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| Titel |
Estimating surface fluxes using eddy covariance and numerical ogive optimization |
| VerfasserIn |
J. Sievers, T. Papakyriakou, S. E. Larsen, M. M. Jammet, S. Rysgaard, M. K. Sejr, L. L. Sørensen |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 15, no. 4 ; Nr. 15, no. 4 (2015-02-26), S.2081-2103 |
| Datensatznummer |
250119461
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| Publikation (Nr.) |
 copernicus.org/acp-15-2081-2015.pdf |
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| Zusammenfassung |
| 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. |
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