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| Home > Publications database > Sensitivity Analysis of a Source Partitioning Method for H$_2$O and CO$_2$ Fluxes via Large Eddy Simulations > print |
| 001 | 862423 | ||
| 005 | 20210130001345.0 | ||
| 024 | 7 | _ | |a 2128/22091 |2 Handle |
| 037 | _ | _ | |a FZJ-2019-02745 |
| 100 | 1 | _ | |a Klosterhalfen, Anne |0 P:(DE-Juel1)159313 |b 0 |e Corresponding author |u fzj |
| 111 | 2 | _ | |a EGU General Assembly 2019 |g EGU 2019 |c Wien |d 2019-04-07 - 2019-04-12 |w Austria |
| 245 | _ | _ | |a Sensitivity Analysis of a Source Partitioning Method for H$_2$O and CO$_2$ Fluxes via Large Eddy Simulations |
| 260 | _ | _ | |c 2019 |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
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| 336 | 7 | _ | |a Poster |b poster |m poster |0 PUB:(DE-HGF)24 |s 1556000441_22955 |2 PUB:(DE-HGF) |x After Call |
| 500 | _ | _ | |a Also supported by Netherlands Science Foundation under contract NWO 15774 |
| 520 | _ | _ | |a For an assessment of the role of soil and vegetation in the climate system, a further understanding of the fluxcomponents of H$_2$O and CO$_2$ and their interaction with physical conditions and physiological functioning ofplants and ecosystems is necessary. Scanlon and Sahu (2008) and Scanlon and Kustas (2010) proposed a sourcepartitioning method (SK10 in the following) to estimate the flux components transpiration, evaporation, photosynthesis,and respiration on the ecosystem scale obtained by the eddy covariance method. High frequency timeseries are needed, and the source partitioning is estimated based on the separate application of the flux-variancesimilarity theory to the stomatal and non-stomatal components of the regarded fluxes, as well as on additionalassumptions on water use efficiency (WUE) on the leaf scale. The estimated WUE has been found to exert a stronginfluence on the performance of the partitioning method.\\Evaluations of SK10 with field observations suffer from the fact that the real source partitioning is usuallyunknown, and that various disturbances may influence the correlation between H$_2$O and CO$_2$ fluctuations at studysites. Therefore, we conducted Large Eddy Simulations (LES), simulating the turbulent transport of H$_2$O andCO$_2$ under consideration of contrasting vertical sink-source-distributions in the canopy, and of soil sources withvarying magnitudes. SK10 was applied to these synthetic high-frequency data and the partitioning performancecould be evaluated depending on canopy type, measurement height, and given sink-source-distributions. For asatisfying performance of SK10, a certain degree of decorrelation of the H$_2$O and CO$_2$ fluctuations was needed,which was enhanced for observations within the roughness sublayer, as well as by a clear separation between soiland canopy sources. The expected dependence of the partitioning results to the WUE input could be observed,where an incorrect estimation of WUE affected the flux components of soil sources stronger than components ofthe canopy sink/source. As a new finding, our LES study indicated that next to a precise WUE estimation, thevalidity of the key assumptions made by Scanlon and Sahu (2008) in the method’s derivation is a crucial pointfor a correct application of SK10. Therefore, a thorough assessment of the conditions at study sites affecting thevalidity of these assumptions would be necessary.\\Scanlon, T.M., Sahu, P., 2008. On the correlation structure of water vapor and carbon dioxide in the atmosphericsurface layer: A basis for flux partitioning. Water Resources Research 44 (10), W10418, 15 pp,https://doi.org/10.1029/2008WR006932.\\Scanlon, T.M., Kustas, W.P., 2010. Partitioning carbon dioxide and water vapor fluxes using correlation analysis.Agricultural and Forest Meteorology 150 (1), 89-99, https://doi.org/10.1016/j.agrformet.2009.09.005. |
| 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 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 1 |
| 700 | 1 | _ | |a Moene, Arnold F. |0 P:(DE-HGF)0 |b 1 |
| 700 | 1 | _ | |a Schmidt, Marius |0 P:(DE-Juel1)144420 |b 2 |u fzj |
| 700 | 1 | _ | |a Scanlon, Todd M. |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Vereecken, Harry |0 P:(DE-Juel1)129549 |b 4 |u fzj |
| 700 | 1 | _ | |a Graf, Alexander |0 P:(DE-Juel1)129461 |b 5 |u fzj |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/862423/files/Poster_EGU2019_Klosterhalfen.pdf |
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