Journal cover Journal topic
Biogeosciences An interactive open-access journal of the European Geosciences Union
Journal topic
Volume 15, issue 16
Biogeosciences, 15, 5015-5030, 2018
https://doi.org/10.5194/bg-15-5015-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Biogeosciences, 15, 5015-5030, 2018
https://doi.org/10.5194/bg-15-5015-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 23 Aug 2018

Research article | 23 Aug 2018

Basic and extensible post-processing of eddy covariance flux data with REddyProc

Thomas Wutzler1, Antje Lucas-Moffat2,3, Mirco Migliavacca1, Jürgen Knauer1, Kerstin Sickel1, Ladislav Šigut4, Olaf Menzer5, and Markus Reichstein1 Thomas Wutzler et al.
  • 1Max Planck Institute for Biogeochemistry, Hans-Knöll-Straße 10, 07745 Jena, Germany
  • 2German Meteorological Service, Centre for Agrometeorological Research, Bundesallee 33, 38116 Braunschweig, Germany
  • 3Thuenen Institute of Climate-Smart Agriculture, Bundesallee 65, 38116 Braunschweig, Germany
  • 4Global Change Research Institute CAS, Bělidla 986/4a, 60300 Brno, Czech Republic
  • 5Department of Geography, University of California, Santa Barbara, CA 93106-4060, USA

Abstract. With the eddy covariance (EC) technique, net fluxes of carbon dioxide (CO2) and other trace gases as well as water and energy fluxes can be measured at the ecosystem level. These flux measurements are a main source for understanding biosphere–atmosphere interactions and feedbacks through cross-site analysis, model–data integration, and upscaling. The raw fluxes measured with the EC technique require extensive and laborious data processing. While there are standard tools1 available in an open-source environment for processing high-frequency (10 or 20Hz) data into half-hourly quality-checked fluxes, there is a need for more usable and extensible tools for the subsequent post-processing steps. We tackled this need by developing the REddyProc package in the cross-platform language R that provides standard CO2-focused post-processing routines for reading (half-)hourly data from different formats, estimating the u* threshold, as well as gap-filling, flux-partitioning, and visualizing the results. In addition to basic processing, the functions are extensible and allow easier integration in extended analysis than current tools. New features include cross-year processing and a better treatment of uncertainties. A comparison of REddyProc routines with other state-of-the-art tools resulted in no significant differences in monthly and annual fluxes across sites. Lower uncertainty estimates of both u* and resulting gap-filled fluxes by 50% with the presented tool were achieved by an improved treatment of seasons during the bootstrap analysis. Higher estimates of uncertainty in daytime partitioning (about twice as high) resulted from a better accounting for the uncertainty in estimates of temperature sensitivity of respiration. The provided routines can be easily installed, configured, and used. Hence, the eddy covariance community will benefit from the REddyProc package, allowing easier integration of standard post-processing with extended analysis.

1http://fluxnet.fluxdata.org/2017/10/10/toolbox-a-rolling-list-of-softwarepackages-for-flux-related-data-processing/, last access: 17 August 2018

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Net fluxes of carbon dioxide at the ecosystem level measured by eddy covariance are a main source for understanding biosphere–atmosphere interactions. However, there is a need for more usable and extensible tools for post-processing steps of the half-hourly flux data. Therefore, we developed the REddyProc package, providing data filtering, gap filling, and flux partitioning. The extensible functions are compatible with state-of-the-art tools but allow easier integration in extended analysis.
Net fluxes of carbon dioxide at the ecosystem level measured by eddy covariance are a main...
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