Synergy of lidar and passive remote sensor data for retrieving profiles of microphysical properties of non-spherical particles

© The Authors, published by EDP Sciences, 2018. This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).In this study we explore how the combination of 3 backscatter and 2 extinction lidar data with data that can be collected with ground-based and space-borne passive remote sensors, e.g. phase function coefficients which can be derived at various measurement wavelengths and scattering angles can result in improved profiles of particle microphysical properties. The algorithm is based on a light-scattering model that uses a mixture of spheres and randomly oriented spheroids.Peer reviewe

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)?

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.Peer reviewe

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)?

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 C 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 d that exceed 0.10 at 532 nm, i.e. in the presence of nonspherical 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 d 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 d 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 d will give lower values of the single-scattering albedo than the traditional 3 + 2 data set. We find that input data sets that include d355 give a spheroid fraction that closely resembles the dust ratio we obtain from using β532 and d532 in a methodology applied in aerosol-type separation. The use of d355 in data sets of two or three d? reduces the spheroid fraction that is retrieved when using d532 and d1064. Use of the latter two parameters without accounting for d355 generally leads to high spheroid fractions that we consider not trustworthy. The use of three d instead of two δ, including the constraint that one of these is measured at 355 nm does not provide any advantage over using 3 + 2 + d355 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 d355 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+2Cδ355 or 3 + 2 + δ355 + δ532. © 2019 The Author(s)

Characterization of Smoke/Dust Episode over West Africa: Comparison of MERRA-2 Modeling with Multiwavelength Mie-Raman Lidar Observations

Observations of multiwavelength Mie-Raman lidar taken during the SHADOW field campaign are used to analyze a smoke/dust episode over West Africa on 24-27 December 2015. For the case considered, the dust layer extended from the ground up to approximately 2000 m while the elevated smoke layer occurred in the 2500 m - 4000 m range. The profiles of lidar measured backscattering, extinction coefficients and depolarization ratios are compared with the vertical distribution of aerosol parameters provided by the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2). The MERRA-2 model simulated the correct location of the near-surface dust and elevated smoke layers. The value of modeled and observed aerosol extinction coefficients at both 355 nm and 532 nm are also rather close. In particular, for the episode reported, the mean value of difference between the measured and modeled extinction coefficients at 355 nm is 0.01 km(exp -1) with standard deviation of 0.042 km(exp -1). The model predicts significant concentration of dust particles inside the elevated smoke layer, which is supported by an increased depolarization ratio of 15% observed in the center of this layer. The modeled at 355 nm the lidar ratio of 65 sr in the near-surface dust layer is close to the observed value (70+/-10) sr. At 532 nm however, the simulated lidar ratio (about 40 sr) is lower than measurements (55+/-8 sr). The results presented demonstrate that the lidar and model data are complimentary and the synergy of observations and models is a key to improve the aerosols characterization

Perspectives of the Explicit Retrieval of the Complex Refractive Index of Aerosols from Optical Data Taken with Lidar

We developed an explicit approach for the retrieval of the complex refractive index from optical data, i.e. backscatter and extinction coefficients measured with lidar. In this approach we assume that we know the particle size distributions as well as the optical data. On the basis of this approach we carried out numerical simulations in order to test the uncertainty of the retrieval of the complex refractive index in dependence of the combination of extinction and backscatter coefficients, the measurement wavelengths and measurement errors

Application of Regularization Algorithm to HSRL-2 Observations During Oracles Campaign: Comparison of Retrieved and

Data obtained from HSRL-2 observations carried out on 20 September 2016 during the ORACLES campaign are publicly accessible. In our presentation we invert 3β+2α data into (1) particle size distributions with a regularization algorithm, and subsequently compute (2) single scattering albedo. We carry out a first comparison to the same particle characteristics measured with airborne in-situ instruments. We find good agreement of the data products. However, a more detailed study is needed as correction factors and sources of retrieval and measurement uncertainties need to be tested

Information content of multiwavelength lidar data on the base of Eigenvalues analysis

Multiwavelength Raman lidar technique in combination with sophisticated inversion algorithms has been recognized as a new tool to derive information about microphysical properties of atmospheric aerosols. The optical input parameter sets, which are provided by respective aerosol Raman lidars, are at the theoretical lower limit at which these inversion algorithms work properly. For that reason there is ongoing intense discussion on the accuracy of the inversion methods used for the retrieval of the microphysical parameters, and the possibility of the simultaneous retrieval of the particle size distribution and the complex refractive index. In our presentation we use eigenvalue analysis to study the information content of multiwavelength lidar data. Such an analysis provides us, oil a rather mathematical base, more insight oil the limitations of these inversion algorithms, it allows us to determine the range of particle microphysical parameters within which the complex refractive index can be derived with sufficient accuracy, and to estimate corresponding uncertainties. It furthermore shows the importance of the simultaneous use of backscattering and extinction coefficients for the retrieval of microphysical parameters

Direct Estimation of Fine and Coarse Mode Particle Parameters from Multiwavelength Lidar Measurements

An approach for the direct estimation (DE) of particle parameters in the fine and coarse mode from multiwavelength lidar measurements is presented. Particle size distributions in both modes are approximated by rectangular functions, so the particle density is estimated directly without solving the inverse problem. The numerical simulation demonstrates that the particle volume in both modes can be estimated from 3β+2α lidar measurements with uncertainty of ~25% for a wide range of size distributions. The technique developed was applied to the observations of NASA GSFC Raman lidar. Comparison of the results obtained with DE and regularization approach applied to the same set of data demonstrates agreement between these two techniques

Direct Estimation of Fine and Coarse Mode Particle Parameters from Multiwavelength Lidar Measurements

An approach for the direct estimation (DE) of particle parameters in the fine and coarse mode from multiwavelength lidar measurements is presented. Particle size distributions in both modes are approximated by rectangular functions, so the particle density is estimated directly without solving the inverse problem. The numerical simulation demonstrates that the particle volume in both modes can be estimated from 3β+2α lidar measurements with uncertainty of ~25% for a wide range of size distributions. The technique developed was applied to the observations of NASA GSFC Raman lidar. Comparison of the results obtained with DE and regularization approach applied to the same set of data demonstrates agreement between these two techniques

Perspectives of the Explicit Retrieval of the Complex Refractive Index of Aerosols from Optical Data Taken with Lidar

We developed an explicit approach for the retrieval of the complex refractive index from optical data, i.e. backscatter and extinction coefficients measured with lidar. In this approach we assume that we know the particle size distributions as well as the optical data. On the basis of this approach we carried out numerical simulations in order to test the uncertainty of the retrieval of the complex refractive index in dependence of the combination of extinction and backscatter coefficients, the measurement wavelengths and measurement errors