Given the need for accurate knowledge of aerosol
microphysical and optical properties with height resolution, various
algorithms combining vertically resolved and column-integrated aerosol
information have been developed in the last years. Here we present new
results of vertically resolved extensive aerosol optical properties
(backscattering, scattering and extinction) and volume concentrations
retrieved with the GRASP (Generalized Retrieval of Aerosol and Surface
Properties) algorithm over a 3-year period. The range-corrected signal (RCS)
at 1064 nm measured with a ceilometer and the aerosol optical depth (AOD)
and sky radiances from a sun/sky photometer have been used as input for this
algorithm. We perform a detailed evaluation of GRASP retrievals with
simultaneous in situ measurements performed at the same height, at the
Montsec mountaintop observatory (MSA) in the Pre-Pyrenees (northeastern
Spain). This is the first long-term evaluation of various outputs of this
algorithm; previous evaluations focused only on the study of aerosol volume
concentration for short-term periods. In general, our results show good
agreement between techniques although GRASP inversions yield higher values
than those measured in situ. The statistical analysis of the extinction
coefficient vertical profiles shows a clear seasonality as well as
significant differences depending on the air mass origin. The observed
seasonal cycle is mainly modulated by a higher development of the
atmospheric boundary layer (ABL) during warm months, which favors the
transport of pollutants to MSA, and higher influence of regional and
North African episodes. On the other hand, in winter, MSA is frequently
influenced by free-troposphere conditions and venting periods and therefore
lower extinction coefficients that markedly decrease with height. This study
shows the potentiality of implementing GRASP in ceilometer and lidar
networks for obtaining aerosol optical properties and volume concentrations
at multiple sites, which will definitely contribute to enhancing the
representativeness of the aerosol vertical distribution as well as to providing
useful information for satellite and global model evaluation.
Introduction
Atmospheric aerosol particles interact directly with the incident solar
radiation by either scattering or absorbing light. These aerosol–radiation
as well as the aerosol–cloud interactions influence the Earth's radiative
budget and therefore have an impact on climate. Aerosol particles are
considered the atmospheric constituents with the largest uncertainty in
global climate forcing estimations (IPCC, 2013). Their high spatial,
vertical and temporal variability is one of the key factors contributing to
their large uncertainty (IPCC, 2013).
During the last years, a great effort has been made by the Aerosols,
Clouds, and Trace gases Research InfraStructure (ACTRIS, https://www.actris.eu, last access: 1 May 2019)
community to extend the temporal and spatial coverage of aerosol property
sampling and to harmonize measurement protocols to increase their
representativeness and the comparability among sites and between measurement
techniques (i.e., in situ versus remote sensing). In situ observatories are
widely distributed and cover a large variety of atmospheric conditions
(urban, rural, background and remote sites). Moreover, in situ
instrumentation is able to provide a complete set of information in terms of
chemical, optical and microphysical aerosol properties. The main drawback of
in situ observatories is that they are only representative of the
atmospheric layer closest to the surface and might not be useful to infer
aerosol radiative properties at elevated layers (Rosati et al., 2016). For
this reason, vertically resolved aerosol observations are needed to
complement surface in situ measurements and column-integrated observations
from satellites or ground-based photometers. Lidar systems are frequently
used for profiling aerosol optical properties, and, depending on the lidar
capabilities and availability of co-located photometer measurements,
vertical profiles of aerosol microphysical properties can be retrieved as
well by using inversion algorithms (Chaikovsky et al., 2008, 2016; Lopatin
et al., 2013).
One of the recently developed inversion algorithms is the Generalized
Retrieval of Aerosol and Surface Properties (GRASP; Dubovik et al., 2014;
https://www.grasp-open.com/, last access: 1 May 2019) code that uses the heritage of the AERONET (Aerosol Robotic
Network) inversion scheme (e.g., Dubovik and King, 2000; Dubovik et al.,
2006). It is a versatile and open-source algorithm capable of obtaining
optical and microphysical aerosol properties from different sets of
measurements (Kokhanovsky et al., 2015; Espinosa et al., 2017; Torres et
al., 2017; Román et al., 2017, 2018). In particular, GRASP allows the
user to combine aerosol optical depths (AODs), sky radiances and range-corrected lidar signal (RCS) values to retrieve columnar and
vertically resolved aerosol properties. Román et al. (2018) proposed a
similar approach but using the RCS values at only one wavelength measured
with ceilometer instead of using multi-wavelength lidar RCS values as done
before. The retrieved vertical profiles of aerosol volume concentration
showed good agreement with in situ measurements from an aircraft campaign
and with in situ measurements from a nearby mountain station during a summer
campaign in southern Spain (Román et al., 2018). The use of ceilometer
measurements in the GRASP algorithm can be a significant advance towards a
better representation of aerosol properties with vertical resolution since
ceilometers are cheaper, require less supervision, provide continuous
measurements and are more extensively distributed compared to more
sophisticated lidar systems (Wiegner et al., 2014; Cazorla et al., 2017;
Dionisi et al., 2018). However, the main drawback of this approach is that
sun/sky photometer measurements are only available during daytime and under
low-cloudiness conditions. Other methodologies, such as the absolute
calibration of the ceilometer (Wiegner and Geiß, 2012), are able to
overcome this issue and provide quantitative backscatter profiles during day
and nighttime. Quantitative ceilometer profiles could be used for
evaluating dust forecast models (Tsekeri et al., 2017) such as the
BSC-DREAM8b, as input to radiative transfer models (Granados-Muñoz et
al., 2019), or can be assimilated in global models (Chen et al., 2018). This
application represents a step forward in the classical use of ceilometers
that were originally developed for cloud base detection (e.g., Martucci et
al., 2010; Wiegner et al., 2014).
The potential of this new technique motivates the present study in which the
GRASP code is used to retrieve long-term vertical profiles of aerosol
optical and microphysical properties combining ceilometer and AERONET
sun/sky photometer measurements over a 3-year period. The main objective of
this paper is to evaluate the performance of the retrieved aerosol products
by GRASP combining ceilometer and photometer measurements using as reference
the in situ measurements performed at the Montsec Global Atmosphere Watch
(GAW) station (MSA, 1570 m a.s.l., NE Spain). Additionally, a statistical
analysis of the vertical structure of aerosol properties based on the
3 years of GRASP retrievals at MSA is presented.
Experimental site and instrumentationMontsec observatory
Measurements used in this study were performed in the northeastern Iberian
Peninsula, with most of them at the Montsec mountaintop station (MSA;
42∘3′ N, 0∘44′ E, 1570 m a.s.l.), located in the
facilities of the Montsec Astronomic Observatory (OAdM,
http://oadm.ieec.cat/, last access: 1 May 2019). The MSA continental background site is part of the
Catalan Air Quality Network (Xarxa de Vigilància i Previsió de la
Contaminació Atmosfèrica, http://territori.gencat.cat/, last access: 1 May 2019), and it is
integrated in the European research infrastructure ACTRIS and in the Global
Atmosphere Watch (GAW) program. It is a remote high-altitude station
situated in the southern side of the Pre-Pyrenees at the Montsec d'Ares
mountain. This region is sparsely populated and isolated from large urban
and industrial agglomerations (140 km from Barcelona to the northwest and 30 km from the largest city in the region). The prevailing atmospheric
conditions are characteristic of Mediterranean climate, with long dry
periods, sporadic but intense rains, and a prevalence of local and regional
atmospheric air mass circulations and Saharan dust intrusions (Ripoll et
al., 2014; Ealo et al., 2016).
