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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 lidar 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 depolarization 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 microphysics 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.

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.

The multi-wavelength lidar technique was applied to the study of a smoke event near Washington, DC on 26–28 August 2013. Satellite observations combined with transport model predictions imply that the smoke plume originated mainly from Wyoming/Idaho forest fires and its transportation to Washington, DC took approximately 5 days. The NASA Goddard Space Flight Center (GSFC) multi-wavelength Mie–Raman lidar was used to measure the smoke particle intensive parameters such as extinction and backscatter Ångström exponents together with lidar ratios at 355 and 532 nm wavelengths. For interpretation of the observed vertical profiles of the backscatter Ångström exponents γβ at 355–532 and 532–1064 nm, numerical simulation was performed. The results indicate that, for fine-mode dominant aerosols, the Ångström exponents γβ(355–532) and γβ(532–1064) have essentially different dependence on the particle size and refractive index. Inversion of 3 β + 2 α lidar observations on 27–28 August provided vertical variation of the particle volume, effective radius and the real part of the refractive index through the planetary boundary layer (PBL) and the smoke layer. The particle effective radius decreased with height from approximately 0.27 μm inside the PBL to 0.15 μm in the smoke layer, which was situated above the PBL. Simultaneously the real part of the refractive index in the smoke layer increased to mR 1.5. The retrievals demonstrate also that the fine mode is predominant in the particle size distribution, and that the decrease of the effective radius with height is due to a shift of the fine mode toward smaller radii.

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.

The feasibility of using a multiwavelength Mie–Raman lidar based on a tripled Nd:YAG laser for profiling aerosol physical parameters in the planetary boundary layer (PBL) under varying conditions of relative humidity (RH) is studied. The lidar quantifies three aerosol backscattering and two extinction coefficients and from these optical data the particle parameters such as concentration, size, and complex refractive index are retrieved through inversion with regularization. The column-integrated, lidar-derived parameters are compared with results from the AERONET sun photometer. The lidar and sun photometer agree well in the characterization of the fine-mode parameters, however the lidar shows less sensitivity to coarse mode. The lidar results reveal a strong dependence of particle properties on RH. The height regions with enhanced RH are characterized by an increase of backscattering and extinction coefficient and a decrease in the Ångström exponent coinciding with an increase in the particle size. The hygroscopic growth factor calculated for a select case is consistent with previous literature results despite the lack of collocated radiosonde data. These results demonstrate the potential of the multiwavelength Raman lidar technique for the study of aerosol humidification process.

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 multi-wavelength 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 3β + 2α) 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.

Vertical profiles of the optical (extinction and backscatter coefficients, lidar ratio and Ångström exponent), microphysical (mean effective radius, mean refractive index, mean number concentration) and geometrical properties as well as the mass concentration of volcanic particles from the Eyjafjallajökull eruption were retrieved at selected heights over Athens, Greece, using multi-wavelength Raman lidar measurements performed during the period 21–24 April 2010. Aerosol Robotic Network (AERONET) particulate columnar measurements along with inversion schemes were initialized together with lidar observations to deliver the aforementioned products. The well-known FLEXPART (FLEXible PARTicle dispersion model) model used for volcanic dispersion simulations is initiated as well in order to estimate the horizontal and vertical distribution of volcanic particles. Compared with the lidar measurements within the planetary boundary layer over Athens, FLEXPART proved to be a useful tool for determining the state of mixing of ash with other, locally emitted aerosol types. The major findings presented in our work concern the identification of volcanic particles layers in the form of filaments after 7-day transport from the volcanic source (approximately 4000 km away from our site) from the surface and up to 10 km according to the lidar measurements. Mean hourly averaged lidar signals indicated that the layer thickness of volcanic particles ranged between 1.5 and 2.2 km. The corresponding aerosol optical depth was found to vary from 0.01 to 0.18 at 355 nm and from 0.02 up to 0.17 at 532 nm. Furthermore, the corresponding lidar ratios (S) ranged between 60 and 80 sr at 355 nm and 44 and 88 sr at 532 nm. The mean effective radius of the volcanic particles estimated by applying inversion scheme to the lidar data found to vary within the range 0.13–0.38 μm and the refractive index ranged from 1.39+0.009i to 1.48+0.006i. This high variability is most probably attributed to the mixing of aged volcanic particles with other aerosol types of local origin. Finally, the LIRIC (LIdar/Radiometer Inversion Code) lidar/sunphotometric combined inversion algorithm has been applied in order to retrieve particle concentrations. These have been compared with FLEXPART simulations of the vertical distribution of ash showing good agreement concerning not only the geometrical properties of the volcanic particles layers but also the particles mass concentration.

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 (ABR355/532) and Ångström-extinction-related (AER355/532) 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. PM10 concentrations levels, PM10 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.

This work deals with the applicability of the linear estimation technique (LE) to invert spectral measurements of aerosol optical depth (AOD) provided by AERONET CIMEL sun photometers. The inversion of particle properties using only direct-sun AODs allows the evaluation of parameters such as effective radius (reff) and columnar volume aerosol content (V) with significantly better temporal resolution than the operational AERONET algorithm which requires both direct sun and sky radiance measurements. Sensitivity studies performed demonstrate that the constraints on the range of the inversion are very important to minimize the uncertainties, and therefore estimates of reff can be obtained with uncertainties less than 30 % and of V with uncertainties below 40 %. The LE technique is applied to data acquired at five AERONET sites influenced by different aerosol types and the retrievals are compared with the results of the operational AERONET code. Good agreement between the two techniques is obtained when the fine mode predominates, while for coarse mode cases the LE results systematically underestimate both reff and V. The highest differences are found for cases where no mode predominates. To minimize these biases, correction functions are developed using the multi-year database of observations at selected sites, where the AERONET retrieval is used as the reference. The derived corrections are tested using data from 18 other AERONET stations offering a range of aerosol types. After correction, the LE retrievals provide better agreement with AERONET for all the sites considered. Finally, the LE approach developed here is applied to AERONET and star-photometry measurements in the city of Granada (Spain) to obtain day-to-night time evolution of columnar aerosol microphysical properties.

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.