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

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

doi:https://doi.org/10.5194/amt-18-5415-2025

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

Supplement

https://doi.org/10.5194/amt-18-5415-2025-supplement

Data sets

MODIS Atmosphere L2 Cloud Product (06_L2) S. Platnick et al. https://doi.org/10.5067/MODIS/MYD06_L2.061

Aerosols above clouds products from POLDER/PARASOL satellite observations (AERO-AC products) F. Waquet et al. https://doi.org/10.25326/82

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.