Articles | Volume 11, issue 3
https://doi.org/10.5194/amt-11-1251-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-11-1251-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Mar 2018
Research article |
| 05 Mar 2018
| 05 Mar 2018
Regional uncertainty of GOSAT XCO2 retrievals in China: quantification and attribution
Nian Bie
Key Laboratory of Digital Earth Science, Institute of Remote
Sensing and Digital Earth, Chinese Academy of Sciences, Beijing
100094, China
University of Chinese Academy of Sciences, Beijing 100049, China
Liping Lei
CORRESPONDING AUTHOR
Key Laboratory of Digital Earth Science, Institute of Remote
Sensing and Digital Earth, Chinese Academy of Sciences, Beijing
100094, China
ZhaoCheng Zeng
Division of Geological and Planetary Sciences, California Institute of
Technology, Pasadena, CA 91125, USA
Bofeng Cai
The Center for Climate Change and Environmental Policy,
Chinese Academy for Environmental Planning, Ministry of
Environmental Protection, Beijing 100012, China
Shaoyuan Yang
Key Laboratory of Digital Earth Science, Institute of Remote
Sensing and Digital Earth, Chinese Academy of Sciences, Beijing
100094, China
University of Chinese Academy of Sciences, Beijing 100049, China
Zhonghua He
Key Laboratory of Digital Earth Science, Institute of Remote
Sensing and Digital Earth, Chinese Academy of Sciences, Beijing
100094, China
University of Chinese Academy of Sciences, Beijing 100049, China
Changjiang Wu
Key Laboratory of Digital Earth Science, Institute of Remote
Sensing and Digital Earth, Chinese Academy of Sciences, Beijing
100094, China
University of Chinese Academy of Sciences, Beijing 100049, China
Ray Nassar
Climate Research Division, Environment and Climate Change
Canada, Toronto, Ontario, Canada
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Cited
16 citations as recorded by crossref.
- A review of datasets and methods for deriving spatiotemporal distributions of atmospheric CO2 C. He et al. 10.1016/j.jenvman.2022.116101
- Comparison of Atmospheric Carbon Dioxide Concentrations Based on GOSAT, OCO-2 Observations and Ground-Based TCCON Data J. Zheng et al. 10.3390/rs15215172
- Global-Scale Evaluation of XCO2 Products from GOSAT, OCO-2 and CarbonTracker Using Direct Comparison and Triple Collocation Method Y. Chen et al. 10.3390/rs14225635
- Global land 1° mapping dataset of XCO2 from satellite observations of GOSAT and OCO-2 from 2009 to 2020 M. Sheng et al. 10.1080/20964471.2022.2033149
- Spatial and temporal distribution and seasonal prediction of satellite measurement of CO2 concentration over Iran F. Golkar & A. Shirvani 10.1080/01431161.2020.1788743
- Validation of Remotely Sensed XCO2 Products With TCCON Observations in East Asia M. Ji et al. 10.1109/JSTARS.2024.3378229
- Spatial and Temporal Variations of Atmospheric CO2 Concentration in China and Its Influencing Factors Z. Lv et al. 10.3390/atmos11030231
- Satellite-Based Reconstruction of Atmospheric CO2 Concentration over China Using a Hybrid CNN and Spatiotemporal Kriging Model Y. Hua et al. 10.3390/rs16132433
- Analysis of atmospheric greenhouse gases in north Xinjiang L. Liu et al. 10.1016/j.atmosenv.2021.118823
- Neural-network-based estimation of regional-scale anthropogenic CO<sub>2</sub> emissions using an Orbiting Carbon Observatory-2 (OCO-2) dataset over East and West Asia F. Mustafa et al. 10.5194/amt-14-7277-2021
- On the performance of satellite-based observations of <i>X</i>CO<sub>2</sub> in capturing the NOAA Carbon Tracker model and ground-based flask observations over Africa's land mass A. Mengistu & G. Mengistu Tsidu 10.5194/amt-13-4009-2020
- Modification of Fraser’s Method for the Atmospheric CO2 Mass Estimation by Using Satellite Data M. Pellegrini et al. 10.3390/atmos13060866
- A Multiyear Constraint on Ammonia Emissions and Deposition Within the US Corn Belt C. Hu et al. 10.1029/2020GL090865
- High-Coverage Reconstruction of XCO2 Using Multisource Satellite Remote Sensing Data in Beijing–Tianjin–Hebei Region W. Wang et al. 10.3390/ijerph191710853
- An Assessment of Anthropogenic CO2 Emissions by Satellite-Based Observations in China S. Yang et al. 10.3390/s19051118
- Specific patterns of XCO2 observed by GOSAT during 2009–2016 and assessed with model simulations over China N. Bie et al. 10.1007/s11430-018-9377-7
16 citations as recorded by crossref.
