Nonlinear Feature of the Abrupt Transitions between Multiple Equilibria States of an Ecosystem Model

Based on a five-variable theoretical ecosystem model, the stability of equilibrium state and the nonlinear feature of the transition between a grassland state and a desert state are investigated. The approach of the conditional nonlinear optimal perturbations （CNOPs）, which are the nonlinear generalization of the linear singular vectors （LSVs）, is adopted. The numerical results indicate that the linearly stable grassland and desert states are nonlinearly unstable to large enough initial perturbations on the condition that the moisture index # satisfies 0.3126 〈 μ 〈 0.3504. The perturbations represent some kind of anthropogenic influence and natural factors. The results obtained by CNOPs, LSVs and Lyapunov vectors （LVs） are compared to analyze the nonlinear feature of the transition between the grassland state and the desert state. Besides this, it is shown that the five-variable model is superior to the three-variable model in providing more visible signals when the transitions occur.

AUTO-EXTRACTING TECHNIQUE OF DYNAMIC CHAOS FEATURES FOR NONLINEAR TIME SERIES

The main purpose of nonlinear time series analysis is based on the rebuilding theory of phase space, and to study how to transform the response signal to rebuilt phase space in order to extract dynamic feature information, and to provide effective approach for nonlinear signal analysis and fault diagnosis of nonlinear dynamic system. Now, it has already formed an important offset of nonlinear science. But, traditional method cannot extract chaos features automatically, and it needs man＇s participation in the whole process. A new method is put forward, which can implement auto-extracting of chaos features for nonlinear time series. Firstly, to confirm time delay r by autocorrelation method; Secondly, to compute embedded dimension m and correlation dimension D; Thirdly, to compute the maximum Lyapunov index λmax; Finally, to calculate the chaos degree Dch of Poincare map, and the non-circle degree Dnc and non-order degree Dno of quasi-phase orbit. Chaos features extracting has important meaning to fault diagnosis of nonlinear system based on nonlinear chaos features. Examples show validity of the proposed method.

An experimental study of the relations between bispectra and nonlinear apparent features of wind waves

To investigate the nonlinear properties of wind waves, experiments are carried out in a wind-wave flume with slope bottom at different wind speeds and fetches. Both the internal structure and apparent features of the nonlin-earity of wind waves are studied by using bispectral and statistical analysis of surface elevations. The relations between bispectra and nonlinear apparent characteristics of wind waves are established and confirmed.

A Further Study on an Extended Nonlinear Ocean-Atmosphere Coupled Hydrodynamic Characteristic System and the Abrupt Feature of ENSO Events

An extended ocean-atmosphere coupled characteristic system including thermodynamic physical processes in ocean mixed layer is formulated in order to describe SST explicitly and remove possible limitation of ocean-atmosphere coupling assumption in hydrodynamic ENSO models. It is revealed that there is a kind of abrupt nonlinear characteristic behaviour, which relates to rapid onset and intermittency of El Nino events, on the second order slow time scale due to the nonlinear interaction between a linear unstable low-frequency primary eigen component of ocean-atmosphere coupled Kelvin wave and its higher order harmonic components under a strong ocean-atmosphere coupling background. And, on the other hand, there is a kind of finite amplitude nonlinear characteristic behaviour on the second order slow time scale due to the nonlinear interaction between the linear unstable primary eigen component and its higher order harmonic components under a weak ocean-atmosphere coupling background in this model system.