Hilbert方法在大气边界层湍流特征分析中的有效性

Effectiveness of Hilbert Spectral Method in ABL Turbulent Characteristic Analysis

介绍一种新的建立在经验模态分解(EMD)方法基础上的非线性、非平稳数据分析技术—Hilbert分析技术,并首次将其应用于大气边界层(PBL)湍流数据的分析,初步探讨了其在PBL湍流研究中的有效性。通过对城市与森林冠层上湍流资料的能量分布特征和统计平稳度进行分析、比较,结果表明:Hilbert谱分析能有效地对PBL湍流信号进行分析。它的边缘谱分析能够有效地探测PBL湍流信号的能量分布特征,统计平稳度分析也能有效地给出PBL湍流信号平稳性的定量化测量,这些将有助于建立合适的数据质量控制方法,以及对现有空气质量与扩散模式中扩散参数的计算加以改进。文中个例分析中,城市和森林冠层上空的湍流有一定相似性,湍流混合都比较充分,但森林冠层上湍流信号的能量更多地集中在大尺度湍涡,且扰动风速的高频部分具有更强的间歇性。对于相近高度的湍流信号来说,多数情况下,森林冠层上相同尺度的湍涡表现得比城市冠层上更不稳定,但湍涡的含能量要更低。

The Hilbert spectral analysis based on the Empirical Mode Decomposition （EMD） method for analyzing nonlinear and non-stationary data is introduced and applied to the analysis of the Atmospheric Boundary Layer （ABL） turbulent signals for the first time. The effectiveness of Hilbert the spectral analysis in the research on the ABL turbulence is explored. The energy distribution characteristics and the degree of statistic stationarity of the turbulent data above the urban and forest canopies are studied. The results show the Hilbert spectral analysis is powerful and effective in the study of ABL turbulence. The Hi bert marginal spectrum is effective to get the energy distribution characteristics of ABL turbulent signals, and the analysis of the statistic stationarity is also effective to quantitatively measure the stationarity of the ABL turbulent signals. This will help establish the appropriate data quality control methods and improve the calculation of diffusion parameters of air quality and dispersion models. The case analysis shows that the turbulent flow is well mixed above both canopies. Compared with the urban canopy, theturbulent energy above the forest canopy is more concentrated in the eddies on larger scales, and the high-frequency part of wind disturbance is dominated by stronger intermittency. At a given height, turbulence eddies above the forest canopy are more unstable and contain less energy than those above the urban canopy.