Nonlinear analysis of magnetospheric data Part II. Dynamical characteristics of the AE index time series and comparison with nonlinear surrogate data

In this study we have used dynamical characteristics such as Lyapunov expon ents, nonlinear dynamic models and mutual information for the nonlinear ana lysis of the magnetospheric AE index time series. Similarly with the geomet rical characteristic studied in Pavlos ct al. (1999b), we have found signif icant differences between the original time series and its surrogate data. These results also suggest the rejection of the null hypothesis that the AE index belongs to the family of stochastic linear signals undergoing a stat ic nonlinear distortion. Finally, we believe that these results support the hypothesis of nonlinearity and chaos for the magnetospheric dynamics.