Vegetation Photosynthesis Model v3.0: Improved Estimates of Terrestrial Gross Primary Production from Individual Eddy Flux Tower Sites to the Globe

作者：Li Pan, Xiangming Xiao, Baihong Pan, Cheng Meng, Russell Doughty, Yuanwei Qin, Chenchen Zhang, Yuan Yao, Chenglong Yin, Shenglai Yin · 发表于：Journal of Remote Sensing · 年份：2025 · DOI：10.34133/remotesensing.0471 · 被引用次数：10 · 研究领域：Atmospheric and Environmental Gas Dynamics、Solar Radiation and Photovoltaics、Plant Water Relations and Carbon Dynamics

Accurate estimation of gross primary production (GPP) of terrestrial vegetation is crucial for comprehending the carbon dynamics. To date, there is still no consensus on the magnitude and seasonality of global GPP among the major global GPP products, underscoring the necessity to improve GPP models for higher accuracy of global GPP estimates. Here, we introduce an improved Vegetation Photosynthesis Model (VPM v3.0), which incorporates site-specific apparent optimum temperature for photosynthesis, leaf-trait-based light absorption (flat leaf vs. needle leaf), and improved water stress estimation. The global VPM simulation is driven by Moderate Resolution Imaging Spectroradiometer images and the ERA5-Land climate dataset. We evaluate VPM v3.0 using GPP from 205 eddy flux tower sites across 11 land cover types (1,658 site-years) (GPP EC ), as well as the TROPOspheric monitoring instrument (TROPOMI) solar-induced fluorescence (SIF) product for 2018 to 2021. The slope, R 2 , and root mean square error between GPP from VPM v3.0 (GPP VPM-v3 ) and GPP EC are 0.97, 0.78, and 1.46 gC m −2 day −1 , respectively. GPP VPM-v3 shows high temporal consistency with TROPOMI SIF. VPM v3.0 provides higher accuracy of GPP estimates at most evaluated sites than VPM v2.0. Comparisons of global GPP from VPM v3.0 with other major global GPP products reveal both spatial–temporal consistency and discrepancies. These findings clearly indicate the improved accuracy of VPM v3.0 in estimating GPP, making i...