ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus PublicationsGöttingen, Germany10.5194/acp-16-11581-2016Saharan dust long-range transport across the Atlantic studied by an airborne
Doppler wind lidar and the MACC modelChouzaFernandofernando.chouza@dlr.deReitebuchOliverhttps://orcid.org/0000-0002-8503-0094BenedettiAngelahttps://orcid.org/0000-0002-9971-9976WeinzierlBernadetthttps://orcid.org/0000-0003-4555-5686Institut für Physik der Atmosphäre, Deutsches Zentrum für
Luft- und Raumfahrt (DLR), Oberpfaffenhofen, GermanyEuropean Centre for Medium-Range Weather Forecasts, Reading, UKFaculty of Physics, University of Vienna, Boltzmanngasse 5, 1090
Vienna, AustriaFernando Chouza (fernando.chouza@dlr.de)20September2016161811581116004May201619May20162September20168September2016This 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/16/11581/2016/acp-16-11581-2016.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/16/11581/2016/acp-16-11581-2016.pdf
A huge amount of dust is transported every year from north Africa
into the Caribbean region. This paper presents an investigation of this
long-range transport process based on airborne Doppler wind lidar (DWL)
measurements conducted during the SALTRACE campaign (June–July 2013), as
well as an evaluation of the ability of the MACC (Monitoring
Atmospheric Composition and Climate) global aerosol model to
reproduce it and its associated features. Although both the modeled winds
from MACC and the measurements from the DWL show a generally good agreement,
some differences, particularly in the African easterly jet (AEJ) intensity,
were noted. The observed differences between modeled and measured wind jet
speeds are between 5 and 10 m s-1. The vertical aerosol distribution
within the Saharan dust plume and the marine boundary layer is investigated
during the June–July 2013 period based on the MACC aerosol model results and
the CALIOP satellite lidar measurements. While the modeled Saharan dust
plume extent shows a good agreement with the measurements, a systematic
underestimation of the marine boundary layer extinction is observed.
Additionally, three selected case studies covering different aspects of the
Saharan dust long-range transport along the west African coast, over the
North Atlantic Ocean and the Caribbean are presented. For the first time,
DWL measurements are used to investigate the Saharan dust long-range
transport. Simultaneous wind and backscatter measurements from the DWL are
used, in combination with the MACC model, to analyze different features
associated with the long-range transport, including an African easterly wave
trough, the AEJ and the intertropical convergence zone.
Introduction
Every year, huge amounts of Saharan dust originating from north Africa is
transported across the Atlantic into the Caribbean region and the north of
South America. The transport, mainly occurring during the summer season,
starts with the uplifting of dust by turbulent convection and low-level winds
with high speed (Bou Karam et al., 2008), is the amount of emitted dust
regulated by different factors like the soil humidity and vegetation. Once
lofted, the dust is dispersed into a deep mixed layer, reaching altitudes of
up to 6 km during summer (Messager et al., 2010). The dominating easterly
winds west advect the dust-laden air masses, which are undercut by the cooler
and moister air from the marine boundary layer (MBL) as they reach the west
African coast, forming an elevated layer of relatively warm, dry and dust-laden
air called Saharan air layer (SAL). As the SAL leaves the African continent,
its lower and upper bounds are defined by a strong inversion at approximately
1.5 km and a relatively weaker inversion at around 5 to 6 km, respectively
(Prospero and Carlson, 1972; Karyampudi et al., 1999).
Along its life cycle, the airborne dust interacts with the environment in
different ways. During its long-range transport phase, the dust modifies the
radiative budget, acts as cloud and ice nuclei and is observed to modify the
cloud glaciation process (e.g., Seifert et al., 2010). Various mechanisms
have been proposed to explain the controversial influence of the SAL on the
evolution of African easterly waves (AEWs) into tropical storms (e.g., Dunion
et al., 2004; Evan et al., 2006; Lau and Kim, 2007). Regularly mineral dust
is impacting aviation, in particular in regions near dust sources, by
inducing poor visibility (Weinzierl et al., 2012). As it deposits, the
Saharan dust can affect the air quality (Prospero, 1999) and serves as
source of nutrients for plankton and the Amazon basin (Yu et al., 2015).