- A review of datasets and methods for deriving spatiotemporal distributions of atmospheric CO2 C. He et al. 10.1016/j.jenvman.2022.116101
- Comparison of Atmospheric Carbon Dioxide Concentrations Based on GOSAT, OCO-2 Observations and Ground-Based TCCON Data J. Zheng et al. 10.3390/rs15215172
- Global-Scale Evaluation of XCO2 Products from GOSAT, OCO-2 and CarbonTracker Using Direct Comparison and Triple Collocation Method Y. Chen et al. 10.3390/rs14225635
- Global land 1° mapping dataset of XCO2 from satellite observations of GOSAT and OCO-2 from 2009 to 2020 M. Sheng et al. 10.1080/20964471.2022.2033149
- Spatial and temporal distribution and seasonal prediction of satellite measurement of CO2 concentration over Iran F. Golkar & A. Shirvani 10.1080/01431161.2020.1788743
- Validation of Remotely Sensed XCO2 Products With TCCON Observations in East Asia M. Ji et al. 10.1109/JSTARS.2024.3378229
- Spatial and Temporal Variations of Atmospheric CO2 Concentration in China and Its Influencing Factors Z. Lv et al. 10.3390/atmos11030231
- Satellite-Based Reconstruction of Atmospheric CO2 Concentration over China Using a Hybrid CNN and Spatiotemporal Kriging Model Y. Hua et al. 10.3390/rs16132433
- Analysis of atmospheric greenhouse gases in north Xinjiang L. Liu et al. 10.1016/j.atmosenv.2021.118823
- Neural-network-based estimation of regional-scale anthropogenic CO<sub>2</sub> emissions using an Orbiting Carbon Observatory-2 (OCO-2) dataset over East and West Asia F. Mustafa et al. 10.5194/amt-14-7277-2021
- On the performance of satellite-based observations of <i>X</i>CO<sub>2</sub> in capturing the NOAA Carbon Tracker model and ground-based flask observations over Africa's land mass A. Mengistu & G. Mengistu Tsidu 10.5194/amt-13-4009-2020
- Modification of Fraser’s Method for the Atmospheric CO2 Mass Estimation by Using Satellite Data M. Pellegrini et al. 10.3390/atmos13060866
- A Multiyear Constraint on Ammonia Emissions and Deposition Within the US Corn Belt C. Hu et al. 10.1029/2020GL090865
- High-Coverage Reconstruction of XCO2 Using Multisource Satellite Remote Sensing Data in Beijing–Tianjin–Hebei Region W. Wang et al. 10.3390/ijerph191710853
- An Assessment of Anthropogenic CO2 Emissions by Satellite-Based Observations in China S. Yang et al. 10.3390/s19051118
- Specific patterns of XCO2 observed by GOSAT during 2009–2016 and assessed with model simulations over China N. Bie et al. 10.1007/s11430-018-9377-7
Latest update: 20 Nov 2024
Short summary
The results imply 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 imply that XCO2 from satellite observations could be reliably applied in the...
