Application of Hilbert Huang Transform Method Based on CEEMD in Forest Boundary Layer Turbulence

Abstract

To address the modal aliasing phenomenon in traditional Empirical Mode Decomposition （EMD） algorithms， the Complementary Ensemble Empirical Mode Decomposition （CEEMD） and Mirror Extension algorithm were introduced to improve the shortcomings in EMD algorithm decomposition.This article selects case data from turbulence observations in the artificial forest area of Mount Si'e.Firstly， the differences between the two methods are compared and analyzed to clarify the advantages of the CEEMD algorithm； Then， case data of stable and unstable layers at different heights were selected， and the Hilbert Huang transformation method was applied to analyze the turbulent characteristics of the wind speed U and temperature T series under this case， exploring the application of the Hilbert Huang transformation method.The results indicate that the algorithm decomposition of CEEMD is more detailed， the mode aliasing defect of the modal function is better suppressed， the modal energy distribution is more focused， the Hilbert marginal spectrum has more energy spikes， and the energy distribution is clearer.Different modal functions have their own characteristic frequencies， and the decomposed modal functions contain motion of different scales， including turbulent motion in the inertial sub region with a slope of -2/3， and low-frequency large-scale modes corresponding to the energy containing region.The marginal spectral energy peaks obtained from CEEMD decomposition well reflect the energy containing characteristics of each modal function.Individual case analysis shows that the CEEMD algorithm can act as a typical binary filter.After CEEMD decomposition， there are gust fluctuations of about 3~6 minutes in the various modal functions of the U-wind in the turbulence signal of this case.The turbulence characteristics vary at different heights and stable layers.The Hilbert marginal spectral amplitude is higher in the unstable layer at noon compared to the stable layer at night， and the three-dimensional wind speed is better mixed at various heights.Moreover， due to the effect of the canopy， there is a crushing effect on large-scale turbulent vortices at lower altitudes， and the marginal spectrum exhibits low frequency small and high frequency large characteristics compared to other altitudes.In this case， the temperature T is different from the three-dimensional wind speed performance： turbulent vortices at different altitudes are better mixed under stable layer structures， while under unstable layer structures， the marginal spectrum amplitude at lower altitudes is higher due to differences in thermal absorption at different altitudes， and decreases with increasing altitude.Overall， this comparative analysis highlights the superior capabilities of the CEEMD algorithm in handling complex turbulence data， ensuring a more precise and insightful examination of atmospheric phenomena.

Keywords

• hilbert huang
• ceemd
• turbulence
• forest underlying surface
• mirror extension