Several studies were conducted during the last years to provide further
insight in the previously mentioned processes, including field campaigns and
long-term studies based on models, satellite, airborne and ground-based
measurements. Among others, we can mention the African Monsoon
Multidisciplinary Analysis (AMMA) and NASA-AMMA (NAMMA) campaigns (Zipser et
al., 2009) conducted in 2006, focused on the analysis of the AEW and its
evolution into tropical cyclones, and the Saharan Mineral Dust Experiments 1
and 2 (SAMUM-1 and SAMUM-2) (Heintzenberg, 2009; Ansmann et al., 2011)
conducted in 2006 and 2008, respectively, which were designed to investigate
the Saharan dust size distribution and morphology, and the relation with the
optical and radiative properties in the west African region. Additionally,
during April–May 2013, a shipborne lidar onboard the research vessel
Meteor conducted a transatlantic cruise between the Caribbean and the west coast of
Africa in order to characterize the mixtures of the Saharan dust with biomass
burning aerosols and evaluate the change in its optical properties as result
of the long-range transport process (Kanitz et al., 2014). While field
campaigns provide an intensive set of observations in relatively small regions
and time intervals, satellite observations provide regular observations with
a limited set of parameters. On the other hand, global and regional models
are frequently used in dust long-range transport studies and forecasting
(e.g., Schepanski et al., 2009; Kim et al., 2014; Gläser et al., 2015), as
they provide valuable information to interpret the observational data
collected by campaigns and satellite measurements. The performance evaluation
of these models, like during the intercomparison initiative AeroCom (Aerosol
Comparison between Observations and Models) (Kinne et al., 2003), is then not
only vital to improve the models but also to know the limits and accuracy of
the conclusions extracted based on these models.
The Saharan Aerosol Long-range Transport and Aerosol-Cloud-Interaction
Experiment (SALTRACE; Weinzierl et al., 2016) performed in June–July 2013 was
framed in this context. SALTRACE was planned as a closure experiment to
investigate the Saharan dust long-range transport between Africa and the
Caribbean, with a focus on the dust aging and deposition processes and the
characterization of its optical properties. The campaign dataset includes a
set of measurements from the ground-based aerosol lidars BERTHA (Backscatter
Extinction lidar-Ratio Temperature Humidity profiling Apparatus) (Haarig et
al., 2015) and POLIS (portable lidar system) (Groß et al., 2015), in situ
and sun photometer instruments deployed on Barbados (main SALTRACE
super-site), Cabo Verde and Puerto Rico and airborne aerosol and wind
measurements from the DLR (Deutsches Zentrum für Luft- und Raumfahrt)
research aircraft Falcon similar to the measurements done during SAMUM
(Weinzierl et al., 2009, 2011). For the first time, an airborne Doppler wind
lidar (DWL) was deployed to study the dust transport across the Atlantic
Ocean, including its interaction with island-induced gravity waves (Chouza et
al., 2016).
In this study, this unique set of DWL wind and extinction measurements along
the main dust transport acquired during SALTRACE are used, in combination
with dropsondes (DSs) and CALIPSO (Cloud–Aerosol Lidar and Infrared Pathfinder
Satellite Observations) satellite measurements, to analyze the Saharan dust
long-range transport and to evaluate the performance of the MACC (Monitoring
Atmospheric Composition and Climate) aerosol global model to reproduce
different associated atmospheric features, like the African easterly jet
(AEJ) and its interaction with the SAL, the AEWs and the ITCZ (intertropical
convergence zone), among others. Such a comparison provides not only an
insight about the current model capabilities, which is of great relevance
for model-based studies, but the opportunity to identify the model
weaknesses and provide a starting point for future improvements. This type
of evaluation has never been performed with a dataset that includes both
meteorological fields as well as atmospheric composition fields. Although
there is no direct feedback from the atmospheric composition fields onto the
meteorological fields (temperature and winds) as the run was not coupled
through interactive radiative processes, the aerosols are transported and
advected by the winds. Hence, an evaluation of both winds and aerosols in the
SAL is a very effective way to understand how well the model represents this
natural phenomenon.
