[A-CG35] Global Carbon Cycle Observation and Analysis

[ACG35-P05] Analyzing changes in terrestrial carbon cycle using a terrestrial carbon cycle model, VISIT and an inversion based estimation

*Kazuhito Ichii¹, Akane Kurihara¹, Ruci Wang¹, Naveen Chandra², Prabir Patra² (1.Chiba University, 2.JAMSTEC)

Keywords:carbon cycle, terrestrial ecosystem, top-down and bottom-up estimation

Atmospheric CO2 concentration and its global cycle play an important role in predicting future atmospheric CO2 concentration and climate change. Terrestrial carbon cycle is one the most uncertain parts due to its spatial heterogenity and differences in its response to climate variability. Thus, understanding of current terresrial carbon cycle is essential. In this study, we evaluated two independent estimations of terrestrial carbon cycle from 2001 to 2021 period. Top-down estimation provides land-atmosphere carbon exchanges from atmospheric CO2 observation and bottom-up estmation provides based on each process and each region. In this study, we used VISIT terrestrial carbon cycle model and machine-learning based estimations as bottom-up methods, and an inversion analysis outputs, MIROC4-ACTM inversion, as an top-down method. VISIT model outpus were overall consistent with other estimationa, such as machine-learning based and top-down estimations in terms of interannual variations. In particular, some regions such as Southeast Asia show good consistency. We will also report results of a series of sensitivity test, and discuss changes in terrestrial carbon cycle.