In situ measurements
Aerosol particles' light-scattering (σsp) and hemispheric-backscattering (σbsp) coefficients were measured at three
wavelengths (450, 525 and 635 nm) with an LED-based integrating nephelometer
(model Aurora 3000, ECOTECH Pty, Ltd., Knoxfield, Australia) with 5 min time
resolution. The aerosol flow in the nephelometer was set to 5 L min-1.
Measurements were performed at dry conditions (RH <40 %) by using
the internal RH-control function of the nephelometer that slightly heats the
sampled air when the RH is above the threshold value. The nephelometer is
periodically calibrated (four times per year) with CO2 and filtered
air. Zero adjustments are performed every midnight using internally filtered
particle-free air. The Aurora 3000 nephelometer used in this study operates
by collecting light scattered within the angular range
10–171∘ (Müller et al., 2011a). The main source of
error is the truncation in the forward direction (0–10∘)
due to the inability of the nephelometer to sense near-forward scattering,
which is an increasingly dominant part of the total scattering for large
particles (Anderson et al., 1996). Non-idealities due to truncation errors
have been corrected following the scheme described by Müller et al. (2011a). The detection limits of the nephelometer over 1 min averaging time
are 0.11, 0.14 and 0.12 Mm-1 for total scattering at 450, 525 and 635 nm, respectively, and 0.12, 0.11 and 0.13 Mm-1 for backscattering
(Müller et al., 2011a).
The aerosol light-absorption coefficient, σap, was measured
with a Multi-Angle Absorption Photometer (MAAP, model 5012, Thermo) at 637 nm (Müller et al., 2011b). A detailed description of the method is
provided by Petzold and Schönlinner (2004). The MAAP draws the ambient
air at constant flow rate of 16.7 L min-1 and provides 1 min values.
The detection limit of the MAAP instrument is lower than 0.6 Mm-1 over
2 min integration. The total method uncertainty for the particle
light-absorption coefficient inferred from MAAP measurements is around
12 % (Petzold and Schönlinner, 2004).
An aerosol optical counter (GRIMM spectrometer, model 1129-Sky-OPC) was used
to measure particle number concentrations in 31 size bins, for particles in
the diameter size range from 0.25 to 32 µm at 5 min time resolution.
The working principle of this instrument is based on multichannel
light-scattering optics (Grimm and Eatough, 2009) in which the intensity of
the measured scattered light is related to the size of the particles. Volume
size distributions were derived from the number size distribution assuming
spherical particles.
All in situ measurements were performed at the MSA station and have been
converted to ambient temperature and pressure using the measurements from an
automatic and collocated weather station. Measurements were performed at low
relative humidity (RH <40 %), as recommended by the World
Meteorological Organization (WMO/GAW, 2003) and ACTRIS infrastructure.
Passive remote sensing measurements
Measurements of column-integrated aerosol properties were determined with a
CE-318 sun/sky photometer (Cimel Electronique, France) included in AERONET
(Holben et al., 1998) and located at the MSA observatory. This instrument
performs direct sun measurements with a 1.2∘ full field of
view at least at 440, 675, 870 and 1020 nm, which are used to derive AOD at
these wavelengths. The sky radiance measurements (almucantar configuration)
are also carried out at 440, 675, 870 and 1020 nm. A full description of the
AERONET products obtained from this instrument can be found in Holben et al. (1998). In this work, AOD and sky radiances, both at 440, 675, 870 and 1020 nm, from version 2 of AERONET level 1.5 data are used.
Active remote sensing measurements
Vertical profiles of RCS at 1064 nm were performed with a Jenoptik CHM 15k
Nimbus (G. Lufft Mess- und Regeltechnik GmbH, Germany) ceilometer that
includes a pulsed Nd:YAG laser, emitting at 1064 nm. The energy emitted per
pulse is 8 µJ and the duration of each pulse is between 1 and 5 ns
with a repetition frequency of 6.5 kHz. The maximum height of the signal is
15.36 km a.g.l., equivalent to 1024 range bins. The ceilometer is located at
800 m a.s.l., at the Center for the Observation of the Universe (COU,
http://www.parcastronomic.cat/, last access: 1 May 2019). The horizontal distance between the
ceilometer and the MSA station is less than 2.5 km. This instrument operates
continuously with a temporal resolution of 1 min and a spatial resolution of
15 m. The RCS profiles provided by the instrument are overlap-corrected
using the manufacturer's overlap function. In addition, according to this
function, the overlap of the telescope and the laser beam is greater than
85 % beyond 770 m from the ceilometer. Thus, the effect of the overlap at
the height of the MSA observatory (1570 m a.s.l.) is expected to be low.
GRASP retrievals
GRASP code is mainly based on two independent modules: (1) the forward module
consisting of a radiative transfer and aerosol model which simulates the
radiative measurements for a given aerosol scenario, and (2) the numerical
inversion module which is not related to the physical nature of the inverted
data (Dubovik et al., 2011, 2014) and is mathematically
based on the multi-term least square method (Dubovik and King, 2000). Detailed
description of the GRASP working principle using sun/sky photometer and RCS
data can be found in Lopatin et al. (2013), where the GARRLiC (Generalized
Aerosol Retrieval from Radiometer and Lidar Combined data) scheme, which is
part of GRASP code, is explained.
In this study, we follow the inversion strategy named GRASPpac
(with subscript meaning “photometer and ceilometer”) introduced by Román et
al. (2018). A GRASPpac retrieval is done for each sky radiance
almucantar sequence available from AERONET if sky radiances and ceilometer
measurements satisfy cloud-free conditions. The following measurements are
used in the GRASP code for each retrieval: (1) the cloud-screened sky radiance
and AOD at 440, 675, 870 and 1020 nm (AERONET version 2 level 1.5); and (2) the normalized ceilometer RCS at 1064 nm, previously cloud-screened,
smoothed and averaged in a ±15 min window centered in the photometer
measurement time, at 60 log-spaced heights as in Lopatin et al. (2013). The
minimum height of these 60 values corresponds to the MSA altitude. The
maximum height selected for the 60 log-spaced bins is 7000 m above MSA,
since aerosol layers are rarely detected above this height and the
ceilometer signal is usually too noisy at higher altitudes due to the low
power of the ceilometer's laser. The RCS at these 60 log-spaced bins is
averaged and then normalized by dividing each value by the integrated RCS
between the minimum and maximum heights. In addition, the bidirectional
reflectance distribution function (BRDF) is needed to make the GRASPpac
retrievals, and, to this end, an 8 d climatology (2000–2014) of the
MCD43C1 product (V005 MODIS Terra+Aqua BRDF/Albedo 16-Day L3 0.05Deg CMG)
of MODIS (Moderate Resolution Imaging Spectroradiometer) is used (Schaaf et
al., 2011).
Since ceilometer measurements are limited to a single wavelength, it is not
possible to vertically differentiate between aerosol modes/types, and
therefore vertical profiles of intensive variables such as the single-scattering albedo (SSA), lidar ratio (LR) or effective radius are assumed to be
vertically constant by this method. As a result, for each GRASPpac
retrieval we obtain aerosol profiles (at 60 points) of backscatter at
180∘; of scattering, extinction and absorption coefficients at
440, 675, 870, 1020 and 1064 nm; and also of aerosol size distribution (but
without changes in the effective radius with height) and the aerosol volume
concentration. The estimated uncertainty for the backscatter coefficient
retrieved with GRASPpac is 31 %, and it is 21 % for the extinction
coefficient and the volume concentration (Román et al., 2017). The
uncertainty in the backscatter profiles retrieved with GRASPpac is
higher than the estimated uncertainty by Wiegner and Geiß (2012) for the
absolute calibration method (10 %). Since the in situ measurements and
GRASPpac retrievals provide different information with respect to the
aerosol backward-scattering properties (hemispheric backscattering versus
backscatter at 180∘), the direct comparison between both
techniques is not possible. To have a sense of the performance of the
GRASPpac backscatter retrieval, for the comparison we have assumed that
the scattering into the backward hemisphere is the same in all directions.
