Photosynthesis by terrestrial plants is the main driver of the global carbon cycle, and the presence of actively photosynthesizing vegetation can now be observed from space. However, challenges remain when translating remotely sensed data into carbon fluxes. One reason is that the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), which documents the presence of photosynthetically active vegetation, relates more directly to leaf development and leaf phenology than to photosynthetic rates. Here, we present a new approach for linking FAPAR and vegetation-to-atmosphere carbon fluxes through variational data assimilation. The scheme extends the Carbon Cycle Data Assimilation System (CCDAS) by a newly developed, globally applicable and generic leaf phenology model, which includes both temperature and water-driven leaf development. CCDAS is run for seven sites, six of them included in the FLUXNET network. Optimization is carried out simultaneously for all sites against 20 months of daily FAPAR from the Medium Resolution Imaging Spectrometer on board the European Space Agency's ENVISAT platform. Fourteen parameters related to phenology and 24 related to photosynthesis are optimized simultaneously, and their posterior uncertainties are computed. We find that with one parameter set for all sites, the model is able to reproduce the observed FAPAR spanning boreal, temperate, humid-tropical, and semiarid climates. Assimilation of FAPAR has led to reduced uncertainty (by >10%) of 10 of the 38 parameters, including one parameter related to photosynthesis, and a moderate reduction in net primary productivity uncertainty. The approach can easily be extended to regional or global studies and to the assimilation of further remotely sensed data.