Vertical assessment of the mineral dust optical and
microphysical properties as retrieved from the synergy
between polarized micro-pulse lidar and sun/sky
photometer observations using GRASP code

O. Dubovik, María-Ángeles López-Cayuela, Marcos Herreras-Giralda, Carmen Córdoba-Jabonero, Anton Lopatin, Juan Luis Guerrero-Rascado

<figure><img src="image_1.png" /></figure>

To cite this version:

O. Dubovik, María-Ángeles López-Cayuela, Marcos Herreras-Giralda, Carmen Córdoba-Jabonero, Anton Lopatin, et al.. Vertical assessment of the mineral dust optical and microphysical properties as retrieved from the synergy between polarized micro-pulse lidar and sun/sky photometer observations using GRASP code. Atmospheric Research, 2021, 264, pp.105818. 10.1016/j.atmosres.2021.105818. insu-03435404

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Distributed under a Creative Commons Attribution 4.0 International License
Vertical assessment of the mineral dust optical and microphysical properties as retrieved
from the synergy between polarized Micro-Pulse Lidar and Sun/sky photometer
observations using GRASP code

María-Ángeles López-Cayuela<fnref n="1" />, Marcos Herreras-Giralda2,3, Carmen Córdoba-Jabonero1,*, Anton
Lopatin<fnref n="2" />, Oleg Dubovik3 and Juan-Luis Guerrero-Rascado4,5

**Abstract**

The potential of the synergetic use of both polarized Micro-Pulse Lidar (P-MPL) and Sun/sky photometer observations by using the GRASP (Generalized Retrieval of Atmosphere and Surface Properties) code for retrieving dust properties has been analysed in this work. Both the columnar and height-resolved variables have been evaluated in comparison, respectively, with AERONET data and vertical P-MPL-derived profiles of the dust optical and microphysical properties over a mid-latitude site. The linear regression analysis together with the mean fractional bias values and relative differences between datasets have been used as the statistical proxies for assessing the degree of agreement by examining 24 selected dust cases. Regarding columnar variables, the microphysical properties (both the particle volume concentration and effective radius) presented a high confidence level between GRASP and AERONET retrievals by taking into account all the proxies in overall. In addition, the single scattering albedo and the real refractive index presented a good confidence level at all the wavelengths, as well, unlike the imaginary refractive index, which was confident at 440 nm only. By analysing the height-resolved properties of the total particle backscatter coefficient and the total volume concentration, the degree of agreement shows a high confidence between GRASP retrievals and P-MPL-derived variables, which were retrieved by using an alternative, well-validated, polarization-based methodology. Indeed, these results can be essential for application with no-polarized systems (e.g., ceilometers, lidars ...). In overall, the synergy between P-MPL and Sun/sky photometer measurements regarding the usual co-location of both MPLNET and AERONET networks in combination with GRASP code represent an improved approach to derive the height-resolved optical and microphysical properties for mineral dust particles with a high degree of confidence.

**Keywords:** AERONET; dust properties; elastic lidar; GRASP; MPLNET; Sun/sky photometer.

<footnote n="1">¹Instituto Nacional de Técnica Aeroespacial (INTA), Atmospheric Research and Instrumentation Branch, Torrejón de Ardoz, 28850-Madrid, Spain</footnote>

<footnote n="2">²GRASP-SAS, Remote sensing developments, Villeneuve d'Ascq, France</footnote>

<footnote n="3">³Laboratoire d'Optique Atmosphérique, CNRS/Université Lille, Villeneuve d'Ascq, France</footnote>

<footnote n="4">⁴University of Granada (UGR), Applied Physics Department, 18071-Granada, Spain</footnote>

<footnote n="5">⁵Andalusian Institute for Earth System Research (IISTA-CEAMA), 18006-Granada, Spain</footnote>

<footnote>*Corresponding author: Carmen Córdoba-Jabonero (cordobajc@inta.es)</footnote>
# 1. Introduction

Atmospheric aerosols play an important role in the Earth's radiative budget and climate forcing due to their both direct and indirect radiative effects (Boucher et al., 2013). On one hand, the aerosol optical and microphysical properties can directly modify the Earth-atmosphere radiative forcing sign, based on the scattering and absorption of the incoming solar and outgoing thermal radiation. On the other hand, aerosol particles can act as cloud condensation nuclei (CCN) and ice nucleating particles (INP) (DeMott et al., 2003; Karydis et al., 2011) and, thus, can indirectly modify the cloudy media properties. For both effects, the improvement on the knowledge of the aerosol vertical distribution is crucial. Indeed, an advanced vertical inversion of the dust properties is important when they are used for determining the aerosol radiative impact. Although, in general terms, aerosol particles mainly produce negative radiative forcing (net cooling effect) due to the predominance of the scattering of solar radiation in all directions, the location of certain particle types at given vertical altitudes can cause perturbations. For instance, aerosols are able to heat the atmospheric regions in which they are present when absorbing solar radiation, in spite of the possible net cooling effect for the atmospheric column (Pilewskie, 2007). As demonstrated by Gobbi et al. (2000), dust particles can modify the atmospheric thermal structure by solar radiation absorption. Also, Perrone and Bergamo (2011) and Perrone et al. (2012) evaluated the impact of mineral dust vertical distribution on the aerosol direct radiative effects and heating rates using ground-based lidar, whereas Granados-Muñoz et al. (2019) applied a combination of satellite platforms, including CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation), for that purpose. In addition, the role of dust fine particles in the dust direct radiative effect can be relevant, as revealed from lidar observations, even when dust coarse particles are predominant as usually under dusty conditions (Córdoba-Jabonero et al., 2021b).

During the 90's the worldwide NASA Aerosol Robotic NETwork (AERONET) was established with the aim of achieving a comprehension of the aerosol distribution on global scale (Holben et al., 1998). This network, by using two kind of photometric measurements, i.e. direct-Sun irradiances and the angular distribution of diffuse sky radiation, and in combination with state-of-the-art retrieval algorithms (Dubovik and King, 2000; Dubovik et al., 2006), provides some column-integrated aerosol optical and microphysical properties that are a key in climate, air quality and health studies, such as Aerosol Optical Depth (AOD), Ångstrom exponent (AE), particle size distribution (PSD), refractive index, single scattering albedo, asymmetry factor and phase function, among others.

