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dc.contributor.authorPARAZOO Nicholasen_GB
dc.contributor.authorCESCATTI Alessandroen_GB
dc.contributor.authorBOWMAN Kevinen_GB
dc.contributor.authorFISHER Joshuaen_GB
dc.contributor.authorFRANKENBERG Christianen_GB
dc.contributor.authorJONES Dylanen_GB
dc.contributor.authorPEREZ-PRIEGO Oscaren_GB
dc.contributor.authorWOHLFAHRT G.en_GB
dc.contributor.authorMONTAGNANI Leonardoen_GB
dc.identifier.citationGLOBAL CHANGE BIOLOGY vol. 20 no. 10 p. 3103–3121en_GB
dc.description.abstractDetermining the spatial and temporal distribution of terrestrial gross primary production (GPP) is a critical step in closing the Earth’s carbon budget. Dynamical global vegetation models (DGVMs) provide mechanistic insight into GPP variability but diverge in predicting the response to climate in poorly investigated regions. Recent advances in the remote sensing of solar-induced chlorophyll fluorescence (SIF) opens up a new possibility to provide direct global observational constraints for GPP. Here, we apply an optimal estimation approach to infer the global distribution of GPP from an ensemble of eight DGVMs constrained by global measurements of SIF from the Greenhouse Gases Observing SATellite (GOSAT). These estimates are compared to flux tower data in N. America, Europe, and tropical S. America, with careful consideration of scale differences between models, GOSAT, and flux towers. Assimilation of GOSAT SIF with DGVMs causes a redistribution of global productivity from northern latitudes to the tropics of 7– 8PgCyr?1 from 2010 to 2012, with reduced GPP in northern forests (~3.6 Pg C yr?1) and enhanced GPP in tropical forests (~3.7 Pg C yr?1). This leads to improvements in the structure of the seasonal cycle, including earlier dry sea- son GPP loss and enhanced peak-to-trough GPP in tropical forests within the Amazon Basin and reduced growing season length in northern croplands and deciduous forests. Uncertainty in predicted GPP (estimated from the spread of DGVMs) is reduced by 40–70% during peak productivity suggesting the assimilation of GOSAT SIF with models is well-suited for benchmarking. We conclude that satellite fluorescence augurs a new opportunity to quantify the GPP responseen_GB
dc.description.sponsorshipJRC.H.7-Climate Risk Managementen_GB
dc.titleTerrestrial gross primary production inferred from satellite fluorescence and vegetation modelsen_GB
dc.typeArticles in periodicals and booksen_GB
JRC Directorate:Sustainable Resources

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