The stochastic resonance mechanism in the Aerosol Index dynamics
  We consider Aerosol Index (AI) time-series extracted from TOMS archive for an area covering Italy $(7-18^o E ; 36-47^o N)$. The missing of convergence in estimating the embedding dimension of the system and the inability of the Independent Component Analysis (ICA) in separating the fluctuations from deterministic component of the signals are evidences of an intrinsic link between the periodic behavior of AI and its fluctuations. We prove that these time series are well described by a stochastic dynamical model. Moreover, the principal peak in the power spectrum of these signals can be explained whereby a stochastic resonance, linking variable external factors, such as Sun-Earth radiation budget and local insolation, and fluctuations on smaller spatial and temporal scale due to internal weather and antrophic components. 
S. De Martino, M. Falanga, L. Mona