Despite its clear advantages regarding spatial coverage, AERONET measurements do not provide vertically-resolved aerosol properties. However, this drawback might be overcome in combination with lidar/ceilometer measurements. Currently, several networks with different level of developments, spatial/temporal coverage, and scientific objectives are deployed covering most of our planet, such as EARLINET (European Aerosol Research Lidar NETwork) (Pappalardo et al., 2014) and E-PROFILE (EUMETNET Profiling Programme) in Europe, LALINET (Latin-American Lidar NETwork) in South America (Guerrero-Rascado et al., 2016; Antuña-Marrero et al., 2017), ADNET (Asian Dust NETwork) in Asia (Murayama et al., 2001), and NASA MPLNET (Micro-Pulse Lidar NETwork) (Welton et al., 2001) and NDACC (Network for the Detection of Atmospheric Composition Change) (De Mazière et al., 2018) world-widely spread, among others. In this work, co-located MPLNET and AERONET aerosol observations have been used. The elastic polarized Micro-Pulse Lidar (P-MPL) is the standard system in operation within MPLNET, which is designed to obtain the vertical structure of aerosols and clouds. Data are collected in a continuous mode (24/7) for long-term observations around the world.
Due to the large number of AERONET/MPLNET co-located stations (21 sites at present), a more
complete assessment of aerosol properties can be achieved, since both columnar-integrated and
vertically-resolved measurements can be combined by using the Generalized Retrieval of Atmosphere
and Surface Properties (GRASP) code (Dubovik et al., 2014) in order to provide a significant
improvement in retrieving advanced aerosol products. The GRASP code, using the heritage of
AERONET inversion scheme (Dubovik and King, 2000; Dubovik et al., 2006), is a versatile and
open-source inversion algorithm capable to retrieve aerosol optical and microphysical properties by
combining active and passive remote sensing techniques (Lopatin et al., 2013). Hence, this code has
been applied, among others, to satellites imagery (e.g., Milinevsky et al., 2014; Kokhanovsky et al.,
2015; Chen et al., 2019; Sayer et al., 2018; Remer et al., 2019; Tan et al., 2019; Li et al., 2019, 2020; Wei
et al., 2020), in situ data (Espinosa et al., 2017, 2019; Schuster et al., 2019), different combinations of
Sun/sky photometer: only spectral AODs (Torres et al., 2017), spectral AODs, sky radiances and
polarized sky radiances (Fedarenka et al., 2016), spectral AODs and sky cameras images (Román et al.,
2017), spectral AODs, sky radiances and lidar/ceilometer signals (e.g., Bovchaliuk et al., 2016;
Benavent-Oltra et al., 2017; Tsekeri et al., 2017; Román et al., 2018; Herreras et al., 2019; Hu et al.,
2019; Titos et al., 2019; Molero et al., 2020), spectral AODs and Raman lidar signals (e.g.,
Benavent-Oltra et al., 2019; Soupiona et al., 2019) and spectral AODs, sky radiances and airborne
backscatter observations (Lopatin et al., 2020). To our knowledge, this is the first time that GRASP code
is used together with the combination of AERONET Sun/sky photometer and MPLNET lidar
observations of Saharan dust at mid-latitudes using a particular lidar-based methodology as reference
for GRASP assessment.

The aim of this study is to analyse the potential of the GRASP products, as obtained from the synergy
between AERONET Sun/sky photometer and elastic P-MPL lidar observations, for deriving columnar
and vertically-resolved aerosol properties. For that purpose, particular mineral dust cases as observed at
the AERONET/MPLNET El Arenosillo site (Huelva, Spain, 37.1°N 6.7°W) along 2018 have been
selected regarding its relatively close proximity to the Saharan dust sources. Hence, a total of 24 cases
under dusty conditions with simultaneous AERONET and MPLNET observations have been analysed,
fulfilling specific GRASP high-quality criteria.

A description of the measurement site, the instrumentation used, the alternative methodology for
comparison purposes, and the GRASP model in addition to the comparative analysis applied for
evaluating the performance of GRASP is shown in **Section 2**. **Section 3** shows the results as obtained
from the comparison between GRASP-retrieved columnar and height-resolved products and,
respectively, AERONET data and P-MPL-derived variables in order to determine the degree of
confidence. Main conclusions are introduced in **Section 4**.

**2. Materials and Methods**

**2.1. Measurement site and instrumentation**

Aerosol observations were performed at the El Arenosillo station, which is located near Huelva (Spain) at the Southwestern Iberian Peninsula (ARN/Huelva, 37.1°N 6.7°W, 59 m a.s.l.), in a rural protected environment nearby the Doñana National Park and less than 1 km from the Atlantic coastline. ARN/Huelva is managed by the Spanish Institute for Aerospace Technology (Instituto Nacional de Técnica Aeroespacial, INTA), and devoted to aerosol-cloud and gases monitoring and research, using
both remote sensing and in-situ instrumentation, together with solar radiation observations. ARN/Huelva is both a NASA/AERONET and NASA/MPLNET site.

The aerosol background at the ARN/Huelva station is mostly from marine and rural origin, and additionally, due to its proximity to the Sahara desert region, ARN/Huelva also has an exceptional situation for first dust detection once crossing over the Southwestern Iberian Peninsula (Córdoba-Jabonero et al., 2011). Hence, Saharan dust air masses arriving at ARN/Huelva present a relevant annual recurrence, being mostly frequent in February/March and summertime (i.e., Toledano et al., 2007; Córdoba-Jabonero et al., 2011; Sorribas et al., 2017). In fact, ARN/Huelva is a representative rural/coastal background site in the Iberian Peninsula, where Saharan dust intrusions represent a significant contribution.

### 2.1.1. AERONET Sun/sky/lunar photometer

Daytime columnar aerosol properties were obtained from the AERONET multiband Sun/sky/lunar photometer (Cimel CE318T, Cimel Electronique) sited at the ARN/Huelva station. The CE318T photometer performs both direct-Sun and sky radiance measurements at different wavelengths.

Direct-Sun irradiance measurements are used to calculate the AOD at eight wavelengths (340, 380, 440, 500, 675, 870, 1020 and 1640 nm), as well as the AE parameter at several wavelength pairs. The AE, which describes the spectral dependency of the AOD, is particularly obtained in this study for the pair of 440 and 675nm ($AE^{440/675}$), regarding the P-MPL laser 532-nm wavelength. Whereas the AOD is related the aerosol load present in the atmospheric column, the AE is an indicator of the predominant particle size; for instance, small values ($AE < 0.60$ at the 440-870 nm wavelength pair) suggest a predominance of coarse particles (e.g., Dubovik et al., 2002). In addition, the spectral fine-mode-fraction (FMF), which is defined as the ratio of the fine-mode optical depth to the total AOD (O'Neill et al., 2001, 2003), is also an AERONET-derived parameter; in particular, the FMF at 500 nm ($FMF^{500}$) is used in this work.

Both the direct-Sun irradiance and the sky radiance measurements are combined to retrieve aerosol optical and microphysical properties such as the single scattering albedo (SSA), the real and imaginary refractive indices (RRI and IRI, respectively), the particle volume size distribution ($VSD$, $\mu m^3 \mu m^{-2}$), the total volume concentration ($VC$, $\mu m^3 \mu m^{-2}$), the total effective radius ($R_{eff}$), among others (Dubovik et al., 2006). In this study, AERONET V3 L2.0 (cloud-screening and quality-assured) data are used for the selected dusty cases. Uncertainties of the AERONET inversion products used in this work are shown in Table 1.

