A Robust Estimate of Continental‐Scale Terrestrial Carbon Sinks Using GOSAT XCO <sub>2</sub> Retrievals
Lingyu Zhang, Fei Jiang, Wei He, Mousong Wu, Jun Wang, Weimin Ju, Hengmao Wang, Yongguang Zhang, Stephen Sitch, Anthony P. Walker, Xu Yue, Shuzhuang Feng, Mengwei Jia, Jing M. Chen
Abstract
Abstract Satellite XCO 2 retrievals could improve the estimates of surface carbon fluxes, but it remains unknown on what scales these estimates are robust. Here, we use the time‐dependent Bayesian synthesis top‐down method and prior net ecosystem exchanges (NEEs) from 12 terrestrial biosphere models (TBMs) to infer the monthly carbon fluxes of 51 land regions with constraints by GOSAT XCO 2 retrievals. We find that the uncertainty (standard deviation of 12 TBMs) reduction rates (uncertainty reduction rate (URR)) decrease significantly at decreasing spatial scales. On the continental‐scale, the mean URR is about 57%, and the annual and seasonal cycle estimates of NEE are rather robust. The evaluation shows that the posterior CO 2 concentrations are significantly improved at the continental scale. Our study suggests that the GOSAT XCO 2 can only promise a robust continental‐scale NEE estimate, and improving the XCO 2 accuracy is an effective way to achieve robust estimates on smaller scales under current spatial coverage.