In situ and remote sensing measurements are the two main approaches used for aerosol observations. The former involves measurements of particles using instruments at the survey points. The latter involves measuring aerosol properties from a distance without direct interaction with particles. Remote sensing methods can be categorized into active and passive depending on the kind of instrument used. Instruments belonging to the passive category measure the modified solar radiation after interactions with particles and terrestrial radiation. One of the most common instruments in this category, a sun/sky photometer, measures both direct and diffuse solar radiation. These data can be used in inversion algorithms to retrieve several column-integrated aerosol properties such as the aerosol optical depth (AOD), single scattering albedo (SSA), particle size distribution (SD), effective radius (reff), and complex refractive index (CRI, including real (RRI) and imaginary (IRI) parts of refractive index). Instruments belonging to the active category of remote sensing measurement scattered radiation emitted by themselves; one of the most well-regarded and widely used instrument in this category is lidar (light detection and ranging). Lidar instruments are used for profiling atmospheric variables such as the temperature, pressure, humidity, wind speed and its direction, and the amount of trace gases and aerosols. The main advantages of lidar measurements include high vertical resolution and applicability during nighttime and in cloudy environments. Current multi-wavelength lidar observations can provide comprehensive and quantitative information regarding aerosol properties .

Several methods, techniques, and algorithms can be used to obtain the optical and microphysical characteristics of aerosols. These methods generally use different sets of data. For instance, AERONET (AErosol RObotic NETwork) inversion code uses only sun/sky-photometer data . Similarly, the Raman technique and regularization algorithm use only lidar data . The LIRIC (LIdar-Radiometer Inversion Code) and GARRLiC (Generalized Aerosol Retrieval from Radiometer and Lidar Combined data) algorithms, in contrast, use both the sun/sky-photometer and lidar data . Because these methods use different datasets, they are applicable during different observational times. For instance, while the Raman technique is most suitable for nighttime observations, sun/sky photometers do not make measurements at that time. Further, the GARRLiC algorithm, which is included in the GRASP (Generalized Retrieval of Atmosphere and Surface Properties) inversion code , can separate the fine and coarse modes of aerosols, thus resulting in the retrieval of particle characteristics separately for both modes. While different methods retrieve different sets of aerosol characteristics, all of them are aimed at obtaining detailed results. The objective of our study is to discriminate and compare the common aerosol characteristics obtained through different methods.

Section 2 describes the observation sites where the measurements were carried out. This section also describes a new lidar system, called LILAS (LIlle Lidar AtmosphereS), which was used at the observation sites. Section 3 presents the methods considered in our study and discusses their potential, applicability, and the common aerosol properties that were considered for comparison. Section 4 presents three dust cases that were selected and analysed by using the algorithms described in Sect. 3. The main conclusions and perspectives are given in the last section.

The lidar system LILAS used in this work belongs to Laboratoire d'Optique Atmospherique (LOA). This system is operated at the campus of Lille University, France. The campus area is influenced mainly by urban and industrial pollutant emissions, marine aerosols, and mineral dust and aerosols from volcanic eruptions several times every year . Other remote sensing and in situ instruments are also operational at this site. Among them is a lunar photometer for observing AOD and Ångström exponent (α) values on clear nights within the half moon to full moon lunar phases. LOA is a permanent lidar site. However, for the study of Saharan dust over West Africa (SHADOW2 campaign), LILAS was moved to M'Bour city (Dakar site) in Senegal at the beginning of January 2015. The Dakar site is influenced by mineral dust during March–April and biomass burning during December–January. The two main objectives of the campaign were (i) to record the physical and chemical properties of aerosols over the regions impacted by considerable amounts of dust particles and (ii) to study the aerosol dynamics. Seven laboratories with 18 instruments took part in the campaign.

The LILAS system was assembled and setup in December 2013, and observations started in January 2014. The system is composed of a laser (Spectra-physics, INDI-40) emitting at wavelengths of 1064, 532, and 355 nm (100 mJ/20 Hz), a Newton telescope, a beam rotator, and a receiving module. The beam rotator can be used for near- or far-range observations by changing the overlap function. Several receiving modules were added in April 2014, and the system now consists of five elastic channels (355 and 532 nm both parallel and perpendicular for analog and photo-counting; 1064 nm for total analog) and three Raman channels (387 nm for analog and photo-counting; 408 and 608 nm for photo-counting). During the SHADOW2 campaign, the vibrational Raman channel at 608 nm was changed to a rotational channel at 530 nm. This rotational Raman channel showed a good and stable performance . The system can be remotely operated and is coupled with a radar (radio detection and ranging) for reasons such as automatic discontinuation control and airplane safety.

