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We are comparing spatially explicit process-model based estimates of the terrestrial carbon balance and its components over Africa and confront them with remote sensing based proxies of vegetation productivity and atmospheric inversions of land-atmosphere net carbon exchange. Particular emphasis is on characterizing the patterns of inter-annual variability(More)
There is a growing consensus that land surface models (LSMs) that simulate terrestrial biosphere exchanges of matter and energy must be better constrained with data to quantify and address their uncertainties. FLUXNET, an international network of sites that measure the land surface exchanges of carbon, water and energy using the eddy covari-ance technique,(More)
Globally, the year 2003 is associated with one of the largest atmospheric CO 2 rises on record. In the same year, Europe experienced an anomalously strong flux of CO 2 from the land to the atmosphere associated with an exceptionally dry and hot summer in Western and Central Europe. In this study we analyze the magnitude of this carbon flux anomaly and key(More)
We evaluate three terrestrial biosphere models (LPJ, Orchidee, Biome-BGC) with respect to their capacity to simulate climate related trends in gross primary production (GPP) of forests in Europe. We compare simulated GPP and leaf area index (LAI) with GPP estimates based on flux separated eddy covariance measurements of net ecosys-5 tem exchange (NEE) and(More)
Recent graphene research has triggered enormous interest in new two-dimensional ordered crystals constructed by the inclusion of elements other than carbon for bandgap opening. The design of new multifunctional two-dimensional materials with proper bandgap has become an important challenge. Here we report a layered two-dimensional network structure that(More)
A detailed understanding of interactions between molecules and graphene is one of the key issues for tailoring the properties of graphene-based molecular devices, because the electronic and structural properties of molecular layers on surfaces are determined by intermolecular and molecule-substrate interactions. Here, we present the atomically resolved(More)
Global, spatially and temporally explicit estimates of carbon and water fluxes derived from empirical up-scaling eddy covariance measurements would constitute a new and possibly powerful data stream to study the variability of the global terrestrial carbon and water cycle. This paper introduces and validates a machine learning approach 5 dedicated to the(More)
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