Flux data gap-filling and flux-partitioning page

News

Oct-2014, New saved query policy
Please note that, effective Oct 1st 2014, queries will be stored at our servers for up to one year at maximum.

Jul-2013, New R based online tool
Eddy covariance gap filling (and soon flux partitioning) now also available as R based online tool and package

Apr-2013, bug fixes online tool
problem with missing columns and plots in output files resolved

Jan-2013, updates
completed output files for flux-partitioning based on Tsoil now available

May-2012, back online
thanks for the patience

Apr-2012, temporary NA
tool unavailable because of changes in the institute's server structure

Mar-2012, full restart
Server problems resolved, tool up and running again

Mar-2012, maintenance
Increased waiting times and temporary unavailability due to server problems

Feb-2012, updates
output variable description included

Jan-2012, tool version 1.1
new features including uncertainties and email service

Jul-2011, beta version updates
Zipped result files now available

Jul-2011, beta version updates
Due to high demand, parallel processing methods were improved

Jun-2011, online tool resurrection
gap-filling tool and flux-partitioning tool up and running again.

The service is provided for the following variables:
  • NEE
  • LE
  • H
  • Rg
  • Tair
  • Tsoil
  • rH
  • precip
I want to go directly to the data input form now.
I want to go directly to the How-to-use section now.


Background

Problem 1: The eddy covariance method delivers continuous data sets of mass and energy exchange between ecosystem and atmosphere. However, gaps due to unfavorable micro-meteorological conditions and due to instrument failure are inherent in the data stream. Thus a standardized filling of those gaps is necessary (gap-filling), e.g. to obtain daily, monthly or annually integrated balances.

Problem 2: The eddy covariance method measures the net ecosystem exchange. However, particularly for CO2 exchange a lot more understanding of the ecosystem is gained, when the net flux is partitioned into the main components, gross carbon uptake (GPP) and ecosystem respiration (Reco) (flux-partitioning).

Problem 3: During stable stratification and low turbulent mixing the eddy covariance method faces several problems that introduce bias and uncertainties. These problems primarily happen during night and lead to an underestimation of the night-time flux, i.e. the ecosystem respiration. These problems can be detected via a micro-meteorological quality control that tests if the assumptions of the eddy covariance method are not too strongly violated for a particular half hour (e.g. Foken and Wichura, 1996; http://www.bayceer.uni-bayreuth.de/qaqc/en/forschung/21826/Task122.php). Under circumstances where the necessary information for those tests is not available, a heuristic class of methods is widely accepted that assumes that a treshhold of friction velocity (u*) can be site and season specifically established above that night-time fluxes are considered valid. This threshold is usually established by relating the night-time flux to friction velocity while accounting for temperature as a covariate (u*-filtering).