Nonlinear chaos-dynamical approach to analysis of atmospheric radon 222Rn concentration time series
We present the theoretical foundations of an effective universal complex chaos-dynamical approach to the analysis and prediction of atmospheric radon 222Rn concentration using the beta particle activity data of radon monitors (with a pair of Geiger–Muller counters). The approach presented consistently includes a number of new or improved available methods (correlation integral, fractal analysis, algorithms of average mutual information and false nearest neighbors, Lyapunov’s exponents, surrogate data, nonlinear prediction schemes, spectral methods, etc.) of modeling and analysis of atmospheric radon 222Rn concentration time series. We first present the data on the topological and dynamical invariants for the time series of the 222Rn concentration. Using the data measurements of the radon concentration time series at SMEAR II station of the Finnish Meteorological Institute, we found the elements of deterministic chaos.
PACS Nos 05.45.+b; 42.50.Ne; 42.55.Px; 42.65.Pc