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000861629 0247_ $$2doi$$a10.5194/bg-16-1111-2019
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000861629 1001_ $$0P:(DE-Juel1)159313$$aKlosterhalfen, Anne$$b0$$eCorresponding author$$ufzj
000861629 245__ $$aSource partitioning of H2O and CO2 fluxes based on high-frequency eddy covariance data: a comparison between study sites
000861629 260__ $$aKatlenburg-Lindau [u.a.]$$bCopernicus$$c2019
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000861629 520__ $$aFor an assessment of the roles of soil and vegetation in the climate system, a further understanding of the fluxcomponents of H2O and CO2 (e.g., transpiration, soil respiration) and their interaction with physical conditions andphysiological functioning of plants and ecosystems is necessary. To obtain magnitudes of these flux components, we appliedsource partitioning approaches after Scanlon and Kustas (2010; SK10) and after Thomas et al. (2008; TH08) tohigh-frequency eddy covariance measurements of 12 study sites covering different ecosystems (croplands, grasslands,and forests) in different climatic regions. Both partitioning methods are based on higher-order statistics of the H2O andCO2 fluctuations, but proceed differently to estimate transpiration, evaporation, net primary production, and soil respiration.We compared and evaluated the partitioning results obtained with SK10 and TH08, including slight modificationsof both approaches. Further, we analyzed the interrelations among the performance of the partitioning methods, turbulencecharacteristics, and site characteristics (such as plant cover type, canopy height, canopy density, and measurement height).We were able to identify characteristics of a data set that are prerequisites for adequate performance of the partitioningmethods.\\SK10 had the tendency to overestimate and TH08 to underestimate soil flux components. For both methods, the partitioningof CO2 fluxes was less robust than for H2O fluxes. Results derived with SK10 showed relatively large dependencieson estimated water use efficiency (WUE) at the leaf level, which is a required input. Measurements of outgoinglongwave radiation used for the estimation of foliage temperature (used in WUE) could slightly increase the qualityof the partitioning results. A modification of the TH08 approach, by applying a cluster analysis for the conditionalsampling of respiration–evaporation events, performed satisfactorily, but did not result in significant advantages comparedto the original method versions developed by Thomas et al. (2008). The performance of each partitioning approachwas dependent on meteorological conditions, plant development, canopy height, canopy density, and measurementheight. Foremost, the performance of SK10 correlated negatively with the ratio between measurement height and canopyheight. The performance of TH08 was more dependent on canopy height and leaf area index. In general, all site characteristicsthat increase dissimilarities between scalars appeared to enhance partitioning performance for SK10 and TH08.
000861629 536__ $$0G:(DE-HGF)POF3-255$$a255 - Terrestrial Systems: From Observation to Prediction (POF3-255)$$cPOF3-255$$fPOF III$$x0
000861629 536__ $$0G:(DE-Juel1)BMBF-01LN1313A$$aIDAS-GHG - Instrumental and Data-driven Approaches to Source-Partitioning of Greenhouse Gas Fluxes: Comparison, Combination, Advancement (BMBF-01LN1313A)$$cBMBF-01LN1313A$$fNachwuchsgruppen Globaler Wandel 4+1$$x1
