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Hydrology / Eddy covariance / METRIC / Primary production / FAPAR / Ecosystem respiration / Flux / International Geosphere-Biosphere Programme / Atmospheric sciences / Earth / FluxNet


Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations
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Document Date: 2014-12-10 05:32:34


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File Size: 3,63 MB

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Wilson / Simmons / Pearson / Agency for the Environment / 17 Forest Services / /

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Europe / Africa / /

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Switzerland / Netherlands / France / Canada / Germany / Italy / Sweden / United States / Ireland / /

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Environmental Issue / /

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European Commission Joint Research Centre / Institute of Plant / Karlsruhe Institute / University College Cork / McMaster University / Institute of Biometeorology / Oregon State University / Clark University / Wageningen University / Institute of Hydrology / University of Toledo / Harvard University / Lund University / University of Tuscia / Max Planck Institute / Free University of Bolzano / /

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measured energy / energy flux / final long‐term harmonized fAPAR product / remote sensing products / artificial neural networks / interim reanalysis product / energy / latent energy / measured energy balance fluxes / respective global reanalysis products / uncertain reanalysis products / tower site / satellite remote sensing / Machine learning algorithms / data processing protocols / extent can algorithms / energy balance residual / forest site / satellite pixel / energy balance / energy balance imbalance / fAPAR product / energy fluxes / energy balance closure / learning algorithms / /

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National Research Council / Free University of Bolzano / Oregon State University / Institut für Agrarrelevante Klimaforschung / Department of Environmental Sciences / Joint Research Centre / Institute for Climate Impact Research / American Geophysical Union / Institute of Hydrology and Meteorology / Centre d’Étude / Institute for Environment / European Commission / Earth Sciences and McMaster Centre for Climate Change / Environmental Monitoring Unit / School of Geography / Department of Meteorology / Climate Change and Air Quality Unit / Lund University / Institute for Environment and Sustainability / McMaster University / Harvard University / Karlsruhe Institute for Technology / Max Planck Institute for Biogeochemistry / Natural Resources Area / Research and Innovation Centre / Technische Universität / Climatic Research Unit / Division of Physical Geography and Ecosystem Analysis / Institute of Plant / University of Tuscia / School of Geography and Earth Sciences / Faculty of Science and Technology / United Nations / Institute of Biometeorology / European Commission Joint Research Centre / University of Toledo / Department of Earth and Ecosystem Sciences / Wageningen University / Institute for Meteorology and Climate Research / Civil and Environmental Engineering Department / Clark University / Department of Organismic and Evolutionary Biology / /

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Edmund Mach / Werner Kutsch / JUNG ET AL / Francesco Vaccari / Tree Ensembles / Martin Jung / Eddy Covariance / LUC CH DC VOC / Johann Heinrich von Thünen / /

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representative / model data fusions / Model Data Integration Group / model trees / Model / /

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Ohio / Bolzano / Ontario / Oregon / Massachusetts / /

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JOURNAL OF GEOPHYSICAL RESEARCH / /

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eastern North America / Northwest America / western Europe / east Asia / central Europe / south Asia / /

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radiation / extent can algorithms / Machine learning algorithms / remote sensing / machine learning / TRIAL+ERROR algorithms / model Tree Induction Algorithm / Environmental Engineering / data processing protocols / /

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