Skewed superstatistical distributions from a Langevin and Fokker-Planck approach

Abstract

The superstatistics concept is a useful statistical method to describe inhomogeneous complex systems for which a system parameter $\beta$ fluctuates on a large spatio-temporal scale. In this paper we analyze a measured time series of wind speed fluctuations and extract the superstatistical distribution function $f(\beta )$ directly from the data. We construct suitable Langevin and Fokker-Planck models with a position dependent $\beta$-field and show that they reduce to standard type of superstatistics in the overdamped limit.

7 pages, 6 figures

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