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| 001 | 859073 | ||
| 005 | 20210130000153.0 | ||
| 024 | 7 | _ | |a 10.1515/intag-2017-0044 |2 doi |
| 024 | 7 | _ | |a 0236-8722 |2 ISSN |
| 024 | 7 | _ | |a 2300-8725 |2 ISSN |
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| 037 | _ | _ | |a FZJ-2019-00024 |
| 082 | _ | _ | |a 640 |
| 100 | 1 | _ | |a Rebmann, Corinna |0 P:(DE-HGF)0 |b 0 |e Corresponding author |
| 245 | _ | _ | |a ICOS eddy covariance flux-station site setup: a review |
| 260 | _ | _ | |a Lublin |c 2018 |b IA PAS |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1547470663_20255 |2 PUB:(DE-HGF) |
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| 520 | _ | _ | |a The Integrated Carbon Observation System Re-search Infrastructure aims to provide long-term, continuous observations of sources and sinks of greenhouse gases such as carbon dioxide, methane, nitrous oxide, and water vapour. At ICOS ecosystem stations, the principal technique for measurements of ecosystem-atmosphere exchange of GHGs is the eddy-covariance technique. The establishment and setup of an eddy-covariance tower have to be carefully reasoned to ensure high quality flux measurements being representative of the investigated ecosystem and comparable to measurements at other stations. To fulfill the requirements needed for flux determination with the eddy-covariance technique, variations in GHG concentrations have to be measured at high frequency, simultaneously with the wind velocity, in order to fully capture turbulent fluctuations. This requires the use of high-frequency gas analysers and ultrasonic anemometers. In addition, to analyse flux data with respect to environmental conditions but also to enable corrections in the post-processing procedures, it is necessary to measure additional abiotic variables in close vicinity to the flux measurements. Here we describe the standards the ICOS ecosystem station network has adopted for GHG flux measurements with respect to the setup of instrumentation on towers to maximize measurement precision and accuracy while allowing for flexibility in order to observe specific ecosystem features. |
| 536 | _ | _ | |a 255 - Terrestrial Systems: From Observation to Prediction (POF3-255) |0 G:(DE-HGF)POF3-255 |c POF3-255 |f POF III |x 0 |
| 536 | _ | _ | |a ICOS - Integrated Carbon Observation System (211574) |0 G:(EU-Grant)211574 |c 211574 |f FP7-INFRASTRUCTURES-2007-1 |x 1 |
| 536 | _ | _ | |a IDAS-GHG - Instrumental and Data-driven Approaches to Source-Partitioning of Greenhouse Gas Fluxes: Comparison, Combination, Advancement (BMBF-01LN1313A) |0 G:(DE-Juel1)BMBF-01LN1313A |c BMBF-01LN1313A |f Nachwuchsgruppen Globaler Wandel 4+1 |x 2 |
| 536 | _ | _ | |a TERENO - Terrestrial Environmental Observatories (TERENO-2008) |0 G:(DE-HGF)TERENO-2008 |c TERENO-2008 |f TERENO-2008 |x 3 |
| 588 | _ | _ | |a Dataset connected to CrossRef |
| 700 | 1 | _ | |a Aubinet, Marc |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Schmid, HaPe |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Arriga, Nicola |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Aurela, Mika |0 P:(DE-HGF)0 |b 4 |
| 700 | 1 | _ | |a Burba, George |0 P:(DE-HGF)0 |b 5 |
| 700 | 1 | _ | |a Clement, Robert |0 P:(DE-HGF)0 |b 6 |
| 700 | 1 | _ | |a De Ligne, Anne |0 P:(DE-HGF)0 |b 7 |
| 700 | 1 | _ | |a Fratini, Gerardo |0 P:(DE-HGF)0 |b 8 |
| 700 | 1 | _ | |a Gielen, Bert |0 P:(DE-HGF)0 |b 9 |
| 700 | 1 | _ | |a Grace, John |0 P:(DE-HGF)0 |b 10 |
| 700 | 1 | _ | |a Graf, Alexander |0 P:(DE-Juel1)129461 |b 11 |u fzj |
| 700 | 1 | _ | |a Gross, Patrick |0 P:(DE-HGF)0 |b 12 |
| 700 | 1 | _ | |a Haapanala, Sami |0 P:(DE-HGF)0 |b 13 |
| 700 | 1 | _ | |a Herbst, Mathias |0 P:(DE-HGF)0 |b 14 |
| 700 | 1 | _ | |a Hörtnagl, Lukas |0 P:(DE-HGF)0 |b 15 |
| 700 | 1 | _ | |a Ibrom, Andreas |0 P:(DE-HGF)0 |b 16 |
| 700 | 1 | _ | |a Joly, Lilian |0 P:(DE-HGF)0 |b 17 |
| 700 | 1 | _ | |a Kljun, Natascha |0 P:(DE-HGF)0 |b 18 |
| 700 | 1 | _ | |a Kolle, Olaf |0 P:(DE-HGF)0 |b 19 |
| 700 | 1 | _ | |a Kowalski, Andrew |0 P:(DE-HGF)0 |b 20 |
| 700 | 1 | _ | |a Lindroth, Anders |0 P:(DE-HGF)0 |b 21 |
| 700 | 1 | _ | |a Loustau, Denis |0 P:(DE-HGF)0 |b 22 |
| 700 | 1 | _ | |a Mammarella, Ivan |0 P:(DE-HGF)0 |b 23 |
| 700 | 1 | _ | |a Mauder, Matthias |0 P:(DE-HGF)0 |b 24 |
| 700 | 1 | _ | |a Merbold, Lutz |0 P:(DE-HGF)0 |b 25 |
| 700 | 1 | _ | |a Metzger, Stefan |0 P:(DE-HGF)0 |b 26 |
| 700 | 1 | _ | |a Mölder, Meelis |0 P:(DE-HGF)0 |b 27 |
| 700 | 1 | _ | |a Montagnani, Leonardo |0 P:(DE-HGF)0 |b 28 |
| 700 | 1 | _ | |a Papale, Dario |0 P:(DE-HGF)0 |b 29 |
| 700 | 1 | _ | |a Pavelka, Marian |0 P:(DE-HGF)0 |b 30 |
| 700 | 1 | _ | |a Peichl, Matthias |0 P:(DE-HGF)0 |b 31 |
| 700 | 1 | _ | |a Roland, Marilyn |0 P:(DE-HGF)0 |b 32 |
| 700 | 1 | _ | |a Serrano-Ortiz, Penélope |0 P:(DE-HGF)0 |b 33 |
| 700 | 1 | _ | |a Siebicke, Lukas |0 P:(DE-HGF)0 |b 34 |
| 700 | 1 | _ | |a Steinbrecher, Rainer |0 P:(DE-HGF)0 |b 35 |
| 700 | 1 | _ | |a Tuovinen, Juha-Pekka |0 P:(DE-HGF)0 |b 36 |
| 700 | 1 | _ | |a Vesala, Timo |0 P:(DE-HGF)0 |b 37 |
| 700 | 1 | _ | |a Wohlfahrt, Georg |0 P:(DE-HGF)0 |b 38 |
| 700 | 1 | _ | |a Franz, Daniela |0 P:(DE-HGF)0 |b 39 |
| 773 | _ | _ | |a 10.1515/intag-2017-0044 |g Vol. 32, no. 4, p. 471 - 494 |0 PERI:(DE-600)2235638-1 |n 4 |p 471 - 494 |t International agrophysics |v 32 |y 2018 |x 2300-8725 |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/859073/files/rebmann_graf_2018_IntAgrophys_ICOS.pdf |
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