PACE hyperspectral observations enable a new paradigm for global mapping of terrestrial gross primary production

Accurate quantification of terrestrial gross primary production (GPP) is fundamental to understanding plant productivity, ecosystem function, and carbon-climate feedbacks. Existing approaches typically rely on meteorological, soil, and other ancillary inputs, which introduce substantial uncertainties at regional to global scales. NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, carrying the Ocean Color Instrument (OCI), provides the first contiguous global hyperspectral observations from space. Using 122 spectral bands from PACE, we developed a data-driven framework based on partial least squares regression to generate an 8-day global GPP product. The model achieves a robust performance (R 2 = 0.71, RMSE = 1.93 gC m −2 d −1 ), comparable to models that incorporate meteorological drivers, and outperforms approaches based on broadband reflectance or vegetation indices. PACE-derived GPP showed broad spatial correspondence with solar-induced fluorescence (SIF), including hotspots across high productivity regions such as the U.S. Corn Belt, the Amazon and Congo basins, and the Indo-Gangetic and North China Plains. This strong spatial coherence supports the physiological relevance of the PACE retrievals. Our results demonstrate that hyperspectral observations provide a direct, observation-driven framework for estimating plant productivity at the global scale, opening new opportunities for monitoring vegetation responses to environmental change.