In this work, dusty cases as observed at ARN/Huelva during 2018 were preliminary selected on the basis of specific threshold values for the AERONET AOD at 500 nm ($AOD^{500}$), $AE^{440/675}$ and $FMF^{500}$. Thus, a case at a given time is classified as 'dusty' if, simultaneously fulfilled the following threshold criteria: $AOD^{500} > 0.20$ and $AE^{440/675} < 0.50$ (as adopted from Córdoba-Jabonero et al., 2011) in addition to $FMF^{500} < 0.40$ for a more conservative selection of the dusty conditions. Hence, 24 dust cases along 13 days in 2018 were found fulfilling those assumed dusty criteria.

<table><caption>**Table 1.** Uncertainties of the AERONET inversion products used in this work.</caption><thead><tr><td>AERONET product</td><td>Uncertainty</td><td>References</td></tr></thead><tbody><tr><td>AOD</td><td></td><td></td></tr></tbody></table>
<table><tr><td>(&gt; 400 nm)</td><td>±0.01</td><td>Holben et al. (1998)</td></tr><tr><td>(&lt; 400 nm)</td><td>±0.02</td><td>Eck et al. (1999)</td></tr><tr><td>AE<sup>440/675</sup></td><td>10%</td><td>Wagner and Silva (2008)</td></tr><tr><td>SSA (#, *)</td><td>±0.03</td><td>Dubovik et al. (2000)</td></tr><tr><td>RRI (#, *)</td><td>±0.04</td><td>Dubovik et al. (2000)</td></tr><tr><td>IRI (#, *)</td><td>30-50%</td><td>Dubovik et al. (2000)</td></tr><tr><td>VSD (**):</td><td></td><td></td></tr><tr><td>0.1 &lt; R &lt; 7</td><td>10-35%</td><td>Dubovik et al. (2000)</td></tr><tr><td>R &lt; 0.1 and R &gt; 7</td><td>35%-100%</td><td></td></tr></table>

(#) AERONET V3 L2.0 SSA, RRI and IRI values are only available for AOD<sup>440</sup> > 0.4.

(*) These uncertainties are for AOD<sup>440</sup> ≥ 0.50.

(**) R is the particle radius (in µm).

### 2.1.2. MPLNET polarized Micro Pulse Lidar

A polarized Micro-Pulse Lidar (P-MPL, v. 4B, Droplet Measurements Technologies, formerly Sigma Space Corp.) was deployed in October 2016 at ARN/Huelva for vertical monitoring of aerosols and clouds. P-MPL routine measurements follow the MPLNET requirements of 1-min integrating time and 75-m (or 15-m) vertical resolution (Welton et al., 2001). The P-MPL system is an elastic lidar with a highly-pulsed (2500 Hz) and low-energy (5-7 µJ) Nd:YVO<sub>4</sub> laser at 532 nm, operating in a full-time continuous mode (24/7). The telescope is 5° tilted off the zenith to avoid normal reflection from ice clouds. Depolarization measurements are also acquired from the co- and cross-signal detection channels. Profiles of both the P-MPL range-corrected signal (RCS) and the volume linear depolarization ratio (VLDR) are the primary lidar data used in this work. A more complete description of the data correction and calibration processing (overlap, RCS, VLDR) can be found in several works (Campbell et al., 2002; Welton and Campbell, 2002; Flynn et al., 2007; Córdoba-Jabonero et al., 2018, 2021a).

For comparison with the GRASP-derived vertical optical products, the profiles of the total particle backscatter coefficient ($\beta_p(z)$, Mm<sup>-1</sup> sr<sup>-1</sup>, where z indicates the height dependence) were obtained by using the AERONET AOD-constrained Klett-Fernald (KF) iterative inversion algorithm (Fernald, 1984; Klett, 1985). This procedure is based on the convergence of the vertically-integrated extinction coefficient, i.e., $\tau = \sum_z [LR \beta_p(z) \Delta z]$ (LR is the particle extinction-to-backscatter ratio or lidar ratio, and $\Delta z$ is the vertical resolution of the lidar profiles), to the AERONET AOD (in particular, AOD<sup>500</sup>, if available), tuning the LR value. Hence, an effective particle lidar ratio, $LR^{eff}$, is also determined, that is, $\tau(LR^{eff}) = AOD^{500}$ must be fulfilled within a certain convergence degree (a convergence factor of 1% is applied in this study). The relative uncertainties found for $\beta_p$ and $LR^{eff}$ are, respectively, of 10-15% and 5-10% (see Córdoba-Jabonero et al., 2018, for more details).

In addition, the height-resolved total volume concentration ($VC(z)$, µm<sup>3</sup> cm<sup>-3</sup>) is also calculated from its relationship with the total extinction coefficient ($\alpha_p(z)$, Mm<sup>-1</sup>) by using specific extinction-to-volume conversion factors ($f_v$, 10<sup>-12</sup> Mm). First, $\alpha_p(z)$ is obtained by using the synergy of the P-MPL measurements with the POLIPHON (Polarization Lidar Photometer Networking) algorithm, as described in Córdoba-Jabonero et al. (2018, 2021b), for dusty mixtures. POLIPHON is a well-validated method based on the lidar depolarization measurements in order to discriminate the optical properties for the individual particle components of aerosol mixtures, taking into account the specific particle
linear depolarization ratio (PLDR) for each of those components (for instance, see Mamouri and Ansmann, 2017, and references therein). Hence, in this work, once $\beta_p(z)$ is separated into its dust (coarse, Dc, and fine, Df) and non-dust (ND) components ($\beta_i(z)$, being $i$ = Dc, Df, and ND), their particular vertical extinction coefficients ($\sigma_i(z)$) are determined as follows

$$ \alpha_i(z) = LR^i \beta_i(z) \qquad (1) $$

where $LR^i$ are typical lidar ratios for each component $i$; in this study, $LR^{Dc} = LR^{Df} = 55$ sr, and $LR^{ND} = 25$ sr are assumed at 532 nm; hence, the total extinction can be calculated as follows

$$ \alpha_p(z) = \sum_i \alpha_i(z). \qquad (2) $$

Additionally, $VC(z)$ is obtained from the following expression

$$ VC(z) = \sum_i f_v^i \alpha_i(z), \qquad (3) $$

where $f_v^i$ are the specific volume conversion factors for each component; in particular, $f_v^{Dc} = 0.83 \times 10^{-12}$ Mm, $f_v^{Df} = 0.23 \times 10^{-12}$ Mm and $f_v^{ND} = 0.30 \times 10^{-12}$ Mm are used in this study, corresponding to those AERONET-derived values for dust from the North African region (Ansmann et al., 2019). Moreover, the relationship between $\alpha_p(z)$ and $VC(z)$ can be then expressed as

$$ VC(z) = f_v^{eff} \alpha_p(z), \qquad (4) $$

being $f_v^{eff}$ the effective (column-integrated) volume conversion factor, which can be calculated from the expression

$$ f_v^{eff} = \frac{v}{\tau}, \qquad (5) $$

where $v$ and $\tau$ are, respectively, the AERONET total volume concentration and total extinction as obtained for each particular dust case. The relative uncertainties found for $\alpha_p$ (and $\alpha^i$) and $VC$ are in the range of 15-30% (Córdoba-Jabonero et al., 2018). Therefore, the GRASP-retrieved height-resolved total volume concentrations ($VC^{GRASP}(z)$) can be analysed in comparison with the lidar-derived total volume concentration profiles ($VC^{lidar}(z)$), which are obtained from either Eq. 3 or Eq. 4.