Therefore, we have extrapolated the backscatter at 180∘ to
the angular range 90–180∘ in order to make it comparable
with the backscattering coefficient measured with the nephelometer. This
assumption constitutes an additional source of error since the actual
angular scattering distribution is not known and typically backscatter at
180∘ is larger than at smaller angles.
Results and discussionGRASP<inline-formula><mml:math id="M35" display="inline"><mml:msub><mml:mi/><mml:mi mathvariant="normal">pac</mml:mi></mml:msub></mml:math></inline-formula> – in situ comparisonOptical properties comparison
In situ extensive aerosol optical properties (i.e.,
hemispheric-backscattering, scattering and extinction coefficients) measured
at MSA over a 3-year period (April 2014–March 2017) are used for
evaluating the retrieval of aerosol optical properties from a ceilometer and
a sun/sky photometer using the GRASPpac method in a long-term frame.
Previous evaluations of this algorithm with in situ data focused on aircraft
campaigns (2–3 study cases) (e.g., Benavent-Oltra et al., 2017; Tsekeri et
al., 2017) or short-term periods (Román et al., 2018). Figure 1 shows
the comparison between the GRASPpac retrievals and in situ-measured
coefficients at low ambient RH (RHambient<50 %). This
restriction has been imposed to avoid cases affected by hygroscopic growth
and consequent enhancement of the optical coefficients detected by the
remote sensing instrumentation. To merge both datasets (GRASPpac and
in situ), the data have been averaged in 1 h intervals. The comparison
has been performed at 1570 m a.s.l., where the in situ instrumentation is
located and coinciding with the first height of the GRASPpac
retrievals. Therefore, the following results and associated discussion on
the comparison between GRASPpac and in situ measurements refer
exclusively to this height. In general, the GRASPpac retrievals are in
agreement with the in situ measurements. The coefficients of determination
span from 0.49 for the backscattering coefficient to 0.77 for the scattering
coefficient and 0.73 for the extinction coefficient (see details in Fig. 1). For both the aerosol light-scattering and the extinction coefficients
the slope and intercept of the regression are >1, while for the
backscattering coefficient the slope is <1. Figure 2 shows the
absolute differences between optical parameters measured in situ and
retrieved by GRASPpac optical parameters. The frequency distributions
of the absolute errors (in situ minus GRASPpac values) for the
scattering and extinction coefficients are tailed towards negative values
evidencing an overestimation of GRASPpac retrievals compared with
in situ measurements. For the extinction coefficient, Herreras et al. (2018)
showed good agreement between the integrated extinction profiles derived
with GRASPpac and AOD from sun photometers located at various heights
(R2>0.6). For the backscattering coefficient, Fig. 2
shows that GRASPpac also overestimates the in situ measurements, but
the frequency distribution of the absolute errors is more symmetrically
distributed around 0. The overestimation of GRASPpac-retrieved
backscattering coefficients is in agreement with the assumption made to
convert the backscatter coefficient at 180∘ provided by
GRASPpac into a hemispheric-backscattering coefficient in order to
perform the comparison with the in situ measurements (see Sect. 3). As the
backscatter at 180∘ is typically larger than at smaller
angles, this overestimation was expected. However, since overestimation of
the total scattering and extinction coefficients also occurs, it is
difficult to discern whether this overestimation originates in the
GRASPpac retrieval or in the assumption made to compare with the
in situ data. On the other hand, this assumption might be contributing to
lower the correlation between the backscattering coefficient from
GRASPpac and in situ measurements in comparison with the results
obtained for the scattering and extinction coefficient comparison (Fig. 1),
which shows higher correlation coefficients.
Scatter plots of the hourly averaged aerosol light-backscattering,
scattering and extinction coefficients determined with GRASPpac from the ceilometer and photometer data at MSA height versus the measured in situ coefficients. This comparison is restricted to situations with low ambient RH (RHambient<50 %). The linear regression and the 1 : 1 line are also shown.
Histograms of the absolute difference between in situ-measured and
retrieved with GRASPpac optical parameters (aerosol backscattering, scattering and extinction coefficients) at low ambient RH (RHambient<50 %).
Figure 3 shows the relationship between the scattering and extinction
coefficients measured in situ and retrieved by GRASPpac. The color scale represents the difference in the single-scattering albedo measured
in situ and retrieved with GRASPpac. For the in situ data, there is a
linear trend between scattering and extinction coefficients (R2=1),
denoting that the aerosol light extinction is dominated by the scattering
process, which is in accordance with previous in situ studies performed at
MSA (Pandolfi et al., 2014). On the contrary, for the GRASPpac
retrievals the correlation is also good but the data points deviate from the
1 : 1 line as the difference in the SSA between in situ and GRASPpac
increases (yellowish colors). In general, GRASPpac retrievals yield
lower SSA values (average SSA of 0.88±0.14) compared with in situ
SSA (0.93±0.04). These discrepancies in the absorption could be
related to the differences in the SSA at ground level (as measured in situ)
and the SSA associated with the total atmospheric column (GRASPpac) due
to absorbing aloft layers. However, the largest disagreements (yellowish
colors in Fig. 3b) coincide with Atlantic air mass influence, which as shown in Sect. 4.2, are characterized by low aerosol load and low
impact of decoupled aerosol layers. On the other hand, Andrews et al. (2017)
showed a systematic difference in the SSA from AERONET retrievals compared
with integrated in situ profiles, revealing that AERONET retrievals yield
higher aerosol absorption than in situ measurements, especially at low
aerosol load. MSA is a remote site with predominantly low aerosol load and
low contribution of absorbing particles. Furthermore, Román et al. (2018) found with synthetic data that SSA values retrieved by GRASPpac
reproduce better the real SSA values for moderate–high aerosol loads. In a
similar way, AERONET, in version 2, only provides SSA values with quality
assurance if the AOD at 440 nm is higher than 0.4 (Dubovik et al., 2000, 2002; Holben et al., 2006). Then, most of the obtained SSA
differences could be associated with the low-aerosol-load conditions, where
the SSA uncertainty is high in GRASPpac values.
Scatter plots of the hourly averaged aerosol light-scattering and
extinction coefficients measured in situ (a) and retrieved with
the GRASPpac algorithm (b). The color scale represents the
relative difference in the single-scattering albedo, SSA, between in situ
and GRASPpac data.
(a) Scatter plot of the hourly averaged aerosol volume
concentration determined with GRASPpac from the ceilometer and
photometer data at MSA height versus the in situ concentrations at low
ambient RH (RHambient<50 %), with the color scale
representing the contribution of fine particles to the total volume
concentration. (b) Same as panel (a) but restricted to situations with
contribution of fine particles to the total aerosol volume concentration
<75 % (Vfine/V<0.75). (c) Frequency of
occurrence of the absolute difference between the volume concentrations
measured in situ and determined with GRASPpac for situations with
Vfine/V<0.75.
Volume size distribution comparison
Figure 4 shows the comparison of the total aerosol volume concentration (V)
determined with GRASPpac and measured in situ at MSA height over the
study period. The color scale represents the ratio Vfine/V that
quantifies the contribution of fine particles (diameter below 1 µm)
to the total volume concentration, as determined from the in situ
measurements. As we can see in Fig. 4a, there is a lack of correlation,
showing a different relationship depending on the ratio Vfine/V. When
fine particles predominate (i.e., Vfine/V>0.75, yellowish
colors) the volume concentration measured in situ is significantly larger
than the volume concentration retrieved from the ceilometer and photometer
data using GRASPpac. On the contrary, when coarse particles predominate
the volume concentration provided by GRASPpac is larger than the one
determined in situ. Limiting the comparison to those cases with Vfine/V<0.75 (Fig. 4b), the correlation improves significantly (R2=0.65) and shows absolute differences within ±5µm3 cm-3 for 85 % of the data (Fig. 4c). Similar to the extinction
and scattering coefficient comparison, GRASPpac retrievals yield
higher aerosol volume concentrations compared with the in situ measurements.
