Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 18, issue 7
Articles | Volume 18, issue 7
https://doi.org/10.5194/amt-18-1675-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-1675-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 7
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

Viewed

Total article views: 1,159 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
839 150 170 1,159 51 45 45
  • HTML: 839
  • PDF: 150
  • XML: 170
  • Total: 1,159
  • Supplement: 51
  • BibTeX: 45
  • EndNote: 45
Views and downloads (calculated since 20 Aug 2024)
Cumulative views and downloads (calculated since 20 Aug 2024)

Viewed (geographical distribution)

Total article views: 1,159 (including HTML, PDF, and XML) Thereof 1,159 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 11 Aug 2025
Download
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.
Read more
Share