We present an inversion algorithm for the retrieval of particle size distribution parameters, i.e., mean (effective) radius, number, surface area, and volume concentration, and complex refractive index from multiwavelength lidar data. In contrast to the classical Tikhonov method, which accepts only that solution for which the discrepancy reaches its global minimum, in our algorithm we perform the averaging of solutions in the vicinity of this minimum. This averaging stabilizes the underlying ill-posed inverse problem, particularly with respect to the retrieval of number concentration. Results show that, for typical tropospheric particles and 10% error in the optical data, the mean radius could be retrieved to better than 20% from a lidar on the basis of a Nd:YAG laser, which provides a combination of backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm. The accuracy is improved if the lidar is also equipped with a hydrogen Raman shifter. In this case two additional backscatter coefficients at 416 and 683 nm are available. The combination of two extinction coefficients and five backscatter coefficients then allows one to retrieve not only averaged aerosol parameters but also the size distribution function. There was acceptable agreement between physical particle properties obtained from the evaluation of multiwavelength lidar data taken during the Lindenberg Aerosol Characterization Experiment in 1998 (LACE 98) and in situ data, which were taken aboard aircraft.

We report on the feasibility of deriving microphysical parameters of bimodal particle size distributions from Mie-Raman lidar based on a triple Nd:YAG laser. Such an instrument provides backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm. The inversion method employed is Tikhonov's inversion with regularization. Special attention has been paid to extend the particle size range for which this inversion scheme works to approximately 10 microm, which makes this algorithm applicable to large particles, e.g., investigations concerning the hygroscopic growth of aerosols. Simulations showed that surface area, volume concentration, and effective radius are derived to an accuracy of approximately 50% for a variety of bimodal particle size distributions. For particle size distributions with an effective radius of < 1 microm the real part of the complex refractive index was retrieved to an accuracy of +/- 0.05, the imaginary part was retrieved to 50% uncertainty. Simulations dealing with a mode-dependent complex refractive index showed that an average complex refractive index is derived that lies between the values for the two individual modes. Thus it becomes possible to investigate external mixtures of particle size distributions, which, for example, might be present along continental rims along which anthropogenic pollution mixes with marine aerosols. Measurement cases obtained from the Institute for Tropospheric Research six-wavelength aerosol lidar observations during the Indian Ocean Experiment were used to test the capabilities of the algorithm for experimental data sets. A benchmark test was attempted for the case representing anthropogenic aerosols between a broken cloud deck. A strong contribution of particle volume in the coarse mode of the particle size distribution was found.

[1] Multiwavelength (MW) Raman lidars have demonstrated their potential to profile particle parameters; however, until now, the physical models used in retrieval algorithms for processing MW lidar data have been predominantly based on the Mie theory. This approach is applicable to the modeling of light scattering by spherically symmetric particles only and does not adequately reproduce the scattering by generally nonspherical desert dust particles. Here we present an algorithm based on a model of randomly oriented spheroids for the inversion of multiwavelength lidar data. The aerosols are modeled as a mixture of two aerosol components: one composed only of spherical and the second composed of nonspherical particles. The nonspherical component is an ensemble of randomly oriented spheroids with size-independent shape distribution. This approach has been integrated into an algorithm retrieving aerosol properties from the observations with a Raman lidar based on a tripled Nd:YAG laser. Such a lidar provides three backscattering coefficients, two extinction coefficients, and the particle depolarization ratio at a single or multiple wavelengths. Simulations were performed for a bimodal particle size distribution typical of desert dust particles. The uncertainty of the retrieved particle surface, volume concentration, and effective radius for 10% measurement errors is estimated to be below 30%. We show that if the effect of particle nonsphericity is not accounted for, the errors in the retrieved aerosol parameters increase notably. The algorithm was tested with experimental data from a Saharan dust outbreak episode, measured with the BASIL multiwavelength Raman lidar in August 2007. The vertical profiles of particle parameters as well as the particle size distributions at different heights were retrieved. It was shown that the algorithm developed provided substantially reasonable results consistent with the available independent information about the observed aerosol event.Citation: Veselovskii, I., O. Dubovik, A. Kolgotin, T. Lapyonok, P. Di Girolamo, D. Summa, D. N. Whiteman, M. Mishchenko, and D. Tanré (2010), Application of randomly oriented spheroids for retrieval of dust particle parameters from multiwavelength lidar measurements,

West Africa and the adjacent oceanic regions are very important locations for studying dust properties and their influence on weather and climate. The SHADOW (study of SaHAran Dust Over West Africa) campaign is performing a multiscale and multilaboratory study of aerosol properties and dynamics using a set of in situ and remote sensing instruments at an observation site located at the IRD (Institute for Research and Development) in Mbour, Senegal (14 • N, 17 • W). In this paper, we present the results of lidar measurements performed during the first phase of SHADOW (study of SaHAran Dust Over West Africa) which occurred in March-April 2015. The multiwavelength Mie-Raman li-dar acquired 3β + 2α + 1δ measurements during this period. This set of measurements has permitted particle-intensive properties, such as extinction and backscattering Ångström exponents (BAE) for 355/532 nm wavelengths' corresponding lidar ratios and depolarization ratio at 532 nm, to be determined. The mean values of dust lidar ratios during the observation period were about 53 sr at both 532 and 355 nm, which agrees with the values observed during the SAMUM-1 and SAMUM-2 campaigns held in Morocco and Cabo Verde in 2006 and 2008. The mean value of the particle depolariza-tion ratio at 532 nm was 30 ± 4.5 %; however, during strong dust episodes this ratio increased to 35 ± 5 %, which is also in agreement with the results of the SAMUM campaigns. The backscattering Ångström exponent during the dust episodes decreased to ∼ −0.7, while the extinction Ångström exponent , though negative, was greater than −0.2. Low values of BAE can likely be explained by an increase in the imaginary part of the dust refractive index at 355 nm compared to 532 nm. The dust extinction and backscattering coefficients at multiple wavelengths were inverted to the particle mi-crophysics using the regularization algorithm and the model of randomly oriented spheroids. The analysis performed has demonstrated that the spectral dependence of the imaginary part of the dust refractive index may significantly influence the inversion results and should be taken into account.

[1] This paper focuses on optical and microphysical properties of long-range transported biomass burning (BB) aerosols and their variation with atmospheric evolution (ageing), as observed by a multiwavelength Raman lidar, part of EARLINET (European Aerosol LIdar NETwork). Chemical analysis of the atmospheric aerosol was done using a colocated aerosol mass spectrometer (AMS). One relevant optical parameter for the ageing process is the Ångström exponent. In our study, we find that it decreases from 2 for fresh to 1.4-0.5 for aged smoke particles. The ratio of lidar (extinction-to-backscatter) ratios (LR 532 /LR 355 ) changes rapidly from values <1 for fresh to >1 for aged particles. The imaginary part of the refractive index is the most sensitive microphysical parameter. It decreases sharply from 0.05 to less than 0.01 for fresh and aged smoke particles, respectively. Singlescattering albedo (SSA) varies from 0.74 to 0.98 depending on aerosol age and source. The AMS was used to measure the marker ions of wood-burning particles during 2 days of measurements when the meteorological conditions favored the downward mixing of aerosols from lofted layers. Particle size distribution and particle effective radius from both AMS and lidar are similar, i.e., particle effective radii were approximately 0.27 mm for fresh BB aerosol particles. Microphysical aerosol properties from inversion of the lidar data agree with similar studies carried out in different regions on the globe. Our study shows that the Ångström exponent LR 532 /LR 355 and the imaginary part of the refractive index can be used to clearly distinguish between fresh and aged smoke particles.