Evaluation of annual trends in carbon cycle variables simulated by CMIP6 Earth system models in China

Systematic evaluation of the carbon cycle physical and biological variables simulated in Earth System Model (ESM) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP 6) is fundamental to the understanding of terrestrial ecosystems, as well as to future projections. Leaf Area Index (LAI), Gross Primary Productivity (GPP), Net Primary Productivity (NPP), Net Ecosystem Productivity (NEP) and Land Surface Temperature (LST) as key indicators of carbon cycle performance in ESM outputs, play a critical role in evaluating ecosystem functions. Assessing these metrics can provide valuable insights into the biases in model-simulated ecosystems and offer guidance for model improvement. In this study, we assessed the interannual trends performance of LAI, GPP, NPP, NEP and LST simulated by 12 CMIP6 ESMs during the historical period by using satellite LAI, NPP, NEP, LST and CSIF data as observations. The findings indicate that: (1) There are significant uncertainties in the overall trends in LAI, NPP, and LST captured by the CMIP6 ESM. Meanwhile, simulated GPP and NEP trends were lower than observations with discrepancies reaching 0.03·yr⁻¹ for GPP and 2.46 g C·m⁻²·yr⁻¹ for NEP. (2) Spatially, these models exhibited widespread misestimation of LAI, GPP, NPP, and NEP trends in most regions of China. The underestimation area except in limited areas, including parts of the western Tibetan Plateau, the Pearl River Basin in southern China, and the North China Plain. Meanwhile, the simulated LST trend is underestimated in northern China, while its overestimations in western and southern China. (3) ESMs inadequate responsiveness to anthropogenic and environmental forcing and incomplete mechanistic representation of plant respiration pathways struggled accurate simulation of trends in LAI, GPP, NPP, NEP and LST.