ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus GmbHGöttingen, Germany10.5194/acp-15-7071-2015Middle East versus Saharan dust extinction-to-backscatter ratiosNisantziA.argyro.nisantzi@cut.ac.cyhttps://orcid.org/0000-0001-8159-248XMamouriR. E.AnsmannA.SchusterG. L.HadjimitsisD. G.Cyprus University of Technology, Dep. of Civil Engineering and Geomatics, Limassol,
CyprusLeibniz Institute for Tropospheric Research, Leipzig, GermanyNASA Langley Research Center, Hampton, Virginia, USAA. Nisantzi (argyro.nisantzi@cut.ac.cy)30June201515127071708431January201524February201501June201503June2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/15/7071/2015/acp-15-7071-2015.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/15/7071/2015/acp-15-7071-2015.pdf
Four years (2010–2013) of observations with polarization lidar and
sun/sky photometer at the combined European Aerosol Research Lidar
Network (EARLINET) and Aerosol Robotic Network (AERONET) site of
Limassol (34.7∘ N, 33∘ E), Cyprus, were used to
compare extinction-to-backscatter ratios (lidar ratios) for desert
dust from Middle East deserts and the Sahara. In an earlier article, we analyzed one case only
and found comparably low lidar ratios < 40 sr for Middle East dust. The complex data
analysis scheme is presented. The quality of the retrieval is
checked within a case study by comparing the results with respective
Raman lidar solutions for particle backscatter, extinction, and
lidar ratio. The applied combined lidar/photometer retrievals
corroborate recent findings regarding the difference between Middle
East and Saharan dust lidar ratios. We found values from
43–65 sr with a mean (±standard deviation) of 53 ± 6 sr for Saharan
dust and from 33–48 sr with a mean of 41 ± 4 sr
for Middle East dust for the wavelength of 532 nm. The presented data analysis, however, also
demonstrates the difficulties in identifying the optical properties
of dust even during outbreak situations in the presence of complex
aerosol mixtures of desert dust, marine particles, fire smoke, and
anthropogenic haze.
Introduction
The particle extinction-to-backscatter ratio or lidar ratio S is an
important quantity in the description of atmospheric aerosols with lidar
and a key input parameter in the
retrieval of vertical profiles of the particle extinction coefficient from
measurements with elastic backscatter lidars
such as the spaceborne Cloud Aerosol Lidar with Orthogonal Polarization
(CALIOP) . Profiles of the particle extinction coefficient
throughout the troposphere and stratosphere belong to the basic input data
sets in atmospheric modeling of the direct aerosol effect on climate.
Dust-related extinction coefficient profiles are also used to estimate ice
nuclei concentrations up to cirrus level . Present
and upcoming spaceborne lidar activities
need lidar-ratio
information for all relevant aerosol types such as urban haze, biomass
burning smoke, desert dust and marine particles in key areas of climate
relevance for a consistent interpretation of the space-lidar-derived aerosol
and cloud products.
Because desert dust is one of the major atmospheric aerosol components
and the Sahara and the deserts in the Middle East (Syria, Jordan,
Israel, Iraq, Arabian peninsula) are among the major dust sources of
the world, the investigation and quantification of the optical
properties including the lidar ratio of Saharan and Middle East
dust is an important contribution to atmospheric and climate
research. Recent Aerosol Robotic Network (AERONET) sun-photometer-based
studies of and combined observations with
polarization lidar and sun/sky photometer by
suggest that lidar ratios of Middle East dust are significantly lower
(35–45 sr) than the ones for Saharan dust
(45–60 sr). The reason seems to be that the illite
concentration in dust particles decreases from values around 80 %
in western Saharan regions to less than 5 % in the dust particles
in eastern Saharan and Middle East desert regions
. As a consequence the real part of the refractive
index decreases from 1.55 for Arabian dust to 1.45 for western Saharan
dust for the 500–550 nm wavelength range and the lidar ratio
drops from values around 60 sr for western Saharan dust to
values around or below 40 sr for Middle East dust.
More studies are needed to corroborate these findings. For this reason we
analyzed the full 2010–2013 lidar/photometer data set available for the
Limassol station regarding Middle East and Saharan dust outbreaks.
demonstrated that a polarization lidar is a basic
requirement for a trustworthy retrieval of dust optical properties. The
polarization lidar approach allows us to distinguish dust and non-dust
contributions to the overall particle optical properties and to extract the
dust-related lidar ratio information from the total aerosol backscatter and
extinction properties. There is almost no continental site in the Northern
Hemisphere which is not affected by omnipresent anthropogenic particles so
that lidar-derived extinction-to-backscatter ratios, even when directly
determined by means of the Raman-lidar or the High Spectral Resolution Lidar
method, are not trustworthy as long as measurements of the depolarization
ratio (showing, e.g., values of > 0.3 in the dust layers at 532 nm) are
not available. After long-range transport across the oceans, significant
mixing with marine particles can never be excluded so that again direct dust
lidar-ratio observations need to be interpreted with care when depolarization
ratio measurements are missing or show values clearly below 0.3 at 532 nm.
There are already a lot of studies on Saharan dust lidar ratios mostly based
on Raman lidar observations . For heavy dust loads the lidar ratio was typically in the
range of 45–60 sr for western Saharan dust sources. Most lidars did
not have a polarization sensitive channel for aerosol type separation so that
it remains unknown to what extent the retrieval of dust optical properties is
biased by the presence of non-dust particles. Respective Raman lidar efforts
regarding Middle East dust lidar ratios are not
available.
High-quality dust lidar ratio observations with lidar are
also required to support respective
photometer-based retrievals, because sun photometers
do not provide direct observations of 180∘ scattering, the lidar
ratio cannot be measured and is obtained from modeling. A spheroidal particle
shape model is used together with the observed spectral aerosol optical
thickness (AOT) and sky radiance measurements to simulate the particle
backscatter coefficient and the lidar ratio . The particle
shape model assumes that the irregularly shaped dust particles are ideal
spheroids. Because column-integrated particle information is measured, lidar
ratios for lofted dust layers and the polluted
boundary layer (PBL) cannot be distinguished.
