Satellite data-driven estimation of daily and 500 m net ecosystem exchange over China during 2003–2020

Abstract

The terrestrial biosphere plays a critical role in mitigating climate change by absorbing anthropogenic CO₂. However, accurately quantifying the net ecosystem exchange (NEE), which is a key indicator for monitoring carbon sequestration of terrestrial ecosystems, remains a major challenge. Widely used products from large-scale ecosystem models and atmospheric inversions operate at coarse resolutions (0.25° or greater), which hinders the ability to resolve the carbon dynamics of heterogeneous landscapes and poses a significant challenge to understanding the impact of climate and land-use changes. In this study, a remote sensing data-driven water‑carbon coupling model with the incorporation of terrestrial carbon cycle processes, Penman–Monteith–Leuning Version 2 Carbon (PMLV2C), is developed for estimating daily NEE over China at a 500 m resolution. The parameters of PML-V2C model were well calibrated against observations from 41 eddy covariance (EC) flux tower sites across nine plant functional types (PFTs) over China, demonstrating a strong performance for daily NEE estimates (r = 0.71, RMSE = 1.85 g C m⁻² day⁻¹). The model is only slightly degraded when compared with independent global FLUXNET data across 157 sites, demonstrating its robustness and transferability across diverse climates and biomes. Applying the model from 2003 to 2020, our product revealed a significant enhancement of China's terrestrial carbon sink with an increasing trend of 0.041 Tg C yr⁻² (p < 0.01). This enhancement was primarily driven by the increasing GPP from forests in Southern China, grasslands in Northern China, and croplands across the East and North China Plain. Our high-resolution, process-based NEE product driven by satellite data provides a new evaluation of the effectiveness of ecosystem restoration and land management policies, offering valuable insights for achieving national carbon neutrality goals.