Articles | Volume 14, issue 12
https://doi.org/10.5194/gmd-14-7775-2021
© 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-14-7775-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model experiment description paper
| 
23 Dec 2021
Model experiment description paper |
| 23 Dec 2021
| 23 Dec 2021
How well can inverse analyses of high-resolution satellite data resolve heterogeneous methane fluxes? Observing system simulation experiments with the GEOS-Chem adjoint model (v35)
Xueying Yu
Department of Soil, Water, and Climate, University of Minnesota, Saint
Paul, Minnesota 55108, United States
Department of Soil, Water, and Climate, University of Minnesota, Saint
Paul, Minnesota 55108, United States
Daven K. Henze
Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, United States
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Cited
20 citations as recorded by crossref.
- Human activities now fuel two-thirds of global methane emissions R. Jackson et al.
- A data driven assessment to link tropospheric methane concentration and surface biophysical factors using remotely sensed data S. Manna et al.
- A high-resolution satellite-based map of global methane emissions reveals missing wetland, fossil fuel, and monsoon sources X. Yu et al.
- A Gridded Inventory of Annual 2012–2018 U.S. Anthropogenic Methane Emissions J. Maasakkers et al.
- Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane D. Jacob et al.
- Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations D. Varon et al.
- Use of Assimilation Analysis in 4D-Var Source Inversion: Observing System Simulation Experiments (OSSEs) with GOSAT Methane and Hemispheric CMAQ S. Voshtani et al.
- Trends and seasonality of 2019–2023 global methane emissions inferred from a localized ensemble transform Kalman filter (CHEEREIO v1.3.1) applied to TROPOMI satellite observations D. Pendergrass et al.
- Quantification of methane emissions from hotspots and during COVID-19 using a global atmospheric inversion J. McNorton et al.
- Comparative Review of Global Methane Budget Estimation: Top-Down, Bottom-Up, and Integrated Approaches B. Alem et al.
- Satellite-Based Methane Emission Monitoring: A Review Across Industries S. Mehrdad & K. Du
- Continuous weekly monitoring of methane emissions from the Permian Basin by inversion of TROPOMI satellite observations D. Varon et al.
- 2019–2024 trends in African livestock and wetland emissions as contributors to the global methane rise N. Balasus et al.
- Spatiotemporal variations in atmospheric CH4 concentrations and enhancements in northern China based on a comprehensive dataset: ground-based observations, TROPOMI data, inventory data, and inversions P. Han et al.
- Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations L. Estrada et al.
- Using new geospatial data and 2020 fossil fuel methane emissions for the Global Fuel Exploitation Inventory (GFEI) v3 T. Scarpelli et al.
- Challenges Regionalizing Methane Emissions Using Aquatic Environments in the Amazon Basin as Examples J. Melack et al.
- Numerical analysis of CH4 concentration distributions over East Asia with a regional chemical transport model L. Qin et al.
- Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al.
- Worldwide inference of national methane emissions by inversion of satellite observations with UNFCCC prior estimates J. East et al.
20 citations as recorded by crossref.
- Human activities now fuel two-thirds of global methane emissions R. Jackson et al.
- A data driven assessment to link tropospheric methane concentration and surface biophysical factors using remotely sensed data S. Manna et al.
- A high-resolution satellite-based map of global methane emissions reveals missing wetland, fossil fuel, and monsoon sources X. Yu et al.
- A Gridded Inventory of Annual 2012–2018 U.S. Anthropogenic Methane Emissions J. Maasakkers et al.
- Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane D. Jacob et al.
- Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations D. Varon et al.
- Use of Assimilation Analysis in 4D-Var Source Inversion: Observing System Simulation Experiments (OSSEs) with GOSAT Methane and Hemispheric CMAQ S. Voshtani et al.
- Trends and seasonality of 2019–2023 global methane emissions inferred from a localized ensemble transform Kalman filter (CHEEREIO v1.3.1) applied to TROPOMI satellite observations D. Pendergrass et al.
- Quantification of methane emissions from hotspots and during COVID-19 using a global atmospheric inversion J. McNorton et al.
- Comparative Review of Global Methane Budget Estimation: Top-Down, Bottom-Up, and Integrated Approaches B. Alem et al.
- Satellite-Based Methane Emission Monitoring: A Review Across Industries S. Mehrdad & K. Du
- Continuous weekly monitoring of methane emissions from the Permian Basin by inversion of TROPOMI satellite observations D. Varon et al.
- 2019–2024 trends in African livestock and wetland emissions as contributors to the global methane rise N. Balasus et al.
- Spatiotemporal variations in atmospheric CH4 concentrations and enhancements in northern China based on a comprehensive dataset: ground-based observations, TROPOMI data, inventory data, and inversions P. Han et al.
- Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations L. Estrada et al.
- Using new geospatial data and 2020 fossil fuel methane emissions for the Global Fuel Exploitation Inventory (GFEI) v3 T. Scarpelli et al.
- Challenges Regionalizing Methane Emissions Using Aquatic Environments in the Amazon Basin as Examples J. Melack et al.
- Numerical analysis of CH4 concentration distributions over East Asia with a regional chemical transport model L. Qin et al.
- Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al.
- Worldwide inference of national methane emissions by inversion of satellite observations with UNFCCC prior estimates J. East et al.
Saved (final revised paper)
Latest update: 18 May 2026
Short summary
We conduct observing system simulation experiments to test how well inverse analyses of high-resolution satellite data from sensors such as TROPOMI can quantify methane emissions. Inversions can improve monthly flux estimates at 25 km even with a spatially biased prior or model transport errors, but results are strongly degraded when both are present. We further evaluate a set of alternate formalisms to overcome limitations of the widely used scale factor approach that arise for missing sources.
We conduct observing system simulation experiments to test how well inverse analyses of...
