We present a new type of deterministic dynamical behaviour that is less predictable than white noise. We call it anti-deterministic (AD) because time series corresponding to the dynamics of such systems do not generate deterministic lines in recurrence plots for small thresholds. We show that...

Coarse grained dynamical entropies characterize in a quantitative way the precision-dependent predictability of a system. This gives a much more complete description than solely the Kolmogorov–Sinai entropy. The concept is applied to two classes of high-entropic systems, to one class which...

The distribution of recurrence times or return intervals between extreme events is important to characterize and understand the behavior of physical systems and phenomena in many disciplines. It is well known that many physical processes in nature and society display long range correlations....

A continuous state Markov chain of suitable order is employed to approximate the dynamics of surface wind speeds recorded at a single site. Using past observations, the model yields probabilistic forecasts of the future. We employ it for the prediction of turbulent gusts.

Deterministic dynamical systems of Langevin type recently introduced by Beck and Roepsdorf (Physica A 145 (1987) 1) generate Langevin dynamics in a suitable limit. We discuss the transition from chaos to randomness in these systems under the point of view of the attractor dimension and dynamical...

We analyse the statistics of extreme events in the boundary layer wind fields. We focus on the wind speeds that are long-term correlated and show that its distribution of the return intervals of rare events is a stretched exponential and the stretching exponent, to within the numerical errors,...