Similar overestimations comparing GRASPpac and in situ data have been
reported before. In particular, Román et al. (2018) compared the
GRASPpac retrievals using also ceilometer and photometer data as input
with in situ measurements performed in a mountain station located
∼25 km apart from the ceilometer and at around 2000 m above
it during an intensive field campaign. Their results show that GRASPpac overestimates the volume concentration with a slope of the comparison
around 1.5. We found similar results, revealing that, in general,
GRASPpac overestimates the aerosol volume concentration (slope of the
comparison of 1.34). However, the comparison between GRASPpac and
in situ measurements shows significant discrepancies when fine particles
predominate (Vfine/V>0.75). The reduced number of cases
with Vfine/V>0.75 (∼15 % of the total
number of data points) makes it difficult to draw conclusive results
concerning the total volume concentration in atmospheric conditions
dominated by fine particles. Previous evaluations of the GRASP algorithm were
mainly conducted during Saharan dust events with predominance of coarse-mode
particles. Benavent-Oltra et al. (2017) found similar coarse volume
concentrations between GRASP retrievals and in situ profiles during two
flights performed under dust-dominated conditions, with slight
underestimation of GRASP in the aloft dust plumes, while significant
overestimation was reported for the fine volume concentration.
Overestimation of fine volume concentrations obtained with the GARRLiC algorithm compared with in situ data was also observed under a
dust-dominated and a marine polluted case (Tsekeri et al., 2017). Using
synthetic data, Román et al. (2018) showed higher discrepancies in the
retrieval of fine volume concentrations than in coarse ones for
GRASPpac. The reason behind these differences was partly attributed to
the use of a long wavelength (1064 nm) as RCS in the retrieval which is less
sensitive to fine particles than shorter wavelengths. Nevertheless, despite
the differences among studies, all of them evidence that the retrieval of
fine volume concentrations is particularly challenging while good results
can be obtained for the coarse volume concentration or total concentration
if the size distribution is dominated by coarse particles.
Finally, several environmental and topographic factors can be brought
forward to partly explain the differences observed among techniques, namely
the measurement atmospheric conditions (temperature, pressure and RH) and
orographic effects affecting wind patterns and atmospheric boundary layer
(ABL) structure and causing spatial inhomogeneities. Concerning the atmospheric
conditions at which the aerosol properties are measured in terms of
temperature, pressure and relative humidity, we expect a low effect on the
comparison since the in situ data have been converted to ambient T and P and
the comparison was restricted to cases with ambient RH <50 %.
Although hygroscopic growth can occur even at low RH (Zieger et al., 2017),
we limit the study to ambient RH <50 % in order to minimize the
RH effect in the comparison (Titos et al., 2016). As can be seen in Fig. S1 of the Supplement, the comparison shows no dependency on RH
for RHambient<50 %. Another possible factor that could
affect the comparison is the fact that the in situ and photometer
measurements are not performed exactly over the ceilometer vertical.
However, due to the short horizontal distance (<2.5 km), this fact
is expected to have little impact on our results.
Statistical analysis of aerosol profiles
In the following section, we focus on the extinction coefficient since it is
the most relevant climate variable from the ones retrieved with
GRASPpac. Figure 5 shows the seasonality of particle extinction
profiles retrieved with GRASPpac using ceilometer and photometer data
as inputs. It is important to recall that GRASPpac retrievals are
performed only during daytime and clear-sky conditions caused by the
combination of the ceilometer with the sun/sky photometer data (see Sect. 3 for further details), which might bias the statistical analysis presented
in this section compared to continuous measurements. Figure S2 of the
Supplement shows the frequency distribution of the number of
profiles retrieved by month and hour of the day. As it can be seen, the
GRASPpac retrievals are restricted to daytime conditions and solar
zenith angles larger than 40∘ (mainly from 6 to 9 h in the
morning and from 14 to 16 h). Accordingly, there are also fewer GRASPpac
retrievals during autumn and winter.
Seasonal variability of vertical profiles of aerosol extinction
coefficients at 675 nm. The line represents the median and the shadowed area
is the interquartile range. The dashed lines represent the 10th and 90th
percentiles. Seasonal statistics are based on daily averaged profiles.
Spring corresponds with March, April and May; summer with June, July and
August; autumn with September, October and November; and winter with December,
January and February.
In average terms, the largest extinction coefficients are observed at the
lowest altitudes sounded. A nearly exponential decrease with height of the
median extinction coefficients is observed during all seasons up to
4000–5000 m a.s.l. An exponential decreasing trend of the extinction
coefficient has been observed in several statistical lidar studies in Europe
(Mattis et al., 2004; Amiridis et al., 2005; Navas-Guzmán et al., 2013).
There is a clear seasonal behavior in the vertical distribution of aerosol
particles, evidencing that during winter most particles are confined to the
first few kilometers above the surface while the median profile in summer
shows the presence of particles at higher altitudes. Also in summer, the
extinction profiles display a larger interquartile range compared with the
other seasons, denoting high variability in the vertical distribution of
aerosol particles. Concerning the extinction coefficients in the lowermost
part of the profiles, Pandolfi et al. (2014) reported a similar seasonality
for continuous in situ measurements at MSA, with the highest extinction
coefficients observed in summer and the lowest ones in winter.
Air masses arriving at MSA have been classified into four sectors following
the procedure of Ripoll et al. (2014): Atlantic (ATL), North African (NAF),
Regional (REG), and Mediterranean and European (MED+EU). Figure 6 shows a
statistical overview of the extinction profiles from GRASPpac
classified according with their air mass origin. There are significant
differences in the extinction vertical distribution depending on the origin
of the air masses affecting the Montsec area. The lowest median extinction
coefficient occurs under Atlantic air masses. This result is in agreement
with the low extinction coefficients found in winter, given that during
colder months the site is frequently affected by Atlantic air masses and is
located within the free troposphere (Ripoll et al., 2014). These profiles
also show low variability (smaller interquartile range). A similar behavior
is obtained for the MED+EU sector, although the extinction coefficient
displays higher variability, which is especially pronounced close to the surface
(high 90th percentile). For air masses with origin in North Africa the
extinction coefficient vertical profiles show the highest variability,
denoting the strong variation in intensity and aerosol-layer stratification
among events. The average extinction coefficient for the lowest atmospheric
layer is slightly lower than the average extinction coefficient found during
dust events at the surface level in MSA using in situ techniques (Pandolfi et
al., 2014). This discrepancy can be attributed to the different study period
and therefore different NAF episodes included in the calculation with
varying intensity and frequency. The air masses grouped in the REG sector
include transport from the Iberian Peninsula as well as recirculation
processes associated with the land–sea breezes regime (Millán et al.,
1997). In this case, the extinction coefficient profiles show high
variability up to 6000 m a.s.l., indicating layering and accumulation of
pollutants under regional recirculation conditions. During these episodes,
pollutants are raised up to upper levels, resulting in the stratification of
aerosol layers along the vertical atmosphere (Pérez et al., 2004). On
the other hand, the MED+EU and ATL sectors show a low 90th percentile and
interquartile range above 3000 m a.s.l., suggesting that the likelihood of
aloft aerosol layers under these atmospheric scenarios is significantly
reduced compared with the REG sector and, more remarkable, with the NAF sector.
