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

Retrieval of spatio-temporal distributions of particle parameters from multiwavelength lidar measurements using the linear estimation technique and comparison with AERONET

The results of the application of the linear estimation technique to multiwavelength Raman lidar measurements performed during the summer of 2011 in Greenbelt, MD, USA, are presented. We demonstrate that multiwavelength lidars are capable not only of providing vertical profiles of particle properties but also of revealing the spatio-temporal evolution of aerosol features. The nighttime 3β + 1α lidar measurements on 21 and 22 July were inverted to spatio-temporal distributions of particle microphysical parameters, such as volume, number density, effective radius and the complex refractive index. The particle volume and number density show strong variation during the night, while the effective radius remains approximately constant. The real part of the refractive index demonstrates a slight decreasing tendency in a region of enhanced extinction coefficient. The linear estimation retrievals are stable and provide time series of particle parameters as a function of height at 4 min resolution. AERONET observations are compared with multiwavelength lidar retrievals showing good agreement

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)

Effects of systematic and random errors on the retrieval of particle microphysical properties from multiwavelength lidar measurements using inversion with regularization

In this work we study the effects of systematic and random errors on the inversion of multiwavelength (MW) lidar data using the well-known regularization technique to obtain vertically resolved aerosol microphysical properties. The software implementation used here was developed at the Physics Instrumentation Center (PIC) in Troitsk (Russia) in conjunction with the NASA/Goddard Space Flight Center. Its applicability to Raman lidar systems based on backscattering measurements at three wavelengths (355, 532 and 1064 nm) and extinction measurements at two wavelengths (355 and 532 nm) has been demonstrated widely. The systematic error sensitivity is quantified by first determining the retrieved parameters for a given set of optical input data consistent with three different sets of aerosol physical parameters. Then each optical input is perturbed by varying amounts and the inversion is repeated. Using bimodal aerosol size distributions, we find a generally linear dependence of the retrieved errors in the microphysical properties on the induced systematic errors in the optical data. For the retrievals of effective radius, number/surface/volume concentrations and fine-mode radius and volume, we find that these results are not significantly affected by the range of the constraints used in inversions. But significant sensitivity was found to the allowed range of the imaginary part of the particle refractive index. Our results also indicate that there exists an additive property for the deviations induced by the biases present in the individual optical data. This property permits the results here to be used to predict deviations in retrieved parameters when multiple input optical data are biased simultaneously as well as to study the influence of random errors on the retrievals. The above results are applied to questions regarding lidar design, in particular for the spaceborne multiwavelength lidar under consideration for the upcoming ACE mission.This work was supported by the NASA/Goddard Space Flight Center, the Spanish Ministry of Science and Technology through projects CGL2010-18782 and CSD2007-00067, the Andalusian Regional Government through projects P10-RNM-6299 and P08-RNM-3568, the EU through ACTRIS project (EU INFRA-2010-1.1.16-262254) and the Postdoctoral Program of the University of Granada

Linear Estimation of Particle Bulk Parameters from Multi-Wavelength Lidar Measurements

An algorithm for linear estimation of aerosol bulk properties such as particle volume, effective radius and complex refractive index from multiwavelength lidar measurements is presented. The approach uses the fact that the total aerosol concentration can well be approximated as a linear combination of aerosol characteristics measured by multiwavelength lidar. Therefore, the aerosol concentration can be estimated from lidar measurements without the need to derive the size distribution, which entails more sophisticated procedures. The definition of the coefficients required for the linear estimates is based on an expansion of the particle size distribution in terms of the measurement kernels. Once the coefficients are established, the approach permits fast retrieval of aerosol bulk properties when compared with the full regularization technique. In addition, the straightforward estimation of bulk properties stabilizes the inversion making it more resistant to noise in the optical data. Numerical tests demonstrate that for data sets containing three aerosol backscattering and two extinction coefficients (so called 3 + 2 ) the uncertainties in the retrieval of particle volume and surface area are below 45% when input data random uncertainties are below 20 %. Moreover, using linear estimates allows reliable retrievals even when the number of input data is reduced. To evaluate the approach, the results obtained using this technique are compared with those based on the previously developed full inversion scheme that relies on the regularization procedure. Both techniques were applied to the data measured by multiwavelength lidar at NASA/GSFC. The results obtained with both methods using the same observations are in good agreement. At the same time, the high speed of the retrieval using linear estimates makes the method preferable for generating aerosol information from extended lidar observations. To demonstrate the efficiency of the method, an extended time series of observations acquired in Turkey in May 2010 was processed using the linear estimates technique permitting, for what we believe to be the first time, temporal-height distributions of particle parameters

