Articles | Volume 6, issue 3
https://doi.org/10.5194/gmd-6-783-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-6-783-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
07 Jun 2013
Development and technical paper |
| 07 Jun 2013
On the parallelization of atmospheric inversions of CO2 surface fluxes within a variational framework
F. Chevallier
Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, L'Orme des Merisiers, UMR8212, Bat 701, 91191 Gif-sur-Yvette, France
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29 citations as recorded by crossref.
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- Global Carbon Budget 2021 P. Friedlingstein et al. 10.5194/essd-14-1917-2022
- Towards Robust Calculation of Interannual CO2 Growth Signal from TCCON (Total Carbon Column Observing Network) L. Labzovskii et al. 10.3390/rs13193868
- The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies A. Berchet et al. 10.5194/gmd-14-5331-2021
- SeaFlux: harmonization of air–sea CO2 fluxes from surface pCO2 data products using a standardized approach A. Fay et al. 10.5194/essd-13-4693-2021
- Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates S. Noël et al. 10.5194/amt-17-2317-2024
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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
- Are Terrestrial Biosphere Models Fit for Simulating the Global Land Carbon Sink? C. Seiler et al. 10.1029/2021MS002946
- Strong Southern Ocean carbon uptake evident in airborne observations M. Long et al. 10.1126/science.abi4355
- Towards monitoring the CO2 source–sink distribution over India via inverse modelling: quantifying the fine-scale spatiotemporal variability in the atmospheric CO2 mole fraction V. Thilakan et al. 10.5194/acp-22-15287-2022
- Improved atmospheric constraints on Southern Ocean CO 2 exchange Y. Jin et al. 10.1073/pnas.2309333121
- Sea-surface pCO2 maps for the Bay of Bengal based on advanced machine learning algorithms A. Joshi et al. 10.1038/s41597-024-03236-w
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- DADA: data assimilation for the detection and attribution of weather and climate-related events A. Hannart et al. 10.1007/s10584-016-1595-3
28 citations as recorded by crossref.
- Evaluation and Analysis of the Seasonal Cycle and Variability of the Trend from GOSAT Methane Retrievals E. Kivimäki et al. 10.3390/rs11070882
- Global Carbon Budget 2020 P. Friedlingstein et al. 10.5194/essd-12-3269-2020
- Variational inverse modeling within the Community Inversion Framework v1.1 to assimilate δ13C(CH4) and CH4: a case study with model LMDz-SACS J. Thanwerdas et al. 10.5194/gmd-15-4831-2022
- Toward High‐Resolution Global Atmospheric Inverse Modeling Using Graphics Accelerators F. Chevallier et al. 10.1029/2022GL102135
- Sensitivity of the recent methane budget to LMDz sub-grid-scale physical parameterizations R. Locatelli et al. 10.5194/acp-15-9765-2015
- Benchmarking carbon fluxes of the ISIMIP2a biome models J. Chang et al. 10.1088/1748-9326/aa63fa
- Multi-year observations reveal a larger than expected autumn respiration signal across northeast Eurasia B. Byrne et al. 10.5194/bg-19-4779-2022
- Contrasting Regional Carbon Cycle Responses to Seasonal Climate Anomalies Across the East‐West Divide of Temperate North America B. Byrne et al. 10.1029/2020GB006598
- Climate-driven variability of the Southern Ocean CO 2 sink N. Mayot et al. 10.1098/rsta.2022.0055
- Retrieving the atmospheric concentrations of carbon dioxide and methane from the European Copernicus CO2M satellite mission using artificial neural networks M. Reuter et al. 10.5194/amt-18-241-2025
- Global Carbon Budget 2021 P. Friedlingstein et al. 10.5194/essd-14-1917-2022
- Towards Robust Calculation of Interannual CO2 Growth Signal from TCCON (Total Carbon Column Observing Network) L. Labzovskii et al. 10.3390/rs13193868
- The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies A. Berchet et al. 10.5194/gmd-14-5331-2021
- SeaFlux: harmonization of air–sea CO2 fluxes from surface pCO2 data products using a standardized approach A. Fay et al. 10.5194/essd-13-4693-2021
- Greenhouse gas retrievals for the CO2M mission using the FOCAL method: first performance estimates S. Noël et al. 10.5194/amt-17-2317-2024
- Inverse modeling of GOSAT-retrieved ratios of total column CH4 and CO2 for 2009 and 2010 S. Pandey et al. 10.5194/acp-16-5043-2016
- Investigation of the renewed methane growth post-2007 with high-resolution 3-D variational inverse modeling and isotopic constraints J. Thanwerdas et al. 10.5194/acp-24-2129-2024
- Carbon Cycle Response to Temperature Overshoot Beyond 2°C: An Analysis of CMIP6 Models I. Melnikova et al. 10.1029/2020EF001967
- Contrasting terrestrial carbon cycle responses to the 1997/98 and 2015/16 extreme El Niño events J. Wang et al. 10.5194/esd-9-1-2018
- Order of magnitude wall time improvement of variational methane inversions by physical parallelization: a demonstration using TM5-4DVAR S. Pandey et al. 10.5194/gmd-15-4555-2022
- CMEMS-LSCE: a global, 0.25°, monthly reconstruction of the surface ocean carbonate system T. Chau et al. 10.5194/essd-16-121-2024
- 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
- Are Terrestrial Biosphere Models Fit for Simulating the Global Land Carbon Sink? C. Seiler et al. 10.1029/2021MS002946
- Strong Southern Ocean carbon uptake evident in airborne observations M. Long et al. 10.1126/science.abi4355
- Towards monitoring the CO2 source–sink distribution over India via inverse modelling: quantifying the fine-scale spatiotemporal variability in the atmospheric CO2 mole fraction V. Thilakan et al. 10.5194/acp-22-15287-2022
- Improved atmospheric constraints on Southern Ocean CO 2 exchange Y. Jin et al. 10.1073/pnas.2309333121
- Sea-surface pCO2 maps for the Bay of Bengal based on advanced machine learning algorithms A. Joshi et al. 10.1038/s41597-024-03236-w
- Representation of the terrestrial carbon cycle in CMIP6 B. Gier et al. 10.5194/bg-21-5321-2024
1 citations as recorded by crossref.
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