Particle extinction coefficient profiles at 675 nm classified by
air mass origin (ATL: Atlantic, REG: Regional, MED+EU:
Mediterranean and European, NAF: North African). The line represents the
median and the shadowed area is the interquartile range. The dashed lines
represent the 10th and 90th percentiles. Statistics are based on
daily average profiles.
The air mass classification and the seasonality of the extinction vertical
profiles are clearly linked. NAF and REG episodes are more frequent during
spring and summer while ATL episodes are more frequent in autumn and winter
(Ripoll et al., 2014). The seasonal cycle observed is mainly modulated by a
higher development of the ABL during warm months and higher influence of
REG and NAF episodes (e.g., Ealo et al., 2018). This combination leads to
high extinction coefficients at higher altitudes and strong variability
(large difference in the 10th and 90th percentiles and
interquartile range) during warmer months. However, in winter, MSA is
frequently influenced by free-troposphere conditions and venting periods
(Ripoll et al., 2014) and therefore lower extinction coefficients. NAF
episodes also affect MSA during winter (i.e., Titos et al., 2017), but their
frequency of occurrence is low and their impact on the extinction vertical
profile is not observed in the median and 90th percentile profiles
(Fig. 6).
Figure 7 shows the center of mass calculated for the median extinction
profile, as well as the 25th and 75th percentile extinction profiles
following the procedure described by Cazorla et al. (2017), as a function of
the air mass origin sector. The center of mass gives in a single number an
indication of the altitude of the aerosol vertical distribution in the
atmosphere. In cases in which a single aerosol layer is present in the
atmosphere, the center of mass gives an indication of its mean altitude; in
cases of multiple layers, however, it could be located in areas without any
considerable aerosol load (Binietoglou et al., 2015; Mona et al., 2006). The
highest center of mass is achieved under NAF air masses, evidencing the
influence of aloft dust layers. During an intense dust outbreak in February
2016, Cazorla et al. (2017) calculated a center of mass of 3000 m a.s.l.
(1430 m a.g.l.) at MSA in the most intense day. An interesting feature of
Fig. 7 is the difference in the centers of mass retrieved from the
percentiles and median profiles for the REG and NAF sectors, while for ATL and
MED+EU the difference in the 25th and 75th percentiles is small.
This fact evidences the high variability in vertical distribution of aerosol
particles occurring during NAF and REG episodes.
Bar plot of the center of mass in meters above sea level (m a.s.l.; note that the MSA
observatory is at 1570 m a.s.l.) of the 25th percentile (P25), median
and 75th percentile (P75) profiles, separated as a function of air mass
(ATL: Atlantic, REG: Regional, MED+EU: Mediterranean and
European, NAF: North African).
Conclusions
In this study, we present a systematic application of the GRASP algorithm
using ceilometer RCS and sun/sky photometer measurements (GRASPpac)
over an extended period of time (3 years). Our unique experimental setup
allows us to perform a long-term evaluation of the GRASPpac retrievals
versus in situ measurements under different atmospheric conditions. The
output variables studied here are the aerosol backscattering, scattering and
extinction coefficients and the volume concentration. The results show an
overall good agreement between GRASP retrievals and in situ measurements,
especially good for scattering and extinction coefficients (R2>0.7). The volume concentration comparison shows differences
depending on the predominance of fine or coarse particles, with poor
agreement when the contribution of fine particles to the total volume
concentration is >75 % and good agreement otherwise.
Restricting the comparison to cases with Vfine/V<0.75,
GRASPpac and in situ measurements show good correlation although
GRASPpac yields higher volume concentrations. A similar overestimation of
GRASPpac is found for the scattering and extinction coefficients. We
found slight discrepancies in the scattering–extinction relationship
obtained with GRASPpac compared to in situ data. In general,
GRASPpac retrievals yield lower SSA values (average SSA of 0.88±0.14) compared with in situ SSA (0.93±0.04). This result can be
linked with previous evaluations of AERONET retrievals that were shown to
yield higher aerosol absorption than in situ measurements, especially at low
aerosol load. Evaluation of the GRASPpac algorithm at different
environments with variable aerosol load and SSA characteristics will
contribute to better understanding and constraining the validity and limitations
of GRASPpac.
The statistical analysis of the extinction coefficient vertical profiles
retrieved with GRASPpac shows a clear seasonality as well as
significant differences depending on the air mass origin. The observed
seasonal cycle is characterized by higher extinction coefficients during
summer with strong day-to-day variability, while during winter the extinction
coefficient is lower in the whole atmospheric column and shows lower
variability. This seasonality is associated with a higher development of the
atmospheric boundary layer during warm months, favoring the transport of
pollutants to MSA. Additionally, the higher influence of regional and
North African episodes in summer contributes to the observed seasonality. On
the other hand, in winter, MSA is frequently influenced by free-troposphere
conditions and venting periods and therefore lower extinction coefficients
that markedly decrease with height.
The use of automated lidars and ceilometers systems for the determination of
vertically resolved aerosol properties has increased in recent years thanks
to their low operation requirements and costs, as well as their capability of
providing continuous unattended measurements. Together with this increased
use of ceilometer systems, there is a growing need for being able to convert
the ceilometer signals into usable aerosol properties. In this context, the
overall good results obtained in our validation are encouraging and
emphasize the potentiality of implementing GRASP in ceilometer and lidar
networks for obtaining aerosol optical properties and volume concentrations
with height resolution and wide spatial coverage. Compared with previous
studies, the present evaluation of GRASPpac retrievals with in situ
data has been performed over a 3-year period, being therefore representative
of varying atmospheric conditions. Nevertheless, it is important to bear in
mind that the results presented in this study are limited to daytime and
low-cloudiness conditions due to the need for simultaneous sun/sky photometer
measurements. Also, further studies investigating the performance of the
application of GRASPpac to ceilometers and automatic lidars with
different characteristics (i.e., wavelength of operation, pulse energy) than
the one used in this study are needed to maximize its potential application.
With this in mind, the implementation of GRASPpac in the frame of
measurement networks will contribute to enhancing the representativeness of
the aerosol vertical distribution as well as to providing useful information for satellite and
models evaluation, in addition to contributing to the objectives of several
international initiatives (Illingworth et al., 2019) such us the EU COST
Action TOPROF (Towards operational ground-based profiling with ceilometers,
Doppler lidars and microwave radiometers for improving weather forecasts) or
the E-PROFILE program of the European Meteorological Services Network.
Data availability
Sun-photometer data are accessible on the AERONET website
(http://aeronet.gsfc.nasa.gov/, last access: 17 June 2019). In
situ data measured at MSA are accessible
on a yearly basis at the World Data
Center for Aerosols website (http://ebas.nilu.no/, last access: 17 June 2019). Ceilometer data and in situ raw data are available from the authors upon request.
The supplement related to this article is available online at: https://doi.org/10.5194/amt-12-3255-2019-supplement.
Author contributions
GT analyzed the data and wrote the manuscript, ME operated the MSA in situ
station, RR performed the GRASP retrievals, AC processed the ceilometer data
in the frame of ICENET, YS operated the sun/sky photometer at MSA, OD
provided feedback on the GRASP algorithm, AA designed the experiment, and MP
operated the ceilometer and designed the experiment. All authors provided
comments on the manuscript.
Competing interests
The authors declare that they have no conflict of
interest.
