Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.668 IF 5.668
  • IF 5-year value: 6.201 IF 5-year
    6.201
  • CiteScore value: 6.13 CiteScore
    6.13
  • SNIP value: 1.633 SNIP 1.633
  • IPP value: 5.91 IPP 5.91
  • SJR value: 2.938 SJR 2.938
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 174 Scimago H
    index 174
  • h5-index value: 87 h5-index 87
Volume 15, issue 4
Atmos. Chem. Phys., 15, 2081-2103, 2015
https://doi.org/10.5194/acp-15-2081-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Interactions between climate change and the Cryosphere: SVALI,...

Atmos. Chem. Phys., 15, 2081-2103, 2015
https://doi.org/10.5194/acp-15-2081-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 26 Feb 2015

Research article | 26 Feb 2015

Estimating surface fluxes using eddy covariance and numerical ogive optimization

J. Sievers1,2, T. Papakyriakou3, S. E. Larsen4, M. M. Jammet5, S. Rysgaard2,3,6,7, M. K. Sejr2,6, and L. L. Sørensen1,2 J. Sievers et al.
  • 1Aarhus University, Department of Environmental Science, 4000 Roskilde, Denmark
  • 2Arctic Research Centre, Aarhus University, 8000 Aarhus, Denmark
  • 3Centre for Earth Observation Science, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
  • 4Department of Wind Energy, Danish Technical University, 4000 Roskilde, Denmark
  • 5Center for Permafrost (CENPERM), Department of Geosciences and Natural Resource Management, University of Copenhagen, 1350 Copenhagen, Denmark
  • 6Greenland Climate Research Centre, c/o Greenland Institute of Natural Resources box 570, Nuuk, Greenland
  • 7Department of Geological Sciences, University of Manitoba, Winnipeg, MB R3T 2N2, Canada

Abstract. Estimating representative surface fluxes using eddy covariance leads invariably to questions concerning inclusion or exclusion of low-frequency flux contributions. For studies where fluxes are linked to local physical parameters and up-scaled through numerical modelling efforts, low-frequency contributions interfere with our ability to isolate local biogeochemical processes of interest, as represented by turbulent fluxes. No method currently exists to disentangle low-frequency contributions on flux estimates. Here, we present a novel comprehensive numerical scheme to identify and separate out low-frequency contributions to vertical turbulent surface fluxes. For high flux rates (|Sensible heat flux| > 40 Wm−2, |latent heat flux|> 20 Wm−2 and |CO2 flux|> 100 mmol m−2 d−1 we found that the average relative difference between fluxes estimated by ogive optimization and the conventional method was low (5–20%) suggesting negligible low-frequency influence and that both methods capture the turbulent fluxes equally well. For flux rates below these thresholds, however, the average relative difference between flux estimates was found to be very high (23–98%) suggesting non-negligible low-frequency influence and that the conventional method fails in separating low-frequency influences from the turbulent fluxes. Hence, the ogive optimization method is an appropriate method of flux analysis, particularly in low-flux environments.

Publications Copernicus
Download
Citation