegetable model. The kurtosis coefficient can perform well in most of the tests used in this study, however, fails to give an early warning in a particular case. Moreover, the magnitude of change of the autocorrelation and kurtosis is much smaller than that of the normalized dynamic range before the four folding models approach its tipping point. Therefore, the performance of the new indicator for warning an abrupt change in advance is better than that of the autocorrelation coefficient as well as kurtosis coefficient, which can make up for the deficiency of the kurtosis coefficient and autocorrelation coefficient to some extent. An abrupt change can occur when a dynamical system approaches a tipping point, which will result in an abrupt shift from one stable state to another stable state. Our results indicate that the changing normalized dynamic range can provide an effectively early warning signal before the generalized logistic model approaches its tipping point.