高分辨率CTD数据的小波去噪技术。紊流海洋流动的表征

J. Piera, R. Quesada, A. Manuel-Lazaro, R. J. Del, S. Shariat Panahi, G. Olivar
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引用次数: 6

摘要

分析高分辨率连续油管垂直剖面(电导率、温度和深度)是表征环境湍流流体动力学的常用方法。分析高分辨率CTD剖面的目标之一是识别流动中的湍流区域(斑块)。由于CTD测量的仪器噪声,以往文献报道的湍流斑块识别方法通常无法识别低密度梯度下的斑块。在此,我们提出了一种新的方法,可以显著提高低密度梯度下的斑块检测。该方法基于小波去噪过程和对CTD传感器数据误差的理论分析。在数值和现场试验中获得的高百分比的验证补丁表明,该方法是流体动力学表征的有力工具,可以广泛应用于环境监测应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wavelet denoising technique for high-resolution CTD data. Characterization of turbulent oceanic flow
The analysis of high-resolution CTD vertical profiles (conductivity, temperature and depth) is a common method for characterizing environmental turbulent fluid dynamics. One of the objectives in analyzing high-resolution CTD profiles is to identify turbulent regions (patches) within the flow. Due to the instrumental noise of CTD measurements, the previous methods for turbulent patch identification, reported in the literature, are usually unable to identify patches at low-density gradient. Here we proposed a new method that significantly improves patch detection at low-density gradients. The method is based on a wavelet-denoising procedure and a theoretical analysis of the error in data obtained from the CTD sensors. The high percentage of validating patches, obtained in numerical and field tests, indicates that the method is a powerful tool for fluid dynamics characterization, and can be applied in a wide range of environmental monitoring applications.
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