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      Contrasting nitrogen fluxes in African tropical forests of the Congo Basin

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          Nutrient Cycling in Moist Tropical Forest

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            Litterfall, Nutrient Cycling, and Nutrient Limitation in Tropical Forests

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              Is Open Access

              GLEAM v3: satellite-based land evaporation and root-zone soil moisture

              The Global Land Evaporation Amsterdam Model (GLEAM) is a set of algorithms dedicated to the estimation of terrestrial evaporation and root-zone soil moisture from satellite data. Ever since its development in 2011, the model has been regularly revised, aiming at the optimal incorporation of new satellite-observed geophysical variables, and improving the representation of physical processes. In this study, the next version of this model (v3) is presented. Key changes relative to the previous version include (1) a revised formulation of the evaporative stress, (2) an optimized drainage algorithm, and (3) a new soil moisture data assimilation system. GLEAM v3 is used to produce three new data sets of terrestrial evaporation and root-zone soil moisture, including a 36-year data set spanning 1980–2015, referred to as v3a (based on satellite-observed soil moisture, vegetation optical depth and snow-water equivalent, reanalysis air temperature and radiation, and a multi-source precipitation product), and two satellite-based data sets. The latter share most of their forcing, except for the vegetation optical depth and soil moisture, which are based on observations from different passive and active C- and L-band microwave sensors (European Space Agency Climate Change Initiative, ESA CCI) for the v3b data set (spanning 2003–2015) and observations from the Soil Moisture and Ocean Salinity (SMOS) satellite in the v3c data set (spanning 2011–2015). Here, these three data sets are described in detail, compared against analogous data sets generated using the previous version of GLEAM (v2), and validated against measurements from 91 eddy-covariance towers and 2325 soil moisture sensors across a broad range of ecosystems. Results indicate that the quality of the v3 soil moisture is consistently better than the one from v2: average correlations against in situ surface soil moisture measurements increase from 0.61 to 0.64 in the case of the v3a data set and the representation of soil moisture in the second layer improves as well, with correlations increasing from 0.47 to 0.53. Similar improvements are observed for the v3b and c data sets. Despite regional differences, the quality of the evaporation fluxes remains overall similar to the one obtained using the previous version of GLEAM, with average correlations against eddy-covariance measurements ranging between 0.78 and 0.81 for the different data sets. These global data sets of terrestrial evaporation and root-zone soil moisture are now openly available at www.GLEAM.eu and may be used for large-scale hydrological applications, climate studies, or research on land–atmosphere feedbacks.
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                Author and article information

                Journal
                Ecological Monographs
                Ecol Monogr
                Wiley
                00129615
                February 2019
                February 2019
                January 02 2019
                : 89
                : 1
                : e01342
                Affiliations
                [1 ]Isotope Bioscience Laboratory - ISOFYS; Department of Green Chemistry and Technology; Ghent University; Coupure Links 653 9000 Gent Belgium
                [2 ]CAVElab, Computational and Applied Vegetation Ecology; Department of Environment; Ghent University; Coupure Links 653 9000 Gent Belgium
                [3 ]Department of Earth Sciences; University of Gothenburg; Box 460 405 30 Gothenburg Sweden
                [4 ]Sustainable Agroecosystems; Department of Environmental Systems Science; ETH Zürich; Tannenstrasse 1 8092 Zürich Switzerland
                [5 ]Laboratory of Soil Science; Department of General Agricultural Sciences; University of Lubumbashi; PO Box 1825 Lubumbashi Democratic Republic of Congo
                [6 ]Faculté d'Agronomie; Université Catholique de Bukavu; Avenue de la Mission, Box 285 Bukavu Democratic Republic of Congo
                [7 ]Plant Department; Faculty of Science; Université de Kisangani; Kisangani Democratic Republic of Congo
                Article
                10.1002/ecm.1342
                9f3a140c-b528-41a7-800c-bcc7b62668f1
                © 2019

                http://doi.wiley.com/10.1002/tdm_license_1.1

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