The Lille site became an observation station of the European Aerosol Research LIdar NETwork (EARLINET) in the summer of 2014. The main goal of the network is to provide a comprehensive, quantitative, and statistically significant database on aerosol distributions. The network has some special criteria for data quality assurance, such as a telecover test, a trigger delay, dark measurements, depolarization calibration, and regular check-ups of the Rayleigh fits . LILAS has passed all the EARLINET tests and check-ups except for depolarization calibration, which is currently in progress.

Depending on the lidar characteristics, different techniques can be used for obtaining optical and microphysical properties of aerosols. All the methods and algorithms that were used for data processing are introduced in this section.

Elastic-backscatter lidar is considered to be a classic form of lidar technology . This technology is based on the measurement of elastically scattered light in the backward direction. The common method that derives aerosol optical characteristics is the Klett method . This method is based on the relationship between the extinction and backscatter coefficients. The algorithm called BASIC based on the Klett method has been developed at LOA and is successfully implemented into routine for mono-wavelength lidar data. This algorithm retrieves an extinction coefficient profile (σaer(z)) following an iterative procedure based on a dichotomy where the lidar ratio (LR) can vary in the range from 10 to 140 sr. The procedure ends when the integral of the extinction profile is close to the AOD measured by a sun/sky photometer within ΔAOD = 0.01 accuracy.

The Raman lidar technique is a widely known technique in the lidar community for obtaining aerosol optical properties (σ, β, LR) . This technique is based on the scattering of incident lidar light with photon energy shifts due to vibrational or rotational modes of the molecules. It is mostly used at nighttime when the signal-to-noise ratio is the highest, owing to the absence of sunlight scattered into the field of view of the lidar. Assuming that the aerosol extinction coefficient depends on the wavelength through α, the former can be found calculated as σaer(λL,z)=ddzln⁡N(z)z2P(z)-σmol(λL,z)-σmol(λR,z)1+λLλRα, where P(z) is the power received at the Raman wavelength λR from distance z, N(z) is the molecule number density, σmol(λL,z) and σmol(λR,z) are the extinction coefficients due to absorption and Rayleigh scattering by atmospheric molecules for emitting lidar and Raman wavelengths, respectively, and α is the Ångström exponent. The aerosol backscatter coefficient can be calculated from the ratio of the elastic signal to Raman signal by using a coefficient determined at a reference point where no aerosol is expected.

A variety of methods can be used to retrieve aerosol microphysical properties using lidar data. They can be divided into three main groups . The methods belonging to the first group combine measurements from several instruments that provide enough information to retrieve aerosol microphysical properties. For such methods, the collocation of measurements by different instruments in space and time is necessary. The LIRIC algorithm belongs to this group; it successfully retrieves height-resolved aerosol optical and microphysical properties separately for fine and coarse modes . The algorithm uses AERONET inversion products such as column volume concentration, volume-specific backscatter, and extinction coefficients as a priori information . The specific products include backscatter (β), extinction (σ), and volume concentration (V) profiles, Ångström exponent (α) values, and LR and depolarization (δ) ratios. A deeper synergy between the lidar and sun/sky-photometer data is achieved in the GARRLiC algorithm developed at LOA . GARRLiC inverts the coincident lidar and sun/sky-photometer radiometric data simultaneously. The other marked distinction between GARRLiC and LIRIC is the inversion of two distinct aerosol modes, which makes it possible to retrieve aerosol optical and microphysical properties independently for both the fine and coarse modes. Such differences in the algorithms can influence the results obtained by the two systems. The GARRLiC method is based on the Dubovik inversion code , which has been previously used for processing AERONET data. The synergistic retrieval is expected to improves aerosol retrieval properties; the lidar observations are expected to improve the observations of the columnar properties of aerosols in the backscattering direction, and sun/sky photometers provide information on aerosol properties, such as their amount or type, required for lidar retrievals without making assumptions based on climatological data.