## 2.2. GRASP retrieval

The GRASP code relies on the heritage of AERONET inversion scheme (Dubovik and King, 2000; Dubovik et al., 2006). Although it is based on a similar philosophy than the LIidar-Radiometer Inversion Code (LIRIC; Chaikovsky et al., 2016), GRASP goes one step further thanks to the incorporation of the Generalized Aerosol Retrieval from Radiometer and Lidar scheme (GARRLiC; Lopatin et al., 2013; Bovchaliuk et al., 2016; Benavent-Oltra et al., 2017) into its code. This allows to derive, simultaneously, the vertical aerosol optical and microphysical properties together with their columnar values by using coincident lidar and Sun/sky photometer measurements. It is worth to highlight that the aerosol properties as retrieved by GRASP are value-added in comparison with those obtained from AERONET alone, since GRASP introduces the possibility to use lidar measurements together with AERONET data in order to additionally derive those properties (or part of them) with vertical resolution.
In this work, the GRASP<sub>pac</sub> method (Román et al., 2018) has been applied with different data inputs to retrieve both the column-integrated and vertically-resolved variables. In general, the GRASP's versatility allows for separating two aerosol modes in the retrieval when sufficient spectral information is provided. However, as a single spectral P-MPL measurement is only available (the P-MPL system operates at 532 nm), the one-mode aerosol retrieval is selected in GRASP for reducing the uncertainties, despite no separation in particle modes is possible. Therefore, the unique height-resolved GRASP-retrieved products are the total backscatter coefficient $β_p(z)$ (and the total extinction, $α_p(z)$) and the total volume concentration $VC(z)$. GRASP also provides an estimation of the systematic and random errors for both the aerosol columnar and vertical properties. **Table 2** shows both the input and output variables regarding the GRASP retrieval by using the synergy between CE-318T and P-MPL measurements.

AERONET V3 L2.0 data are introduced in the GRASP<sub>pac</sub> scheme as input variables. These variables are both the AOD and the sky radiance measurements (almucantar sequence) measurements at 440, 675, 870 and 1020 nm (see Sect. 2.1.1, and Table 2). In order to ensure that the input data are suitable to derive quality-assured aerosol retrievals, similarly to AERONET L2.0 data lidar cloud-contaminated observations were also previously discarded and some quality control criteria were applied. A detailed explanation of these criteria can be found in Román et al. (2018). In summary, the number of the sky radiance measurements at each wavelength must be higher or, at least, equal to 10; at each wavelength there must be one radiance value at least at four ranges as identified by the scattering angles: 3.2° - 6°, 6° - 30°, 30° - 80° and ≥ 80° (Holben et al., 2006). Moreover, for reducing the bias produced by errors in the calibration coefficients, the sky radiance measurements are chosen if the solar zenith angle SZA > 40° (Torres et al., 2017). The closest AOD values, also used in the retrieval, must be within ±15 min of the sky radiance measurements for the four wavelengths.

<table><caption>**Table 2.** GRASP retrieval by using both AERONET Sun/sky photometer (CE-318T) and MPLNET lidar (P-MPL) measurements: Specific (input and output) columnar and vertical variables used in this work.</caption><thead><tr><th colspan="2">Inputs</th></tr><tr><th>AERONET column-integrated data</th><th>MPLNET vertical profiles</th></tr></thead><tbody><tr><td>Sky radiances<sup>a</sup></td><td>Range-corrected signal at 532 nm</td></tr><tr><td>AOD(λ)<sup>b</sup></td><td>RCS(z)<sup>c</sup></td></tr></tbody><thead><tr><th colspan="2">Outputs</th></tr></thead><tbody><tr><td>Single scattering albedo (SSA(λ))<sup>d</sup></td><td></td></tr><tr><td>Real and imaginary refractive indexes<br>(RRI(λ), IRI(λ))<sup>d</sup></td><td></td></tr><tr><td>Particle volume size distribution (VSD)</td><td></td></tr><tr><td>Total volume concentration (VC<sup>c</sup>)<sup>e</sup></td><td>Total volume concentration (VC(z))</td></tr><tr><td>Total effective radius (R<sub>eff</sub>)</td><td></td></tr><tr><td>Lidar ratio (LR(λ)<sup>c</sup>)<sup>d, e</sup></td><td>Total backscatter coefficient (β<sub>p</sub>(z, λ))<sup>d, f</sup></td></tr><tr><td>AOD(λ)<sup>d</sup></td><td>Total extinction coefficient (σ<sub>p</sub>(z, λ))<sup>d, f</sup></td></tr></tbody></table>

<footnote>a λ = 440, 675, 870 and 1020 nm.</footnote>
b $\lambda$ = 440, 500, 675, 870 and 1020 nm.

c z denotes the height-dependence.

d $\lambda$ = 440, 532, 675, 870 and 1020 nm.

e c denotes columnar-integrated value.

f For comparison purposes, $\lambda$ = 532 nm is that used.

By following the GRASP<sub>pac</sub> scheme, for each almucantar radiance dataset, the successive P-MPL 1-min
RCS profiles (cloud-contaminated profiles are discarded) are averaged in a ±15-min window centred on
the almucantar-recorded time. For reducing the noise of the profiles, a minimum of 15 cloud-free RCS
profiles is imposed for calculating the average and, consequently, running GRASP. Besides, these
time-averaged RCS profiles must be normalized, before being introduced into GRASP, at 60
equally-spaced bins between the minimal height ($z_{min}$) of 500 m a.g.l. (avoiding overlap concerns) and
the maximal one ($z_{max}$), where the aerosol-free atmosphere is found. The vertical RCS is normalized,
NRCS(z), and discretely distributed in those 60 height-levels, $z_i$ ($i$ = 1, ...60), according to the
following expression (Dubovik et al., 2020):

$$
NRCS(z_i) = \frac{\frac{1}{n_i} \sum_{z=z_1}^{z=z_{min}} RCS(z)}{\sum_{z_{min}}^{z_{max}} RCS(z) \Delta z}, \quad (6)
$$

where NRCS(zᵢ) is the normalized RCS at zᵢ-bin, nᵢ is the number of RCS(z) values within the zᵢ
height-interval ranging from z₁ to zNᵢ, and Δz is the P-MPL vertical resolution (Δz = 75 m in this
work).

