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@ARTICLE{Sabbatini:859074,
author = {Sabbatini, Simone and Mammarella, Ivan and Arriga, Nicola
and Fratini, Gerardo and Graf, Alexander and Hörtnagl,
Lukas and Ibrom, Andreas and Longdoz, Bernard and Mauder,
Matthias and Merbold, Lutz and Metzger, Stefan and
Montagnani, Leonardo and Pitacco, Andrea and Rebmann,
Corinna and Sedlák, Pavel and Šigut, Ladislav and Vitale,
Domenico and Papale, Dario},
title = {{E}ddy covariance raw data processing for {CO}2 and energy
fluxes calculation at {ICOS} ecosystem stations},
journal = {International agrophysics},
volume = {32},
number = {4},
issn = {2300-8725},
address = {Lublin},
publisher = {IA PAS},
reportid = {FZJ-2019-00025},
pages = {495 - 515},
year = {2018},
abstract = {The eddy covariance is a powerful technique to estimate the
surface-atmosphere exchange of different scalars at the
ecosystem scale. The EC method is central to the ecosystem
component of the Integrated Carbon Observation System, a
monitoring network for greenhouse gases across the European
Continent. The data processing sequence applied to the
collected raw data is complex, and multiple robust options
for the different steps are often available. For Integrated
Carbon Observation System and similar networks, the
standardisation of methods is essential to avoid
methodological biases and improve comparability of the
results. We introduce here the steps of the processing chain
applied to the eddy covariance data of Integrated Carbon
Observation System stations for the estimation of final CO2,
water and energy fluxes, including the calculation of their
uncertainties. The selected methods are discussed against
valid alternative options in tenns of suitability and
respective drawbacks and advantages. The main challenge is
to warrant standardised processing for all stations in spite
of the large differences in e.g. ecosystem traits and site
conditions. The main achievement of the Integrated Carbon
Observation System eddy covariance data processing is making
CO2 and energy flux results as comparable and reliable as
possible, given the current micrometeorological
understanding and the generally accepted state-of-the-art
processing methods.},
cin = {IBG-3},
ddc = {640},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {255 - Terrestrial Systems: From Observation to Prediction
(POF3-255) / ICOS - Integrated Carbon Observation System
(211574) / IDAS-GHG - Instrumental and Data-driven
Approaches to Source-Partitioning of Greenhouse Gas Fluxes:
Comparison, Combination, Advancement (BMBF-01LN1313A) /
TERENO - Terrestrial Environmental Observatories
(TERENO-2008)},
pid = {G:(DE-HGF)POF3-255 / G:(EU-Grant)211574 /
G:(DE-Juel1)BMBF-01LN1313A / G:(DE-HGF)TERENO-2008},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000453410400004},
doi = {10.1515/intag-2017-0043},
url = {https://juser.fz-juelich.de/record/859074},
}