000861629 536__ $$0G:(DE-HGF)TERENO-2008$$aTERENO - Terrestrial Environmental Observatories (TERENO-2008)$$cTERENO-2008$$fTERENO-2008$$x2
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000861629 7001_ $$0P:(DE-Juel1)129461$$aGraf, Alexander$$b1
000861629 7001_ $$0P:(DE-Juel1)142357$$aBrüggemann, Nicolas$$b2
000861629 7001_ $$00000-0002-8240-9031$$aDrüe, Clemens$$b3
000861629 7001_ $$0P:(DE-Juel1)129450$$aEsser, Odilia$$b4$$ufzj
000861629 7001_ $$0P:(DE-HGF)0$$aGonzález-Dugo, María P.$$b5
000861629 7001_ $$00000-0002-4831-9016$$aHeinemann, Günther$$b6
000861629 7001_ $$00000-0003-4079-9067$$aJacobs, Cor M. J.$$b7
000861629 7001_ $$00000-0002-8789-163X$$aMauder, Matthias$$b8
000861629 7001_ $$00000-0003-3614-8544$$aMoene, Arnold F.$$b9
000861629 7001_ $$0P:(DE-Juel1)166467$$aNey, Patrizia$$b10$$ufzj
000861629 7001_ $$0P:(DE-Juel1)129523$$aPütz, Thomas$$b11$$ufzj
000861629 7001_ $$00000-0002-8665-0375$$aRebmann, Corinna$$b12
000861629 7001_ $$0P:(DE-HGF)0$$aRamos Rodríguez, Mario$$b13
000861629 7001_ $$00000-0001-8869-1675$$aScanlon, Todd M.$$b14
000861629 7001_ $$0P:(DE-Juel1)144420$$aSchmidt, Marius$$b15$$ufzj
000861629 7001_ $$00000-0002-5931-4210$$aSteinbrecher, Rainer$$b16
000861629 7001_ $$00000-0003-2277-6013$$aThomas, Christoph K.$$b17
000861629 7001_ $$0P:(DE-Juel1)165760$$aValler, Veronika$$b18
000861629 7001_ $$00000-0001-9186-2519$$aZeeman, Matthias J.$$b19
000861629 7001_ $$0P:(DE-Juel1)129549$$aVereecken, Harry$$b20$$ufzj
000861629 773__ $$0PERI:(DE-600)2158181-2$$a10.5194/bg-16-1111-2019$$gVol. 16, no. 6, p. 1111 - 1132$$n6$$p1111 - 1132$$tBiogeosciences$$v16$$x1726-4189$$y2019
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000861629 9101_ $$0I:(DE-HGF)0$$60000-0002-8240-9031$$aDepartment of Environmental Meteorology, University of Trier$$b3
000861629 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)129450$$aForschungszentrum Jülich$$b4$$kFZJ
000861629 9101_ $$0I:(DE-HGF)0$$6P:(DE-HGF)0$$aIFAPA – Consejería de Agricultura, Pesca y Desarrollo Rural, Centro Alameda del Obispo$$b5
000861629 9101_ $$0I:(DE-HGF)0$$60000-0002-4831-9016$$aDepartment of Environmental Meteorology, University of Trier$$b6
000861629 9101_ $$0I:(DE-HGF)0$$60000-0003-4079-9067$$aWageningen Environmental Research, Wageningen University and Research$$b7
000861629 9101_ $$0I:(DE-HGF)0$$60000-0002-8789-163X$$aInstitute of Meteorology and Climate Research, IMK-IFU, Karlsruhe Institute of Technology$$b8
000861629 9101_ $$0I:(DE-HGF)0$$60000-0003-3614-8544$$aMeteorology and Air Quality Group, Wageningen University and Research$$b9
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000861629 9101_ $$0I:(DE-HGF)0$$60000-0002-8665-0375$$aDepartment Computational Hydrosystems, Helmholtz Centre for Environmental Research, UFZ$$b12
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000861629 9101_ $$0I:(DE-HGF)0$$60000-0001-8869-1675$$aDepartment of Environmental Sciences, University of Virginia$$b14
000861629 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)144420$$aForschungszentrum Jülich$$b15$$kFZJ
000861629 9101_ $$0I:(DE-HGF)0$$60000-0002-5931-4210$$aInstitute of Meteorology and Climate Research, IMK-IFU, Karlsruhe Institute of Technology$$b16
000861629 9101_ $$0I:(DE-HGF)0$$60000-0003-2277-6013$$aMicrometeorology Group, University of Bayreuth$$b17
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000861629 9101_ $$0I:(DE-HGF)0$$60000-0001-9186-2519$$aInstitute of Meteorology and Climate Research, IMK-IFU, Karlsruhe Institute of Technology$$b19
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