The assumption of a spheroidal shape of the dust particles may cause
uncertainties in the column dust lidar ratios of the order of 10 % or
even more . However,
emphasized the strong influence of the real part of the
refractive index on the particle optical properties. The real part dictates
the scattering efficiency and has a strong impact on the computation of the
extinction and backscatter coefficients. Any fine-mode aerosol contribution
to the column aerosol observation was found to decrease the column-integrated
real part derived with AERONET and to increase the derived column lidar
ratio. thus contrasted polluted dust for which the
fine-mode volume fraction FVF is > 0.05 and pure dust scenarios with
FVF < 0.05.
Another source of uncertainty in AERONET lidar-ratio retrievals arise from
the fact that the presence of particles with radius > 15 µm is
ignored in the complex data analysis which is partly based on inversion
methods for which the size spectrum of the particles
have to be known a priori. AERONET measurement in the source regions, at
heavy dust conditions, or even after long-range transport, but within 30 h
after emission, may be affected by the presence of giant dust particles
.
In this article, we summarize our 4 year lidar-ratio observations and present
the dust lidar-ratio findings of 17 Middle East and 32 Saharan dust
outbreaks. A first lidar-based study of a strong Middle East desert dust
outbreak was presented by to highlight the comparably low
lidar ratios (34–39 sr) for Arabian dust. The Limassol lidar station at the
island of Cyprus in the eastern Mediterranean Sea is unique because it is the
only site of the European Aerosol Research Lidar Network (EARLINET) which is
influenced by a statistically significant number of dust outbreaks from both
the Middle East (5–7 per year) and the Sahara (> 10 per year). However,
the eastern Mediterranean and the adjacent southwestern Asian and northern
African areas are also highly polluted, which strongly complicates the data
analysis. As already observed during the United Arab Emirates Unified Aerosol
Experiment (UAE2) campaign , the Southwest Asian region is
one of the most difficult environments in the world regarding characterizing,
modeling and monitoring of the atmospheric state. Frequent dust storms, high
anthropogenic aerosol levels, and complex air flow pattern dominate the
region. This is reflected in our observations, too.
Simultaneous EARLINET lidar and AERONET sun photometer observations were
conducted at Limassol almost daily over the 4 year period from May 2010 to
December 2013. One of the goals is to cover the overpass times of polar
orbiting satellites. Therefore the observations were usually taken between
07:00 and 13:00 UTC (09:00–15:00 local time). Night-time (Raman lidar)
observations were only occasionally performed. The data analysis is thus
based on the 532 nm elastic backscatter signals and makes use of the
methodology recently introduced by
.
In Sect. 2, the lidar and sun/sky photometer instruments are briefly
described. Section 3 presents the method applied to derive dust-related lidar
ratios from elastic-backscatter signal profiles. The results are discussed in
Sects. 4.1 and 4.2. The reliability of our methodology for the retrieval of
dust-related lidar ratios, outlined in Sect. 3, is checked by means of direct
Saharan dust lidar-ratio observation by applying the Raman lidar method
during a major Saharan dust storm (Sect. 4.3). In Sect. 5,
we compare a limited number of lidar ratio observations with results derived
from the AERONET sun photometer measurements alone .
Summarizing and concluding remarks are presented in Sect. 6.
Instrumentation
The remote sensing station of the Cyprus University of Technology
(CUT) at Limassol (34.7∘ N, 33∘ E,
50 ma.s.l.) is equipped with an EARLINET lidar
and AERONET sun/sky photometer (CUT–TEPAK site,
Limassol, Cyprus, http://aeronet.gsfc.nasa.gov)
and is located about 150 km south of Turkey
and 250 km west of Syria.
The laser transmits linearly polarized laser pulses at 532 and 1064 nm, and
detects the parallel and cross-polarized signal components at 532 nm.
Calibration of the polarization channels is performed by rotating the box
with the polarization sensitive channels following the methodology of
. Further measurement channels collect lidar return
signals at 607 nm (nitrogen Raman channel) and 1064 nm
(elastic backscatter). The full overlap of the laser beam with the receiver
field of view of the 20 cm Cassegrain telescope is obtained at
heights around 300 ma.s.l. and therefore in most cases within the
shallow planetary boundary layer (PBL) reaching up to 350–500 m
height. The basic temporal and spatial signal resolution, with which the raw
signals are stored, is 50 s and 7.5 m, respectively.
The lidar system started performing systematic measurements in May 2010 as a
532 nm elastic-backscatter lidar. A hardware upgrade was realized in mid-2012 by integrating a 607 nm Raman channel. In order to provide homogeneous
lidar data during the study period (May 2010–December 2013) we used the
vertical profiles of the 532 nm backscatter signals, only. Raman-lidar
retrievals are only available at nighttime and only for the EARLINET
measurement times (Monday and Thursday evenings). The Raman-lidar observation
on 23 May 2013 was used to validate our lidar-ratio approach in the case of a
strong Saharan dust outbreak with almost pure dust above 2.5 km height
emitted in the central part of the Saharan desert.
In this paper, we will mainly make use of the determined particle backscatter
coefficient and the particle depolarization ratio at 532 nm. The
range-corrected signal at 1064 nm was used only to better illustrate the
evolution of dust outbreaks in time-height displays (color plot in
Sect. 4.3). The retrieval products are computed from cloud-screened data
sets, averaged over almost 1 h and vertically smoothed with window
lengths of 45 m (up to 2.5 km height), 60 m (up to 4 km height), and
90 m (above 4 km height). All data files showing low-level cloud
contamination were removed before signal averaging.
Further information of the lidar, the methods applied to analyze the data,
the products, and basic retrieval uncertainties can be found in
and . Details of the
determination of the basic volume depolarization ratio profile are given by
.
