Detecting Near-Surface Coherent Structure Characteristics Using Wavelet Transform with Different Meteorological Elements

Abstract

In the present study, three wavelet basis functions, i.e., Mexican-hat, Morlet, and Wave, were used to analyze the atmospheric turbulence data obtained from an eddy covariance system in order to determine the effect of six meteorological elements including three-dimensional wind speed, temperature, and CO2 and H2O concentrations on the time scale of coherent structures. First, we used the degree of correlation between original and reconstructed waveforms to test the three wavelets'performance when determining the time scale of coherent structures. The Wave wavelet's reconstructed coherent structure signal best matched the original signal; thus, it was used to further analyze the time scale, number, and time cover of the meteorological elements. We found similar results for all elements, though there was some internal variation, suggesting that coherent structures are not inherently dependent on these elements. Our results provide a basis for proper coherent structure detection in atmospheric turbulence and improve the understanding of similarities and differences between coherent structure characteristics of different meteorological elements, which is helpful for further research into atmospheric turbulence and boundary layers.