{"title":"Removing biases in oceanic turbulent kinetic energy dissipation rate estimated from microstructure shear data","authors":"B. Ferron, P. Aubertot, Y. Cuypers, C. Vic","doi":"10.1175/jtech-d-22-0035.1","DOIUrl":null,"url":null,"abstract":"\nTo calculate a turbulent kinetic energy dissipation 11 rate from the microstructure vertical shear of the horizontal velocity via a spectral analysis, shear spectra need first to be cleaned from vibrations of the moving vehicle. Unambiguously, this study shows that the spectral cleaning must be applied all over the frequency range and not only at frequencies larger than 10 Hz, as a recent study suggested. For a Vertical Microstructure Profiler VMP-6000, not correcting for vehicle vibrations below 10 Hz leads to overestimated dissipation rates from 50 to 700% for usual downcast velocities and for weak dissipation rates (ε < 1 × 10−9 W kg−1). Vibrations concern all vehicles but the exact vibrational frequency signature depends on the vehicle shape and its downcast velocity. In any case, a spectral cleaning over the whole frequency range is strongly advised.\nThis study also reports on a systematic low bias of inferred dissipation rates induced by the spectral cleaning when too few degrees of freedom are available for the cleaning, which is usually the default of the standard processing. Whatever the dissipation rate level, not correcting for the bias leads to underestimated dissipation rates by a factor 1.4 to 2.7 (with usual parameters), the exact amplitude of the bias depending on the number of degrees of freedom and on the number of independent accelerometer-axis used for the cleaning. It is strongly advised that such a bias is taken into account to recompute dissipation rates of past data sets and for future observations.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Atmospheric and Oceanic Technology","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1175/jtech-d-22-0035.1","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, OCEAN","Score":null,"Total":0}
引用次数: 0
Abstract
To calculate a turbulent kinetic energy dissipation 11 rate from the microstructure vertical shear of the horizontal velocity via a spectral analysis, shear spectra need first to be cleaned from vibrations of the moving vehicle. Unambiguously, this study shows that the spectral cleaning must be applied all over the frequency range and not only at frequencies larger than 10 Hz, as a recent study suggested. For a Vertical Microstructure Profiler VMP-6000, not correcting for vehicle vibrations below 10 Hz leads to overestimated dissipation rates from 50 to 700% for usual downcast velocities and for weak dissipation rates (ε < 1 × 10−9 W kg−1). Vibrations concern all vehicles but the exact vibrational frequency signature depends on the vehicle shape and its downcast velocity. In any case, a spectral cleaning over the whole frequency range is strongly advised.
This study also reports on a systematic low bias of inferred dissipation rates induced by the spectral cleaning when too few degrees of freedom are available for the cleaning, which is usually the default of the standard processing. Whatever the dissipation rate level, not correcting for the bias leads to underestimated dissipation rates by a factor 1.4 to 2.7 (with usual parameters), the exact amplitude of the bias depending on the number of degrees of freedom and on the number of independent accelerometer-axis used for the cleaning. It is strongly advised that such a bias is taken into account to recompute dissipation rates of past data sets and for future observations.
为了通过光谱分析从水平速度的微观结构垂直剪切计算湍流动能耗散率,首先需要从移动车辆的振动中清除剪切光谱。毫无疑问,这项研究表明,正如最近的一项研究所建议的那样,频谱清洁必须应用于整个频率范围,而不仅仅是大于10Hz的频率。对于垂直微结构剖面仪VMP-6000,如果不对低于10 Hz的车辆振动进行校正,则会导致对通常下行速度和弱耗散率(ε<1×10−9 W kg−1)的耗散率估计过高,从50%到700%。振动涉及所有车辆,但确切的振动频率特征取决于车辆形状及其下行速度。在任何情况下,强烈建议在整个频率范围内进行频谱清理。本研究还报告了当可用于清洁的自由度太少时,光谱清洁引起的推断耗散率的系统低偏差,这通常是标准处理的默认情况。无论耗散率水平如何,不校正偏差都会导致耗散率被低估1.4至2.7倍(使用通常的参数),偏差的确切幅度取决于自由度的数量和用于清洁的独立加速度计轴的数量。强烈建议在重新计算过去数据集的耗散率和未来观测时考虑这种偏差。
期刊介绍:
The Journal of Atmospheric and Oceanic Technology (JTECH) publishes research describing instrumentation and methods used in atmospheric and oceanic research, including remote sensing instruments; measurements, validation, and data analysis techniques from satellites, aircraft, balloons, and surface-based platforms; in situ instruments, measurements, and methods for data acquisition, analysis, and interpretation and assimilation in numerical models; and information systems and algorithms.