GARRLIC has been designed to provide two independent vertical concentration profiles for the fine and coarse modes of aerosols, since in most cases, aerosols are believed to consist of two modes. However, it works for single mode inversions as well. In such cases, a single value for the total amount of particles is retrieved. The algorithm is quite flexible in this regard; single or double mode inversion can be chosen by the user. Further, single- or multi-wavelength lidar data can be used. In the case of multi-wavelength lidar data, aerosol properties can be retrieved for fine and coarse modes separately or together for the total amount of particles. In the case of single-wavelength lidar data, the aerosol properties can be retrieved only for the total amount of aerosols. Depending on the different configurations of single or double mode inversion employed and the use of single- or multi-wavelength lidar data, different sets of aerosol parameters can be retrieved (see Fig. ). Spectral information from multiple wavelengths is used to distinguish the contribution of fine and coarse aerosol modes. It should be noted that aerosol events characterized mainly by one type of aerosols or a mixture of particles similar in size (aerosol types are not distinguished inside the mode of particles) should be retrieved by using the configuration of single mode inversion.

As for the second group of methods, optical properties (β and σ profiles) are calculated using Mie theory and are compared with the results obtained by using the Raman technique . In these methods, aerosol microphysical properties such as SD and CRI are assumed as a priori information. Such methods are used in case of atmospheric layers with single, well-known type of particles. For instance, such methods can characterize the particles of polar stratospheric clouds, volcanic ejecta, and some stratospheric particles. However, owing to the presence of a variety of particles and rapid changes in the atmospheric conditions, such methods are not applicable to the troposphere.

The third group consists of mathematical approaches that use β and σ coefficient profiles at multiple wavelengths (only lidar measurements). Such methods were developed from the methods of the second group, but they require a lower number of a priori parameters . The algorithm called inversion with regularization developed by has also been considered in this work. A simplified set of lidar data (three backscatter (355, 532, and 1064 nm) and two extinction (355 and 532 nm) coefficients – the so-called 3β+2σ dataset) allows the retrieval of the main aerosol microphysical properties . Aerosol optical properties that are required for the regularization algorithm can be derived using the Raman technique. The main aerosol microphysical products of the regularization algorithm are the CRI, reff, number, surface area, and volume concentrations .

These groups of retrieval methods use different types of measurements and, also, different amounts of information. For instance, while regularization uses the 3β+2σ set of optical data, AERONET uses up to ∼ 30 measurements (direct and diffuse almucantar measurements) at each wavelength. Hence, it is important to compare the particle properties retrieved with these methods for these different groups. If different algorithms retrieve similar aerosol properties, it will mean that they are in agreement and can complement each other for data processing during long-term day–night observations.

Aerosol characteristics that are common to LIRIC, GARRLiC, and regularization algorithms are σ, LR, CRI, V, and reff. The challenging issue here is that no perfectly coincident measurements exist that can be used by these algorithms. The standard Raman technique preferably uses lidar measurements during nighttime, while the sun/sky photometers require sunlight. Consequently, for a comparison of the retrieved aerosol properties by using the GARRLiC/LIRIC and regularization algorithms, early morning or late evening data under stable atmospheric conditions should be selected. Three events fulfilling these requirements were selected and analysed.

Several dust events were selected from the LILAS measurements over the Lille and Dakar sites. These days had moderate (AOD ≃ 0.5 at 440 nm) to high (AOD ≃ 1.5 at 440 nm) aerosol loads. Back trajectories and the NMMB/BSC-Dust model (Non-hydrostatic Multiscale/Barcelona Supercomputing Centre Dust model confirmed the origin of mineral dust from Sahara and showed the source locations. In the case of local dust events, the back-trajectory analysis was not used. More details and results of the comparison of each event are presented below.

The AERONET products are presented herein for comparison. As it is used as a priori information for the LIRIC algorithm, the LRs retrieved by LIRIC are presented along with the AERONET characteristics (marked by ** in Tables  and ). Mass concentration profiles were obtained simply by multiplying the volume concentration profiles, V, with the mass density of fine and coarse mode particles. The densities of the fine and coarse modes are 1.5 and 2.6 g cm-3, respectively . This density for the coarse mode is also considered in the NMMB/BSC-Dust model.

The GARRLiC and LIRIC algorithms produce uncertainties with the retrieved aerosol properties. For the GARRLiC algorithm, systematic and random errors are presented. For the LIRIC algorithm, only the dispersion of aerosol volume concentration profiles is presented. This work presents only the uncertainties regarding the directly retrieved aerosol properties. Uncertainties on the derived aerosol properties (σ, LR, SSA profiles) are not presented due to their high values as derived by GARRLiC (rough estimations were about 100 % and more). The uncertainties in the volume concentration profiles retrieved using the regularization algorithm are assumed to be about 20 % .

