Articles | Volume 11, issue 3
https://doi.org/10.5194/amt-11-1529-2018
https://doi.org/10.5194/amt-11-1529-2018
Research article
 | 
19 Mar 2018
Research article |  | 19 Mar 2018

Bayesian aerosol retrieval algorithm for MODIS AOD retrieval over land

Antti Lipponen, Tero Mielonen, Mikko R. A. Pitkänen, Robert C. Levy, Virginia R. Sawyer, Sami Romakkaniemi, Ville Kolehmainen, and Antti Arola

Viewed

Total article views: 2,981 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,909 979 93 2,981 392 69 60
  • HTML: 1,909
  • PDF: 979
  • XML: 93
  • Total: 2,981
  • Supplement: 392
  • BibTeX: 69
  • EndNote: 60
Views and downloads (calculated since 01 Nov 2017)
Cumulative views and downloads (calculated since 01 Nov 2017)

Viewed (geographical distribution)

Total article views: 2,981 (including HTML, PDF, and XML) Thereof 2,817 with geography defined and 164 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 29 Mar 2023
Download
Short summary
Atmospheric aerosols are small solid or liquid particles suspended in the atmosphere and they have a significant effect on the climate. Satellite data are used to get global estimates of atmospheric aerosols. In this work, a statistics-based Bayesian aerosol retrieval algorithm was developed to improve the accuracy and quantify the uncertainties related to the aerosol estimates. The algorithm is tested with NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data.