Acknowledgements
Marco Pandolfi is funded by a Ramón y Cajal Fellowship (RYC-2013-14036) awarded by
MINECO. Roberto Román is funded by MINECO under postdoctoral program Juan de la Cierva – Incorporación (IJCI-2016-30007). Gloria Titos is funded by MINECO under postdoctoral program Juan de la Cierva (FJCI-2014-20819
and IJCI-2016-29838). We thank the OAdM and COU astronomical observatories for their support. Thanks are due to the AERONET
and RIMA networks for the scientific and technical support. The MODIS MCD43C1 data product was retrieved from the online Data
Pool, courtesy of the NASA Land Processes Distributed Active Archive Center (LP DAAC), USGS/Earth Resources Observation and Science (EROS) Center. The authors acknowledge the use of the GRASP inversion algorithm (https://www.grasp-open.com/) and
also thank David Fuertes, Anton Lopatín and Benjamín Torres for their feedback
in the use of GRASP.
Financial support
This research has been supported by the Spanish Ministry of Science and Education (grant nos. CGL2012-39623-C02/00 and CGL2016-78594-R), the Generalitat Catalunya (grant no. AGAUR 2017 SGR0041) and the H2020 Research Infrastructures (ACTRIS-2, grant no. 654109).
Review statement
This paper was edited by Jun Wang and reviewed by three anonymous referees.
ReferencesAmiridis, V., Balis, D. S., Kazadzis, S., Bais, A., Giannakaki, E., Papayannis, A., and Zerefos, C.: Four-year aerosol observations with a Raman lidar at
Thessaloniki, Greece, in the framework of European Aerosol Research Lidar
Network (EARLINET), J. Geophys. Res., 110, D21203,
10.1029/2005JD006190, 2005.
Anderson, T. L., Covert, D. S., Marshall, S. F., Laucks, M. L., Charlson, R. J., Waggoner, A. P., Ogren, J. A., Caldow, R., Holm, R. L., Quant, F. R., Sem, G. J., Wiedensohler, A., Ahlquist, N. A., and Bates, T. S.: Performance
characteristics of a high-sensitivity, three-wavelength, total
scatter/backscatter nephelometer, J. Atmos. Ocean. Tech., 13, 967–986,
1996.Andrews, E., Ogren, J. A., Kinne, S., and Samset, B.: Comparison of AOD, AAOD and column single scattering albedo from AERONET retrievals and in situ profiling measurements, Atmos. Chem. Phys., 17, 6041–6072, 10.5194/acp-17-6041-2017, 2017.Benavent-Oltra, J. A., Román, R., Granados-Muñoz, M. J., Pérez-Ramírez, D., Ortiz-Amezcua, P., Denjean, C., Lopatin, A., Lyamani, H., Torres, B., Guerrero-Rascado, J. L., Fuertes, D., Dubovik, O., Chaikovsky, A., Olmo, F. J., Mallet, M., and Alados-Arboledas, L.: Comparative assessment of GRASP algorithm for a dust event over Granada (Spain) during ChArMEx-ADRIMED 2013 campaign, Atmos. Meas. Tech., 10, 4439–4457, 10.5194/amt-10-4439-2017, 2017.Binietoglou, I., Basart, S., Alados-Arboledas, L., Amiridis, V., Argyrouli, A., Baars, H., Baldasano, J. M., Balis, D., Belegante, L., Bravo-Aranda, J. A., Burlizzi, P., Carrasco, V., Chaikovsky, A., Comerón, A., D'Amico, G., Filioglou, M., Granados-Muñoz, M. J., Guerrero-Rascado, J. L., Ilic, L., Kokkalis, P., Maurizi, A., Mona, L., Monti, F., Muñoz-Porcar, C., Nicolae, D., Papayannis, A., Pappalardo, G., Pejanovic, G., Pereira, S. N., Perrone, M. R., Pietruczuk, A., Posyniak, M., Rocadenbosch, F., Rodríguez-Gómez, A., Sicard, M., Siomos, N., Szkop, A., Terradellas, E., Tsekeri, A., Vukovic, A., Wandinger, U., and Wagner, J.: A methodology for investigating dust model performance using synergistic EARLINET/AERONET dust concentration retrievals, Atmos. Meas. Tech., 8, 3577–3600, 10.5194/amt-8-3577-2015, 2015.Cazorla, A., Casquero-Vera, J. A., Román, R., Guerrero-Rascado, J. L., Toledano, C., Cachorro, V. E., Orza, J. A. G., Cancillo, M. L., Serrano, A., Titos, G., Pandolfi, M., Alastuey, A., Hanrieder, N., and Alados-Arboledas, L.: Near-real-time processing of a ceilometer network assisted with sun-photometer data: monitoring a dust outbreak over the Iberian Peninsula, Atmos. Chem. Phys., 17, 11861–11876, 10.5194/acp-17-11861-2017, 2017.
Chaikovsky, A., Dubovik, O., Goloub, P., Balashevich, N., Lopatsin, A.,
Karol, Y., Denisov, S., and Lapyonok, T.: Software package for the retrieval of
aerosol microphysical properties in the vertical column using combined
lidar/photometer data (test version), Technical Report,
Institute of Physics, National Academy of Sciences of Belarus, Minsk, Belarus, 2008.Chaikovsky, A., Dubovik, O., Holben, B., Bril, A., Goloub, P., Tanré, D., Pappalardo, G., Wandinger, U., Chaikovskaya, L., Denisov, S., Grudo, J., Lopatin, A., Karol, Y., Lapyonok, T., Amiridis, V., Ansmann, A., Apituley, A., Allados-Arboledas, L., Binietoglou, I., Boselli, A., D'Amico, G., Freudenthaler, V., Giles, D., Granados-Muñoz, M. J., Kokkalis, P., Nicolae, D., Oshchepkov, S., Papayannis, A., Perrone, M. R., Pietruczuk, A., Rocadenbosch, F., Sicard, M., Slutsker, I., Talianu, C., De Tomasi, F., Tsekeri, A., Wagner, J., and Wang, X.: Lidar-Radiometer Inversion Code (LIRIC) for the retrieval of vertical aerosol properties from combined lidar/radiometer data: development and distribution in EARLINET, Atmos. Meas. Tech., 9, 1181–1205, 10.5194/amt-9-1181-2016, 2016.Chen, C., Dubovik, O., Henze, D. K., Lapyonak, T., Chin, M., Ducos, F., Litvinov, P., Huang, X., and Li, L.: Retrieval of desert dust and carbonaceous aerosol emissions over Africa from POLDER/PARASOL products generated by the GRASP algorithm, Atmos. Chem. Phys., 18, 12551–12580, 10.5194/acp-18-12551-2018, 2018.Dionisi, D., Barnaba, F., Diémoz, H., Di Liberto, L., and Gobbi, G. P.: A multiwavelength numerical model in support of quantitative retrievals of aerosol properties from automated lidar ceilometers and test applications for AOT and PM10 estimation, Atmos. Meas. Tech., 11, 6013–6042, 10.5194/amt-11-6013-2018, 2018.
Dubovik, O. and King, M. D.: A flexible inversion algorithm for retrieval of
aerosol optical properties from sun and sky radiance measurements, J.
Geophys. Res.-Atmos. 105, 20673–20696, 2000.
Dubovik, O., Smirnov, A., Holben, B. N., King, M. D., Kaufman, Y. J., Eck,
T. F., and Slutsker, I.: Accuracy assessments of aerosol optical properties
retrieved from Aerosol Robotic Network (AERONET) Sun and sky radiance
measurements, J. Geophys. Res.-Atmos., 105, 9791–9806, 2000.
Dubovik, O., Holben, B., Eck, T. F., Smirnov, A., Kaufman, Y. J., King, M. D.,
Tanré, D., and Slutsker, I.: Variability of absorption and optical
properties of key aerosol types observed in worldwide locations, J.
