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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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https://doi.org/10.5194/amt-2017-237
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
10 Oct 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).
Regional uncertainty of GOSAT XCO2 retrievals in China: Quantification and attribution
Nian Bie1,2, Liping Lei1, Zhaocheng Zeng3, Bofeng Cai4, Shaoyuan Yang1,2, Zhonghua He1,2, Changjiang Wu1,2, and Ray Nassar5 1Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
2University of Chinese Academy of Sciences, Beijing 100049, China
3Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA91125, USA
4The Center for Climate Change and Environmental Policy, Chinese Academy for Environmental Planning, Ministry of Environmental Protection, Beijing, 100012, China
5Climate Research Division, Environment and Climate Change, Canada
Abstract. The regional uncertainty of XCO2 (column-averaged dry air mole fraction of CO2) retrieved using different algorithms from the Greenhouse gases Observing SATellite (GOSAT) and its attribution are still not well understood. This paper investigates the regional performance of XCO2 within a band of 37° N–42° N segmented into 8 cells in a grid of 5° from west to east (80° E–120° E) in China, where there are typical land surface types and geographic conditions. The former include the various land covers of desert, grassland and built-up areas mixed with cropland, and the latter include anthropogenic emissions that tend to be small to large from west to east, including those from the megacity of Beijing. For these specific cells, we evaluate the regional uncertainty of GOSAT XCO2 retrievals by quantifying and attributing the consistency of XCO2 retrievals from five algorithms (ACOS, NIES, EMMA, OCFP, and SRFP) by intercomparison and particularly by comparing these with simulated XCO2 from the Goddard Earth Observing System 3-D chemical transport model (GEOS-Chem), the nested model in East Asia. We introduce the anthropogenic CO2 emissions data generated from the investigation of surface emitting point sources that was conducted by the Ministry of Environmental Protection of China to GEOS-Chem simulations of XCO2 over the Chinese mainland. The results indicate that (1) regionally, the five algorithms demonstrate smaller absolute biases between 0.9–1.5 ppm in eastern cells, which are covered by built-up areas mixed with cropland with intensive anthropogenic emissions, than those in the western desert cells with a high-brightness surface, 1.2–2.2 ppm from the pairwise comparison results of XCO2 retrievals. The inconsistency of XCO2 from the five algorithms tends to be high in the Taklimakan Desert in western cells, which is likely induced by high surface albedo in addition to dust aerosols in this region. (2) Compared with XCO2 simulated by GEOS-Chem (GEOS-XCO2), the XCO2 values of ACOS and SRFP better agree with GEOS-XCO2, while OCFP is the least consistent with GEOS-XCO2. (3) Viewing attributions of XCO2 in the spatio-temporal pattern, ACOS, SRFP and EMMA demonstrate similar patterns, while OCFP is largely different from the others. In conclusion, the discrepancy in the five algorithms is the smallest in eastern cells in the investigated band where the megacity of Beijing is located and where there are strong anthropogenic CO2 emissions, which implies that XCO2 from satellite observations could be reliably applied in the assessment of atmospheric CO2 enhancements induced by anthropogenic CO2 emissions. The large inconsistency among the five algorithms presented in western deserts with a high albedo and dust aerosols, moreover, demonstrates that further improvement is still necessary in such regions, even though many algorithms have endeavored to minimize the effects of aerosols and albedo.

Citation: Bie, N., Lei, L., Zeng, Z., Cai, B., Yang, S., He, Z., Wu, C., and Nassar, R.: Regional uncertainty of GOSAT XCO2 retrievals in China: Quantification and attribution, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-237, in review, 2017.
Nian Bie et al.
Nian Bie et al.
Nian Bie et al.

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Short summary
The results implies that XCO2 from satellite observations could be reliably applied in the assessment of atmospheric CO2 enhancements induced by anthropogenic CO2 emissions. The large inconsistency among different algorithms presented in western deserts with a high albedo and dust aerosols, demonstrates that further improvement is still necessary in such regions, even though many algorithms have endeavored to minimize the effects of aerosols and albedo.
The results implies that XCO2 from satellite observations could be reliably applied in the...
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