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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41 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
- Assimilation of Remotely-Sensed Leaf Area Index into a Dynamic Vegetation Model for Gross Primary Productivity Estimation R. Ma et al. 10.3390/rs9030188
- 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
- Potential Impacts of Assimilating Every-10-Minute Himawari-8 Satellite Radiance with the POD-4DEnVar Method J. Wang et al. 10.3390/rs13183765
- An Efficient Algorithm for Retrieving CO2 in the Atmosphere From Hyperspectral Measurements of Satellites: Application of NLS-4DVar Data Assimilation Method Z. Jin et al. 10.3389/feart.2021.688542
- A fundamental theorem of Earth’s surface modelling T. Yue et al. 10.1007/s12665-016-5310-5
- FY-3A Microwave Data Assimilation Based on the POD-4DEnVar Method M. Zhang et al. 10.3390/atmos9050189
- Simultaneous estimation of surface soil moisture and soil properties with a dual ensemble Kalman smoother N. Chu et al. 10.1007/s11430-015-5175-6
- Application of a Physical Ensemble Method in the POD-4DEnVar Y. Yang et al. 10.1175/WAF-D-17-0169.1
- 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
- A non-linear least squares enhanced POD-4DVar algorithm for data assimilation X. Tian & X. Feng 10.3402/tellusa.v67.25340
- 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
- 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
- Improvement of PM2.5 forecast over China by the joint adjustment of initial conditions and emissions with the NLS-4DVar method S. Zhang et al. 10.1016/j.atmosenv.2021.118896
- Regional CO2 Inversion Through Ensemble‐Based Simultaneous State and Parameter Estimation: TRACE Framework and Controlled Experiments H. Chen et al. 10.1029/2022MS003208
- Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation K. Hu et al. 10.3390/rs16183394
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- 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
- 基于中国大气反演系统的卫星<bold>CO</bold><sub><bold>2</bold></sub>数据同化对全球碳收支的评估 哲. 金 et al. 10.1360/N072022-0123
- 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: 21 Nov 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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