Application of nonlinear dynamical methods in abrupt climate change detection

Abstract

The research of abrupt climate change is an important field in the climate change. The rapid and accurate detection of the abrupt climate change has important practical significance and major economic-social costs, which will help us understand climate change and forecast the future evolutionary trend of the climate system. The detection results of most traditional abrupt climate change depend on the selection of the time scale concerned, which may result in the fact that we cannot identify an abrupt climate change until the event has been past for a long time. Moreover, these detection methods cannot extract the dynamical changes from the observational data of the climate system. As the rapid development in nonlinear science, the abrupt climate change detection technology has also been improved gradually. This article briefly reviews several new progresses in abrupt dynamical detection methods developed on the basis of recent nonlinear technologies, and some applications in the real observational data. These new methods mainly contain the technologies based on the long-range correlation of climate systems, such as moving detrended fluctuation analysis, moving cut data-detrended fluctuation analysis, moving cut data-R/S analysis, degenerate fingerprinting, and red noise. Moreover, some abrupt dynamical detection methods developed by the complexity of the time series, namely, entropy, such as approximate entropy, moving cutting data-approximate entropy, Fisher information, and wavelet Fisher's information measure. Furthermore, there are some other abrupt dynamical detection methods based on the theory of phase space, such as the dynamics exponent Q. Climate system is a complex dynamical system with nonlinear and interactive nature, which has long-range persistence in spatio-temporal variation, thus the abrupt detection method on spatial field change is pointed out to be a promising direction for further research in future. Because the spatial field contains abundance of information about the evolution of climate system which is much more than that in a time series in single meteorological station, the detecting methods on spatial field will greatly help us detect an abrupt climate change as soon as possible. And then we will have enough time to take action and make preparations for the new challenges due to the abrupt climate change.