Articles | Volume 18, issue 7
https://doi.org/10.5194/amt-18-1675-2025
https://doi.org/10.5194/amt-18-1675-2025
Research article
 | 
11 Apr 2025
Research article |  | 11 Apr 2025

Deep transfer learning method for seasonal TROPOMI XCH4 albedo correction

Alexander C. Bradley, Barbara Dix, Fergus Mackenzie, J. Pepijn Veefkind, and Joost A. de Gouw

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Cited articles

Akoglu, H.: User's guide to correlation coefficients, Turk. J. Emerg. Med., 18, 91–93, https://doi.org/10.1016/j.tjem.2018.08.001, 2018. 
Allen, D.: Attributing Atmospheric Methane to Anthropogenic Emission Sources, Acc. Chem. Res., 49, 1344–1350, https://doi.org/10.1021/acs.accounts.6b00081, 2016. 
Allen, D. T.: Methane emissions from natural gas production and use: reconciling bottom-up and top-down measurements, Curr. Opin. Chem. Eng., 5, 78–83, https://doi.org/10.1016/j.coche.2014.05.004, 2014. 
Annual Energy Outlook 2023: https://www.eia.gov/outlooks/aeo/index.php, last access: 16 January 2025. 
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Short summary
Currently, measurement of methane from the TROPOMI satellite is biased with respect to surface reflectance. This study demonstrates a new method of correcting for this bias on a seasonal timescale to allow for differences in surface reflectance in areas of intense agriculture where growing seasons may introduce a reflectance bias. We have successfully implemented this technique in the Denver–Julesburg basin, where agriculture and methane extraction infrastructure is often co-located.
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