Articles | Volume 15, issue 2
https://doi.org/10.5194/acp-15-1087-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-15-1087-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
30 Jan 2015
Research article |
| 30 Jan 2015
A regional carbon data assimilation system and its preliminary evaluation in East Asia
Z. Peng
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Nanjing University, Nanjing 210093, China
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
X. Kou
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
Graduate School of Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
X. Tian
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
X. Ma
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
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Cited
22 citations as recorded by crossref.
- Dynamics-based estimates of decline trend with fine temporal variations in China's PM2.5 emissions Z. Peng et al. 10.5194/acp-23-14505-2023
- Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation K. Hu et al. 10.3390/rs16183394
- Improving PM<sub>2. 5</sub> forecast over China by the joint adjustment of initial conditions and source emissions with an ensemble Kalman filter Z. Peng et al. 10.5194/acp-17-4837-2017
- Atmospheric CO2 column concentration over Iran: Emissions, GOSAT satellite observations, and WRF-GHG model simulations S. Karbasi et al. 10.1016/j.atmosres.2024.107818
- Revealing the sulfur dioxide emission reductions in China by assimilating surface observations in WRF-Chem T. Dai et al. 10.5194/acp-21-4357-2021
- A regional data assimilation system for estimating CO surface flux from atmospheric mixing ratio observations—a case study of Xuzhou, China L. Lu et al. 10.1007/s11356-019-04246-7
- Aerosol data assimilation using data from Fengyun-4A, a next-generation geostationary meteorological satellite X. Xia et al. 10.1016/j.atmosenv.2020.117695
- A fundamental theorem of Earth’s surface modelling T. Yue et al. 10.1007/s12665-016-5310-5
- Spatiotemporal analysis of global atmospheric XCO2 concentrations before and after COVID-19 using HASM data fusion method Y. Liu et al. 10.3389/fenvs.2022.1079480
- 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) X. Kou et al. 10.5194/acp-23-6719-2023
- China's methane emissions derived from the inversion of GOSAT observations with a CMAQ and EnKS-based regional data assimilation system X. Kou et al. 10.1016/j.apr.2024.102333
- Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System S. Voshtani et al. 10.3390/rs14020371
- Assimilation of OCO-2 retrievals with WRF-Chem/DART: A case study for the Midwestern United States Q. Zhang et al. 10.1016/j.atmosenv.2020.118106
- Characteristics of the Spatio-Temporal Dynamics of Aerosols in Central Asia and Their Influencing Factors Y. Zhou et al. 10.3390/rs14112684
- CO2 Flux Inversion With a Regional Joint Data Assimilation System Based on CMAQ, EnKS, and Surface Observations Z. Peng et al. 10.1029/2022JD037154
- CMAQ simulation of atmospheric CO2 concentration in East Asia: Comparison with GOSAT observations and ground measurements R. Li et al. 10.1016/j.atmosenv.2017.03.056
- Simulation and analysis of XCO2 in North China based on high accuracy surface modeling Y. Liu et al. 10.1007/s11356-018-2683-x
- The impact of multi-species surface chemical observation assimilation on air quality forecasts in China Z. Peng et al. 10.5194/acp-18-17387-2018
- CO2 Flux over the Contiguous United States in 2016 Inverted by WRF-Chem/DART from OCO-2 XCO2 Retrievals Q. Zhang et al. 10.3390/rs13152996
- Regional CO2 Inversion Through Ensemble‐Based Simultaneous State and Parameter Estimation: TRACE Framework and Controlled Experiments H. Chen et al. 10.1029/2022MS003208
- Accounting for CO2 variability over East Asia with a regional joint inversion system and its preliminary evaluation X. Kou et al. 10.1007/s13351-017-6149-8
- Large-scale transport of PM2.5 in the lower troposphere during winter cold surges in China J. Wang et al. 10.1038/s41598-017-13217-2
22 citations as recorded by crossref.
- Dynamics-based estimates of decline trend with fine temporal variations in China's PM2.5 emissions Z. Peng et al. 10.5194/acp-23-14505-2023
- Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation K. Hu et al. 10.3390/rs16183394
- Improving PM<sub>2. 5</sub> forecast over China by the joint adjustment of initial conditions and source emissions with an ensemble Kalman filter Z. Peng et al. 10.5194/acp-17-4837-2017
- Atmospheric CO2 column concentration over Iran: Emissions, GOSAT satellite observations, and WRF-GHG model simulations S. Karbasi et al. 10.1016/j.atmosres.2024.107818
- Revealing the sulfur dioxide emission reductions in China by assimilating surface observations in WRF-Chem T. Dai et al. 10.5194/acp-21-4357-2021
- A regional data assimilation system for estimating CO surface flux from atmospheric mixing ratio observations—a case study of Xuzhou, China L. Lu et al. 10.1007/s11356-019-04246-7
- Aerosol data assimilation using data from Fengyun-4A, a next-generation geostationary meteorological satellite X. Xia et al. 10.1016/j.atmosenv.2020.117695
- A fundamental theorem of Earth’s surface modelling T. Yue et al. 10.1007/s12665-016-5310-5
- Spatiotemporal analysis of global atmospheric XCO2 concentrations before and after COVID-19 using HASM data fusion method Y. Liu et al. 10.3389/fenvs.2022.1079480
- 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) X. Kou et al. 10.5194/acp-23-6719-2023
- China's methane emissions derived from the inversion of GOSAT observations with a CMAQ and EnKS-based regional data assimilation system X. Kou et al. 10.1016/j.apr.2024.102333
- Assimilation of GOSAT Methane in the Hemispheric CMAQ; Part I: Design of the Assimilation System S. Voshtani et al. 10.3390/rs14020371
- Assimilation of OCO-2 retrievals with WRF-Chem/DART: A case study for the Midwestern United States Q. Zhang et al. 10.1016/j.atmosenv.2020.118106
- Characteristics of the Spatio-Temporal Dynamics of Aerosols in Central Asia and Their Influencing Factors Y. Zhou et al. 10.3390/rs14112684
- CO2 Flux Inversion With a Regional Joint Data Assimilation System Based on CMAQ, EnKS, and Surface Observations Z. Peng et al. 10.1029/2022JD037154
- CMAQ simulation of atmospheric CO2 concentration in East Asia: Comparison with GOSAT observations and ground measurements R. Li et al. 10.1016/j.atmosenv.2017.03.056
- Simulation and analysis of XCO2 in North China based on high accuracy surface modeling Y. Liu et al. 10.1007/s11356-018-2683-x
- The impact of multi-species surface chemical observation assimilation on air quality forecasts in China Z. Peng et al. 10.5194/acp-18-17387-2018
- CO2 Flux over the Contiguous United States in 2016 Inverted by WRF-Chem/DART from OCO-2 XCO2 Retrievals Q. Zhang et al. 10.3390/rs13152996
- Regional CO2 Inversion Through Ensemble‐Based Simultaneous State and Parameter Estimation: TRACE Framework and Controlled Experiments H. Chen et al. 10.1029/2022MS003208
- Accounting for CO2 variability over East Asia with a regional joint inversion system and its preliminary evaluation X. Kou et al. 10.1007/s13351-017-6149-8
- Large-scale transport of PM2.5 in the lower troposphere during winter cold surges in China J. Wang et al. 10.1038/s41598-017-13217-2
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Latest update: 13 Dec 2024
Short summary
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.
We associated the smoothing operator with the atmospheric transport model to constitute the...
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