Most often observations and measurements of geophysical systems and dynamical phenomena are obtained as time series. Dynamics of the system are inferred from characteristics of these time series. In this short course different methods of time series analysis will be explained. Results from nonlinear and nonstationary decomposition methods (as the Empirical Mode Decomposition or its multivariate extension), time-frequency techniques (e.g., Wavelets and Fourier analysis), stochastic and chaotic approaches as well as fractal and multifractal methods (as DFA, MF-DFA, ROMA and novel fractal-based approaches), applied in different fields, from climate to solar wind turbulence, will be presented.

The focus will be on comparison between different methods for similar studies that should be helpful to investigate several aspects of both known and identify unknown physical processes.