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Titel |
Characterizing ecosystem-atmosphere interactions from short to interannual time scales |
VerfasserIn |
M. D. Mahecha, M. Reichstein, H. Lange, N. Carvalhais, C. Bernhofer, T. Grünwald, D. Papale, G. Seufert |
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 ; 4, no. 5 ; Nr. 4, no. 5 (2007-09-13), S.743-758 |
Datensatznummer |
250001958
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Publikation (Nr.) |
copernicus.org/bg-4-743-2007.pdf |
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Zusammenfassung |
Characterizing ecosystem-atmosphere interactions in terms of carbon and water
exchange on different time scales is considered a major challenge in
terrestrial biogeochemical cycle research. The respective time series
currently comprise an observation period of up to one decade. In this study,
we explored whether the observation period is already sufficient to detect
cross-relationships between the variables beyond the annual cycle, as they
are expected from comparable studies in climatology.
We investigated the potential of Singular System Analysis (SSA) to extract
arbitrary kinds of oscillatory patterns. The method is completely data
adaptive and performs an effective signal to noise separation.
We found that most observations (Net Ecosystem Exchange, NEE, Gross
Primary Productivity, GPP, Ecosystem Respiration, Reco, Vapor Pressure Deficit, VPD, Latent Heat, LE,
Sensible Heat, H, Wind Speed, u, and Precipitation,
P) were influenced significantly by low-frequency components
(interannual variability). Furthermore, we extracted a set of nontrivial
relationships and found clear seasonal hysteresis effects except for the
interrelation of NEE with Global Radiation (Rg).
SSA provides a new tool for the investigation of these phenomena explicitly
on different time scales. Furthermore, we showed that SSA has great potential
for eddy covariance data processing, since it can be applied as a novel gap
filling approach relying on the temporal correlation structure of the time
series structure only. |
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