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Abstract The interpretation of tower‐based eddy‐covariance (EC) turbulent flux measurements above forests hinges on three key assumptions: (1) steadiness in the flow statistics, (2) planar homogeneity of scalar sources or sinks, and (3) planar homogeneity in the flow statistics. Large eddy simulations (LESs) were used to control the first two so as to explore the break‐down of the third for idealized and real gentle topography such as those encountered in Amazonia. The LES runs were conducted using uniformly distributed sources inside homogeneous forests covering complex terrain to link the spatial patterns of scalar turbulent fluxes to topographic features. Results showed strong modulation of the fluxes by flow features induced by topography, including large area with negative fluxes compensating “chimney” regions with fluxes almost an order of magnitude larger than the landscape flux. Significant spatial heterogeneity persisted up to at least two canopy heights, where most eddy‐covariance measurements are performed above tall forests. A heterogeneity index was introduced to characterize and contrast different scenarios, and a topography categorization was shown to have predictive capabilities in identifying regions of negative and enhanced fluxes.
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Intercomparison of eddy-covariance software for urban tall-tower sites
Abstract. Long-term tall-tower eddy-covariance (EC) measurements have been recently established in three European pilot cities as part of the ICOS-Cities project. We conducted a comparison of EC software to ensure a reliable generation of interoperable flux estimates, which is the prerequisite for avoiding methodological biases and improving the comparability of the results. We analyzed datasets covering 5 months collected from EC tall-tower installations located in urbanized areas of Munich, Zurich, and Paris. Fluxes of sensible heat, latent heat, and CO2 were calculated using three software packages (i.e., TK3, EddyPro, and eddy4R) to assess the uncertainty of flux estimations attributed to differences in implemented postprocessing schemes. A very good agreement on the mean values and standard deviations was found across all three sites, which can probably be attributed to a uniform instrumentation, data acquisition, and preprocessing. The overall comparison of final flux time series products showed a good but not yet perfect agreement among the three software packages. TK3 and EddyPro both calculated fluxes with low-frequency spectral correction, resulting in better agreement than between TK3 and the eddy4R workflow with disabled low-frequency spectral treatment. These observed flux discrepancies indicate the crucial role of treating low-frequency spectral loss in flux estimation for tall-tower EC systems.
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- PAR ID:
- 10523739
- Publisher / Repository:
- EGU
- Date Published:
- Journal Name:
- Atmospheric Measurement Techniques
- Volume:
- 17
- Issue:
- 9
- ISSN:
- 1867-8548
- Page Range / eLocation ID:
- 2649 to 2669
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/amt-17-2649-2024