Atmos. Sci., 59, 590–608, 2002.Dubovik, O., Sinyuk, A., Lapyonok, T., Holben, B.N., Mishchenko, M., Yang,
P., Eck, T., Volten, H., Munoz, O., Veihelmann, B., Van Der Zande, W.J.,
Leon, J., Sorokin, M., and Slutsker, I.: Application of spheroid models to
account for aerosol particle nonsphericity in remote sensing of desert dust,
J. Geophys. Res.-Atmos. 111, D11208, 10.1029/2005JD006619,
2006.Dubovik, O., Herman, M., Holdak, A., Lapyonok, T., Tanré, D., Deuzé, J. L., Ducos, F., Sinyuk, A., and Lopatin, A.: Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations, Atmos. Meas. Tech., 4, 975–1018, 10.5194/amt-4-975-2011, 2011.Dubovik, O., Lapyonok, T., Litvinov, P., Herman, M., Fuertes, D., Ducos, F.,
Lopatin, A., Chaikovsky, A., Torres, B., Derimian, Y., Huang, X.,
Aspetsberger, M., and Federspiel, C.: GRASP: A Versatile Algorithm for
Characterizing the Atmosphere, SPIE
Newsroom, 10.1117/2.1201408.005558, 2014.Ealo, M., Alastuey, A., Ripoll, A., Pérez, N., Minguillón, M. C., Querol, X., and Pandolfi, M.: Detection of Saharan dust and biomass burning events using near-real-time intensive aerosol optical properties in the north-western Mediterranean, Atmos. Chem. Phys., 16, 12567–12586, 10.5194/acp-16-12567-2016, 2016.Ealo, M., Alastuey, A., Pérez, N., Ripoll, A., Querol, X., and Pandolfi, M.: Impact of aerosol particle sources on optical properties in urban, regional and remote areas in the north-western Mediterranean, Atmos. Chem. Phys., 18, 1149–1169, 10.5194/acp-18-1149-2018, 2018.Espinosa, W. R., Remer, L. A., Dubovik, O., Ziemba, L., Beyersdorf, A., Orozco, D., Schuster, G., Lapyonok, T., Fuertes, D., and Martins, J. V.: Retrievals of aerosol optical and microphysical properties from Imaging Polar Nephelometer scattering measurements, Atmos. Meas. Tech., 10, 811–824, 10.5194/amt-10-811-2017, 2017.Granados-Muñoz, M. J., Sicard, M., Román, R., Benavent-Oltra, J. A., Barragán, R., Brogniez, G., Denjean, C., Mallet, M., Formenti, P., Torres, B., and Alados-Arboledas, L.: Impact of mineral dust on shortwave and longwave radiation: evaluation of different vertically resolved parameterizations in 1-D radiative transfer computations, Atmos. Chem. Phys., 19, 523–542, 10.5194/acp-19-523-2019, 2019.Grimm, H. and Eatough, D. J.: Aerosol measurement: The use of optical light
scattering for the determination of particulate size distribution, and
particulate mass, including the semi-volatile fraction, J. Air Waste Manage.
Assoc., 59, 101–107, 10.3155/1047-3289.59.1.101, 2009.
Herreras, M., Román, R., Cazorla, A., Toledano, C., Lyamani, H., Torres,
B., Cachorro, V.E., Olmo, F.J., Alados-Arboledas, L., and de Frutos, A. M.:
Integrated Aerosol Extinction Profiles from Ceilometer and Sunphotometer
Combination against Sunphotometer Measurements at Various Heights. IGARSS
2018–2018 IEEE International Geoscience and Remote Sensing Symposium, IEEE, 22–27 July 2018, Valencia, Spain,
7564–7567, 2018.
Holben, B. N., Eck, T. F., Slutsker, I., Tanré, D., Buis, J. P., Setzer,
A., Vermote, E., Reagan, J. A., Kaufman, Y. J., Nakajima, T., Lavenu, F.,
Jankowiak, I., and Smirnov, A.: AERONET – a federated instrument network
and data archive for aerosol characterization, Remote Sens. Environ., 66,
1–16, 1998.Holben, B. N., Eck, T. F., Slutsker, I., Smirnov, A., Sinyuk, A., Schafer, J., Giles, D., and Dubovik, O.: AERONET's version 2.0 quality assurance
criteria. Proc. SPIE 6408, Remote Sensing of the Atmosphere and Clouds,
64080Q, 10.1117/12.706524, 2006.Illingworth, A., Cimini, D., Haefele, A., Haeffelin, M., Hervo, M.,
Kotthaus, S., Löhnert, U., Martinet, P., Mattis, I., O'Connor, E., and
Potthast, R.: How can Existing Ground-Based Profiling Instruments Improve
European Weather Forecasts?, B. Am. Meteorol. Soc., 605–619,
10.1175/BAMS-D-17-0231.1, 2019.
Intergovernmental Panel on Climate Change (IPCC): Contribution of Working
Group I to the Fifth Assessment Report of the Intergovernmental Panel on
Climate Change, in Summary for Policymakers in Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., 590–600, Cambridge Univ. Press, New York, USA, 2013.Kokhanovsky, A. A., Davis, A. B., Cairns, B., Dubovik, O., Hasekamp, O. P.,
Sano, I., Mukai, S., Rozanov, V. V., Litvinov, P., Lapyonok, T., Kolomiets,
I. S., Oberemok, Y. A., Savenkov, S., Martin, W., Wasilewski, A., Di Noia, A.,
Stap, F. A., Rietjens, J., Xu, F., Natraj, V., Duan, M., Cheng, T., and
Munro, R.: Space-based remote sensing of atmospheric aerosols: the
multi-angle spectro-polarimetric frontier, Earth Sci. Rev., 145, 85–116,
10.1016/j.earscirev.2015.01.012, 2015.Lopatin, A., Dubovik, O., Chaikovsky, A., Goloub, P., Lapyonok, T., Tanré, D., and Litvinov, P.: Enhancement of aerosol characterization using synergy of lidar and sun-photometer coincident observations: the GARRLiC algorithm, Atmos. Meas. Tech., 6, 2065–2088, 10.5194/amt-6-2065-2013, 2013.
Martucci, G., Milroy, C., and O'Dowd, C. D.: Detection of cloudbase height
using Jenoptik CHM15K and Vaisala CL31 ceilometers, J. Atmos. Ocean.
Tech., 2, 305–318, 2010.Mattis, I., Ansmann, A., Muller, D., Wandinger, U., and Althausen, D.:
Multiyear aerosol observations with dual wavelength Raman lidar in the
framework of EARLINET, J. Geophys. Res.-Atmos., 109, D13203,
10.1029/2004JD004600, 2004.Millán, M. M., Salvador, R., Mantilla, E., and Kallos, G.: Photooxidant
dynamics in the Mediterranean basin in summer: Results from European
research projects, J. Geophys. Res., 102, 8811,
10.1029/96JD03610, 1997.Mona, L., Amodeo, A., Pandolfi, M., and Pappalardo, G.: Saharan dust intrusions
in the Mediterranean area: Three years of Raman lidar measurements, J.
