Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 21, issue 3
Articles | Volume 21, issue 3
https://doi.org/10.5194/acp-21-1797-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-1797-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 21, issue 3
Research article
 | 
10 Feb 2021
Research article |  | 10 Feb 2021

Satellite retrieval of aerosol combined with assimilated forecast

Mayumi Yoshida, Keiya Yumimoto, Takashi M. Nagao, Taichu Y. Tanaka, Maki Kikuchi, and Hiroshi Murakami

Viewed

Total article views: 3,349 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,476 802 71 3,349 87 108
  • HTML: 2,476
  • PDF: 802
  • XML: 71
  • Total: 3,349
  • BibTeX: 87
  • EndNote: 108
Views and downloads (calculated since 27 May 2020)
Cumulative views and downloads (calculated since 27 May 2020)

Viewed (geographical distribution)

Total article views: 3,349 (including HTML, PDF, and XML) Thereof 3,325 with geography defined and 24 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 07 Nov 2025
Download
Short summary
We developed a new aerosol satellite retrieval algorithm combining a numerical aerosol forecast. This is the first study that utilizes the assimilated model forecast of aerosol as an a priori estimate of the retrieval. Aerosol retrievals were improved by effectively incorporating both model and satellite information. By using the assimilated forecast as an a priori estimate, information from previous observations can be propagated to future retrievals, thus leading to better retrieval accuracy.
Read more
Share
Altmetrics
Final-revised paper
Preprint