The CUT AERONET sun photometer provides AOT measurements at eight wavelengths
from 339 to 1638 nm. It also provides retrievals of column-integrated
particle size distributions, complex refractive index, and the number
percentage of spherical particles . This is sufficient
information to compute the column lidar ratio SA. From the particle size distribution the fine-mode
volume fraction FVF is obtained. We further use the Ångström exponent
AE , determined from the spectral AOT distribution, and
the fine mode fraction FMF (fraction of fine–mode AOT to total AOT)
.
During the yearly CIMEL calibration period and/or in case of technical
problems, we performed measurements with a MICROTOPS II sun photometer (Solar
Light Company, USA) to obtain aerosol optical properties at 440, 500, 675,
870, and 936 nm. To assure high accuracy the sun photometer was
mounted on a tripod.
Our study includes a careful investigation of the air mass origin and
long-range aerosol transport by means of backward trajectory analysis. The
HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) model was
used for this purpose. Access is provided via the NOAA ARL READY Website
(http://www.arl.noaa.gov/HYSPLIT.php). HYSPLIT is described in detail
by , and .
Data analysis procedure
The data analysis is based on simultaneous observations with polarization
lidar and sun/sky photometer (daytime measurements) and follows the procedure
outlined in . For the correction of Rayleigh
backscattering and extinction contributions to the observed signals we
calculated the air molecule optical properties by assuming standard
atmospheric conditions adjusted to actual surface conditions regarding
temperature and pressure. The results in terms of particle backscatter
coefficients differ by no more than a few percent (typically by 1 %) from
calculation with temperature and pressure profiles taken from numerical
weather prediction model outputs.
The following data analysis comprises 10 steps. The products include the
profiles of the particle backscatter coefficient separately for dust and
non-dust aerosol components, the free tropospheric (FT) column dust and
non-dust lidar ratios, and dust and non-dust-related particle optical depths
of the lofted outbreak plumes. These 10 steps are as follows:
We computed the profile of the particle backscatter coefficient
with Eq. (2) in with the 532 nm AOT from the AERONET
observations as a constraint. The 532 nm AOT follows from the measured 500 nm AOT combined with the
440–675 nm Ångström exponent. The conventional two-layer Fernald
data analysis is
applied. Layer 1 is the PBL reaching up to 350–500 m
height. Layer 2 extends from the top of the PBL to the top of the
lofted FT aerosol layer. By assuming a lidar ratio for the PBL of
SPBL=25–35 sr, we obtain the particle lidar
ratio ST for the entire tropospheric column and
SFT for the free tropospheric column. The PBL over the
coastal city contains a mixture of marine particles showing a lidar ratio of
about 20 sr and urban haze with lidar ratios of about
50 sr. SPBL values around 30 sr are typical for
aerosol mixtures of anthropogenic haze and marine particles
. The PBL AOT contribution is usually about 0.02–0.03, and thus < 10–15 % of the total AOT during dust outbreaks.
The particle linear depolarization ratio is calculated from the
volume linear depolarization ratio by means of the particle
backscatter coefficient profile .
HYSPLIT backward trajectory analysis together with the profiles
of the particle depolarization ratio is used to identify cases with
long-range transport of desert dust from the Middle East deserts or
from northern Africa (Sahara region). 20–30 Middle East dust
outbreaks of different strengths crossed Cyprus during the 4 years
understudy. More than 50 cases of Saharan dust long-range transport
were identified. For each case, we run the HYSPLIT model with respect to the
height of the layers observed over Limassol to identify the source region(s)
for the observed aerosol. Observations with passive satellite sensors and
estimated PBL heights over the potential source regions were also taken into
account in the final decision and identification of contributing aerosol
sources.
From the total set of dust outbreaks we considered for further analysis (in Sect. 4) only cases
in which the particle linear depolarization ratio exceeded 0.15 in the free
troposphere and this for a height range of at least 500 m. In this
way, we obtained 17 Middle East dust cases and 32 Saharan dust cases for our
dust lidar-ratio investigations. A comparably low depolarization ratio
threshold had to be selected to avoid the omission of too many dust layers.
Pure dust layers are rare over Cyprus. Furthermore, fine–mode-dominated dust
layers may show a low depolarization ratio close to 0.15
, but should be included in our data set.
Lofted free–tropospheric desert dust layers (shown as vertical
lines from bottom to top) observed between May 2010 and December 2013. The
brown and orange vertical lines indicate 32 Saharan dust and 17 Middle East
dust cases. The average bottom and top heights (plus the SD) of all detected
dust layers are given as numbers. Median values are given in parentheses.
In the next step, we calculated the geometrical properties of
the remaining dust-containing layers (bottom and top heights). The
height range for which the particle linear depolarization ratio is
> 0.15 in the free troposphere represents the FT dust
layer. Figure shows base and top heights
of all considered dust layers. The base of the FT dust layers
frequently coincided with the top of the PBL. The PBL top height was
determined from the lidar profiles. The first minimum of the first derivative
of the lidar signal normalized to the calculated backscatter signal from
atmospheric molecules was taken in most cases as PBL top height
. However, during dust outbreaks with dust layer base at
PBL top, this method did not work. The PBL top was then usually indicated by
a clear change in the signal strength as well as in the depolarization ratio.
The depolarization
ratio was often enhanced in the PBL, compared to a value around 2–3 % as
expected for a mixture of marine particles and urban haze. The presence of
dust in the PBL does not affect the assumed lidar ratio SPBL
much, because this PBL lidar ratio is still dominated by the marine–urban
aerosol mixture. The lidar ratios for urban haze and desert dust are not very
different so that the additional presence of desert dust may have increased
SPBL towards 35 sr. We took this into account in the uncertainty
analysis below. The top of the dust layers
often reached heights of 4–8 kma.s.l. This is in
agreement with the spaceborne CALIOP lidar study presented by
.