Optical-microphysical properties of Saharan dust aerosols and composition relationship using a multi-wavelength Raman lidar, in situ sensors and modelling: a case study analysis

A strong Saharan dust event that occurred over the city of Athens, Greece (37.9° N, 23.6° E) between 27 March and 3 April 2009 was followed by a synergy of three instruments: a 6-wavelength Raman lidar, a CIMEL sun-sky radiometer and the MODIS sensor. The BSC-DREAM model was used to forecast the dust event and to simulate the vertical profiles of the aerosol concentration. Due to mixture of dust particles with low clouds during most of the reported period, the dust event could be followed by the lidar only during the cloud-free day of 2 April 2009. The lidar data obtained were used to retrieve the vertical profile of the optical (extinction and backscatter coefficients) properties of aerosols in the troposphere. The aerosol optical depth (AOD) values derived from the CIMEL ranged from 0.33–0.91 (355 nm) to 0.18–0.60 (532 nm), while the lidar ratio (LR) values retrieved from the Raman lidar ranged within 75–100 sr (355 nm) and 45–75 sr (532 nm). Inside a selected dust layer region, between 1.8 and 3.5 km height, mean LR values were 83 ± 7 and 54 ± 7 sr, at 355 and 532 nm, respectively, while the Ångström-backscatter-related (ABR<sub>355/532</sub>) and Ångström-extinction-related (AER<sub>355/532</sub>) were found larger than 1 (1.17 ± 0.08 and 1.11 ± 0.02, respectively), indicating mixing of dust with other particles. Additionally, a retrieval technique representing dust as a mixture of spheres and spheroids was used to derive the mean aerosol microphysical properties (mean and effective radius, number, surface and volume density, and mean refractive index) inside the selected atmospheric layers. Thus, the mean value of the retrieved refractive index was found to be 1.49( ± 0.10) + 0.007( ± 0.007)i, and that of the effective radiuses was 0.30 ± 0.18 μm. The final data set of the aerosol optical and microphysical properties along with the water vapor profiles obtained by Raman lidar were incorporated into the ISORROPIA II model to provide a possible aerosol composition consistent with the retrieved refractive index values. Thus, the inferred chemical properties showed 12–40% of dust content, sulfate composition of 16–60%, and organic carbon content of 15–64%, indicating a possible mixing of dust with haze and smoke. PM<sub>10</sub> concentrations levels, PM<sub>10</sub> composition results and SEM-EDX (Scanning Electron Microscope-Energy Dispersive X-ray) analysis results on sizes and mineralogy of particles from samples during the Saharan dust transport event were used to evaluate the retrieval

Microphysical particle properties derived from inversion algorithms developed in the framework of EARLINET

© Author(s) 2015. CC Attribution 3.0 License. An earlier version of this paper was published in Atmospheric Measurement Techniques Discussions: https://dx.doi.org/10.5194/amtd-8-12823-2015.We present a summary on the current status of two inversion algorithms that are used in EARLINET for the inversion of data collected with EARLINET multiwavelength Raman lidars. These instruments measure backscatter coecients at 355, 532, and 1064 nm, and extinction coecients at 355 and 532 nm. Development of these two algorithms started in 2000 when EARLINET was founded. The algorithms are based on manually controlled inversion of optical data which allows for detailed sensitivity studies and thus provides us with comparably high quality of the derived data products. The algorithms allow us to derive particle eective radius, and volume and surface-area concentration with comparably high confidence. The retrieval of the real and imaginary parts of the complex refractive index still is a challenge in view of the accuracy required for these parameters in climate change studies in which light-absorption needs to be known with high accuracy. Single-scattering albedo can be computed from the retrieved microphysical parameters and allows us to categorize aerosols into high and low absorbing aerosols. We discuss the current status of these manually operated algorithms, the potentially achievable accuracy of data products, and the goals for future work on the basis of a few exemplary simulations with synthetic optical data. The optical data used in our study cover a range of Ångström exponents and extinction-to-backscatter (lidar) ratios that are found from lidar measurements of various aerosol types.We also tested aerosol scenarios that are considered highly unlikely, e.g., the lidar ratios fall outside the commonly accepted range of values measured with Raman lidar, even though the underlying microphysical particle properties are not uncommon. The goal of this part of the study is to test robustness of the algorithms toward their ability to identify aerosol types that have not been measured so far, but cannot be ruled out based on our current knowledge of aerosol physics. We computed the optical data from monomodal logarithmic particle size distributions, i.e., we explicitly excluded the more complicated case of bimodal particle size distributions which is a topic of ongoing research work. Another constraint is that we only considered particles of spherical shape in our simulations. We considered particle radii as large as 7–10 μm in our simulations. That particle size does not only cover the size range of particles in the fine-mode fraction of naturally occurring particle size distributions but also covers a considerable part of the coarse-mode fraction of particle size distributions. We considered optical-data errors of 15% in the simulation studies. We target 50% uncertainty as a reasonable threshold for our data products, though we attempt to obtain data products with less uncertainty in future work.Peer reviewe

