A Robust Estimate of Continental‐Scale Terrestrial Carbon Sinks Using GOSAT XCO2 Retrievals

Author:

Zhang Lingyu1,Jiang Fei123ORCID,He Wei1ORCID,Wu Mousong1ORCID,Wang Jun1ORCID,Ju Weimin123ORCID,Wang Hengmao1ORCID,Zhang Yongguang123ORCID,Sitch Stephen4ORCID,Walker Anthony P.5ORCID,Yue Xu6ORCID,Feng Shuzhuang1,Jia Mengwei1,Chen Jing M.7ORCID

Affiliation:

1. Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology International Institute for Earth System Science Nanjing University Nanjing China

2. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing China

3. Frontiers Science Center for Critical Earth Material Cycling Nanjing University Nanjing China

4. College of Life and Environmental Sciences University of Exeter Exeter UK

5. Environmental Sciences Division and Climate Change Science Institute Oak Ridge National Laboratory Oak Ridge TN USA

6. School of Environmental Science and Engineering Nanjing University of Information Science & Technology (NUIST) Nanjing China

7. Department of Geography and Planning University of Toronto Toronto Ontario Canada

Abstract

AbstractSatellite XCO2 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 XCO2 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 CO2 concentrations are significantly improved at the continental scale. Our study suggests that the GOSAT XCO2 can only promise a robust continental‐scale NEE estimate, and improving the XCO2 accuracy is an effective way to achieve robust estimates on smaller scales under current spatial coverage.

Funder

National Natural Science Foundation of China

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Geophysics

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