Analysis Of Extreme Events And Phase Synchronization In Complex Climate System

At present,global warming is an indisputable fact.Extreme events are having great impacts on human society.It is very important to explore the mechanism of extreme events,which has attracted great attention of us and government policymakers all over the world.In recent years,nonlinear time series analysis method based on chaotic theory has provided scientists with new ideas for understanding the occurrences of extreme events.In this paper,we use nonlinear dynamics method in statistical physics to analyze the complexity of climate systems.We discuss the characteristics of EI Ni?o in lowdimensional chaotic dynamical systems,as well as apply phase synchronization method to reveal teleconnections,a kind of nonlinear interaction,among different regions.Firstly,we study the dynamical characteristics of extreme events as generated by a low-order ENSO model,as well as figure out the consistency of extreme events between the model and the real observations.In addition,machine learning is applied to chaotic series prediction.Results show that low-order ENSO model can well describe the statistical characteristics of El Ni?o extreme events.By the time series predicted by machine learning show the same statistical features,which provide us with better understanding of the dynamical behavior of ENSO and the mechanisms of the associated extreme events.We are able to better understand the ENSO dynamical behavior as well as the mechanisms behind the occurrence of extreme events.Secondly,we generalize the traditional phase synchronization method to conduct teleconnection analysis among distinct regions of the Earth.In particular,we show the mutual couplings between the rainfall in Northeastern Brazil and the surrounding oceans,focusing on the continuous drought events in the recent decade.From the perspective of complex system,this paper shows that the sea surface temperature of tropical North Atlantic has a direct dominant role on the drought.Furthermore,we find that there is a conspicuous phase synchronization between El Ni?o Southern Oscillation and the North Atlantic Ocean.In addition,we show the different modulation effects of strong El Ni?o and strong La Ni?a on the instantaneous angular frequency of sea surface temperature,increasing the probability of phase synchronization between different regions.This work deepens our understanding of extreme events,which helps us to improve the current regional climate model and provides guidance for early prediction of extreme events.