Intercomparison of eddy-covariance software for urban tall-tower sites

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Changxing Lan - (Author)
  • Matthias Mauder - , Chair of Meteorology (Author)
  • Stavros Stagakis - (Author)
  • Benjamin Loubet - (Author)
  • Claudio D'Onofrio - (Author)
  • Stefan Metzger - (Author)
  • David Durden - (Author)
  • Pedro-Henrique Herig-Coimbra - (Author)

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.

Details

Original languageEnglish
Pages (from-to)2649-2669
Number of pages21
JournalAtmospheric measurement techniques
Volume17 (2024)
Issue number9
Publication statusPublished - 7 May 2024
Peer-reviewedYes

External IDs

Scopus 85192726019
Mendeley 3906ed13-574f-35ac-8460-3bbb5a6ab890

Keywords

Library keywords