GRASP<sub>pac</sub> retrieval provides the aerosol columnar properties (see **Table 2**) together to the so-called
aerosol vertical profile function, AVP(z) (where the height discretization, z<sub>i</sub>, is omitted for simplicity
hereafter). GRASP<sub>pac</sub> allows to obtain vertical profiles of the total volume concentration, VC(z), in
addition to the total particle backscatter, β<sub>p</sub>(z, λ), and extinction, α<sub>p</sub>(z, λ), coefficients from the
following expressions (Dubovik et al., 2020):

$$
\alpha_p(z, \lambda) = AOD(\lambda) AVP(z), \tag{7}
$$

$$
\beta_p(z, \lambda) = \frac{AOD(\lambda) AVP(z)}{LR^c(\lambda)}, \text{ and} \tag{8}
$$

$$
VC(z) = VC^c AVP(z), \tag{9}
$$

where all those variables are defined in **Table 2**; in particular, they are examined at $\lambda$ = 532 nm for
comparison purposes with similar lidar-derived variables.

Finally, a total of 24 dust cases, regarding the dusty criteria adopted (see **Sect. 2.1.1**) together with
simultaneous AERONET and P-MPL measurements and also fulfilling the required conditions following
the GRASP<sub>pac</sub> scheme, were selected. However, in particular, 19 out of those 24 cases with AOD<sup>500</sup> > 0.4
were only analysed regarding the GRASP retrieval of SSA, RRI and IRI due to their unavailability in
AERONET V3 L2.0 data. In addition, as stated before, $\beta_p(z)$ and $VC(z)$ profiles were also retrieved as
described in **Sect. 2.1.2** from the P-MPL measurements. Due to the different vertical resolution between
GRASP and P-MPL profiles, those $\beta_p(z)$ and $VC(z)$ profiles were degraded to those fixed height-levels, $z_i$, as used in GRASP (see Eq. 6), for comparison purposes.

## 2.3. Comparative analysis

In order to quantify the discrepancies obtained between the GRASP<sub>pac</sub>-derived and AERONET-columnar variables, a linear regression analysis is performed between both datasets for all the 24 dusty cases (19 cases for the optical properties, in particular; see Sect. 2.2). Both the slope ($m$), as constrained to zero the intersection value, and the correlation coefficient ($r$) of that linear fitting are obtained for the optical and microphysical properties (see Table 2), as a measure of the similarity of both methodologies. In addition, a linear regression is also performed between height-resolved GRASP and lidar-derived (see Sect. 2.1.2) variables for each single dust case; those statistical $m$ and $r$ parameters are also used as a measure of the model capability to reproduce the shape of the aerosol profiling. Moreover, the Mean Fractional Bias (MFB) is used as a proxy of the systematic errors, regarding an under- or over-estimation of the GRASP-derived values. The MFB is calculated, likewise in Córdoba-Jabonero et al. (2019), using the following formula:

$$MFB = \frac{1}{N} \sum_{i=1}^{N} 2 \frac{X_G^i - X_M^i}{X_G^i + X_M^i}, \qquad (10)$$

where $i$ represents either the case study for the GRASP/AERONET comparison or the height-level for the GRASP/lidar comparison, and $X$ is the (either columnar or height-resolved) variable to be compared (i.e., $X = SSA, RRI, IRI, R_{eff}, VC^c, \beta_p(z), VC(z)$; see Table 2). $G$ denotes the GRASP<sub>pac</sub>-retrieved variable and $M$ represents the measurements, either AERONET (columnar) data or vertical P-MPL-derived variables. $N$ is either the number of total cases (i.e., $N = 24$, or 19 for the optical variables) for the column-integrated aerosol properties or the number of total height-bins for the vertical profiles (i.e., $N = 60$; hence, a MFB is obtained for each dust case). MFB values within ±30% (±60%) represent an optimal (acceptable) confidence between datasets.

Besides, the relative differences ($\Delta^{rel}X$, in %) are also calculated, that is,

$$\Delta^{rel}X = 100 \frac{X_G - X_M}{X_M}, \qquad (11)$$

which are evaluated by using a frequency analysis within discrete intervals of ±5%. An acceptable confidence is assumed for $\Delta^{rel}X$ values between ±20% for all the variables, except for the SSA and RRI (±5% instead), and IRI (±30% instead). In addition, the total occurrence $\chi$ (%) of dust cases fulfilling their $\Delta^{rel}$ are within that selected acceptable confidence for each variable is also introduced. Therefore, all those proxies, i.e., those obtained from the regression analysis ($m$ and $r$) together with the MFB and $\Delta^{rel}X$ (and $\chi$), are assessed in overall in order to determine the degree of agreement of the GRASP retrievals with respect to those obtained from the synergy between AERONET data and P-MPL measurements. In general, a high confidence level is accepted when the following conditions are altogether achieved: $m$ is within the 0.80-1.20 interval, $r > 0.60$, MFB < |±60%| (acceptable performance) and $\chi > 40\%$ of occurrence of dust cases.
It should be noted that differences in that GRASP comparative analysis are expected because the algorithms involved in the comparison are different, regarding their diverse inputs, assumptions and equations used (see Sects. 2.1 and 2.2). Thus, a recent study showed dissimilarities in the GRASP-derived columnar properties in comparison with the AERONET ones when introducing the lidar signal as added value in the GRASP configuration retrieval (Molero el al., 2020).

## 3. Results

### 3.1. Columnar aerosol properties: comparison between GRASP and AERONET

GRASP-retrieved columnar microphysical (VC^c, R_{eff}, and VSD) and optical (SSA, RRI, and IRI at 440, 675, 870 and 1020 nm) properties are evaluated in comparison with AERONET data.

#### 3.1.1. Microphysical properties

**Figure 1** shows the total volume concentration (VC^c, µm³ µm⁻²) and the total effective radius (R_{eff}, µm) as derived from GRASP and AERONET, considering those selected 24 dust cases. The linear regression as performed between both datasets, providing the slope (m) and the correlation coefficient (r), together to the MFB (as estimated by Eq. 10) is shown in the top panels. Additionally, the frequency analysis of the relative differences (Δ^{rel}, %) is shown in the bottom panels, where the χ values are also included.

