Articles | Volume 23, issue 12
https://doi.org/10.5194/acp-23-6719-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-23-6719-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Jun 2023
Research article |
| 20 Jun 2023
| 20 Jun 2023
The carbon sink in China as seen from GOSAT with a regional inversion system based on the Community Multi-scale Air Quality (CMAQ) and ensemble Kalman smoother (EnKS)
Xingxia Kou
Institute of Urban Meteorology, China Meteorological Administration, Beijing, China
Key Laboratory of Urban Meteorology, China Meteorological Administration, Beijing, China
Zhen Peng
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Meigen Zhang
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
University of Chinese Academy of Sciences, Beijing, China
Fei Hu
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
University of Chinese Academy of Sciences, Beijing, China
Xiao Han
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
University of Chinese Academy of Sciences, Beijing, China
Ziming Li
Beijing Meteorological Observatory, Beijing, China
Lili Lei
School of Atmospheric Sciences, Nanjing University, Nanjing, China
Key Laboratory of Mesoscale Severe Weather, Ministry of Education, Nanjing University, Nanjing, China
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Z. Peng, M. Zhang, X. Kou, X. Tian, and X. Ma
Atmos. Chem. Phys., 15, 1087–1104, https://doi.org/10.5194/acp-15-1087-2015, https://doi.org/10.5194/acp-15-1087-2015, 2015
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We associated the smoothing operator with the atmospheric transport model to constitute the persistence dynamical model to forecast the surface CO2 flux scaling factors for the purpose of resolving the "signal-to-noise" problem, as well as transporting the useful observed information onto the next assimilation cycle. Based on this improvement, a regional surface CO2 flux inversion system, CFI-CMAQ, has been developed. The OSSEs showed that the performance of CFI-CMAQ is effective and promising.
X. Han, M. Zhang, J. Gao, S. Wang, and F. Chai
Atmos. Chem. Phys., 14, 10231–10248, https://doi.org/10.5194/acp-14-10231-2014, https://doi.org/10.5194/acp-14-10231-2014, 2014
L. Liu, F. Hu, and X.-L. Cheng
Nonlin. Processes Geophys., 21, 463–475, https://doi.org/10.5194/npg-21-463-2014, https://doi.org/10.5194/npg-21-463-2014, 2014
K. Wang, C. Liu, X. Zheng, M. Pihlatie, B. Li, S. Haapanala, T. Vesala, H. Liu, Y. Wang, G. Liu, and F. Hu
Biogeosciences, 10, 6865–6877, https://doi.org/10.5194/bg-10-6865-2013, https://doi.org/10.5194/bg-10-6865-2013, 2013
Related subject area
Subject: Climate and Earth System | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
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Short summary
A CMAQ EnSRF-based regional inversion system was extended to resolve satellite retrievals into biogenic source–sink changes. The size of the assimilated biosphere sink in China inferred from GOSAT was −0.47 Pg C yr−1. The biosphere flux at the provincial scale was re-estimated following the refined description in the regional inversion.
A CMAQ EnSRF-based regional inversion system was extended to resolve satellite retrievals into...
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