Articles | Volume 15, issue 16
Research article
29 Aug 2022
Research article |  | 29 Aug 2022

Combining Mie–Raman and fluorescence observations: a step forward in aerosol classification with lidar technology

Igor Veselovskii, Qiaoyun Hu, Philippe Goloub, Thierry Podvin, Boris Barchunov, and Mikhail Korenskii


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2022-81', Anonymous Referee #1, 05 May 2022
  • RC2: 'Comment on amt-2022-81', Anonymous Referee #2, 28 May 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Qiaoyun Hu on behalf of the Authors (06 Jul 2022)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (09 Jul 2022) by Daniel Perez-Ramirez
RR by Anonymous Referee #1 (26 Jul 2022)
RR by Anonymous Referee #2 (02 Aug 2022)
ED: Publish subject to technical corrections (04 Aug 2022) by Daniel Perez-Ramirez
AR by Qiaoyun Hu on behalf of the Authors (04 Aug 2022)  Author's response    Manuscript
Short summary
An approach to reveal variability in aerosol type at a high spatiotemporal resolution, by combining fluorescence and Mie–Raman lidar data, is presented. We applied this new classification scheme to lidar data obtained by LOA, University of Lille, in 2020–2021. It is demonstrated that the separation of the main particle types, such as smoke, dust, pollen, and urban, can be performed with a height resolution of 60 m and temporal resolution better than 10 min for the current lidar configuration.