Articles | Volume 15, issue 19
https://doi.org/10.5194/acp-15-11133-2015
© 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-15-11133-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
07 Oct 2015
Research article |
| 07 Oct 2015
On the statistical optimality of CO2 atmospheric inversions assimilating CO2 column retrievals
F. Chevallier
CORRESPONDING AUTHOR
Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, L'Orme des Merisiers, Bat 701, 91191 Gif-sur-Yvette, France
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- A CO-based method to determine the regional biospheric signal in atmospheric CO<sub>2</sub> B. Oney et al. 10.1080/16000889.2017.1353388
35 citations as recorded by crossref.
- Global inverse modeling of CH<sub>4</sub> sources and sinks: an overview of methods S. Houweling et al. 10.5194/acp-17-235-2017
- 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
- Ensemble-based satellite-derived carbon dioxide and methane column-averaged dry-air mole fraction data sets (2003–2018) for carbon and climate applications M. Reuter et al. 10.5194/amt-13-789-2020
- Global Carbon Budget 2017 C. Le Quéré et al. 10.5194/essd-10-405-2018
- Can a regional-scale reduction of atmospheric CO<sub>2</sub> during the COVID-19 pandemic be detected from space? A case study for East China using satellite XCO<sub>2</sub> retrievals M. Buchwitz et al. 10.5194/amt-14-2141-2021
- Using airborne HIAPER Pole-to-Pole Observations (HIPPO) to evaluate model and remote sensing estimates of atmospheric carbon dioxide C. Frankenberg et al. 10.5194/acp-16-7867-2016
- Utilizing OCO-2 satellite transect in comparing XCO2 concentrations among administrative regions in Northeast Asia S. Park et al. 10.1007/s41324-017-0111-9
- Intercomparison of Remote Sensing Retrievals: An Examination of Prior-Induced Biases in Averaging Kernel Corrections H. Nguyen & J. Hobbs 10.3390/rs12193239
- Mission CO2ntrol: A Statistical Scientist's Role in Remote Sensing of Atmospheric Carbon Dioxide N. Cressie 10.1080/01621459.2017.1419136
- A biogenic CO<sub>2</sub> flux adjustment scheme for the mitigation of large-scale biases in global atmospheric CO<sub>2</sub> analyses and forecasts A. Agustí-Panareda et al. 10.5194/acp-16-10399-2016
- Improving Error Estimates for Evaluating Satellite-Based Atmospheric CO2 Measurement Concepts through Numerical Simulations B. Silveira et al. 10.3390/rs16132452
- Global environmental vulnerability and the survival period of all living beings on earth M. Hossain 10.1007/s13762-018-1722-y
- Toward High‐Resolution Global Atmospheric Inverse Modeling Using Graphics Accelerators F. Chevallier et al. 10.1029/2022GL102135
- Constraining a terrestrial biosphere model with remotely sensed atmospheric carbon dioxide T. Kaminski et al. 10.1016/j.rse.2017.08.017
- Age of air as a diagnostic for transport timescales in global models M. Krol et al. 10.5194/gmd-11-3109-2018
- Invisible transportation infrastructure technology to mitigate energy and environment M. Hossain 10.1186/s13705-017-0128-x
- The potential of satellite spectro-imagery for monitoring CO<sub>2</sub> emissions from large cities G. Broquet et al. 10.5194/amt-11-681-2018
- Objective evaluation of surface- and satellite-driven carbon dioxide atmospheric inversions F. Chevallier et al. 10.5194/acp-19-14233-2019
- XCO<sub>2</sub> retrieval for GOSAT and GOSAT-2 based on the FOCAL algorithm S. Noël et al. 10.5194/amt-14-3837-2021
- A Data-Driven Assessment of Biosphere-Atmosphere Interaction Impact on Seasonal Cycle Patterns of XCO2 Using GOSAT and MODIS Observations Z. He et al. 10.3390/rs9030251
- Reviews and syntheses: Flying the satellite into your model: on the role of observation operators in constraining models of the Earth system and the carbon cycle T. Kaminski & P. Mathieu 10.5194/bg-14-2343-2017
- Sensitivity of Optimal Estimation Satellite Retrievals to Misspecification of the Prior Mean and Covariance, with Application to OCO-2 Retrievals H. Nguyen et al. 10.3390/rs11232770
- Global Carbon Budget 2016 C. Le Quéré et al. 10.5194/essd-8-605-2016
- XCO<sub>2</sub> estimates from the OCO-2 measurements using a neural network approach L. David et al. 10.5194/amt-14-117-2021
- Global satellite observations of column-averaged carbon dioxide and methane: The GHG-CCI XCO2 and XCH4 CRDP3 data set M. Buchwitz et al. 10.1016/j.rse.2016.12.027
- Five decades of northern land carbon uptake revealed by the interhemispheric CO2 gradient P. Ciais et al. 10.1038/s41586-019-1078-6
- On the performance of satellite-based observations of <i>X</i>CO<sub>2</sub> in capturing the NOAA Carbon Tracker model and ground-based flask observations over Africa's land mass A. Mengistu & G. Mengistu Tsidu 10.5194/amt-13-4009-2020
- Spatial Retrievals of Atmospheric Carbon Dioxide from Satellite Observations J. Hobbs et al. 10.3390/rs13040571
- How Much CO2 Is Taken Up by the European Terrestrial Biosphere? M. Reuter et al. 10.1175/BAMS-D-15-00310.1
- Plant gross primary production, plant respiration and carbonyl sulfide emissions over the globe inferred by atmospheric inverse modelling M. Remaud et al. 10.5194/acp-22-2525-2022
- Global Carbon Budget 2015 C. Le Quéré et al. 10.5194/essd-7-349-2015
- Extreme Level of CO2 Accumulation into the Atmosphere Due to the Unequal Global Carbon Emission and Sequestration M. Hossain 10.1007/s11270-022-05581-1
- On the potential of a neural-network-based approach for estimating XCO2 from OCO-2 measurements F. Bréon et al. 10.5194/amt-15-5219-2022
- Global atmospheric CO<sub>2</sub> inverse models converging on neutral tropical land exchange, but disagreeing on fossil fuel and atmospheric growth rate B. Gaubert et al. 10.5194/bg-16-117-2019
- Comment F. Chevallier & F. Bréon 10.1080/01621459.2017.1419138
1 citations as recorded by crossref.
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Short summary
We demonstrate that the current two-step approach to infer the CO2 surface fluxes from satellite measured radiances, with CO2 retrievals as an intermediate product, is not optimal. This suboptimality corrupts the 4D information flow from the radiance measurements to the surface flux estimates. It is amplified by current retrieval strategies where prior errors are much larger than the performance of prior CO2 simulations used in atmospheric inversions.
We demonstrate that the current two-step approach to infer the CO2 surface fluxes from satellite...
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