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

Data sets

University of Leicester GOSAT Proxy XCH 4 v9.0 Robert Parker and Hartmut Boesch https://doi.org/10.5285/18ef8247f52a4cb6a14013f8235cc1eb

CropScape - Cropland Data Layer (CDL) USDA NASS (National Agricultural Statistics Service) https://nassgeodata.gmu.edu/CropScape/

Model code and software

tropomi_seasonal_albedo_correction Alexander C. Bradley https://doi.org/10.5281/zenodo.12809441

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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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