REddyProcWeb online tool

The REddyProc online tool implements the standardized methods for processing Eddy-Covariance data. This online tool is based on the REddyProc R package which can be used offline in R with more options and flexibility.

Citation: Wutzler T, Lucas-Moffat A, Migliavacca M, Knauer J, Sickel K, Sigut, Menzer O & Reichstein M (2018) Basic and extensible post-processing of eddy covariance flux data with REddyProc. Biogeosciences, Copernicus, 15, doi: 10.5194/bg-15-5015-2018

Ustar filtering

Algorithms for the calculation of the u* threshold.

UStar threshold is estimated by the Moving Point Test according to Papale et al. 2006.

The default definition of the seasons differs from standard Fluxnet processing: seasons that span from December to February can be now selected across years instead of using calendar year boundaries

Estimation of uncertainty of the threshold differs from FLUXNET processing by bootstrapping the data within seasons instead of within one year.

Gap filling

Algorithms to fill the gaps in half-hourly eddy covariance data

The gap filling service is provided for the following variables:

• Fluxes (including uncertainty estimates): NEE, LE, H
• Meteo: Rg, VPD, rH, Tair, Tsoil
• Other variables with suffix '_MDS'

Flux partitioning

The algorithm for partitioning NEE_f into ecosystem respiration Reco and gross primary production GPP_f. Both night-time (Reichstein et al., 2005) and day-time (Lasslop et al., 2010) partitioning algorithms are implemented

Data plotting

All processed variables are plotted:

• Fingerprint
• Half-hourly fluxes and their daily means
• Daily sums (and their uncertainties)
• Diurnal cycle

2015 version of the online tool

The previous 2015 online tool implemented the algorithms in PV-Wave. Due to slight modifications, there might be some differences in the results between the two tools.

Where to go next?

• Please check out the information linked above in the menu, e.g.
  • Description of the methods: Methods
  • Description of the data formats and results example: Data Formats
  • Start processing: Processing
    • review the Data protection statement
  • Download the package: R-Package
  • View the history of changes