Articles | Volume 14, issue 23
https://doi.org/10.5194/acp-14-13281-2014
© Author(s) 2014. 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-14-13281-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
12 Dec 2014
Research article |
| 12 Dec 2014
A joint data assimilation system (Tan-Tracker) to simultaneously estimate surface CO2 fluxes and 3-D atmospheric CO2 concentrations from observations
X. Tian
CORRESPONDING AUTHOR
ICCES, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing, 210044, China
LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Z. Cai
LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
Y. Fu
Climate Change Research Center (CCRC), Chinese Academy of Sciences, Beijing, China
H. Zhang
Institute of Geographic Science and Natural Resources Research, Chinese Academy of Sciences, China
L. Feng
School of GeoSciences, University of Edinburgh, King's Buildings, Edinburgh EH9 3JN, UK
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42 citations as recorded by crossref.
- Evaluating the Role of the EOF Analysis in 4DEnVar Methods X. Kou et al. 10.3390/atmos8080146
- The TanSat mission: preliminary global observations Y. Liu et al. 10.1016/j.scib.2018.08.004
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- Linking gold prices, fossil fuel costs and energy consumption to assess progress towards sustainable development goals in newly industrialized countries M. Bashir et al. 10.1016/j.gsf.2023.101755
- Testing the impact of the gold price, oil price, and renewable energy on carbon emissions in South Africa: Novel evidence from bootstrap ARDL and NARDL approaches M. Ali et al. 10.1016/j.resourpol.2022.102984
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- A fundamental theorem of Earth’s surface modelling T. Yue et al. 10.1007/s12665-016-5310-5
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- Features of the annual evolution of CO 2 and CH 4 in the atmosphere of a Mediterranean climate site studied using a nonparametric and a harmonic function I. Pérez et al. 10.1016/j.apr.2016.06.006
- Simulation and analysis of XCO2 in North China based on high accuracy surface modeling Y. Liu et al. 10.1007/s11356-018-2683-x
- Spatio-Temporal Consistency Evaluation of XCO2 Retrievals from GOSAT and OCO-2 Based on TCCON and Model Data for Joint Utilization in Carbon Cycle Research Y. Kong et al. 10.3390/atmos10070354
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- Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation K. Hu et al. 10.3390/rs16183394
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- TanSat Mission Achievements: from Scientific Driving to Preliminary Observations Y. LIU et al. 10.11728/cjss2018.05.627
- Global Carbon Budget 2022 P. Friedlingstein et al. 10.5194/essd-14-4811-2022
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- A regional carbon data assimilation system and its preliminary evaluation in East Asia Z. Peng et al. 10.5194/acp-15-1087-2015
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Saved (final revised paper)
Latest update: 13 Dec 2024
Short summary
A new carbon cycle data assimilation system (Tan-Tracker) is developed based on an advanced hybrid assimilation approach, as a part of the preparation for the launch of the Chinese carbon dioxide observation satellite (TanSat). Tan-Tracker adopts a joint data assimilation framework to simultaneously estimate CO2 concentrations and CFs and thus gradually reduce the uncertainty in the CO2 concentration evolution through continuously fitting model CO2 concentration simulations to the observations.
A new carbon cycle data assimilation system (Tan-Tracker) is developed based on an advanced...
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