the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluating When and Where TROPOMI XCH4 Uncertainties Yield Consistent Flux Estimation over East, South, and Central Asia
Abstract. Satellite remote sensing of methane (CH4) offers the potential to monitor emissions across large scales, but skepticism remains among regulators, policymakers, and the scientific community of both the precision and accuracy of such estimations due to unquantified observational uncertainties. Using 500 perturbation experiments with four error distributions applied to TROPOMI XCH4 over East, South, and Central Asia, we systematically assess where and when divergence‑based emission estimates are reliable. We show that the shape of the uncertainty distribution – not just its magnitude – governs error propagation and thus effects the stability of derived fluxes. Furthermore we show that uncertainty propogates over both space and time, indicating that purely local accounting may lead to an underestimate of uncertainty. Coal‑dominated industrial grids retain trustworthy signals (30% retention of valid perturbations), whereas agricultural and mixed‑use grids retain only 16%, indicating that current filtering practices are insufficient for these land types. These results provide a practical, uncertainty‑aware filter for satellite‑derived methane emissions, directly supporting the Global Methane Pledge and national greenhouse gas inventories by identifying where satellite data can be trusted (coal‑dominated regions) and where additional caution or alternative approaches are needed. The process is data-neutral and can be extended to other satellite platforms and adopted by other regions around the globe.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
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Status: open (until 19 Nov 2026)
- RC1: 'Comment on egusphere-2026-4468', Anonymous Referee #1, 16 Oct 2026 reply
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As the emerging methane sensing technology, satellite-based observations are increasingly applied in monitoring methane emissions. The investigations of the inherent measurement uncertainty and the potent bias for the emissions estimates are highly needed. This study investigates the impact of residual random noise in observed datasets, and demonstrate that small absolute perturbations in the divergence can be substantially amplified, potentially leading to biased emission estimates or false signal detection. To address this issue, the manuscript introduces a set of assumptions and applies an unbiased filtering criterion to evaluate the proportion of samples that yield robust and stable emission estimates.
Overall, this work is likely to be of interest to the remote sensing and air quality research communities, as it provides useful insights into the robustness and limitations of divergence-based emission estimation approaches. Subject to the authors addressing the minor comments raised below, I consider the manuscript suitable for publication.