Satellite‐Derived Leaf Photosynthetic Capacity Data Set Improves Atmospheric Inversion of Terrestrial Carbon Fluxes

Accurately estimating the terrestrial carbon sink is crucial for understanding the global carbon cycle. Here, we examine how different parameterizations of the key leaf photosynthetic capacity parameter, namely the maximum Rubisco carboxylation rate normalized to 25°C ( V cmax25 ), influence terrestrial carbon flux estimates within an atmospheric inversion system. We demonstrate that using a spatially heterogeneous and seasonally varying V cmax25 data set derived from satellite solar‐induced fluorescence (SIF) and leaf chlorophyll content (LCC) yields more realistic spatial patterns of net ecosystem exchange (NEE) compared to the conventional plant functional type (PFT)‐fixed approach. This improvement subsequently enhances both prior and posterior CO 2 simulations constrained by GOSAT or OCO‐2 vertically averaged CO 2 (XCO 2 ) retrievals, as validated against independent Observation Package (ObsPack) surface flask and aircraft measurements, as well as Total Carbon Column Observing Network (TCCON) retrievals. Our results highlight that accurate photosynthesis parameterization is fundamental to advancing top‐down estimates of the terrestrial carbon sink.