For each case, the layer-mean linear particle depolarization
ratio and the corresponding SD, indicating the variability of the
values from base to top within the layer, was computed. Figure
provides an overview of the obtained layer-mean particle linear
depolarization ratios. In most cases, the mean depolarization ratio
was in the range from 0.17 to 0.28, and indicate aerosol mixtures
with dust contributions to particle backscattering of 50–90 %
according to Fig. 1 of .
By using the height profiles of the particle depolarization
ratio and the particle backscatter coefficient we determine the dust
and non-dust backscatter coefficient profiles
and, based on these profiles, we calculated the FT dust and non-dust column
backscatter values (as given in Eq. 4 in ). In this approach, we assumed
a particle linear depolarization ratio of 0.05 for non-dust
particles and 0.31 for dust particles so that depolarization ratios
< 0.05 and > 0.31 indicate a pure non-dust aerosol and a pure
dust aerosol, respectively .
Mixtures are indicated by depolarization
ratios ranging from 0.05–0.31.
Free-tropospheric dust layer mean particle linear depolarization
ratio of all 32 Saharan dust (brown circles) and 17 Middle East dust cases
(orange circles). The shown SDs (vertical bars) indicate the vertical
variability within each layer in terms of the FT depolarization ratio.
In the retrieval of the FT dust lidar ratio SFT,d
(in the next step 9), we need to assume a FT column lidar-ratio
SFT,s for (spherical) non-dust particles. For this, we
carefully inspected the backward trajectories. If the air masses only
crossed maritime areas before arriving at Limassol, we selected
SFT,s from 25–30 sr. This is for example the
case when dust layers are advected from the Sahara over the polluted Mediterranean Sea to Cyprus in the most
direct way. An example is shown in Sect. 4.1 (30 September 2010). If the dust-laden air masses crossed continental (industrialized,
urbanized) areas at low heights then we selected 50–55 sr for
SFT,s. Section 4.1 also contains an example for this scenario (17 May 2011). If satellite imagery
indicated that the air masses crossed regions with biomass
burning, we selected SFT,s of 65–70 sr in a few cases. This
step of the retrieval introduces a large uncertainty. It was found
that the impact of the SFT,s assumption is low for FT
dust backscatter fractions Dβ>0.8, and high
for dust backscatter fractions Dβ around 0.5, which was frequently the
case. The FT column dust backscatter fraction Dβ is defined
as the ratio of column-integrated dust backscatter coefficient to
column-integrated total (dust and non-dust) particle backscatter
coefficient for the free troposphere from base height R1 to top height
R2:
Dβ=∫R1R2βFT,d(z)dz∫R1R2βFT(z)dz.
By using the selected SFT,s value, we estimated
finally SFT,d, after Eq. (4) in .
Rearrangement of this equation yields
SFT,d=SFT-(1-Dβ)SFT,sDβ.
Finally we compute (a) the FT aerosol particle optical thickness
AOTFT from the particle backscatter coefficient
profile and the column FT lidar ratio SFT, (b) the FT
dust and non-dust particle optical thicknesses
AOTFT,d and AOTFT,s from the
FT dust and non-dust backscatter coefficient profiles and the
respective column lidar ratios SFT,d and
SFT,s, and (c) we estimated the dust fraction DF,
DF=τFT,dτT
with the free-tropospheric dust AOT τFT,d and the tropospheric
AOT τT as measured with the AERONET sun photometer.
Retrieval uncertainties
As outlined in , the uncertainty in SFT,d is
almost completely a function of the uncertainties in the assumed PBL lidar
ratio SPBL and the free tropospheric non-dust aerosol lidar ratio
SFT,s. By varying each of the two input lidar ratios by
±10 sr (around the assumed values), we estimated the mean
uncertainty for each case and each of the two input parameters. In this way,
we determined the mean uncertainties for both input lidar ratios
SPBL and SFT,s for all 49 cases. The uncertainty in
SFT,d for each case is then calculated from the square root of the
quadratic sum of the SPBL and SFT,s error contributions
plus a respective uncertainty term resulting from a 10 % uncertainty in the
separation of the dust and spherical particle components with the
depolarization–ratio technique. These uncertainties are shown as error bars
in the last figure of Sect. 4.2. This error computation yields typical
uncertainties of 13–19 % in the dust lidar ratios.
In this error analysis, we ignore minor contributions by signal noise,
uncertainties in the required Rayleigh extinction and backscatter
calculations, and in the particle reference value, which may increase the
overall relative uncertainty by a further 5–10 %. We also ignore a minor
impact of a few percent by the assumption of the backscatter profile slope in
the lowermost 300 m (region of incomplete laser-beam
receiver-field-of-view overlap, see respective particle backscatter profile
in several figures of Sect. 4). Here, we used the same assumption (linear
decrease of particle backscattering from the surface to 300 m height
by a factor of 2) as in .
Results
We begin the discussion of our 4 year observations with two measurement
examples to explain the different steps of the data analysis in detail
(Sect. 4.1). An overview of all measurements is then presented in Sect. 4.2.
During a few major dust outbreaks, the Raman lidar method
could be applied so that desert-dust lidar ratios could directly be
determined in the dense dust layers, in which the particle depolarization
ratio showed values around 0.3 at 532 nm. In this way, an in-depth
evaluation of our entire analysis concept as described in Sect. 3 could be
performed. Such a case is discussed in Sect. 4.3.
Case studies of 30 September 2010 (Saharan dust) and 17
May 2013 (Middle East dust)
All observational cases considered in our study were conducted at times from
07:00–13:00 UTC. For all cases sun photometer observations (AERONET or with
hand-held MICROTOPS II sun photometer) are available.
Figure shows two cases with pronounced dust layers above
the PBL. According to the backward trajectories in
Fig. , a Saharan dust layer and a Middle East
desert dust plume were monitored. In both cases, the FT AOT of 0.16 and 0.87
strongly contributed to the total tropospheric AOT of 0.22 and 0.91,
respectively.
532 nm particle backscatter coefficient (green) and particle
linear depolarization ratio (black) during a Saharan dust outbreak on 30
September 2010 (left) and a Middle East desert dust outbreak on 17 May 2011
(right). The gray-shaded areas indicate the identified main FT dust layers.
