Articles | Volume 15, issue 1
Atmos. Meas. Tech., 15, 149–164, 2022
https://doi.org/10.5194/amt-15-149-2022
Atmos. Meas. Tech., 15, 149–164, 2022
https://doi.org/10.5194/amt-15-149-2022
Research article
06 Jan 2022
Research article | 06 Jan 2022

A Bayesian parametric approach to the retrieval of the atmospheric number size distribution from lidar data

Alberto Sorrentino et al.

Related authors

The unprecedented 2017–2018 stratospheric smoke event: decay phase and aerosol properties observed with the EARLINET
Holger Baars, Albert Ansmann, Kevin Ohneiser, Moritz Haarig, Ronny Engelmann, Dietrich Althausen, Ingrid Hanssen, Michael Gausa, Aleksander Pietruczuk, Artur Szkop, Iwona S. Stachlewska, Dongxiang Wang, Jens Reichardt, Annett Skupin, Ina Mattis, Thomas Trickl, Hannes Vogelmann, Francisco Navas-Guzmán, Alexander Haefele, Karen Acheson, Albert A. Ruth, Boyan Tatarov, Detlef Müller, Qiaoyun Hu, Thierry Podvin, Philippe Goloub, Igor Veselovskii, Christophe Pietras, Martial Haeffelin, Patrick Fréville, Michaël Sicard, Adolfo Comerón, Alfonso Javier Fernández García, Francisco Molero Menéndez, Carmen Córdoba-Jabonero, Juan Luis Guerrero-Rascado, Lucas Alados-Arboledas, Daniele Bortoli, Maria João Costa, Davide Dionisi, Gian Luigi Liberti, Xuan Wang, Alessia Sannino, Nikolaos Papagiannopoulos, Antonella Boselli, Lucia Mona, Giuseppe D'Amico, Salvatore Romano, Maria Rita Perrone, Livio Belegante, Doina Nicolae, Ivan Grigorov, Anna Gialitaki, Vassilis Amiridis, Ourania Soupiona, Alexandros Papayannis, Rodanthi-Elisaveth Mamouri, Argyro Nisantzi, Birgit Heese, Julian Hofer, Yoav Y. Schechner, Ulla Wandinger, and Gelsomina Pappalardo
Atmos. Chem. Phys., 19, 15183–15198, https://doi.org/10.5194/acp-19-15183-2019,https://doi.org/10.5194/acp-19-15183-2019, 2019

Related subject area

Subject: Aerosols | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
Atmospheric visibility inferred from continuous-wave Doppler wind lidar
Manuel Queißer, Michael Harris, and Steven Knoop
Atmos. Meas. Tech., 15, 5527–5544, https://doi.org/10.5194/amt-15-5527-2022,https://doi.org/10.5194/amt-15-5527-2022, 2022
Short summary
Identification of smoke and sulfuric acid aerosol in SAGE III/ISS extinction spectra
Travis N. Knepp, Larry Thomason, Mahesh Kovilakam, Jason Tackett, Jayanta Kar, Robert Damadeo, and David Flittner
Atmos. Meas. Tech., 15, 5235–5260, https://doi.org/10.5194/amt-15-5235-2022,https://doi.org/10.5194/amt-15-5235-2022, 2022
Short summary
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
Atmos. Meas. Tech., 15, 4881–4900, https://doi.org/10.5194/amt-15-4881-2022,https://doi.org/10.5194/amt-15-4881-2022, 2022
Short summary
Effective uncertainty quantification for multi-angle polarimetric aerosol remote sensing over ocean
Meng Gao, Kirk Knobelspiesse, Bryan A. Franz, Peng-Wang Zhai, Andrew M. Sayer, Amir Ibrahim, Brian Cairns, Otto Hasekamp, Yongxiang Hu, Vanderlei Martins, P. Jeremy Werdell, and Xiaoguang Xu
Atmos. Meas. Tech., 15, 4859–4879, https://doi.org/10.5194/amt-15-4859-2022,https://doi.org/10.5194/amt-15-4859-2022, 2022
Short summary
Employing relaxed smoothness constraints on imaginary part of refractive index in AERONET aerosol retrieval algorithm
Alexander Sinyuk, Brent N. Holben, Thomas F. Eck, David M. Giles, Ilya Slutsker, Oleg Dubovik, Joel S. Schafer, Alexander Smirnov, and Mikhail Sorokin
Atmos. Meas. Tech., 15, 4135–4151, https://doi.org/10.5194/amt-15-4135-2022,https://doi.org/10.5194/amt-15-4135-2022, 2022
Short summary

Cited articles

Alados-Arboledas, L., Müller, D., Guerrero-Rascado, J., Navas-Guzmán, F., Pérez-Ramírez, D., and Olmo, F.: Optical and microphysical properties of fresh biomass burning aerosol retrieved by Raman lidar, and star-and sun-photometry, Geophys. Res. Lett., 38, L01807, https://doi.org/10.1029/2010GL045999, 2011. a, b
Ansmann, A., Riebesell, M., and Weitkamp, C.: Measurement of atmospheric aerosol extinction profiles with a Raman lidar, Opt. Lett., 15, 746–748, 1990. a
Ansmann, A., Riebesell, M., Wandinger, U., Weitkamp, C., Voss, E., Lahmann, W., and Michaelis, W.: Combined Raman elastic-backscatter lidar for vertical profiling of moisture, aerosol extinction, backscatter, and lidar ratio, Appl. Phys. B-Lasers O., 55, 18–28, 1992. a
Balis, D., Giannakaki, E., Müller, D., Amiridis, V., Kelektsoglou, K., Rapsomanikis, S., and Bais, A.: Estimation of the microphysical aerosol properties over Thessaloniki, Greece, during the SCOUT-O3 campaign with the synergy of Raman lidar and Sun photometer data, J. Geophys. Res.-Atmos., 115, D08202, https://doi.org/10.1029/2009JD013088, 2010. a
Böckmann, C.: Hybrid regularization method for the ill-posed inversion of multiwavelength lidar data in the retrieval of aerosol size distributions, Appl. Optics, 40, 1329–1342, 2001. a
Download
Short summary
We present a novel approach that can be used to obtain microphysical properties of atmospheric aerosol, up to several kilometers in the atmosphere, from lidar measurements taken from the ground. Our approach provides accurate reconstructions under many different experimental conditions. Our results can contribute to the expansion of the use of remote sensing techniques for air quality monitoring and atmospheric science in general.