Articles | Volume 18, issue 21
https://doi.org/10.5194/amt-18-6093-2025
https://doi.org/10.5194/amt-18-6093-2025
Research article
 | 
04 Nov 2025
Research article |  | 04 Nov 2025

Five years of GOSAT-2 retrievals with RemoTeC: XCO2 and XCH4 data products with quality filtering by machine learning

Andrew Gerald Barr, Jochen Landgraf, Mari Martinez-Velarte, Mihalis Vrekoussis, Ralf Sussmann, Isamu Morino, Kimberly Strong, Minqiang Zhou, Voltaire A. Velazco, Hirofumi Ohyama, Thorsten Warneke, Frank Hase, and Tobias Borsdorff

Viewed

Total article views: 5,640 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
4,449 1,058 133 5,640 138 206
  • HTML: 4,449
  • PDF: 1,058
  • XML: 133
  • Total: 5,640
  • BibTeX: 138
  • EndNote: 206
Views and downloads (calculated since 24 Apr 2025)
Cumulative views and downloads (calculated since 24 Apr 2025)

Viewed (geographical distribution)

Total article views: 5,640 (including HTML, PDF, and XML) Thereof 5,628 with geography defined and 12 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 19 May 2026
Download
Short summary

The Greenhouse Gases Observing Satellite-2 (GOSAT-2) is a satellite dedicated to measuring concentrations of greenhouse gases from space. Since its launch, the increase of CH4 and CO2 concentrations in the atmosphere is clear. The datasets obtained from GOSAT-2 are used in the Copernicus atmospheric services to monitor the climate, in light of the Paris Agreement. Here we present robust datasets of these gases from GOSAT-2, including a novel machine learning approach to data quality filtering.

Share