Strong monsoon influence on South Asian methane emissions in 2020 revealed by a Bayesian inversion constrained by satellite observations

Subramanian, Rakesh; Thompson, Rona L.; Vojta, Martin; Schneising, Oliver; Stohl, Andreas

doi:10.5194/acp-26-9757-2026

Articles | Volume 26, issue 13

https://doi.org/10.5194/acp-26-9757-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Greenhouse gas monitoring in the Asia–Pacific region...

https://doi.org/10.5194/acp-26-9757-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 26, issue 13

Research article

|

13 Jul 2026

Research article |

| 13 Jul 2026

Strong monsoon influence on South Asian methane emissions in 2020 revealed by a Bayesian inversion constrained by satellite observations

Rakesh Subramanian, Rona L. Thompson, Martin Vojta, Oliver Schneising, and Andreas Stohl

Supplement

https://doi.org/10.5194/acp-26-9757-2026-supplement

Data sets

CAMS global greenhouse gas reanalysis (EGG4) Copernicus Atmosphere Monitoring Service https://doi.org/10.24381/cda4ed31

ERA5-Land hourly data from 1950 to present Joaquín Muñoz Sabater https://doi.org/10.24381/cds.e2161bac

Model code and software

Flexpart-Flexinvert Framework. In Strong monsoon influence on South Asian methane emissions in 2020 revealed by a Bayesian inversion constrained by satellite observations Rakesh Subramanian et al. https://doi.org/10.5281/zenodo.20925612

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Short summary

We used satellite observations and atmospheric models to understand methane emissions over South Asia, a region with large uncertainties. The study finds that the total emissions are moderately higher than previously thought, with important spatial and seasonal differences, especially in areas affected by monsoon rainfall and seasonal flooding. The results highlight the influence of rainfall, wetlands, and agriculture on CH₄ emissions and show the need for seasonally resolved emission estimates.