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  Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations

Jung, M., Reichstein, M., Margolis, H. A., Cescatti, A., Richardson, A. D., Arain, M. A., et al. (2011). Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations. Journal of Geophysical Research - Biogeosciences, 116, G00j07. doi:10.1029/2010jg001566.

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Jung, M.1, Autor           
Reichstein, M.1, Autor           
Margolis, H. A., Autor
Cescatti, A., Autor
Richardson, A. D., Autor
Arain, M. A., Autor
Arneth, A., Autor
Bernhofer, C., Autor
Bonal, D., Autor
Chen, J. Q., Autor
Gianelle, D., Autor
Gobron, N., Autor
Kiely, G., Autor
Kutsch, W., Autor
Lasslop, G.1, Autor           
Law, B. E., Autor
Lindroth, A., Autor
Merbold, L., Autor
Montagnani, L., Autor
Moors, E. J., Autor
Papale, D., AutorSottocornola, M., AutorVaccari, F., AutorWilliams, C., Autor mehr..
Affiliations:
1Research Group Biogeochemical Model-data Integration, Dr. M. Reichstein, Max Planck Institute for Biogeochemistry, Max Planck Society, ou_1497760              

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Schlagwörter: net ecosystem exchange energy-balance closure CO2 flux primary productivity vegetation model climate uncertainty respiration sensitivity dynamics
 Zusammenfassung: We upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE). We trained MTE to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use. We applied the trained MTEs to generate global flux fields at a 0.5 degrees x 0.5 degrees spatial resolution and a monthly temporal resolution from 1982 to 2008. Cross-validation analyses revealed good performance of MTE in predicting among-site flux variability with modeling efficiencies (MEf) between 0.64 and 0.84, except for NEE (MEf = 0.32). Performance was also good for predicting seasonal patterns (MEf between 0.84 and 0.89, except for NEE (0.64)). By comparison, predictions of monthly anomalies were not as strong (MEf between 0.29 and 0.52). Improved accounting of disturbance and lagged environmental effects, along with improved characterization of errors in the training data set, would contribute most to further reducing uncertainties. Our global estimates of LE (158 +/- 7 J x 10(18) yr(-1)), H (164 +/- 15 J x 10(18) yr(-1)), and GPP (119 +/- 6 Pg C yr(-1)) were similar to independent estimates. Our global TER estimate (96 +/- 6 Pg C yr(-1)) was likely underestimated by 5-10%. Hot spot regions of interannual variability in carbon fluxes occurred in semiarid to semihumid regions and were controlled by moisture supply. Overall, GPP was more important to interannual variability in NEE than TER. Our empirically derived fluxes may be used for calibration and evaluation of land surface process models and for exploratory and diagnostic assessments of the biosphere.

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Sprache(n): eng - English
 Datum: 2011
 Publikationsstatus: Erschienen
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 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: DOI: 10.1029/2010jg001566
ISI: ://WOS:000294615800001
Anderer: BGC1536
 Art des Abschluß: -

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Titel: Journal of Geophysical Research - Biogeosciences
Genre der Quelle: Zeitschrift
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Seiten: - Band / Heft: 116 Artikelnummer: - Start- / Endseite: G00j07 Identifikator: ISSN: 0148-0227