Total tropospheric AOT, AOTFT for the free troposphere,
and several retrieved lidar ratios (SFT, SFT,d) are
given as numbers. The dust fraction was DF = 0.72 (30 September) and 0.96
(17 May). Assumed lidar ratios are SPBL=30sr and
SFT,s=25sr (left panel) and 55 sr (right panel).
The relative uncertainty in the backscatter coefficient and depolarization
ratio is about 10 % .
In the first step, we obtain the height profile of the particle backscatter
coefficient and the FT lidar ratio SFT. The
532 nm particle optical depth measured with the sun photometer is used as
constraint. A boundary-layer lidar ratio of 30 sr is assumed. It is further
assumed that the backscatter coefficient linearly increases by a
factor of 2 from 300 m above ground down to
the surface as mentioned above. In step 2, we determine the particle
depolarization ratio, and subsequently, the backscatter contributions by
non-dust and dust particles (step 7, example is shown in Sect. 4.3 and in
and ), and the backscatter
fraction Dβ (step 8). In step 9, we obtain the FT dust lidar ratio
SFT,d with Eq. (). Here, we need to assume the
non-dust lidar ratio SFT,s. We selected 25 sr
(Fig. left, assuming a slightly polluted marine aerosol
besides desert dust) and 55 sr (Fig. right, assuming
mainly anthropogenic particles in the FT aerosol mixture besides the dust).
Finally, we are able to estimate all optical depth contributions of the
different aerosol components, and the dust fraction DF (step 10).
6-day HYSPLIT backward trajectories arriving at Limassol, Cyprus, at
1500 m (red, top) and 2000 m (red, bottom), 3000 m
(blue), 4000 m (green, bottom), and 4500 m height (green,
top) on 30 September 2010, 09:00 UTC (top) and 17 May 2011, 09:00 UTC
(bottom).
The dust backscatter fractions of Dβ=0.84 and 0.98 indicate that dust clearly dominated the
optical properties in the free troposphere. The layer mean particle
depolarization ratios were high with values of 0.26 (Saharan dust) and
0.30 (Middle East dust). DF was 0.72 (Saharan dust) and 0.96 (Middle East dust).
Note that even at 4.5–5 km height dust is detected over Cyprus on
30 September 2010, although the backward trajectory arriving at 4.5 km
height is permanently above 4.5 km height. This indicates that dust plumes
over northern Africa typically reach heights of up to 4–6 km above ground
during the summer half year . Because all Saharan
trajectories indicate a direct air mass transport from the Sahara towards
Cyprus (across the polluted Mediterranean Sea) and therefore a very low
influence of European haze on the aerosol mixture, we selected a non-dust
lidar ratio for free tropospheric aerosols of SFT,s=25sr
which may indicate the impact of marine particles as well as anthropogenic
aerosols over northern Africa. The resulting dust lidar ratio
SFT,d was comparably low with a value of 47 sr. However,
this value may be representative for the northeastern Saharan region in
agreement with the findings of who noticed a steady
decrease of the lidar ratio from values of 50–60 sr for western
Saharan dust towards 40–45 sr for Middle East dust.
In contrast to the Saharan dust case, a large AOT of 0.91 was observed during
a Middle East dust event on 17 May 2011. An almost pure dust plume reached
from 500 m to 5 km height. According to the backward
trajectories (see Fig. , lower panel), all air
masses which crossed Cyprus between 2–5 km height were close to the
ground over the Middle East region. This explains the high dust load at all
heights up to 5 km in this case. Non-dust aerosol contributions to the
observed aerosol mixture were related to European haze, marine particles over
the Mediterranean, and anthropogenic aerosols over the southwestern Asian
states according to the backward trajectories. As a consequence, we selected
an FT non-dust lidar ratio of SFT,s=55sr. However, at
these dust-dominating conditions, this estimate (and the related
uncertainties) has almost no influence on the result in terms of dust lidar
ratio SFT,d, which was 43 sr and thus close to the values
found by and . Unfortunately we have
no AERONET-derived lidar ratio for these two days because of problems with
the sun photometer. Only hand-held MICROTOPS sun photometer observations of
the AOT could be performed on these days.
Statistics: Middle East vs. Saharan dust lidar ratios
The initial goal of the study was to provide lidar ratios for pronounced
desert dust layers with dominant backscattering by mineral dust particles.
However, as mentioned above, such conditions are rare. Dust layers mixed with
anthropogenic aerosol and marine particles prevail over Cyprus (see
Table ). Almost pure dust layers are observed when
Dβ>0.8 (see Eq. ). For these
conditions, our retrieval delivers the most reliable results and the relative
uncertainty in the dust lidar ratio is low with values down to 10 %. In
Figs. and overviews of
our data analysis for all 17 major Middle East and 32 Saharan dust outbreaks
are presented. Figure shows the Middle East dust
lidar ratios. For the observed six cases with dust backscatter fractions of
Dβ>0.8 and corresponding layer mean particle depolarization ratios
of > 0.25 (April 2011 to May 2012), SFT,d ranges from
42–46 sr. For the less dust-dominated 11 cases with Dβ from
0.22–0.7 most dust lidar ratios were found between SFT,d=35
and 40 sr. Here the uncertainty in the SFT,d values
introduced by the non-dust lidar ratio assumptions is high (of the order of
10–15 sr). The mean Middle East dust lidar ratio of all 17 cases is
41.1±4.3sr.
(Top) Retrieved FT 532 nm lidar ratio SFT
(black diamonds), dust-related lidar ratio SFT,d (orange
circles), and assumed non-dust lidar ratio SFT,s (gray
triangles) for 17 Middle East dust outbreaks, (center) mean
532 nm particle linear depolarization ratio
δFT for the FT dust layer, and (bottom) 532 nm AOT dust fraction DF (orange
pentagons, Eq. ), and FT dust backscatter fraction
Dβ (gray squares, Eq. ).
