Statistical and wavelet analysis of the solar wind data

Abstract

We perform statistical and wavelet analysis of three time series based on the solar wind velocity of the year 2000, the original time series and two filtered components. We use the Haar Wavelet Transform to separate this annual time-series into two parts, corresponding to high and low frequencies. We then calculate the kurtosis and skewness parameters for the three time-series. The results show that these parameters present high values in the low-pass filtered time-series, indicating that the intermittence level is superior at large scales (low-frequencies) if compared with the small scales of the turbulence. It is possible to conjecture that the Coherent Structures are responsible for this behavior. The use of the Morlet Wavelet Transform is presented to understand this behavior in terms of the gradient and nonlinear interaction of energy between scales.

Investigation of Intermittency in Magnetohydrodynamics and Solar Wind Turbulence: Scale-Dependent Kurtosis

“…In this way, the influence of small-scale coherent structures in producing intermittency can be detected. The usual way that this has been implemented (Voros et al 2002;Bruno et al 2003;Bolzan 2005;Chian & Miranda 2009) is to compute the kurtosis of the increments of the fluctuations. Then letting the increment lag become smaller, one expects increased kurtosis if smallscale coherent structures are present.…”