The paper is organized as follows. Section 2 presents a brief description of
the datasets used for this study, including an evaluation of the DWL accuracy
based on collocated dropsonde measurements. Section 3 provides a comparison
between the DWL and CALIPSO measurements with the backscatter and winds from
the MACC model in the west African and Caribbean regions for the time period
of the SALTRACE campaign. Section 4 presents three case studies with relevant
features of the Saharan dust long-range transport. Finally, the summary and
relevant conclusions are presented in Sect. 5.
Observations and model data
During the SALTRACE campaign, the DLR Falcon research aircraft conducted 31
research flights between 10 June and 15 July 2013, with most of the flights
concentrated close to the west African coast and the Caribbean (Fig. 1). The
DLR Falcon was equipped with a set of instruments for in situ particle
measurements, a DWL and dropsondes. Ground-based measurements were conducted
in Cabo Verde, Puerto Rico and Barbados. Two aerosol lidars and sun
photometers were installed on the west coast of Barbados, at the Caribbean
Institute for Meteorology and Hydrology (CIMH) (13∘08′55′′ N,
59∘37′30′′ W; 110 m .s.l.), while a sun photometer and a set of
ground-based in situ instruments were deployed at Ragged Point, Barbados
(Kristensen et al., 2016). A complete list of the instruments involved in the
campaign can be found on the SALTRACE website
(http://www.pa.op.dlr.de/saltrace/instruments.html) and an overview of
SALTRACE is given in Weinzierl et al. (2016). The following subsections
describe in detail the characteristics of the datasets used for this study,
including the used fields from the MACC model.
DLR Falcon flight tracks during SALTRACE. Dropsondes'
launch positions are indicated with black crosses. Black boxes indicate the
regions which were used in this study (west Africa: 0–30∘ N; 10–30∘ W and Caribbean:
0–30∘ N; 50–70∘ W). Colored
tracks indicate measurement flights included in this study. Black dashed
tracks indicate transfer flights which are not used in this work.
Comparison between DSs and DWL horizontal
wind vector measurements. A total of 22 DWL/dropsonde profiles are included
in this comparison, totaling 1329 speed–direction pairs.
Dropsondes
A set of 34 Vaisala RD93 dropsondes, operated in conjunction with the NCAR
AVAP system (Busen, 2012), were launched from the Falcon during SALTRACE,
providing vertical profiles of temperature, relative humidity and wind speed
with a vertical resolution of approximately 10 m. According to the
manufacturer, the horizontal wind measurements have an accuracy of
0.5 m s-1 rms (root mean square) (Vaisala, 2009), where this accuracy
definition incorporates both the systematic and the random error of the
measurements. Figure 1 indicates the geographical position at which each
dropsonde was launched.
Doppler wind lidar
The coherent DWL deployed on the DLR Falcon 20 research aircraft during
SALTRACE is based on a CLR Photonics instrument (Henderson et al., 1993)
combined with a two-wedge scanner and acquisition system developed at DLR
(Köpp et al., 2004; Reitebuch, 2012). The system operates at a wavelength
of 2.02254 µm, with a pulse duration full width at half maximum
(FWHM) of 400 ns, a pulse energy of 1–2 mJ and a repetition frequency of
500 Hz.
Comparison between 22 DSs and the
corresponding collocated DWL horizontal wind vector measurements. Panels (a, c) show the mean
of the DS and DWL wind speed and direction measurements,
respectively; (b, d) show the difference between the mean DWL and DS wind speed and
direction, respectively (dots, black), together with the corresponding 1000 m moving average (solid, black) and the standard deviation of the difference
(shaded, grey); (e) shows the number of compared measurement points as a function of the
altitude.