Figure shows the retrieval results for the Saharan
dust outbreaks. For the six cases found with Dβ>0.8 we obtain lidar
ratios from 47–65 sr with four values in the range from
55–60 sr. We found 14 cases (out of the 32 Saharan dust cases) with
layer mean particle depolarization ratios > 0.25. For these cases, the
lidar ratios accumulate in the range from 50–55 sr. In contrast to
the Middle East dust events, we assumed low FT non-dust lidar ratios
SFT,s because the air masses have a comparably long travel
distance across the Mediterranean Sea towards Cyprus and the anthropogenic
aerosol level over North Africa is lower than over the southwestern Asian
region. Most FT dust backscatter fractions Dβ and Saharan DF values
were in the range from 0.4–0.8 and 0.4–0.7, respectively, which clearly
indicates that non-dust aerosol types always contributed to the observed
particle backscatter and extinction properties. The mean value of the 32
Saharan dust lidar ratios is 52.7±6.1sr. This lidar ratio is
close to the value of 55 sr found by for pure
Saharan dust cases.
Same as Fig. , except for Saharan
dust outbreaks.
Dust-related lidar ratio SFT,d as shown in
Fig. (orange, Middle East dust) and
Fig. (brown, Saharan dust) with error bars
(standard deviation) caused by realistic ±10 sr uncertainties in the
lidar-ratio input parameters SPBL and SFT,s, and a
10 % uncertainty in the separation of non-dust and dust backscatter
coefficient. The solid and dashed (orange and brown) horizontal lines
indicate the mean value of the 17 Middle East and 32 Saharan dust lidar
ratios and the mean uncertainty (mean error bar length), respectively.
Figure provides an impression of the uncertainty in
the lidar-ratio retrieval. Realistic uncertainties in the most important
input parameters are simulated to produce the shown error bars. Although the
error bars show uncertainties of the order of 5–12 sr and the corresponding
mean SDs (indicated as dashed horizontal lines) in
Fig. are large, a difference between the Saharan and
Middle East dust lidar ratios is visible. According to the mean values
(horizontal solid lines), the Middle East dust lidar ratios are, on average,
lower by 12 sr than the Saharan dust lidar ratios.
Table provides additional insight into the aerosol
mixing characteristics of the evaluated aerosol scenarios. There were only
minor differences between the listed values for Middle East and Saharan dust
outbreaks. Comparably high Ångström exponents were measured over Cyprus
with the AERONET sun photometer during the dust events. These column
observations always include the more polluted lowest parts of the atmosphere
over the island. Pure dust extinction (and AOT) usually causes an
Ånsgtröm exponents of 0.0–0.2 . Also
the fine mode fraction, FMF, is high compared to values of 0.1–0.25 for
strong dust outbreaks . The dust AOT fraction DF
and the dust backscatter fractions Dβ are, on average, much lower
than for clearly dust-dominating cases with values of > 0.8.
Table also contains statistics on the derived
Saharan and Middle East dust lidar ratios, separately for Dβ>0.8
and when considering the full data sets.
Desert dust layer statistics for 49 outbreaks (2010–2013): AERONET
Ångström exponent (440–870 nm) and fine-mode fraction (ratio of
500 nm fine-mode AOT to AOT) for the tropospheric vertical column (T), and
lidar-derived 532 nm dust AOT for the free troposphere (FT), dust fraction DF
(Eq. ), the dust-layer mean particle linear
depolarization ratio (532 nm), the backscatter fraction Dβ
(Eq. ), and the different lidar ratios (for Middle
East, M. E., and Saharan dust). Mean value and standard deviation (SD) are
given together with the range of observed values (from minimum to maximum
value).
ParameterMeanSDMinMaxÅngström exponent (T)0.750.420.041.63Fine-mode fraction (T)0.440.130.180.68Dust AOT (FT)0.200.200.041.15Dust AOT fraction, DF (FT)0.640.210.180.99Depolarization ratio (FT)0.240.040.170.35Backscatt. fraction, Dβ (FT)0.620.220.190.99Lidar ratio (M.E.), Dβ>0.84414346Lidar ratio (M.E.)4143348Lidar ratio (Sah.), Dβ>0.85664765Lidar ratio (Sah.)5364365
It is worth to note that values in Table are in
agreement with a study by . During the UAE2 campaign,
performed in the United Arab Emirates and the adjacent Arabian Gulf region in
August–September 2004, they found, on average, Ångström exponents of
0.5–0.77 (440–870 nm spectrum) for the 14 AERONET stations with
slightly higher values for coastal and island sites compared to stations in
the center of continental desert regions. Mean 500 nm FMF values
ranged from 0.2–0.8. These values were mainly caused by strong fine-mode
particle sources from petroleum extraction and processing facilities. Only
during rather strong dust events (over the desert stations) the
Ångström exponent dropped to typical dust values of 0.22–0.31 and the
FMF were in the range from 0.24–0.29. According to and
it was hard to observe pure dust optical properties, even in
desert-dominated areas.
Case study of 23 May 2013: Raman lidar observation
We checked the quality of the results obtained with the method described in
Sect. 3 for cases where we could include the Raman signals in the aerosol
analysis. The Raman lidar technique makes use of both, the elastic
backscatter signals at 532 nm and the nitrogen Raman signals measured
at 607 nm wavelength, and provides height profiles of the particle
backscatter and extinction coefficients and thus a direct vertically resolved
observation of the desert dust lidar ratio in pronounced dust layers
, if the depolarization ratio is around 0.3 at 532 nm
which is the case here. In the following, we compare the findings obtained
with the Raman lidar method and with our approach (Sect. 3) which is based on
elastic-backscatter signals only.
Saharan dust outbreak advecting dust particles between 2 and
6 km height towards Limassol, Cyprus, on 23 May 2013. Range-corrected
1064 nm backscatter signals (in arbitrary units, A.U.) are shown. Red
features above 7 km indicate ice clouds.
