Online Eddy covariance gap

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Online Eddy covariance gap

2023-03-26 08:45| 来源: 网络整理| 查看: 265

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).



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