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| Titel |
On the choice of the driving temperature for eddy-covariance carbon dioxide flux partitioning |
| VerfasserIn |
G. Lasslop, M. Migliavacca, G. Bohrer, M. Reichstein, M. Bahn, A. Ibrom, C. Jacobs, P. Kolari, D. Papale, T. Vesala, G. Wohlfahrt, A. Cescatti |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1726-4170
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| Digitales Dokument |
URL |
| Erschienen |
In: Biogeosciences ; 9, no. 12 ; Nr. 9, no. 12 (2012-12-18), S.5243-5259 |
| Datensatznummer |
250007468
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| Publikation (Nr.) |
 copernicus.org/bg-9-5243-2012.pdf |
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| Zusammenfassung |
| Networks that merge and harmonise eddy-covariance measurements from many
different parts of the world have become an important observational resource
for ecosystem science. Empirical algorithms have been developed which combine
direct observations of the net ecosystem exchange of carbon dioxide with
simple empirical models to disentangle photosynthetic (GPP) and respiratory
fluxes (Reco). The increasing use of these estimates for the analysis of
climate sensitivities, model evaluation and calibration demands a thorough
understanding of assumptions in the analysis process and the resulting
uncertainties of the partitioned fluxes. The semi-empirical models used in
flux partitioning algorithms require temperature observations as input, but
as respiration takes place in many parts of an ecosystem, it is unclear which
temperature input – air, surface, bole, or soil at a specific depth –
should be used. This choice is a source of uncertainty and potential biases.
In this study, we analysed the correlation between different temperature
observations and nighttime NEE (which equals nighttime respiration) across
FLUXNET sites to understand the potential of the different temperature
observations as input for the flux partitioning model. We found that the
differences in the correlation between different temperature data streams and
nighttime NEE are small and depend on the selection of sites. We investigated
the effects of the choice of the temperature data by running two flux
partitioning algorithms with air and soil temperature. We found the time lag
(phase shift) between air and soil temperatures explains the differences in
the GPP and Reco estimates when using either air or soil temperatures for
flux partitioning. The impact of the source of temperature data on other
derived ecosystem parameters was estimated, and the strongest impact was
found for the temperature sensitivity. Overall, this study suggests that the
choice between soil or air temperature must be made on site-by-site basis by
analysing the correlation between temperature and nighttime NEE. We recommend
using an ensemble of estimates based on different temperature observations to
account for the uncertainty due to the choice of temperature and to assure
the robustness of the temporal patterns of the derived variables. |
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