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)?

• Published in: Atmospheric measurement techniques Vol. 12; no. 8; pp. 4421 - 4437
• Main Authors: Tesche, Matthias, Kolgotin, Alexei, Haarig, Moritz, Burton, Sharon P, Ferrare, Richard A, Hostetler, Chris A, Müller, Detlef
• Format: Journal Article
• Language: English
• Published: Katlenburg-Lindau Copernicus GmbH 19-08-2019; Copernicus Publications
• Subjects: Aerosols; Albedo; Algorithms; Ash; Atmospheric aerosols; Atmospheric particulates; Backscatter; Backscattering; Biomass burning; Burning; Coefficients; Data; Datasets; Depolarization; Deserts; Dust; Dust control; Dust particles; Dust storms; Instruments; Inversion; Lidar; Lidar measurements; Light; Light scattering; Mathematical models; Measuring instruments; Observations; Optical radar; Parameters; Particulate matter; Properties; Ratios; Remote sensing; Smoke; Smoke particles; Spheroids; Trustworthiness; Volcanic ash; Volcanic dust; Wavelength; Wavelengths; Germany
• ISSN: 1867-8548; 1867-1381; 1867-8548
• DOI: 10.5194/amt-12-4421-2019

The typical multiwavelength aerosol lidar data set for inversion of optical to microphysical parameters is composed of three backscatter coefficients (β) at 355, 532, and 1064 nm and two extinction coefficients (α) at 355 and 532 nm. This data combination is referred to as a 3β+2α or 3+2 data set. This set of data is sufficient for retrieving some important microphysical particle parameters if the particles have spherical shape. Here, we investigate the effect of including the particle linear depolarization ratio (δ) as a third input parameter for the inversion of lidar data. The inversion algorithm is generally not used if measurements show values of δ that exceed 0.10 at 532 nm, i.e. in the presence of non-spherical particles such as desert dust, volcanic ash, and, under special circumstances, biomass-burning smoke. We use experimental data collected with instruments that are capable of measuring δ at all three lidar wavelengths with an inversion routine that applies the spheroidal light-scattering model of Dubovik et al. (2006) with a fixed axis-ratio distribution to replicate scattering properties of non-spherical particles. The inversion gives the fraction of spheroids required to replicate the optical data as an additional output parameter. This is the first systematic test of the effect of using all theoretically possible combinations of δ taken at 355, 532, and 1064 nm as input in the lidar data inversion. We find that depolarization information of at least one wavelength already provides useful information for the inversion of optical data that have been collected in the presence of non-spherical mineral dust particles. However, any choice of δλ will give lower values of the single-scattering albedo than the traditional 3+2 data set. We find that input data sets that include δ355 give a spheroid fraction that closely resembles the dust ratio we obtain from using β532 and δ532 in a methodology applied in aerosol-type separation. The use of δ355 in data sets of two or three δλ reduces the spheroid fraction that is retrieved when using δ532 and δ1064. Use of the latter two parameters without accounting for δ355 generally leads to high spheroid fractions that we consider not trustworthy. The use of three δλ instead of two δλ, including the constraint that one of these is measured at 355 nm does not provide any advantage over using 3+2+δ355 for the observations with varying contributions of mineral dust considered here. However, additional measurements at wavelengths different from 355 nm would be desirable for application to a wider range of aerosol scenarios that may include non-spherical smoke particles, which can have values of δ355 that are indistinguishable from those found for mineral dust. We therefore conclude that – depending on measurement capability – the future standard input for inversion of lidar data taken in the presence of mineral dust particles and using the spheroid model of Dubovik et al. (2006) might be 3+2+δ355 or 3+2+δ355+δ532.