Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 16, issue 23
Articles | Volume 16, issue 23
https://doi.org/10.5194/amt-16-5725-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-16-5725-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 23
Research article
 | 
29 Nov 2023
Research article |  | 29 Nov 2023

A nonlinear data-driven approach to bias correction of XCO2 for NASA's OCO-2 ACOS version 10

William R. Keely, Steffen Mauceri, Sean Crowell, and Christopher W. O'Dell

Viewed

Total article views: 1,293 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
978 262 53 1,293 44 50
  • HTML: 978
  • PDF: 262
  • XML: 53
  • Total: 1,293
  • BibTeX: 44
  • EndNote: 50
Views and downloads (calculated since 12 Apr 2023)
Cumulative views and downloads (calculated since 12 Apr 2023)

Viewed (geographical distribution)

Total article views: 1,293 (including HTML, PDF, and XML) Thereof 1,293 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 20 Nov 2024
Download
Short summary
Measurement errors in satellite observations of CO2 attributed to co-estimated atmospheric variables are corrected using a linear regression on quality-filtered data. We propose a nonlinear method that improves correction against a set of ground truth proxies and allows for high throughput of well-corrected data.
Read more