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Biogeosciences An interactive open-access journal of the European Geosciences Union
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Volume 12, issue 22
Biogeosciences, 12, 6721–6735, 2015
https://doi.org/10.5194/bg-12-6721-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Biogeosciences, 12, 6721–6735, 2015
https://doi.org/10.5194/bg-12-6721-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Technical note 26 Nov 2015

Technical note | 26 Nov 2015

Technical note: Time lag correction of aquatic eddy covariance data measured in the presence of waves

P. Berg1, C. E. Reimers2, J. H. Rosman3, M. Huettel4, M. L. Delgard1, M. A. Reidenbach1, and H. T. Özkan-Haller2 P. Berg et al.
  • 1Department of Environmental Sciences, University of Virginia, Charlottesville, Virginia, USA
  • 2College of Earth, Ocean and Atmospheric Sciences, Oregon State University, Corvallis, Oregon, USA
  • 3Institute of Marine Sciences, University of North Carolina at Chapel Hill, Morehead City, North Carolina, USA
  • 4Department of Earth, Ocean and Atmospheric Science, Florida State University, Tallahassee, Florida, USA

Abstract. Extracting benthic oxygen fluxes from eddy covariance time series measured in the presence of surface gravity waves requires careful consideration of the temporal alignment of the vertical velocity and the oxygen concentration. Using a model based on linear wave theory and measured eddy covariance data, we show that a substantial error in flux can arise if these two variables are not aligned correctly in time. We refer to this error in flux as the time lag bias. In one example, produced with the wave model, we found that an offset of 0.25 s between the oxygen and the velocity data produced a 2-fold overestimation of the flux. In another example, relying on nighttime data measured over a seagrass meadow, a similar offset reversed the flux from an uptake of −50 mmol m−2 d−1 to a release of 40 mmol m−2 d−1. The bias is most acute for data measured at shallow-water sites with short-period waves and low current velocities. At moderate or higher current velocities (> 5–10 cm s−1), the bias is usually insignificant. The widely used traditional time shift correction for data measured in unidirectional flows, where the maximum numerical flux is sought, should not be applied in the presence of waves because it tends to maximize the time lag bias or give unrealistic flux estimates. Based on wave model predictions and measured data, we propose a new time lag correction that minimizes the time lag bias. The correction requires that the time series of both vertical velocity and oxygen concentration contain a clear periodic wave signal. Because wave motions are often evident in eddy covariance data measured at shallow-water sites, we encourage more work on identifying new time lag corrections.

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Extracting benthic oxygen fluxes from eddy covariance data measured in the presence of wave motions requires careful consideration of the temporal alignment of the vertical velocity and the oxygen concentration. We show that substantial errors in flux estimates can arise if these two variables are not aligned correctly in time. Due to the limited time response of all oxygen sensors used today, such a misalignment cannot be entirely avoided. We finally propose a new correction for this problem.
Extracting benthic oxygen fluxes from eddy covariance data measured in the presence of wave...
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