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

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by David Giles on behalf of the Authors (08 Dec 2018)  Author's response    Manuscript
ED: Publish subject to minor revisions (review by editor) (11 Dec 2018) by Vassilis Amiridis
AR by David Giles on behalf of the Authors (12 Dec 2018)  Author's response    Manuscript
ED: Publish as is (13 Dec 2018) by Vassilis Amiridis
AR by David Giles on behalf of the Authors (17 Dec 2018)  Author's response    Manuscript
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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.