Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 18, issue 20
Articles | Volume 18, issue 20
https://doi.org/10.5194/amt-18-5415-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-5415-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 20
Research article
 | 
16 Oct 2025
Research article |  | 16 Oct 2025

Above Cloud Aerosol Detection and Retrieval from Multi-Angular Polarimetric Satellite Measurements in a Neural Network Ensemble Approach

Zihao Yuan, Guangliang Fu, Hai Xiang Lin, Jan Willem Erisman, and Otto P. Hasekamp

Viewed

Total article views: 4,768 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
3,510 1,084 174 4,768 85 212 200
  • HTML: 3,510
  • PDF: 1,084
  • XML: 174
  • Total: 4,768
  • Supplement: 85
  • BibTeX: 212
  • EndNote: 200
Views and downloads (calculated since 08 Apr 2025)
Cumulative views and downloads (calculated since 08 Apr 2025)

Viewed (geographical distribution)

Total article views: 4,768 (including HTML, PDF, and XML) Thereof 4,628 with geography defined and 140 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 21 Sep 2026
Download
Short summary
This work develops an Neural-Network-based above cloud aerosol (ACA) detection and retrieval scheme for multi-angular polarimetric (MAP) instruments. On one year of the retrieval, the retrieved aerosol properties (aerosol optical thickness, AOT, Angstrom Exponent, AE, and Single Scattering Albedo, SSA) agree well with adjacent clear-sky aerosol retrievals. The seasonal global pattern of ACA events and above cloud AOT are also within expectation.
Read more
Share