Articles | Volume 15, issue 17
https://doi.org/10.5194/acp-15-9747-2015
© 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-15-9747-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
01 Sep 2015
Research article |
| 01 Sep 2015
Comparing the CarbonTracker and TM5-4DVar data assimilation systems for CO2 surface flux inversions
A. Babenhauserheide
CORRESPONDING AUTHOR
IMK-ASF, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
Earth System Research Laboratory, Global Monitoring Division, National Oceanic and Atmospheric Administration, Boulder, Colorado, USA
S. Houweling
Netherlands Institute of Space Research (SRON), Utrecht, the Netherlands
W. Peters
Department of Meteorology and Air Quality, Environmental Sciences Group Wageningen University, Wageningen, the Netherlands
University of Groningen, Centre for Isotope Research, Groningen, the Netherlands
IMK-ASF, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany
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Cited
19 citations as recorded by crossref.
- The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies A. Berchet et al. https://doi.org/10.5194/gmd-14-5331-2021
- A CO-based method to determine the regional biospheric signal in atmospheric CO<sub>2</sub> B. Oney et al. https://doi.org/10.1080/16000889.2017.1353388
- Effect of Data Assimilation Parameters on The Optimized Surface CO2 Flux in Asia H. Kim et al. https://doi.org/10.1007/s13143-017-0049-9
- Why do inverse models disagree? A case study with two European CO2 inversions S. Munassar et al. https://doi.org/10.5194/acp-23-2813-2023
- Spatiotemporal Drivers of Urban Vegetation Carbon Sequestration in the Yangtze River Delta Urban Agglomeration: A Remote Sensing-Based GWR-RF-SEM Framework Analysis W. Ma et al. https://doi.org/10.3390/rs17122110
- A comprehensive evaluation of the spatiotemporal variation of CO2 and its driving forces over China X. Jin et al. https://doi.org/10.3389/fenvs.2023.1129639
- Global-Scale Evaluation of XCO2 Products from GOSAT, OCO-2 and CarbonTracker Using Direct Comparison and Triple Collocation Method Y. Chen et al. https://doi.org/10.3390/rs14225635
- Diurnal and seasonal dynamics of regional CO2 drawdown at Harvard Forest: Integrating remote sensing and modeling perspectives Y. Li et al. https://doi.org/10.1016/j.scitotenv.2025.179580
- Using an Inverse Model to Reconcile Differences in Simulated and Observed Global Ethane Concentrations and Trends Between 2008 and 2014 S. Monks et al. https://doi.org/10.1029/2017JD028112
- Contribution of China’s carbon budget on global radiative forcing N. Li et al. https://doi.org/10.1007/s11442-025-2320-9
- A Surface Ocean CO2 Reference Network, SOCONET and Associated Marine Boundary Layer CO2 Measurements R. Wanninkhof et al. https://doi.org/10.3389/fmars.2019.00400
- Atmospheric carbon dioxide measurement from aircraft and comparison with OCO-2 and CarbonTracker model data Q. Wang et al. https://doi.org/10.5194/amt-14-6601-2021
- Global Atmospheric CO2 Simulations with the IAP-AACM Model Using an Improved Vertical Diffusion Scheme and Evaluation with Multi-Source Data Z. Zou et al. https://doi.org/10.3390/atmos17080787
- The CarbonTracker Data Assimilation Shell (CTDAS) v1.0: implementation and global carbon balance 2001–2015 I. van der Laan-Luijkx et al. https://doi.org/10.5194/gmd-10-2785-2017
- Multi-Year Comparison of CO2 Concentration from NOAA Carbon Tracker Reanalysis Model with Data from GOSAT and OCO-2 over Asia F. Mustafa et al. https://doi.org/10.3390/rs12152498
- The Potential of the Geostationary Carbon Cycle Observatory (GeoCarb) to Provide Multi-scale Constraints on the Carbon Cycle in the Americas B. Moore III et al. https://doi.org/10.3389/fenvs.2018.00109
- Accounting for model error in air quality forecasts: an application of 4DEnVar to the assimilation of atmospheric composition using QG-Chem 1.0 E. Emili et al. https://doi.org/10.5194/gmd-9-3933-2016
- Net CO2 fossil fuel emissions of Tokyo estimated directly from measurements of the Tsukuba TCCON site and radiosondes A. Babenhauserheide et al. https://doi.org/10.5194/amt-13-2697-2020
- Comparison between the Local Ensemble Transform Kalman Filter (LETKF) and 4D‐Var in atmospheric CO2 flux inversion with the Goddard Earth Observing System‐Chem model and the observation impact diagnostics from the LETKF J. Liu et al. https://doi.org/10.1002/2016JD025100
19 citations as recorded by crossref.
