Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 416966
Title Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations
Author(s) Jung, M.; Reichstein, M.; Cescatti, A.; Richardson, A.D.; Arain, A.; Arneth, A.; Bernhofer, C.; Bonal, D.; Chen, J.; Gianelle, D.; Gobron, N.; Lasslop, G.; Moors, E.J.
Source Journal of Geophysical Research: Biogeosciences 116 (2011)G3. - ISSN 2169-8953 - 16 p.
DOI https://doi.org/10.1029/2010JG001566
Department(s) CWC - Earth System Science and Climate Change
WIMEK
Publication type Refereed Article in a scientific journal
Publication year 2011
Keyword(s) net ecosystem exchange - energy-balance closure - co2 flux - primary productivity - vegetation model - climate - uncertainty - respiration - sensitivity - dynamics
Abstract 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° × 0.5° 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 × 1018 yr-1), H (164 ± 15 J × 1018 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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