Airborne multiwavelength High Spectral Resolution Lidar (HSRL-2) observations during TCAP 2012 : Vertical profiles of optical and microphysical properties of a smoke/urban haze plume over the northeastern coast of the US

© Author(s) 2014. This work is distributed under the Creative Commons Attribution 3.0 License.We present measurements acquired by the world's first airborne 3 backscatter (β) + 2 extinction (α) High Spectral Resolution Lidar (HSRL-2). HSRL-2 measures particle backscatter coefficients at 355, 532, and 1064 nm, and particle extinction coefficients at 355 and 532 nm. The instrument has been developed by the NASA Langley Research Center. The instrument was operated during Phase 1 of the Department of Energy (DOE) Two-Column Aerosol Project (TCAP) in July 2012. We observed pollution outflow from the northeastern coast of the US out over the western Atlantic Ocean. Lidar ratios were 50-60 sr at 355 nm and 60-70 sr at 532 nm. Extinction-related Ångström exponents were on average 1.2-1.7, indicating comparably small particles. Our novel automated, unsupervised data inversion algorithm retrieved particle effective radii of approximately 0.2 μm, which is in agreement with the large Ångström exponents. We find good agreement with particle size parameters obtained from coincident in situ measurements carried out with the DOE Gulfstream-1 aircraft.Peer reviewedFinal Published versio

HSRL-2 aerosol optical measurements and microphysical retrievals vs. airborne in situ measurements during DISCOVER-AQ 2013: : an intercomparison study

This is an Open Access article distributed under the Creative Commons Attribution 3.0 License, https://creativecommons.org/licenses/by/3.0/. © Author(s) 2017. Published by Copernicus Publications on behalf of the European Geosciences Union.We present a detailed evaluation of remotely-sensed aerosol microphysical properties obtained from an advanced, multi-wavelength High Spectral Resolution Lidar (HSRL-2) during the 2013 NASA DISCOVER-AQ field campaign. Vertically resolved retrievals of fine mode aerosol number, surface area, and volume concentration as well as aerosol effective radius are compared to 108 co-located, airborne in situ measurement profiles in the wintertime San Joaquin Valley, California, and in summertime Houston, Texas. An algorithm for relating the dry in situ aerosol properties to those obtained by the HSRL at ambient relative humidity is discussed. We show that the HSRL-2 retrievals of ambient fine mode aerosol surface area and volume concentrations agree with the in situ measurements to within 25% and 10%, respectively, once hygroscopic growth adjustments have been applied to the dry in situ data. Despite this excellent agreement for the microphysical properties, extinction and backscatter coefficients at ambient relative humidity derived from the in situ aerosol measurements using Mie theory are consistently smaller than those measured by the HSRL, with average differences of 31% 5% and 53% 11% for California and Texas, respectively. This low bias in the in situ estimates is attributed to the presence of coarse mode aerosol that are detected by HSRL-2 but that are too large to be well sampled by the in situ instrumentation. Since the retrieval of aerosol volume is most relevant to current regulatory efforts targeting fine particle mass (PM2:5), these findings highlight the advantages of an advanced 3+2 HSRL for constraining the vertical distribution of the aerosol volume or mass loading relevant for air quality.Peer reviewedFinal Published versio