High-latitude ionospheric plasma turbulence: advanced analysis methods and results

In recent years, a great progress has been made in improving our understanding of irregular behaviour of physical processes. A fundamental result of this study is that even a simple, deterministic, but nonlinear and dissipative system can exhibit irregular, random-like behaviour. Before applying sophisticated, nonlinear methods of data analysis, it is necessary to test if the data show signatures of nonlinearity. The surrogate data test bas become a popular and simple tool used to distinguish between stochastic and nonlinear nature of the process hidden in the data. We briefly describe the surrogate test algorithm and show that small-scale ionospheric plasma irregularities are generated in the nonlinear processes. The wavelet transform is a relatively new technique which allows for decomposition of a signal into both space and scale contributions. It proved to be an effective diagnostic tool in studying fluid turbulence and can find application in the ionosphere. The basic notion of the wavelet transform is briefly described and several examples of its application to the analysis of ionospheric plasma turbulence are given. In particular, we discuss higher order statistic, evidence for the cascade processes, and the local properties of the turbulence.