Articles | Volume 14, issue 4
https://doi.org/10.5194/amt-14-2787-2021
https://doi.org/10.5194/amt-14-2787-2021
Research article
 | 
12 Apr 2021
Research article |  | 12 Apr 2021

Reducing cloud contamination in aerosol optical depth (AOD) measurements

Verena Schenzinger and Axel Kreuter

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Short summary
When measuring the aerosol optical depth of the atmosphere, clouds in front of the sun lead to erroneously high values. Therefore, measurements that are potentially affected by clouds need to be removed from the dataset by an automatic process. As the currently used algorithm cannot reliably identify thin clouds, we developed a new one based on a method borrowed from machine learning. Tests with 10 years of data show improved performance of the new routine and therefore higher data quality.