Effects of sampling frequency on magnitude and sign correlations in small-scale wind speed fluctuations

The magnitude and sign of a time series measured from physical process contain rich information about the dynamical mechanisms. In this paper, we study the scaling properties of the magnitude and the sign from the small-scale wind speed fluctuations using the detrended fluctuation analysis (DFA), and show the impact of sampling frequency on their scaling properties. We find long-range positive correlations in the magnitude sub-series, which are weaker as sampling frequency decreases. In contrast, we find short-range anti-correlations in sign sub-series, which are almost the same under different sampling frequencies. Since the magnitude series relates to the nonlinear properties of the original time series and the sign series relates to the linear properties, our findings suggest that the nonlinearity of the wind speed gradually loses with the sampling frequency decreasing. These results yield deep insight into the dynamic behaviors underlying the small-scale wind records, and would be particularly helpful in appropriate anemometer selection applications.