Articles | Volume 21, issue 3
Atmos. Chem. Phys., 21, 2211–2227, 2021
https://doi.org/10.5194/acp-21-2211-2021

Special issue: EARLINET aerosol profiling: contributions to atmospheric and...

Atmos. Chem. Phys., 21, 2211–2227, 2021
https://doi.org/10.5194/acp-21-2211-2021

Research article 15 Feb 2021

Research article | 15 Feb 2021

Aerosol type classification analysis using EARLINET multiwavelength and depolarization lidar observations

Maria Mylonaki et al.

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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Maria Mylonaki on behalf of the Authors (26 Dec 2020)  Author's response    Manuscript
ED: Publish as is (04 Jan 2021) by Eduardo Landulfo
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Short summary
We introduce an automated aerosol type classification method, SCAN. The output of SCAN is compared with two aerosol classification methods: (1) the Mahalanobis distance automatic aerosol type classification and (2) a neural network aerosol typing algorithm. A total of 97 free tropospheric aerosol layers from four EARLINET stations in the period 2014–2018 were classified.
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