Turbulence and eddy‐covariance measurements on a floating platform over water surfaces can be contaminated by platform oscillations, which may affect the calculated air‐water exchange. The conventional method for decontamination of the platform oscillations from the wind velocity measurements requires the installation of an additional sensitive, and often costly, motion sensor. This paper examines a new mathematical decontamination method, termed Lorentzian filter, which avoids the need for such an instrument. The method, based on the Lorentzian function, capitalizes on the pseudo‐harmonic behavior of the platform oscillations and reduces the amplitude of turbulent wind velocity data detected as artifacts at the specific natural frequencies of the platform. The Lorentzian filter was applied to wind velocity data measured by sonic anemometer and eddy‐covariance system over the Dead Sea, Israel, for 30 days. We examined two approaches of dealing with motion contamination: Lorentzian filter decontamination and motion sensor decontamination. Both approaches were compared to nonfiltered raw wind velocity as well. Using the 3D wind velocity series, we examined the wind spectra, the cospectra of water vapor concentration and horizontal wind speed with vertical wind speed, and H₂O and momentum fluxes. The Lorentzian filter performed very well in decontaminating the wind spectrum, meaning that it efficiently identified the contamination in the natural oscillation frequency and returned a decontaminated wind velocity time series. The cospectra and fluxes were less prone to the contamination of platform oscillations, presumably due to low correlations between the spurious wind velocity components and other measured scalars, such as water vapor.

中文翻译：

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振荡浮动平台上湍流测量值的洛伦兹滤波器校正：对风谱和涡度协方差通量的影响

水面上方的浮动平台上的湍流和涡度协方差测量结果可能会受到平台振动的污染，这可能会影响所计算的空气-水交换。用于从风速测量中净化平台振动的常规方法需要安装附加的灵敏的，通常是昂贵的运动传感器。本文研究了一种称为Lorentzian过滤器的新型数学去污方法，该方法可以避免使用这种仪器。该方法基于洛伦兹函数，利用了平台振动的拟谐特性，并减小了在平台特定固有频率处被检测为伪像的湍流风速数据的幅度。洛伦兹滤波器被用于以色列死海上30天的风速数据，该数据是由声速计和涡动协方差系统测得的。我们研究了两种处理运动污染的方法：洛伦兹过滤器去污和运动传感器去污。两种方法也都与未过滤的原始风速进行了比较。使用3D风速序列，我们检查了风谱，水蒸气浓度和水平风速与垂直风速的共谱以及H₂ O和动量通量。洛伦兹滤波器在净化风谱方面表现非常出色，这意味着它可以有效地识别自然振荡频率中的污染并返回经过净化的风速时间序列。互谱和通量较不容易受到平台振荡的污染，这可能是由于杂散风速分量与其他测量标量（例如水蒸气）之间的相关性较低。