<figure><img src="image_3.png" /></figure>

**Figure 1.** Comparison between GRASP and AERONET: (Left) the columnar total volume concentration (VC^c, µm³ µm⁻²) and (Right) the total effective radius (R_{eff}). (Top panels) Linear regression between datasets, showing the slope (m) and the correlation coefficient (r) (the 1:1 line is also shown by a black dashed one) together to the MFB; and (Bottom panels) relative differences (Δ^{rel}, %), indicating the total occurrence χ(%) of dust cases fulfilling their Δ^{rel} are within ±20% (as marked by a grey band), where green and red bars show those Δ^{rel} in ±5%-wide intervals, respectively, within and out of that selected confidence range.
In general, high correlations ($r > 0.90$) are obtained for both microphysical properties with linear slopes close to 1 for $VC^c$ ($m = 1.02$), and lower than 1 for $R_{eff}$ ($m = 0.77$). In addition, their MFB values are within the optimal confidence level (±30%) for both variables, being rather better for $VC^c$ (values closer to zero), and negative for $R_{eff}$, indicating an underestimation, in general, of the GRASP-derived $R_{eff}$ values with respect to AERONET data. The occurrence of dust cases with $\Delta^{rel}$ values within ±20% (good level of confidence) is 100% and 38% for $VC^c$ and $R_{eff}$, respectively; that percentage for $R_{eff}$ increases up to 50% considering $\Delta^{rel}$ within ±30%. In overall, meanwhile a very good agreement is obtained for the total volume concentration concerning all the confidence proxies, fulfilling the high confidence conditions, the degree of agreement for $R_{eff}$ just relies on two of those three confidence parameters, i.e., on both the linear correlation and MFB ($\chi$ is slightly lower than 40%, as assumed for the high confidence conditions). This particular disagreement found for $R_{eff}$ between GRASP and AERONET datasets is mostly depending on the retrieved particle volume size distributions (VSD), where the discrepancies found with AERONET are mostly highlighted for the fine mode, as shown in **Figure 2**.

**Figure 2** shows both the GRASP-retrieved and AERONET VSD for each dust case, indicating also their particular AOD at 500 nm ($AOD^{500}$). In overall, despite the GRASP VSD is slightly displaced with respect to the AERONET VSD, two particle modes are clearly highlighted. However, a better coincidence is observed for the coarse mode, which is also the predominant one, with respect to the fine one, which presents larger discrepancies. In order to examine the degree of agreement between GRASP and AERONET VSD datasets, the same confidence proxies as for the $VC^c$ and $R_{eff}$ were obtained for each of those 24 dust cases, that is, a linear regression was performed and both the MFB and $\Delta^{rel}$ (and $\chi$) were calculated. Results are shown in **Table S1** of the Supplementary Material, including the slope $m$ and the correlation coefficient $r$, and the MFB and $\chi$ values as obtained for each dust case, including those corresponding to the fine ($fm$) and coarse ($cm$) modes, separately.
<figure><img src="image_4.png" /><figcaption>**Figure 2.** Particle volume size distributions (VSD) as derived from GRASP (red line) and AERONET (black line) retrievals for the selected 24 dust cases (their particular AOD<sup>500</sup> is also indicated in each panel).</figcaption></figure>

In general, a good degree of agreement is found in overall for the GRASP-derived total VSD with respect to AERONET ones in the basis of a 96%, 100%, 100% and 50% out of those 24 dust cases satisfy the high confidence conditions as defined by, respectively, *m* = 0.80-1.20, *r* > 0.60, MFB < |±60%| (acceptable performance) and *χ* > 40% of occurrence. Similar results are found for the coarse mode, whereas for the fine mode the percentage of cases fulfilling the high confidence conditions is 33%, 70%, 100% and 8%, respectively, for *m*, *r*, MFB and *χ* (see **Table S1** of the Supplementary Material).

### 3.1.2. Optical properties

**Figure 3** shows the single scattering albedo (SSA) (Fig. 3a) and both the real (RRI) (Fig. 3b) and imaginary (IRI) (Fig. 3c) refractive indexes at four wavelengths (440, 675, 870 and 1020 nm) as derived
from GRASP and AERONET, considering only 19 out of those selected 24 dust cases with $AOD^{500}$ > 0.40 (see Sect. 2.2). The linear regression ($m$ and $r$ values) as performed between both datasets together to the MFB values are shown in their top panels for each variable. The relative differences ($\Delta^{rel}$, %) are shown in their corresponding bottom panels, where the total occurrence $\chi$ (%) of dust cases fulfilling their $\Delta^{rel}$ are within ±5% for SSA and RRI and 30% for IRI (assumed as a good level of confidence for those variables) is also introduced.

In general, linear slopes values with $m$ close to 1 and high correlations ($r$ ~ 1) are obtained for the optical properties of SSA and RRI at all the wavelengths (see Figs. 3a and 3b, top panels). However, the IRI comparison reveals $m$ ~ 1 at 440 nm only, increasing from 1.5 to 1.9 along with the wavelength; additionally, the correlation coefficient is rather high at all the wavelengths (see Fig. 3c, top panels). Regarding the MFB, an optimal confidence level is found for the SSA and RRI at all the wavelengths. Meanwhile negative MFB values are found for SSA, indicating an underestimation of the GRASP-derived SSA with respect to AERONET data, the MFB for RRI decreases as wavelength increases, reaching negative values at 870 and 1020 nm; that is, GRASP RRI values are overestimated and underestimated, respectively, at 440 and 675 and 870 and 1020 nm (see Figs. 3a and 3b, top panels). However, the MFB confidence is acceptable for the IRI at 440 and 675 nm with positive MFB values representing GRASP overestimated IRI values with respect to AERONET ones, being out of the confidence interval at higher wavelengths of 870 and 1020 nm (see Fig. 3c, top panels). Also, an overestimation is found for the IRI, although results are worse in comparison with AERONET values.

In addition, the relative differences $\Delta^{rel}$ as obtained between GRASP and AERONET show $\chi$ values (with confident occurrence within ±5%) of 95% (63%) for the SSA (RRI) at 440 nm and 100%) at those other wavelengths (except for RRI at 1020 nm with a value of 95%; see Figs. 3a and 3b, bottom panels). However, despite a 74% of dust cases present $\Delta^{rel}$ values within ±30% at 440 nm, rather lower $\chi$ values (less than 11%) are found for the IRI at the other higher wavelengths, as expected. The $\Delta^{rel}$ values are positive (with occurrences of 10-70%; see Fig. 3c, bottom panel), showing the GRASP IRI overestimation, as also commented before. $\chi$ increases up to 95% and 42% for IRI at 440 and 675 nm when an acceptable confidence level for $\Delta^{rel}$ of ±50% is considered (note that the maximum uncertainty for AERONET IRI values is 50%, see Table 1), remaining $\chi$ for the IRI at the other two wavelengths unchanged. All these results are particularly shown in Table S2 of the Supplementary Material.
<figure><img src="image_5.png" /><figcaption>**Figure 3.** Comparison between GRASP and AERONET for (a) the columnar single scattering albedo (SSA), (b) the real refractive index (RRI) and (c) the imaginary refractive index (IRI) at 440, 675, 870 and 1020 nm (from left to right). (Top panels) Linear regression between datasets, showing the slope</figcaption></figure>

455
(m) and the correlation coefficient (r) (the 1:1 line is also shown by a black dashed one), together to the MFB. (Bottom panels) Frequency analysis of the corresponding relative differences (Δ<sup>rel</sup>, %), indicating the total occurrence χ (%, see the legend) of dust cases fulfilling their Δ<sup>rel</sup> are within ±5% for SSA and RRI and ±30% for IRI (as marked by a grey band), where green and red bars show those Δ<sup>rel</sup> in ±5%-wide intervals within and out of, respectively, the selected acceptable confidence interval.

