[1] Clustering and intermittency in atmospheric turbulent flows above different natural surfaces are investigated with reference to their dependency on surface roughness and thermal stratification. The dualism between active and quiescent phases within measured time series is isolated by using the telegraphic approximation (TA), which is able to eliminate the contributions to intermittency originating from amplitude variability associated with the energetic states. The presence of linear correlation relating the scaling exponents of energy spectra for the original series (n) and its TA counterpart (m) within the inertial sub-range (ISR) suggests that amplitude variability acts as a de-correlation factor for the series. Clustering exponents a estimated from velocity and scalar time series exhibit a weak dependence on the Taylor micro-scale Reynolds number (Re l ).The average values of intermittency exponents for the original (m s ) and the TA series (m TA ) are linearly correlated to a for longitudinal velocity and scalars. The derived relationships shows that in the atmospheric surface layer (ASL), amplitude intermittency plays a smoothing role on the clusterization of events. On the other hand, within the canopy sublayer (CSL) above canopies, scalars are more clustered and amplitude excursions tend to amplify (or not alter) clusterization. Moreover, reducing surface roughness results in a de-correlation between a and m TA for the vertical velocity component. Additionally, the probability density functions of inter-pulse periods (I p ) were shown to be well approximated by the law p(I p ) $ I p Àg for I p within the ISR when g ≈ 3 À m, which also holds for sand pile models of self organized criticality in the large pile limit.Citation: Cava, D., G. G. Katul, A. Molini, and C. Elefante (2012), The role of surface characteristics on intermittency and zero-crossing properties of atmospheric turbulence,

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