Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 19, issue 20
Articles | Volume 19, issue 20
https://doi.org/10.5194/amt-19-6805-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-19-6805-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 20
Research article
 | 
28 Oct 2026
Research article |  | 28 Oct 2026

A blue-band surface residual correction method for land aerosol optical depth retrieval from DQ-1 WSI

Jingxuan Zhao, Yujing Wang, Hui Chen, Mengjie Zhang, Lili Wang, Xingchuan Yang, Shuo Dong, Wenji Zhao, and Pengfei Ma

Viewed

Total article views: 384 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
188 120 76 384 65 74 58
  • HTML: 188
  • PDF: 120
  • XML: 76
  • Total: 384
  • Supplement: 65
  • BibTeX: 74
  • EndNote: 58
Views and downloads (calculated since 18 Aug 2026)
Cumulative views and downloads (calculated since 18 Aug 2026)

Viewed (geographical distribution)

Total article views: 384 (including HTML, PDF, and XML) Thereof 379 with geography defined and 5 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 28 Oct 2026
Download
Short summary
Satellite estimates of airborne particles can be inaccurate when light reflected by land is poorly estimated. We developed a method for China's DaQi-1 satellite that uses machine learning to correct this land signal while retaining a physics-based calculation. Comparisons with ground observations showed reduced errors in spring and autumn–winter. The method also reduced errors the following spring without retraining, suggesting more reliable monitoring over complex land surfaces.
Read more
Share
Altmetrics
Final-revised paper
Preprint