In general, GRASP-retrieved SSA and RRI values at all wavelengths present a rather good degree of
agreement with respect to AERONET data by analysing the results of m, r, MFB and Δrel in overall.
However, unlike the GRASP IRI at 440 nm presents a good confidence level, this variable at 675, 870
and 1020 nm must be examined in more detail, taking into account the high degree of uncertainty for the
AERONET IRI value (~ 50%, see Table 1). It must also be noted that, in the particular GRASP
retrieval using the 1-λ lidar (active) + Sun-photometer (passive) measurements configuration, the
initializing variables of the model could be relevant for retrieving results with a high convergence. We
applied the well-stablished GRASPpac configuration as described by Román et al. (2018), as they used
a similar configuration with a ceilometer system at 1064 nm + sun-photometer measurements. They
obtained good results within the GRASP error intervals of the IRI for the only two dust case studies. In
this work, we examined a more extended database (19 cases in total); therefore, those IRI differences
found at wavelengths higher than 440 nm might be just based on the sampling data, highlighting a worse
agreement for the GRASP-derived IRI variable at those wavelengths that is only observed by analysing
a given high number of dust cases. Therefore, in the IRI comparison case, a sensitive analysis should be
performed in order to obtain improved results by upgrading the GRASP initializing IRI parameters.

**3.2. GRASP-derived height-resolved aerosol properties**

Height-resolved optical and microphysical properties as derived by GRASP are analysed in comparison
with the corresponding variables as retrieved from alternative methodologies, which are based on the
synergy between the P-MPL measurements and the POLIPHON method (Córdoba-Jabonero et al.,
2018). In particular, the profiles of both the particle backscatter coefficient βₚ(z) at 532 nm and the
total volume concentration VC(z) are evaluated against those retrieved by the synergetic
P-MPL/POLIPHON algorithm (see Sect. 2).

**3.2.1. Particle backscatter coefficient: comparison between GRASP and KF retrievals**

The height-resolved particle backscatter coefficient $\beta_p(z)$ (Mm$^{-1}$ sr$^{-1}$) at 532 nm is derived by applying
the KF algorithm to the P-MPL measurements (see **Sect. 2.1.2**). **Figure 4** shows the vertical $\beta_p(z)$
profiles as derived by both GRASP and KF methods for the selected 24 dust cases as ordered in
increasing $AOD^{500}$. Note that the height-resolved P-MPL measurements were degraded into 60
height-levels in coincidence with those used in GRASP (see **Sect. 2.2**) for comparison purposes.
Similarly to the columnar variables, but for each dust case individually, a linear regression analysis was
performed between the GRASP and P-MPL-derived profiles, hence determining *m* and *r*, and both the
*MFB* and *χ* values were also calculated. In particular, **Figure S1** of the Supplementary Material shows
the relative differences $\Delta^{rel}\beta_p(z)$ as a function of height (see **Eq. 11**) for each dust case, where the
confidence level within the ±20% interval is marked by a shaded grey band (the ±40% interval by a
shaded light grey one). $\Delta^{rel}\beta_p(z)$ within ±20% mostly correspond to altitudes where the dust layer (Dc
and Df particles) is predominantly present. Results from the comparative analysis are shown in **Table S3** of the Supplementary Material.

Despite $\beta_p$ is underestimated by GRASP at all the altitudes, in general, a relatively good degree of agreement is found for the GRASP-derived $\beta_p$ profiles with respect to those corresponding synergetic P-MPL/POLIPHON retrievals. This is based on a 54%, 100%, 88% and 67% out of those 24 dust cases satisfy the high confidence conditions as defined by, respectively, $m = 0.80-1.20$, $r > 0.60$, $MFB < |\pm60\%|$ (acceptable performance) and $\chi^2 > 40\%$ of occurrence; in particular, $m$ ranges between 0.63 and 1.01 and $r > 0.96$ (see **Table S3** of the Supplementary Material). That relatively low percentage found for $m$ (54%) indicates an underestimation of GRASP values in the $\beta_p$ profiles. Moreover, that 67% of those cases for a high confidence $\chi^2$ values, increase up to 88 and 100% of cases if the confidence level for $\Delta^{rel}\beta_p(z)$ is within $\pm30\%$ and $\pm40\%$, respectively. This can be due to the difference in the lidar ratio as retrieved by the GRASP model and the KF algorithm. Indeed, the mean lidar ratio obtained by GRASP among all the dust cases ($LR^{GRASP} = 63 \pm 6$ sr) is higher than the mean KF-retrieved $LR^{eff}$, being the relative difference of 20% in average.
<figure><img src="image_6.png" /><figcaption>**Figure 4.** Comparison between GRASP and KF retrievals of the vertical particle backscatter coefficient $\beta_p(z)$ (Mm$^{-1}$ sr$^{-1}$) at 532 nm (GRASP in red, and KF in black) for the selected 24 dust cases. From left to right, and from top to bottom, those cases are displayed in increasing $AOD^{500}$ (as indicated in each panel). Corresponding errors are shown by shaded bands.</figcaption></figure>

### 3.2.2. Total volume concentration: comparison between GRASP and synergetic P-MPL/POLIPHON retrievals

The height-resolved total volume concentration $VC(z)$ (µm$^3$ cm$^{-3}$) is derived by applying the procedure as described in Sect. 2.1.2 (see Eq. 3). Figure 5 shows the vertical $VC(z)$ profiles as derived by both methods, i.e., GRASP and the synergetic P-MPL/POLIPHON retrieval, for the selected 24 dust cases as ordered by increasing $AOD^{500}$. Similarly to $\beta_p(z)$ for each dust case, $m$ and $r$, and both the MFB and $\chi$ values were also determined. In particular, Figure 6 shows the relative differences $\Delta^{rel}VC(z)$ as
530

a function of height (see Eq. 11) for each dust case. The confidence level within the ±20% (±40%) interval is marked by a shaded grey (light grey) band (relative differences within those confidence levels are marked in green). As for $\Delta^{rel}\beta_p$, high confidence values of $\Delta^{rel}VC(z)$ are found at altitudes with predominance of dust particles. Results from the comparative analysis are shown in **Table S4** of the Supplementary Material.

