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

Authors :
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
Source :
Geophysical Research Letters, Vol 50, Iss 6, Pp n/a-n/a (2023)
Publication Year :
2023
Publisher :
Wiley, 2023.

Abstract

Abstract Satellite 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.

Details

Language :
English
ISSN :
19448007 and 00948276
Volume :
50
Issue :
6
Database :
Directory of Open Access Journals
Journal :
Geophysical Research Letters
Publication Type :
Academic Journal
Accession number :
edsdoj.7ad156082f545209edffdcdf2ff980e
Document Type :
article
Full Text :
https://doi.org/10.1029/2023GL102815