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Aerosol Typing Based on Multiwavelength Lidar Observations and Meteorological Model Data

Authors :
Mylonaki Maria
Giannakaki Elina
Papayannis Alexandros
Floca Elena
Komppula Mika
Source :
EPJ Web of Conferences, Vol 237, p 08003 (2020)
Publication Year :
2020
Publisher :
EDP Sciences, 2020.

Abstract

Three different aerosol classification methods have been used to characterize lidar observations: Mahalanobis distance automatic aerosol type classification, Neural Network Aerosol Typing Algorithm (NATALI) and Source and Analysis (SCAN) aerosol classification. The data selection has been made through the EARLINET database depending on the 3b+2a+1δ optical property availability. One hundred aerosol layers from four EARLINET stations (Bucharest, Kuopio, Leipzig and Potenza) have been classified. We present a typical case study of aerosol characterization observed by the MUSA system over Potenza on the 11th of April 2016 (20:30-21:30 UTC).

Subjects

Subjects :
Physics
QC1-999

Details

Language :
English
ISSN :
2100014X
Volume :
237
Database :
Directory of Open Access Journals
Journal :
EPJ Web of Conferences
Publication Type :
Academic Journal
Accession number :
edsdoj.868803d777934f8a89afbf7d6dd7e135
Document Type :
article
Full Text :
https://doi.org/10.1051/epjconf/202023708003