Geophys. Res., 111, D16203, 10.1029/2005JD006569, 2006.Müller, T., Laborde, M., Kassell, G., and Wiedensohler, A.: Design and performance of a three-wavelength LED-based total scatter and backscatter integrating nephelometer, Atmos. Meas. Tech., 4, 1291–1303, 10.5194/amt-4-1291-2011, 2011a.Müller, T., Henzing, J. S., de Leeuw, G., Wiedensohler, A., Alastuey, A., Angelov, H., Bizjak, M., Collaud Coen, M., Engström, J. E., Gruening, C., Hillamo, R., Hoffer, A., Imre, K., Ivanow, P., Jennings, G., Sun, J. Y., Kalivitis, N., Karlsson, H., Komppula, M., Laj, P., Li, S.-M., Lunder, C., Marinoni, A., Martins dos Santos, S., Moerman, M., Nowak, A., Ogren, J. A., Petzold, A., Pichon, J. M., Rodriquez, S., Sharma, S., Sheridan, P. J., Teinilä, K., Tuch, T., Viana, M., Virkkula, A., Weingartner, E., Wilhelm, R., and Wang, Y. Q.: Characterization and intercomparison of aerosol absorption photometers: result of two intercomparison workshops, Atmos. Meas. Tech., 4, 245–268, 10.5194/amt-4-245-2011, 2011b.Navas-Guzmán, F., Bravo-Aranda, J. A., Guerrero-Rascado, J. L.,
Granados-Muñoz, M. J., and Alados-Arboledas, L.: Statistical analysis of
aerosol optical properties retrieved by Raman lidar over Southeastern Spain,
Tellus B, 65, 21234, 10.3402/tellusb.v65i0.21234, 2013.Pandolfi, M., Ripoll, A., Querol, X., and Alastuey, A.: Climatology of aerosol optical properties and black carbon mass absorption cross section at a remote high-altitude site in the western Mediterranean Basin, Atmos. Chem. Phys., 14, 6443–6460, 10.5194/acp-14-6443-2014, 2014.Pérez, C., Sicard, M., Jorba, O., Comerón, A., and Baldasano, J. M.:
Summertime re-circulations of air pollutants over the north-eastern Iberian
coast observed from systematic EARLINET lidar measurements in Barcelona,
Atmos. Environ., 38, 3983–4000, 10.1016/j.atmosenv.2004.04.010, 2004.Petzold, A. and Schönlinner, M.: Multi-angle absorption photometry – A
new method for the measurement of aerosol light absorption and atmospheric
black carbon, J. Aerosol Sci., 35, 421–441,
10.1016/j.jaerosci.2003.09.005, 2004.Ripoll, A., Pey, J., Minguillón, M. C., Pérez, N., Pandolfi, M., Querol, X., and Alastuey, A.: Three years of aerosol mass, black carbon and particle number concentrations at Montsec (southern Pyrenees, 1570 m a.s.l.), Atmos. Chem. Phys., 14, 4279–4295, 10.5194/acp-14-4279-2014, 2014.Román, R., Torres, B., Fuertes, D., Cachorro, V.E., Dubovik, O.,
Toledano, C., Cazorla, A., Barreto, A., Bosch, J. L., Lapyonok, T.,
González, R., Goloub, P., Perrone, M. R., Olmo, F. J., de Frutos, A., and
Alados-Arboledas, L.: Remote sensing of lunar aureole with a sky camera:
adding information in the nocturnal retrieval of aerosol properties with
GRASP code, Remote Sens. Environ., 196, 238–252,
10.1016/j.rse.2017.05.013, 2017.Román, R., Benavent-Oltra, J. A., Casquero-Vera, J. A., Lopatin, A.,
Cazorla, A., Lyamani, H., Denjean, C., Fuertes, D., Pérez-Ramírez,
D., Torres, B., Toledano, C., Dubovik, O., Cachorro, V. E., de Frutos, A. M.,
Olmo, F. J., and Alados-Arboledas, L.: Retrieval of aerosol profiles
combining sunphotometer and ceilometer measurements in GRASP code, Atmos.
Res., 204, 161–177, 10.1016/j.atmosres.2018.01.021, 2018.Rosati, B., Herrmann, E., Bucci, S., Fierli, F., Cairo, F., Gysel, M., Tillmann, R., Größ, J., Gobbi, G. P., Di Liberto, L., Di Donfrancesco, G., Wiedensohler, A., Weingartner, E., Virtanen, A., Mentel, T. F., and Baltensperger, U.: Studying the vertical aerosol extinction coefficient by comparing in situ airborne data and elastic backscatter lidar, Atmos. Chem. Phys., 16, 4539–4554, 10.5194/acp-16-4539-2016, 2016.
Schaaf, C. L. B., Liu, J., Gao, F., and Strahler, A. H.: MODIS Albedo and
Reflectance Anisotropy Products from Aqua and Terra, in: Land Remote Sensing
and Global Environmental Change: NASA's Earth Observing System and the
Science of ASTER and MODIS, Remote Sensing and Digital Image Processing
Series, 11, edited by: Ramachandran, B., Justice, C., and Abrams, M., Springer-Cerlag, New York, USA, 549–561, 2011.Titos, G., Cazorla, A., Zieger, P., Andrews, E., Lyamani, H.,
Granados-Muñoz, M. J., Olmo, F. J., and Alados-Arboledas, L.: Effect of
hygroscopic growth on the aerosol light-scattering coefficient: A review of
measurements, techniques and error sources, Atmos. Environ., 141, 494–507,
10.1016/j.atmosenv.2016.07.021, 2016.Titos, G., Ealo, M., Pandolfi, M., Pérez, N., Sola, Y., Sicard, M.,
Comerón, A., Querol, X., and Alastuey, A.: Spatiotemporal evolution of a
severe Winter dust event in the western Mediterranean: Aerosol optical and
physical properties, J. Geophys. Res.-Atmos., 122, 4052–4069,
10.1002/2016JD026252, 2017.
Torres, B., Dubovik, O., Fuertes, D., Schuster, G., Cachorro, V. E., Lapyonok, T., Goloub, P., Blarel, L., Barreto, A., Mallet, M., Toledano, C., and Tanré, D.: Advanced characterisation of aerosol size properties from measurements of spectral optical depth using the GRASP algorithm, Atmos. Meas. Tech., 10, 3743–3781, 10.5194/amt-10-3743-2017, 2017.Tsekeri, A., Lopatin, A., Amiridis, V., Marinou, E., Igloffstein, J., Siomos, N., Solomos, S., Kokkalis, P., Engelmann, R., Baars, H., Gratsea, M., Raptis, P. I., Binietoglou, I., Mihalopoulos, N., Kalivitis, N., Kouvarakis, G., Bartsotas, N., Kallos, G., Basart, S., Schuettemeyer, D., Wandinger, U., Ansmann, A., Chaikovsky, A. P., and Dubovik, O.: GARRLiC and LIRIC: strengths and limitations for the characterization of dust and marine particles along with their mixtures, Atmos. Meas. Tech., 10, 4995–5016, 10.5194/amt-10-4995-2017, 2017.Wiegner, M. and Geiß, A.: Aerosol profiling with the Jenoptik ceilometer CHM15kx, Atmos. Meas. Tech., 5, 1953–1964, 10.5194/amt-5-1953-2012, 2012.Wiegner, M., Madonna, F., Binietoglou, I., Forkel, R., Gasteiger, J., Geiß, A., Pappalardo, G., Schäfer, K., and Thomas, W.: What is the benefit of ceilometers for aerosol remote sensing? An answer from EARLINET, Atmos. Meas. Tech., 7, 1979–1997, 10.5194/amt-7-1979-2014, 2014.
World Meteorological Organization (WMO): Aerosol measurement procedures
guidelines and recommendations, GAW Rep. 153, 72 pp., Geneva, Switzerland,
2003.Zieger, P., Väisänen, O., Corbin, J. C., Partridge, D. G.,
Bastelberger, S., Mousavi-Fard, M., Rosati, B., Gysel, M., Krieger, U. K.,
Leck, C., Nenes, A., Riipinen, I., Virtanen, A., and Salter, M. E.: Revising
the hygroscopicity of inorganic sea salt particles, Nat. Commun., 8,15883,
10.1038/ncomms15883, 2017.