Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 19, issue 16
Articles | Volume 19, issue 16
https://doi.org/10.5194/acp-19-10961-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/acp-19-10961-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 16
Research article
 | 
29 Aug 2019
Research article |  | 29 Aug 2019

Comparison of two automated aerosol typing methods and their application to an EARLINET station

Kalliopi Artemis Voudouri, Nikolaos Siomos, Konstantinos Michailidis, Nikolaos Papagiannopoulos, Lucia Mona, Carmela Cornacchia, Doina Nicolae, and Dimitris Balis

Viewed

Total article views: 2,881 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,921 886 74 2,881 94 117
  • HTML: 1,921
  • PDF: 886
  • XML: 74
  • Total: 2,881
  • BibTeX: 94
  • EndNote: 117
Views and downloads (calculated since 05 Dec 2018)
Cumulative views and downloads (calculated since 05 Dec 2018)

Viewed (geographical distribution)

Total article views: 2,881 (including HTML, PDF, and XML) Thereof 2,795 with geography defined and 86 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 18 Nov 2025
Download
Short summary
In this study, a first attempt at comparing and evaluating two classification tools developed within EARLINET that provide near-real-time aerosol typing information for the lidar profiles of Thessaloniki is presented. Our aim is (i) to check the performance of both supervised learning techniques in their low-resolution mode and (ii) to investigate the reasons for typing agreement and disagreement with respect to the uncertainties and the threshold criteria applied.
Read more
Share
Special issue
EARLINET aerosol profiling: contributions to atmospheric and...
Altmetrics
Final-revised paper
Preprint