Articles | Volume 17, issue 6
https://doi.org/10.5194/essd-17-3009-2025
https://doi.org/10.5194/essd-17-3009-2025
Data description paper
 | 
30 Jun 2025
Data description paper |  | 30 Jun 2025

CEDAR-GPP: spatiotemporally upscaled estimates of gross primary productivity incorporating CO2 fertilization

Yanghui Kang, Maoya Bassiouni, Max Gaber, Xinchen Lu, and Trevor F. Keenan

Data sets

CEDAR-GPP: A Spatiotemporally Upscaled Dataset of Gross Primary Productivity Incorporating CO2 Fertilization Yanghui Kang et al. https://doi.org/10.5281/zenodo.8212706

Model code and software

yanghuikang/CEDAR-GPP_upscale: CEDAR-GPP upscaling code Y. Kang https://doi.org/10.5281/zenodo.8400968

Download
Short summary
CEDAR-GPP provides spatiotemporally upscaled estimates of gross primary productivity (GPP) globally, uniquely incorporating the direct effect of elevated atmospheric CO2 on photosynthesis. This dataset was produced by upscaling eddy covariance data with machine learning and a broad range of satellite and climate variables. Available at monthly and 0.05° resolution from 1982 to 2020, CEDAR-GPP offers critical insights into ecosystem–climate interactions and the global carbon cycle.
Share
Altmetrics
Final-revised paper
Preprint