As this work mainly deals with mineral dust sometimes mixed with marine aerosol particles, it will be useful to consider the particle properties obtained from previous studies. According to , , , , and , the typical values of reff for desert dust vary within the range of 1.2–2.4 µm, and reff for the coarse mode of sea salt is close to 2.7 µm . The SSA for dust particles increases from 0.80 to 0.99 in the ultraviolet–near-infrared range . The SSA for marine aerosols is high, at ∼ 0.98, and the value remains stable at all wavelengths. The RRI varies from 1.5 to 1.6 for dust particles and is close to 1.36 for marine particles. The IRI decreases from 0.02 to 0.001 in the ultraviolet–near-infrared range for dust particles and is close to 0.001 for marine particles. For Saharan dust, the LR varies within the range of 50–80 sr at a wavelength of 532 nm, and it is significantly lower, at 20–35 sr, for marine particles . The depolarization ratio is high, being close to 30–35 % for dust particles, whereas marine particles have a significantly lower δ, i.e. close to 5 % .

As mentioned previously, the main objective of this article is to compare aerosol properties retrieved by different algorithms. This helps to know to what extent these algorithms can be used in a complementary way for long-term day–night aerosol observations and data processing.

Three dust events were selected from LILAS measurements. The first event over Lille on 30 March 2014 was characterized by transported mineral dust particles from the Saharan region. Three different layers of aerosols were observed: (i) assumed urban particles up to 2.5 km, (ii) dust layer in the altitude range of 2.5 to 6 km, and (iii) cirrus clouds with a negligible AOD impact at heights of 11 to 12 km.

The second and third events over Dakar were characterized by a layer consisting of a dust and marine (small contribution) aerosol mixture during the daytime and only dust particles during the nighttime. In both cases, AOD values decrease over the day- to nighttime measurement time frame, and, therefore, it was not possible to compare the day- and nighttime σ. GARRLiC, LIRIC, and Raman daytime σ profiles are in agreement on 29 March. However, σ profiles retrieved by the same algorithms on 10 April differ. The latter was a more complex event with different types of particles in the same size range. Development, such as introducing depolarization profile into the GARRLiC algorithm, should enhance the algorithm and make it possible to distinguish aerosols with different shapes inside one mode. In both dust cases, reff were found to be higher during daytime in comparison with the nighttime cases. Raman LRs increased over the day- to nighttime measurement time frame, which could be caused by the absent of marine particles at night. However, depolarization ratios were always indicative of dust particles. GARRLiC LR values were always lower than the ones obtained by LIRIC and Raman. Also, GARRLiC sphericity was always higher than the one obtained by AERONET. Also, the presence of marine particles should decrease RRI values during the day, but daytime RRI values were higher in comparison with the nighttime ones. However, daytime IRI values were lower in comparison with the ones obtained at night, which agrees with the presence of marine particles, which absorb less than dust particles. These features indicate the challenges in description of optical properties of non-spherical particles in backscattering, on top of possible inconsistencies between the retrieval algorithms used herein. The studies by , , and suggest that the difficulties with reproduction of the observations relate to inaccuracies in the spheroidal model in reproduction of scattering properties in backwards direction. However, those studies are focused on observations of desert dust particle depolarization that were not used in GARRLiC and LIRIC analysis of this study. At the same time, it is worth mentioning that recent research by has reported very encouraging agreement of spheroidal model with dust observations. More events should be analysed in order to distinguish the inconsistencies between the algorithms. The second phase of the SHADOW2 campaign will be taking place in December–January 2016.

In future studies, it will be interesting to select morning measurements excluding see-breeze and marine particles. GARRLiC development (for instance, by incorporating the Raman technique and/or depolarization profile into the code) will make it possible to distinguish vertically resolved aerosol optical properties more accurately, i.e. improved extinction and volume concentration profiles. After such improvements, similar studies should be carried out and, again, the algorithm results should be compared to determine whether they are able to complement each other for long-term day–night measurements.

AERONET data for Dakar and Lille instrumentation sites are available at http://aeronet.gsfc.nasa.gov/. Lidar data available at http://www-loa.univ-lille1.fr/index.php/observation/lidar.html.