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AMT | Articles | Volume 12, issue 1
Atmos. Meas. Tech., 12, 169–209, 2019
https://doi.org/10.5194/amt-12-169-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 12, 169–209, 2019
https://doi.org/10.5194/amt-12-169-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

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 et al.
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Alexandrov, M. D., Schmid, B., Turner, D. D., Cairns, B., Oinas, V., Lacis, A. A., Gutman, S. I., Westwater, E. R., Smirnov, A., and Eilers, J.: Columnar water vapor from multifilter rotating shadowband radiometer data, J. Geophys, Res., 114, D02306, https://doi.org/10.1029/2008JD010543, 2009. 
Andrews, E., Ogren, J. A., Kinne, S., and Samset, B.: Comparison of AOD, AAOD and column single scattering albedo from AERONET retrievals and in situ profiling measurements, Atmos. Chem. Phys., 17, 6041–6072, https://doi.org/10.5194/acp-17-6041-2017, 2017. 
Ångström, A.: Apparent solar constant variations and their relation to variability of atmospheric transmission, Tellus, 22, 205–218, https://doi.org/10.3402/tellusa.v22i2.10215, 1970. 
Arola, A. and Koskela, T.: On the sources of bias in aerosol optical depth retrieval in the UV range, J. Geophys. Res., 109, D08209, https://doi.org/10.1029/2003JD004375, 2004. 
Barreto, A., Cuevas, E., Damiri, B., Guirado, C., Berkoff, T., Berjón, A. J., Hernández, Y., Almansa, F., and Gil, M.: A new method for nocturnal aerosol measurements with a lunar photometer prototype, Atmos. Meas. Tech., 6, 585–598, https://doi.org/10.5194/amt-6-585-2013, 2013. 
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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.
Clouds or instrumental anomalies may perturb ground-based solar measurements used to calculate...
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