Articles | Volume 12, issue 8
https://doi.org/10.5194/amt-12-4421-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-12-4421-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
3+2 + X: what is the most useful depolarization input for retrieving microphysical properties of non-spherical particles from lidar measurements using the spheroid model of Dubovik et al. (2006)?
Matthias Tesche
CORRESPONDING AUTHOR
School of Physics, Astronomy and Mathematics, University of Hertfordshire, Hatfield, UK
now at: Leipzig Institute for Meteorology (LIM), Leipzig University, Leipzig, Germany
Alexei Kolgotin
A. M. Prokhorov General Physics Institute, Moscow, Russia
Moritz Haarig
Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany
Sharon P. Burton
NASA Langley Research Center, Hampton, USA
Richard A. Ferrare
NASA Langley Research Center, Hampton, USA
Chris A. Hostetler
NASA Langley Research Center, Hampton, USA
Detlef Müller
School of Physics, Astronomy and Mathematics, University of Hertfordshire, Hatfield, UK
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Cited
13 citations as recorded by crossref.
- Potential of Polarization Lidar to Profile the Urban Aerosol Phase State during Haze Episodes W. Tan et al. 10.1021/acs.estlett.9b00695
- Advantages of an Additional Raman Channel in Laser Sounding at Wavelengths of 355–1064 nm for Retrieving Microphysical Parameters of Atmospheric Aerosol S. Samoilova et al. 10.1134/S1024856023060179
- Separate retrieval of microphysical characteristics in aerosol fractions from laser sensing data S. Samoiliva et al. 10.1016/j.jqsrt.2022.108168
- A Bayesian parametric approach to the retrieval of the atmospheric number size distribution from lidar data A. Sorrentino et al. 10.5194/amt-15-149-2022
- Retrieval of aerosol microphysical properties from atmospheric lidar sounding: an investigation using synthetic measurements and data from the ACEPOL campaign W. McLean et al. 10.5194/amt-14-4755-2021
- Simulated polarization as a signature of aerosol type P. Hamill et al. 10.1016/j.atmosenv.2020.117348
- Seasonal characteristics of aerosol vertical structure and autumn enhancement of non-spherical particle over the semi-arid region of northwest China T. Zhou et al. 10.1016/j.atmosenv.2020.117912
- Modeling a Spheroidal Particle Ensemble and Inversion by Generalized Runge–Kutta Regularizers from Limited Data S. Samaras et al. 10.3390/appliedmath2040032
- Investigating the dependence of mineral dust depolarization on complex refractive index and size with a laboratory polarimeter at 180.0° lidar backscattering angle A. Miffre et al. 10.5194/amt-16-403-2023
- Retrieval of microphysical properties of dust aerosols from extinction, backscattering and depolarization lidar measurements using various particle scattering models Y. Chang et al. 10.5194/acp-25-6787-2025
- On the use of light polarization to investigate the size, shape, and refractive index dependence of backscattering Ångström exponents A. Miffre et al. 10.1364/OL.385107
- This is FAST: multivariate Full-permutAtion based Stochastic foresT method—improving the retrieval of fine-mode aerosol microphysical properties with multi-wavelength lidar N. Wang et al. 10.1016/j.rse.2022.113226
- Single-scattering properties of ellipsoidal dust aerosols constrained by measured dust shape distributions Y. Huang et al. 10.5194/acp-23-2557-2023
13 citations as recorded by crossref.
- Potential of Polarization Lidar to Profile the Urban Aerosol Phase State during Haze Episodes W. Tan et al. 10.1021/acs.estlett.9b00695
- Advantages of an Additional Raman Channel in Laser Sounding at Wavelengths of 355–1064 nm for Retrieving Microphysical Parameters of Atmospheric Aerosol S. Samoilova et al. 10.1134/S1024856023060179
- Separate retrieval of microphysical characteristics in aerosol fractions from laser sensing data S. Samoiliva et al. 10.1016/j.jqsrt.2022.108168
- A Bayesian parametric approach to the retrieval of the atmospheric number size distribution from lidar data A. Sorrentino et al. 10.5194/amt-15-149-2022
- Retrieval of aerosol microphysical properties from atmospheric lidar sounding: an investigation using synthetic measurements and data from the ACEPOL campaign W. McLean et al. 10.5194/amt-14-4755-2021
- Simulated polarization as a signature of aerosol type P. Hamill et al. 10.1016/j.atmosenv.2020.117348
- Seasonal characteristics of aerosol vertical structure and autumn enhancement of non-spherical particle over the semi-arid region of northwest China T. Zhou et al. 10.1016/j.atmosenv.2020.117912
- Modeling a Spheroidal Particle Ensemble and Inversion by Generalized Runge–Kutta Regularizers from Limited Data S. Samaras et al. 10.3390/appliedmath2040032
- Investigating the dependence of mineral dust depolarization on complex refractive index and size with a laboratory polarimeter at 180.0° lidar backscattering angle A. Miffre et al. 10.5194/amt-16-403-2023
- Retrieval of microphysical properties of dust aerosols from extinction, backscattering and depolarization lidar measurements using various particle scattering models Y. Chang et al. 10.5194/acp-25-6787-2025
- On the use of light polarization to investigate the size, shape, and refractive index dependence of backscattering Ångström exponents A. Miffre et al. 10.1364/OL.385107
- This is FAST: multivariate Full-permutAtion based Stochastic foresT method—improving the retrieval of fine-mode aerosol microphysical properties with multi-wavelength lidar N. Wang et al. 10.1016/j.rse.2022.113226
- Single-scattering properties of ellipsoidal dust aerosols constrained by measured dust shape distributions Y. Huang et al. 10.5194/acp-23-2557-2023
Latest update: 09 Jul 2025
Short summary
Today, few lidar are capable of triple-wavelength particle linear depolarization ratio (PLDR) measurements. This study is the first systematic investigation of the effect of different choices of PLDR input on the inversion of lidar measurements of mineral dust and dusty mixtures using light scattering by randomly oriented spheroids. We provide recommendations of the most suitable input parameters for use with the applied methodology, based on a relational assessment of the inversion output.
Today, few lidar are capable of triple-wavelength particle linear depolarization ratio (PLDR)...