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An automatic observation-based aerosol typing method for EARLINET

Author
Papagiannopoulos, N.; Mona, L.; Amodeo, A.; D'Amico, G.; Comeron, A.; Rodriguez-Gomez, A.; Sicard, M.
Type of activity
Journal article
Journal
Atmospheric chemistry and physics
Date of publication
2018-11-06
Volume
18
Number
21
First page
15879
Last page
15901
DOI
https://doi.org/10.5194/acp-18-15879-2018 Open in new window
Project funding
European natural airborne disaster information and coordination system for aviation
Repository
http://hdl.handle.net/2117/125208 Open in new window
URL
https://www.atmos-chem-phys.net/18/15879/2018/ Open in new window
Abstract
We present an automatic aerosol classification method based solely on the European Aerosol Research Lidar Network (EARLINET) intensive optical parameters with the aim of building a network-wide classification tool that could provide near-real-time aerosol typing information. The presented method depends on a supervised learning technique and makes use of the Mahalanobis distance function that relates each unclassified measurement to a predefined aerosol type. As a first step (training phase), a ...
Citation
Papagiannopoulos, N., Mona, L., Amodeo, A., D'Amico, G., Comeron, A., Rodriguez-Gomez, A., Sicard, M. An automatic observation-based aerosol typing method for EARLINET. "Atmospheric chemistry and physics", 6 Novembre 2018, vol. 18, núm. 21, p. 15879-15901.
Group of research
RSLAB - Remote Sensing Lab

Participants