7-day HYSPLIT backward trajectories arriving at Limassol, Cyprus, at
1750 m (red), 3000 m (blue), and 4500 m height
(green) on 23 May 2013, 19:00 UTC.
Mean vertical profiles of the 532 nm particle extinction
coefficient, backscatter coefficient, and lidar ratio for the observational
period from 17:47–20:50 UTC on 23 May 2013. The Raman lidar method is
applied. Vertical signal smoothing lengths of 600 m (below
1.1 km height), 1500 m (1.1–2.8 km height), and
2100 m (above 2.8 km height) are applied before computing the
extinction coefficients and lidar ratios. The signal smoothing length is
750 m for the shown backscatter coefficient profile. Total AOT (given
as number in the left panel) and layer mean values of the lidar ratio for the
0.7–0.85 km height layer (influenced by marine and local haze
particles), the 0.86–1.5 km layer (influenced by European haze) and
for the pure dust layer (2.1–5.2 km height range) are given as
numbers. Error bars provide the uncertainty (standard deviation) by signal
noise.
Figure shows the arrival of the thick Saharan dust plume
over Limassol in the morning of 23 May 2013. According to the backward
trajectories arriving above 2 km height at 19:00 UTC (see
Fig. ), the lofted Saharan dust layer between 2.5 and
5.5 km height originated from the central parts of the Sahara. Over
about 4–5 days, dust could be collected by the air masses before traveling
to Cyprus within 1–2 days. The layer below 2 km height contained
a mixture of Saharan dust, European haze, and maritime particles according to
the red backward trajectories for the arrival height of 1750 m.
Mean profiles (3-h
average) of the 532 nm particle backscatter coefficient (left,
green), particle linear depolarization ratio (left, black), dust backscatter
coefficient (right, red), and non-dust particle backscatter coefficient
(right, blue). The elastic-backscatter lidar method (explained in Sect. 3) is
applied to the same observation as shown in Fig. .
Retrieved column lidar ratios for the total troposphere (ST), the
free troposphere (SFT), and derived from the AERONET data
(SA for the 13:00–14:00 UTC period) for the total tropospheric
column after are given as numbers in the left panel.
SPBL of 30 sr is assumed for the height range up to
500 m. The retrieved dust-related lidar ratio SFT,d and
the assumed non-dust lidar ratio (SFT,s) are given in the right
panel together with the dust AOT (red number), non-dust AOT (blue number) for
the total troposphere, and the FT dust backscatter fractions Dβ
(column dust backscatter to total particle backscatter in the free
troposphere above 500 m height). Again, the relative uncertainty in
the particle backscatter coefficient and depolarization ratio is 10 %, and
of the order of 20 % for the dust-related backscatter coefficient
.
An almost constant aerosol layering was observed above 2000 m
from 17:30–20:50 UTC (see Fig. , second
observational period after 17:30 UTC). We used this period for
a detailed inspection of the optical properties of the Saharan dust
plume by applying the Raman lidar method.
Figure shows the mean profiles of the
532 nm particle backscatter and extinction coefficients for
the 17:47–20:50 UTC time period, and the respective height profile
of the lidar ratio. The 532 nm dust-related optical depth was close to
0.38. As can be seen, in agreement with the backward trajectories, the
lidar ratio shows typical Saharan dust values between
50–60 sr around the center of the dust layer at
3.5–4.0 km height. In the layer with European haze
between 1.0 and 1.5 km height, the lidar ratio is close to
50 sr, and decreases to values below 30 sr at heights
<1.0km. As mentioned, values of 25–35 sr are typical for
a mixture of anthropogenic and maritime particles .
In Fig. , the products obtained with our retrieval scheme
(Sect. 3) are presented. Because after sunset no AERONET data are available,
we used the lidar-derived total particle AOT of 0.45 as a constraint in
step 1 (see Sect. 3). The AOT was determined from the extinction profile in
Fig. (left panel) down to 1 km height and the
backscatter profile below 1 km multiplied by a lidar ratio of
30 sr for the lowermost 1 km of the troposphere. The
laser-beam RFOV overlap function prohibits a trustworthy extinction profiling
by means of the Raman-lidar method below about 500–700 m. As a result of
step 1, we obtain the column lidar ratio of SFT=57sr for
the free troposphere and of ST=55.8sr for the total
tropospheric column. This value is close to the AERONET-derived total
tropospheric lidar ratio of SA=58sr obtained from the
afternoon sun photometer observations (13:00–14:00 UTC). The tropospheric
AOT was 0.33 at 500 nm to that time, measured during periods without cirrus
clouds.
In step 2 of the data analysis, the particle linear depolarization ratio
shown in Fig. is computed. By means of the profiles of
the particle backscatter coefficient and depolarization ratio the profile of
the dust backscatter coefficient can then be calculated (step 7, red profile
in Fig. ) so that the column dust backscatter value for
the free troposphere and the respective dust fraction Dβ can be
calculated (given as number in Fig. ). The profiles for
the particle backscatter coefficient in Figs. and
slightly differ because of different methods (Raman-lidar
versus Fernald method) used in the two figures and the different signal
smoothing lengths (750 m versus 45–90 m).
To obtain the dust-related lidar ratio SFT,d (steps 8 and 9), we
use Eq. (). Disregarding the clear evidence that we
observed a pronounced dust layer above 2 km on 23 May 2013, we split
the troposphere into the PBL (reaching up to 500 m) and the free
troposphere (from 500–7000 m height). This was generally done for
all cases of the 4 year period discussed below. We assumed a PBL lidar ratio
of SPBL=30sr and a non-dust lidar ratio
SFT,s=50sr for the free troposphere accounting for the
anthropogenic particles mainly confined to the layer from 500–2000 m
height.
