A machine learning approach for aerosol classification using sun photometer and lidar data

Joelle Buxmann; Martin Osborne; Mike Protts; Panuganti C.S. Devara; Pawan Gupta; Elena S. Lind; Govindan Pandithurai; Debbie O'Sullivan

doi:10.1051/epjconf/202636210003

Open Access

Issue		EPJ Web Conf. Volume 362, 2026 31^st International Laser Radar Conference (ILRC 31) Held Together with the 22^nd Coherent Laser Radar Conference (CLRC 22)


Article Number		10003
Number of page(s)		4
Section		Airborne Lidar Investigations, Large Scale Field Experiments, and Synergistic Use of Lidar and Other Instruments
DOI		https://doi.org/10.1051/epjconf/202636210003
Published online		09 April 2026

EPJ Web of Conferences 362, 10003 (2026)
https://doi.org/10.1051/epjconf/202636210003

A machine learning approach for aerosol classification using sun photometer and lidar data

Joelle Buxmann^(a), Martin Osborne^(a), Mike Protts^(a), Panuganti C.S. Devara^(b), Pawan Gupta^(c), Elena S. Lind^(c), Govindan Pandithurai^(d) and Debbie O'Sullivan^(a)

^(a) the Met Office, Exeter, UK
^(b) Amity Centre for Ocean-Atmospheric Science and Technology, Amity University Haryana, India
^(c) Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
^(d) Indian Institute of Tropical. Meteorology, Pune, India Lead Author e-mail address: This email address is being protected from spambots. You need JavaScript enabled to view it.

Published online: 9 April 2026

Abstract

The Met Office operates a ground based operational network of nine polarisation Raman lidars (aerosol profiling instruments) and sun photometers (column integrated information) across the United Kingdom (UK). An aerosol classification scheme using supervised machine learning has been developed. The concept of Mahalanobis (~normalized) distance to identify the aerosol type from individual Aerosol Robotic Network (AERONET) measurements including Extinction Angstrom Exponent, Absorption Angstrom Exponent, Single Scattering Albedo and Index of refraction is used for a subset of AERONET stations around the globe of known main aerosol types (training set). The aerosol types so far include marine, urban industrial, biomass burning and dust. The relation of particle linear depolarisation ratio (PLDR) and lidar ratio (LR) from the Raman lidar is used in synergy to validate the particle type.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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