Correction of Simulation Biases in Stratospheric Methane Concentrations for the Inverse Analysis of Satellite Column Observations

Global chemical transport models often overestimate stratospheric methane concentrations due to inaccuracies in simulating stratospheric circulation. If uncorrected, these biases can distort inverse analyses of satellite methane column observations (e.g., GOSAT), which encompass contributions from both the troposphere and the stratosphere, and lead to erroneous estimates of surface emissions and tropospheric sinks. To overcome this limitation and advance methane modeling, we developed and evaluated several novel bias correction approaches (e.g., empirically derived polynomial correction, age‐of‐air proxy correction, and offline correction by replacing the stratospheric fields with observations). Crucially, we implemented the first online correction by assimilating independent satellite observations (e.g., ACE‐FTS and MIPAS), dynamically accounting for interannual variabilities and stratosphere‐troposphere exchange (STE) processes. These innovative methods yield significant quantitative improvements: correcting for stratospheric biases on average resulted in a 22‐Tg a −1 increase in inferred global methane emissions from GOSAT data, but with notable differences among methods (3–54 Tg a −1 ). The correction increased extratropical emissions by 47 (26–101) Tg a −1 but decreased tropical emissions by 24 (11–47) Tg a −1 , highlighting a substantial impact on regional emission apportionment. Our results also indicate that stratospheric biases can distort tropospheric simulation through STE, potentially affecting the analysis of surface methane observations. This work provides essential methodological advancements—particularly the online correction framework—for robust global methane budget quantification, significantly reducing uncertainties in satellite‐based inversions.