Articles | Volume 12, issue 1
https://doi.org/10.5194/amt-12-169-2019
https://doi.org/10.5194/amt-12-169-2019
Research article
 | 
11 Jan 2019
Research article |  | 11 Jan 2019

Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements

David M. Giles, Alexander Sinyuk, Mikhail G. Sorokin, Joel S. Schafer, Alexander Smirnov, Ilya Slutsker, Thomas F. Eck, Brent N. Holben, Jasper R. Lewis, James R. Campbell, Ellsworth J. Welton, Sergey V. Korkin, and Alexei I. Lyapustin

Viewed

Total article views: 19,169 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
14,737 4,277 155 19,169 276 265
  • HTML: 14,737
  • PDF: 4,277
  • XML: 155
  • Total: 19,169
  • BibTeX: 276
  • EndNote: 265
Views and downloads (calculated since 10 Sep 2018)
Cumulative views and downloads (calculated since 10 Sep 2018)

Viewed (geographical distribution)

Total article views: 19,169 (including HTML, PDF, and XML) Thereof 17,783 with geography defined and 1,386 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 20 Nov 2024
Download
Short summary
Clouds or instrumental anomalies may perturb ground-based solar measurements used to calculate aerosol optical depth (AOD). This study presents a new algorithm of automated near-real-time (NRT) quality controls with improved cloud screening for AERONET AOD measurements. Results from the new and old algorithms have excellent agreement for the highest-quality AOD level, while the new algorithm provides higher-quality NRT AOD for applications such as data assimilation and satellite evaluation.