- The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies A. Berchet et al. https://doi.org/10.5194/gmd-14-5331-2021
- A CO-based method to determine the regional biospheric signal in atmospheric CO<sub>2</sub> B. Oney et al. https://doi.org/10.1080/16000889.2017.1353388
- Effect of Data Assimilation Parameters on The Optimized Surface CO2 Flux in Asia H. Kim et al. https://doi.org/10.1007/s13143-017-0049-9
- Why do inverse models disagree? A case study with two European CO2 inversions S. Munassar et al. https://doi.org/10.5194/acp-23-2813-2023
- Spatiotemporal Drivers of Urban Vegetation Carbon Sequestration in the Yangtze River Delta Urban Agglomeration: A Remote Sensing-Based GWR-RF-SEM Framework Analysis W. Ma et al. https://doi.org/10.3390/rs17122110
- A comprehensive evaluation of the spatiotemporal variation of CO2 and its driving forces over China X. Jin et al. https://doi.org/10.3389/fenvs.2023.1129639
- Global-Scale Evaluation of XCO2 Products from GOSAT, OCO-2 and CarbonTracker Using Direct Comparison and Triple Collocation Method Y. Chen et al. https://doi.org/10.3390/rs14225635
- Diurnal and seasonal dynamics of regional CO2 drawdown at Harvard Forest: Integrating remote sensing and modeling perspectives Y. Li et al. https://doi.org/10.1016/j.scitotenv.2025.179580
- Using an Inverse Model to Reconcile Differences in Simulated and Observed Global Ethane Concentrations and Trends Between 2008 and 2014 S. Monks et al. https://doi.org/10.1029/2017JD028112
- Contribution of China’s carbon budget on global radiative forcing N. Li et al. https://doi.org/10.1007/s11442-025-2320-9
- A Surface Ocean CO2 Reference Network, SOCONET and Associated Marine Boundary Layer CO2 Measurements R. Wanninkhof et al. https://doi.org/10.3389/fmars.2019.00400
- Atmospheric carbon dioxide measurement from aircraft and comparison with OCO-2 and CarbonTracker model data Q. Wang et al. https://doi.org/10.5194/amt-14-6601-2021
- Global Atmospheric CO2 Simulations with the IAP-AACM Model Using an Improved Vertical Diffusion Scheme and Evaluation with Multi-Source Data Z. Zou et al. https://doi.org/10.3390/atmos17080787
- The CarbonTracker Data Assimilation Shell (CTDAS) v1.0: implementation and global carbon balance 2001–2015 I. van der Laan-Luijkx et al. https://doi.org/10.5194/gmd-10-2785-2017
- Multi-Year Comparison of CO2 Concentration from NOAA Carbon Tracker Reanalysis Model with Data from GOSAT and OCO-2 over Asia F. Mustafa et al. https://doi.org/10.3390/rs12152498
- The Potential of the Geostationary Carbon Cycle Observatory (GeoCarb) to Provide Multi-scale Constraints on the Carbon Cycle in the Americas B. Moore III et al. https://doi.org/10.3389/fenvs.2018.00109
- Accounting for model error in air quality forecasts: an application of 4DEnVar to the assimilation of atmospheric composition using QG-Chem 1.0 E. Emili et al. https://doi.org/10.5194/gmd-9-3933-2016
- Net CO2 fossil fuel emissions of Tokyo estimated directly from measurements of the Tsukuba TCCON site and radiosondes A. Babenhauserheide et al. https://doi.org/10.5194/amt-13-2697-2020
- Comparison between the Local Ensemble Transform Kalman Filter (LETKF) and 4D‐Var in atmospheric CO2 flux inversion with the Goddard Earth Observing System‐Chem model and the observation impact diagnostics from the LETKF J. Liu et al. https://doi.org/10.1002/2016JD025100
Saved (final revised paper)
Latest update: 11 Oct 2026
Short summary
We compare two different data assimilation systems for estimating sources and sinks of CO_2 from concentration measurements. The systems are CarbonTracker and TM5-4DVar, which have both been used in a number of scientific studies. We analyze the differences between both models as well as the sensitivity of the estimated sources and sinks to the observation coverage. The results provide a lower limit for the uncertainty of surface carbon fluxes with the current measurement network.
We compare two different data assimilation systems for estimating sources and sinks of CO_2 from...
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