EGU25-15516, updated on 15 Mar 2025
https://doi.org/10.5194/egusphere-egu25-15516
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Tuesday, 29 Apr, 14:10–14:20 (CEST)
 
Room 0.11/12
An advanced aerosol optical depth retrieval algorithm based on an improved scattering angle scheme for Geostationary satellite
Mansing Wong1,2,3, Jiaqi Jin1, Jing Li1, Kwonho Lee4, Janet Elizabeth Nichol5, and Pw Chan6
Mansing Wong et al.
  • 1Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, China (ls.charles@polyu.edu.hk)
  • 2Research Institute for Sustainable Urban Development, The Hong Kong Polytechnic University, Hong Kong, China
  • 3Research Institute of Land and Space, The Hong Kong Polytechnic University, Hong Kong SAR, China.
  • 4Department of Atmospheric & Environmental Sciences, Gangneung-Wonju National University, Gangneung, Korea (kwonho.lee@gmail.com)
  • 5School of Global Studies, University of Sussex, Brighton, U.K. (janet.nichol@connect.polyu.hk)
  • 6Hong Kong Observatory, Hong Kong, China

The Advanced Himawari Imager onboard the Himawari-8/9 geostationary satellite offers a powerful tool for aerosol monitoring at high temporal resolution, with observations available every 10 minutes. Aerosol optical depth (AOD), a key parameter for characterizing aerosols, is commonly retrieved using physics-based algorithms that depend on prior assumptions about surface reflectance and aerosol models. However, these assumptions often fail to account for the complexities of land and atmospheric conditions. This study introduces a novel AOD retrieval algorithm that enhances the accuracy of surface reflectance estimation and aerosol modeling by utilizing time-series geostationary observations and clustering aerosol properties based on precise ground-based measurements. AOD retrievals were performed for the period from 2022 to 2023 over southern China, primarily Guangdong Province, and validated using ground-based measurements from the AErosol RObotic NETwork (AERONET) and the Sun-sky radiometer Observation NETwork (SONET). The results were also compared against aerosol products from the MODerate Resolution Imaging Spectroradiometer (MODIS). The proposed algorithm demonstrated strong agreement with AERONET and SONET observations, achieving a correlation coefficient of 0.74, an RMSE of 0.18, and over 52% of retrievals falling within the expected error (EE) range of ±(0.05 + 15%). By comparison, the AOD products from the Japan Aerospace Exploration Agency (JAXA) had a lower correlation coefficient of 0.232, an RMSE of 0.330, and only about 30% of retrievals within the EE of ±(0.05 + 15%). Furthermore, the proposed algorithm outperformed MODIS in terms of accuracy over their shared retrieval regions. The algorithm’s performance benefits from a newly developed scattering scheme that significantly enhances diurnal retrieval accuracy, making it a promising approach for application to other geostationary satellites.

How to cite: Wong, M., Jin, J., Li, J., Lee, K., Nichol, J. E., and Chan, P.: An advanced aerosol optical depth retrieval algorithm based on an improved scattering angle scheme for Geostationary satellite, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15516, https://doi.org/10.5194/egusphere-egu25-15516, 2025.