Reply on RC1

Abstract

The paper presents an innovative approach to reveal variability of aerosol type at high spatio-temporal resolution, by combining fluorescence and Mie-Raman lidar observations. The multi-wavelength Mie-Raman lidar system in operation at the ATOLL platform (ATmospheric Observatory of liLLe), Laboratoire d’Optique Atmosphérique, University of Lille, includes, since 2019, a wideband fluorescence channel allowing the derivation of the fluorescence backscattering coefficient βF. The fluorescence capacity GF, which is the ratio of βF to the aerosol backscattering coefficient, is an intensive particle’s property, strongly changing with aerosol type, thus providing a relevant basis for aerosol classification. In this first single version of the algorithm, only two intensive properties are used for classification: the particle depolarization ratio at 532 nm, and the fluorescence capacity, GF. We applied our new classification approach to ATOLL high performance lidar data obtained during 2020–2021 period, which includes strong smoke, dust and pollen episodes. It is demonstrated that separation of the main particle’s types and their mixtures can be performed with height resolution about 60 m and temporal resolution better than 10 minutes for the current lidar configuration.