The FT column dust backscatter value Dβ of 0.834 in
Fig. indicates a dominating dust contribution to the
measured optical effects. DF was also 0.83. The FT column dust lidar ratio
SFT,d was found to be close to 58 sr and thus close to
the dust layer mean lidar ratio of 56 sr derived from the Raman lidar
observations (see Fig. ). The influence of uncertainties
in the assumed PBL lidar ratio SPBL on the retrieved dust lidar
ratio SFT,d is low because the AOT of the PBL is less than
10 % of the total AOT. The uncertainty introduced by an error in the FT
non-dust lidar ratio SFT,s of 10 sr results in an
uncertainty of <5sr in the derived SFT,d value.
Figures and corroborate that our
retrieval scheme presented in Sect. 3 allows us to determine dust-related
lidar ratios with good accuracy.
Comparison with AERONET observations of dust lidar ratios
Only a limited number of published lidar-ratio studies is available for
comparison. As mentioned in the introduction, most lidar studies did not take
the non-dust particle contribution to the observed mixed-aerosol lidar ratios
into consideration. and extensively
discuss Saharan and Middle East dust lidar ratios based on AERONET
observations. As also mentioned, these column-integrated measurements include
the contribution of PBL aerosols (marine particles, local anthropogenic haze,
local road and soil dust) and are frequently affected by long-range transport
of non-dust aerosol (fire smoke, lofted marine particles, anthropogenic
aerosol).
During events with a strong dust load with AOTs exceeding 0.4,
found mean values for the desert dust lidar ratio at
532 nm wavelength of 56.4 sr (over North African AERONET
sites), 57.8 sr (Non-Sahel African stations), 55.1 sr
(African Sahel sites), and 47.2 sr (AERONET stations in Middle East
desert areas) for dust-dominated summer months from May to September in the
years of 2006 to 2009. During very strong dust events (pure dust cases) with
fine-mode volume fraction FVF < 0.05 and thus negligible impact of
anthropogenic particles on the computations the lidar ratios were on average
about 10 % lower.
Lidar-derived total tropospheric lidar ratio ST vs.
respective AERONET-derived lidar ratio SA after
. 14 Saharan dust events and 6 Middle East dust cases,
observed over Limassol in the 2010–2013 period, could be analyzed. The solid
line shows the 1:1 correlation line.
analyzed the main dust periods from 1994 to 2004
over eastern Asian, Middle East, and North African AERONET stations
and found mean values of 39–41 sr for several Middle East
sites and 35–38 sr for Saharan sites for the wavelength of
550 nm. used an older, less sophisticated
AERONET inversion technique which may explain the differences with
respect to the results of .
Figure provides a comparison between
lidar-based (ST) and AERONET-based (SA) retrieval
results for the total tropospheric column. Six Middle East dust events and 14
Saharan dust cases are available for this comparison. Only this limited
number of AERONET data could be analyzed. Most of the data are
quality-assured AERONET data (level 2.0). However, the majority of AERONET
observations were performed at AOTs clearly below 0.4 so that the uncertainty
is high . None of the shown cases passed the
pure-dust criteria (FVF < 0.05). As mentioned in the introduction, the
problem with fine-mode haze is that these particles lower the overall
refractive index. The fine mode is more optically efficient than the coarse
mode, and increases the lidar ratio when compared to pure-dust scenarios. The
impact of anthropogenic aerosol is less dominant in the case of lidar
retrievals (Fernald data analysis) at 532 nm wavelength. Coarse mode
particles widely control the measured optical effects during dust outbreak
situations. This is consistent with the results in
Fig. . The tropospheric column lidar ratios
retrieved from the AERONET observations are in most of the selected dust
outbreak cases larger than the lidar-derived lidar ratios. If we further keep
in mind that the dust lidar ratio SFT,d is, on average,
8 ± 4 sr higher than the tropospheric lidar ratio ST for
the considered 14 Saharan dust scenes according to the lidar data analysis
and lower by about 3 ± 2 sr for the six Middle East dust cases, one
may conclude that it is almost impossible to retrieve reliable dust lidar
ratios at sites in the Mediterranean region from AERONET observations, or
mode general, outside the deserts.
Conclusions
A study of dust particle lidar ratios for two major desert dust regions and
sources for atmospheric dust has been presented. The particle lidar ratio is
an important quantity in the description of atmospheric aerosols and aerosol
mixtures in the framework of aerosol typing efforts. It is a key input
parameter in the retrieval of height profiles of climate relevant particle
extinction coefficient, derived from widely used elastic backscatter lidars
including the spaceborne lidar CALIOP. Present and upcoming spaceborne lidar
activities need lidar-ratio information for all relevant aerosol types for
a consistent interpretation of the space-lidar-derived aerosol and cloud
products around the globe.
We found a significant difference with mean values of 53±6 and 41±4sr for Saharan and Middle East desert dust, respectively, which is
in good agreement with literature values. A recently introduced polarization
lidar technique for the extraction of dust lidar ratio
information from elastic-backscatter lidar observations was applied to the
4-year Cyprus data set.
The study corroborates earlier findings that desert dust plumes contain
a mixture of desert dust and a variety of other aerosol components (marine
particles, fire smoke, anthropogenic haze). Lofted pure desert dust plumes
are more the exception than the rule. From this point of view it is a rather
difficult effort to select the optimum lidar ratio in the analysis of CALIOP
observations over deserts and adjacent regions. The measurement of the
particle depolarization ratio is of crucial importance in order to be able to
identify and quantify the dust contribution to the aerosol load and more
generally for a high-quality aerosol typing.
Acknowledgements
The authors thank the CUT Remote Sensing Laboratory for their
support. The work was co-funded by the European Regional
Development Fund and the Republic of Cyprus through the Research
Promotion Foundation (PENEK/0311/05). The research leading to these
results has also received scientific support from the European Union
Seventh Framework Programme (FP7/2011–2015) under grant agreement
no. 262 254 (ACTRIS project). The authors gratefully acknowledge
the NOAA Air Resources Laboratory (ARL) for the provision of the
HYSPLIT transport and dispersion model as well for the provision of
Global Data Assimilation System (GDAS) data used in this
publication. We are also grateful to AERONET for high-quality
sun/sky photometer measurements. Edited by: M. Tesche
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