<figure><img src="image_7.png" /><figcaption>**Figure 5.** Comparison between GRASP and synergetic P-MPL/POLIPHON retrievals of the vertical total volume concentration $VC(z)$ (µm$^3$ cm$^{-3}$) (GRASP in red, P-MPL/POLIPHON in black) for the selected 24 dust cases. From left to right, and from top to bottom, those cases are displayed in increasing AOD$^{500}$ (as indicated in each panel). Corresponding errors are shown by shaded bands.</figcaption></figure>

535
<figure><img src="image_8.png" /><figcaption>**Figure 6.** GRASP vs. synergetic P-MPL/POLIPHON retrieval comparison: relative differences $\Delta^{relVC}(z)$ (%) for the selected 24 dust cases. From left to right, and from top to bottom, those cases are displayed in increasing $AOD^{500}$ (as shown in each panel). Those $\Delta^{relVC}$ values within ±20% (confidence interval, as marked by a shaded grey band) are indicated by green points (the ±40% confidence interval is also indicated by a shaded light grey band).</figcaption></figure>

In general, a good degree of agreement is found in overall for the GRASP-derived *VC* profiles with respect to those corresponding synergetic P-MPL/POLIPHON retrievals. This is in the basis of a 75%, 100%, 100% and 63% out of those 24 dust cases satisfy the high confidence conditions as defined by, respectively, *m* = 0.80-1.20, *r* > 0.60, *MFB* < |±60%| (acceptable performance) and *χ* > 40% of occurrence, ranging *m* values from 0.63 to 1.08 and *r* > 0.96 (see **Table S4** of the Supplementary Material). In particular, that 63% increases up to 92 and 100% of cases if the confidence level for
$\Delta^{rel}VC(z)$ is within ±30% and ±40%, respectively, as also observed for $\Delta^{rel}\beta_p$. The lower, but not worse, percentages found for *m* and $\chi$ could be related to differences between the *VC* profiles due to the use of selected extinction-to-volume conversion factors, which were statistically determined from AERONET long-term measurements of Saharan dust (Ansmann et al. 2019), in the synergetic P-MPL/POLIPHON retrieval, instead of the actual ones. A 10% difference is found between the $f_v$ as applied in this work (see Sect. 2.1.2) and the particular $f_v^{eff}$ for each dust case.

## 4. Conclusions

For the first time, the performance of the GRASP model for the retrieval of the aerosol optical and microphysical properties of Saharan dust at mid-latitudes by using the combination of the AERONET AOD and radiances at several wavelengths and the polarized Micro-Pulse lidar (P-MPL) profiles at 532 nm as input parameters was examined in this work. In particular, 24 selected dust cases were analysed for evaluating the degree of agreement of the GRASP products. This evaluation relied on their comparison with those similar variables as derived from either AERONET columnar data (single scattering albedo, real and imaginary refractive indexes, volume concentration, particle effective radius, particle volume size distribution) or the vertical P-MPL-retrieved profiles of both the particle backscatter coefficient and volume concentration, which were obtained from alternative, widely validated, polarization-based methods. Several proxies were used as indicators of the level of confidence between datasets; among those were both the slope and correlation of the linear regression, the mean fractional bias and the relative differences.

A good agreement is found between GRASP and AERONET for aerosol columnar, as optical as microphysical, properties with the exception of the imaginary refractive index at 675, 870 and 1020 nm, which unsatisfied the acceptable confidence conditions ($m = 0.80-1.2$, $r > 0.60$, $MFB < |\pm60\%|$ (acceptable performance) and $\chi > 40\%$ of occurrence) in overall. The GRASP-derived single scattering albedo at all the wavelengths is usually underestimated, meanwhile the real refractive index values are overestimated and underestimated, respectively, at 440 and 675 nm and 870 and 1020 nm. Regarding the microphysical properties, high correlations (> 0.90) are found for both the total volume concentration and the total effective radius, although that former is moderately underestimated by GRASP, likely due to the discrepancies found for the fine mode. In addition, the *VSD* as obtained for the 24 dust cases satisfy all the assumed high confidence conditions in overall.

The height-resolved GRASP products, as the particle backscatter coefficient and the total volume concentration, were also analysed in comparison with the synergetic P-MPL/POLIPHON retrievals. Despite a single spectral P-MPL measurement is available (e.g., the P-MPL operates at 532 nm only), and hence, the unique height-resolved GRASP products are the total backscatter (and extinction) coefficient and the total volume concentration (no separation in particle modes), a good agreement is obtained from the comparison between both datasets, finding rather high correlations for those two height-resolved variables. High confidence conditions among all the dust cases are achieved, although GRASP values are underestimated at all the altitudes in overall. In particular, by considering the relative differences for $\beta_p$ and *VC* profiles within ±30%, $\chi > 40\%$ is fulfilled for the 88 and 92% of dust cases, respectively. Discrepancies found in a few cases could be associated, to some extent, to the differences observed in both the lidar ratio and the volume conversion factors used, but they are generally small.

The synergy between P-MPL and Sun/sky photometer measurements regarding the usual co-location of both MPLNET and AERONET networks in combination with GRASP code represent an improved
methodology to derive the height-resolved optical and microphysical properties for mineral dust particles with a high degree of confidence. Indeed, these results can be essential for application with no-polarized systems (e.g., ceilometers, lidars ...).

**Code/Data availability:** GRASP retrieval algorithm is an open source code available at http://www.grasp-open.com. Part of the data used in this publication were obtained as part of the AERONET and MPLNET networks and are publicly available. For additional data or information, please contact the authors.

**Author Contributions:** M-AL-C and CC-J designed the study and wrote the original draft paper. M-AL-C and MH-G performed data analysis with contributions from CC-J and JLG-R. AL and OD designed the initial model setup. All authors reviewed and edited the final version of the manuscript. All the authors agreed to the final version of the paper.

**Funding:** This work was funded by the Spanish Ministry of Science and Innovation (MICINN, grant PID2019-104205GB-C21), the Spanish Ministry of Economy and Competitiveness (MINECO, grant INTA13-1E-2696, Infraestructura cofinanciada con el Fondo Europeo de Desarrollo Regional (FEDER) "Una manera de hacer Europa"), and partly by the Spanish Ministry of Science, Innovation and Universities (MCIU, grant CGL2017-90884-REDT). Authors acknowledge the support by the European Union's H2020 research and innovation programme (GA n. 654109, 871115). Authors also thank the Association Nationale de la Recherche et de la Technologie (ANRT) by the CIFRE program 2019/0003. This work was partially supported by the Spanish Ministry of Economy and Competitiveness through project CGL2017-83538-C3-1-R.

**Acknowledgments:** Authors would like to acknowledge the use of GRASP inversion algorithm software (http://www.grasp-open.com) and its training through the GRASP-ACE project (H2020-MSCA-RISE-2017, GA 778349). Authors also thank the PIs of the AERONET and MPLNET El Arenosillo site and its technical staff for maintenance and operation support. The MPLNET project is funded by the NASA Radiation Sciences Program and Earth Observing System. Although none of the data of the paper have been extracted from MPLNET, the MPLNET staff at NASA GSFC is warmly acknowledged for the continuous help in keeping the MPL systems and the data analysis up-to-date. We particularly thank Judd Welton for providing the MPL unit in place at El Arenosillo site during the selected days of this work.

**Conflicts of Interest:** The authors declare no conflict of interest.

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