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Dryad

Lorentzian filter correction of turbulence measurements on oscillating floating platforms: impact on wind spectra and eddy covariance fluxes

Cite this dataset

Ezraty, Roee (2020). Lorentzian filter correction of turbulence measurements on oscillating floating platforms: impact on wind spectra and eddy covariance fluxes [Dataset]. Dryad. https://doi.org/10.5061/dryad.qz612jmbb

Abstract

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 three approaches of dealing with motion contamination: Lorentzian filter decontamination, motion sensor decontamination, and non-filtered raw wind velocity. Using the 3D wind velocity series, we examined the wind spectra, the co-spectra 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 co-spectra 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.

Methods

The Loretzian filter is a MATLAB code.

 Raw data was acquired from Eddy Covariance stations and processed through MATLAB using the Lorentzian filter or the code of Ikawa and Oechel et al. (2015) mentioned in the paper to achieve filtered data. Then, the data was processed through the EddyPro software (Licor) to achieve wind spectra, co-spectra and the different fluxes.

 

Usage notes

ReadMe and an instruction file for the Lorentzian filter are attached.