10.5061/DRYAD.QZ612JMBB
Ezraty, Roee
0000-0003-3180-3095
Hebrew University of Jerusalem
Lorentzian filter correction of turbulence measurements on oscillating
floating platforms: impact on wind spectra and eddy covariance fluxes
Dryad
dataset
2020
FOS: Earth and related environmental sciences
2020-09-23T00:00:00Z
2020-09-23T00:00:00Z
en
66936977 bytes
5
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
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.
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.
ReadMe and an instruction file for the Lorentzian filter are attached.