Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3383-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-3383-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
07 Jun 2021
Model description paper |
| 07 Jun 2021
| 07 Jun 2021
Regional CO2 inversions with LUMIA, the Lund University Modular Inversion Algorithm, v1.0
Guillaume Monteil
CORRESPONDING AUTHOR
Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
Marko Scholze
Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
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Cited
16 citations as recorded by crossref.
- CO2 Flux Inversion With a Regional Joint Data Assimilation System Based on CMAQ, EnKS, and Surface Observations Z. Peng et al. 10.1029/2022JD037154
- A comprehensive evaluation of the use of Lagrangian particle dispersion models for inverse modeling of greenhouse gas emissions M. Vojta et al. 10.5194/gmd-15-8295-2022
- Why do inverse models disagree? A case study with two European CO2 inversions S. Munassar et al. 10.5194/acp-23-2813-2023
- 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
- Modeling support for an extensive Δ14CO2 flask sample monitoring campaign over Europe to constrain fossil CO2 emissions C. Gómez-Ortiz et al. 10.5194/acp-25-10747-2025
- Lagrangian inversion of anthropogenic CO2 emissions from Beijing using differential column measurements K. Che et al. 10.1088/1748-9326/ac7477
- Towards improving top–down national CO2 estimation in Europe: potential from expanding the ICOS atmospheric network in Italy Y. Villalobos et al. 10.1088/1748-9326/adc41e
- A CO2–Δ14CO2 inversion setup for estimating European fossil CO2 emissions C. Gómez-Ortiz et al. 10.5194/acp-25-397-2025
- Regional CO2 Inversion Through Ensemble‐Based Simultaneous State and Parameter Estimation: TRACE Framework and Controlled Experiments H. Chen et al. 10.1029/2022MS003208
- To what extent does the CO2 diurnal cycle impact flux estimates derived from global and regional inversions? S. Munassar et al. 10.5194/acp-25-639-2025
- The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies A. Berchet et al. 10.5194/gmd-14-5331-2021
- Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation K. Hu et al. 10.3390/rs16183394
- Assimilating multi-site eddy-covariance data to calibrate the wetland CH4 emission module in a terrestrial ecosystem model J. Kallingal et al. 10.5194/bg-22-4061-2025
- Reconciling the Carbon Balance of Northern Sweden Through Integration of Observations and Modelling A. Sathyanadh et al. 10.1029/2021JD035185
- The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990–2020 M. McGrath et al. 10.5194/essd-15-4295-2023
- Do State‐Of‐The‐Art Atmospheric CO2 Inverse Models Capture Drought Impacts on the European Land Carbon Uptake? W. He et al. 10.1029/2022MS003150
15 citations as recorded by crossref.
- CO2 Flux Inversion With a Regional Joint Data Assimilation System Based on CMAQ, EnKS, and Surface Observations Z. Peng et al. 10.1029/2022JD037154
- A comprehensive evaluation of the use of Lagrangian particle dispersion models for inverse modeling of greenhouse gas emissions M. Vojta et al. 10.5194/gmd-15-8295-2022
- Why do inverse models disagree? A case study with two European CO2 inversions S. Munassar et al. 10.5194/acp-23-2813-2023
- 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
- Modeling support for an extensive Δ14CO2 flask sample monitoring campaign over Europe to constrain fossil CO2 emissions C. Gómez-Ortiz et al. 10.5194/acp-25-10747-2025
- Lagrangian inversion of anthropogenic CO2 emissions from Beijing using differential column measurements K. Che et al. 10.1088/1748-9326/ac7477
- Towards improving top–down national CO2 estimation in Europe: potential from expanding the ICOS atmospheric network in Italy Y. Villalobos et al. 10.1088/1748-9326/adc41e
- A CO2–Δ14CO2 inversion setup for estimating European fossil CO2 emissions C. Gómez-Ortiz et al. 10.5194/acp-25-397-2025
- Regional CO2 Inversion Through Ensemble‐Based Simultaneous State and Parameter Estimation: TRACE Framework and Controlled Experiments H. Chen et al. 10.1029/2022MS003208
- To what extent does the CO2 diurnal cycle impact flux estimates derived from global and regional inversions? S. Munassar et al. 10.5194/acp-25-639-2025
- The Community Inversion Framework v1.0: a unified system for atmospheric inversion studies A. Berchet et al. 10.5194/gmd-14-5331-2021
- Review of Satellite Remote Sensing of Carbon Dioxide Inversion and Assimilation K. Hu et al. 10.3390/rs16183394
- Assimilating multi-site eddy-covariance data to calibrate the wetland CH4 emission module in a terrestrial ecosystem model J. Kallingal et al. 10.5194/bg-22-4061-2025
- Reconciling the Carbon Balance of Northern Sweden Through Integration of Observations and Modelling A. Sathyanadh et al. 10.1029/2021JD035185
- The consolidated European synthesis of CO2 emissions and removals for the European Union and United Kingdom: 1990–2020 M. McGrath et al. 10.5194/essd-15-4295-2023
1 citations as recorded by crossref.
Latest update: 16 Oct 2025
Short summary
LUMIA is a Python library for atmospheric inversions, originally developed at Lund University to perform regional atmospheric CO2 inversions. The inversions rely on coupling the regional transport model FLEXPART and the global transport model TM5. The paper presents the modeling setup and some first results, and it introduces the LUMIA Python package as a toolbox for inversions beyond the use case presented in the paper.
LUMIA is a Python library for atmospheric inversions, originally developed at Lund University to...