When mounted on an aircraft, the system can be operated in two modes: the
conical scanning and the nadir pointing mode. The conical scanning mode
consists of 24 lines of sight (LOS) in a conical distribution with an
off-nadir angle of 20∘ and a staring duration of 1 s per LOS
direction. The inversion algorithm (Smalikho, 2003; Weissmann et al., 2005)
is then applied to the 24 LOS measurements from each scan to retrieve
horizontal wind speed vector with a horizontal resolution of around 6–10 km
(depending on the aircraft speed) and a vertical resolution of 100 m. On the
other hand, the nadir pointing mode can be used to retrieve vertical wind
measurements with a horizontal resolution of approximately 200 m (Chouza et
al., 2016). Both modes allow, by means of an adequate calibration, the
retrieval of backscatter and extinction coefficients with a horizontal
resolution of approximately 200 m and a vertical resolution of 100 m
(Chouza et al., 2015). As in the case of CALIOP, the backscatter and
extinction retrievals form the DWL measurements require assuming a lidar
ratio for each aerosol type. For the retrievals presented in this study, a
lidar ratio of 55 sr was used for the Saharan dust, while 30 and 35 sr were
used for the marine boundary layer and the marine-dust mixed layer,
respectively. To determine the accuracy of the DWL backscatter and extinction
retrieval, the DWL profiles were compared to measurements from the
ground-based aerosol lidar POLIS and the CALIPSO satellite, exhibiting a good
agreement, with systematic differences lower than 20 % in the backscatter
coefficient retrievals.
During SALTRACE, the DWL totalized 75 h of measurements, from which 56 h
were performed in scanning mode. The atmospheric conditions present during
most of the campaign flights, characterized by a large dust load between
the ground and 4 to 6 km, provided excellent backscatter conditions for the DWL.
In order to evaluate the accuracy of the horizontal wind speed and direction
measurements performed by the DWL, a set of vertical profiles were compared
to those retrieved from collocated dropsonde observations. Only DWL profiles
with less than 1 min of difference with respect to the dropsonde launch
time were included in the comparison, while the dropsonde measurements were
vertically averaged to match the DWL vertical resolution. The results,
summarized in Figs. 2 and 3, indicate a systematic difference (bias) of
0.08 ms-1 and a standard deviation of 0.92 ms-1 for the wind
speed difference between the DWL and the dropsondes measurements. The bias
and the standard deviation does not exhibit significant dependence with the
measurement altitude or measured wind speed, while the amount of points
available for comparison as a function of altitude illustrates the average
DWL coverage observed during SALTRACE. The mean wind speed measured by the
dropsondes and the DWL exhibits a maximum between 4 and 6 km, associated with
the presence of the AEJ. For the case of the wind
direction, the mean difference is 0.5∘ and the standard deviation is
10∘, with values of around 5∘ between the ground and 6 km, and
higher values between 6 and 8 km. The mean direction values between the ground
and 6 km are between 90 and 100∘, compatible with the easterly dust
transport direction. The DWL performance evaluation shows results which are
generally consistent with those obtained in the North Atlantic region during
the Atlantic THORPEX Regional Campaign (A-TReC) in November 2003 (Weissmann
et al., 2005), with slightly higher standard deviation for the wind direction
measurements and smaller differences in the wind speed for the SALTRACE
dataset.
CALIOP
The Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP), the primary
instrument of the CALIPSO satellite, is a two-wavelength
polarization-sensitive lidar launched in 2006 by NASA (Winker et al., 2009).
Based on a three-channel receiver, one for backscatter measurements at 1064 nm
and two for the parallel and cross-polarized backscatter at 532 nm, the
lidar is able to provide aerosol type classification, aerosol optical depth
(AOD) and extinction coefficient vertical profiles. This allows a
characterization of the mean Saharan dust vertical distribution close to the
source and in the Caribbean region during the SALTRACE campaign, as well as
an evaluation of the model to reproduce it. The dust vertical distribution
is a key parameter which has a direct influence in the radiative transfer
calculations and the atmospheric stability.
For this study, the level 2 (V3.3) dataset was used
(https://www-calipso.larc.nasa.gov/search/). This dataset includes
aerosol type classification, total column cloud, aerosol and stratospheric
optical depth and extinction profiles with a vertical resolution of 60 m
and a horizontal resolution of 5 km. In order to include only the most
accurate measurements retrieved by CALIOP, a series of masks were applied to
the data. First, profiles for which the cloud and stratospheric optical
depth was not zero were masked out. A second mask was applied to keep only
bins with the “Volume description Bit” equal to 0 (“clean air”) or 3
(“aerosols”), cloud–aerosol discrimination (CAD) score is less than -80 and
quality control (QC) flag is equal to 0 or 1. Finally, the AOD was derived from
the vertical integration of extinction profiles where no data points were
missing.
Since the CALIOP extinction coefficient retrieval relies on assumed lidar
ratios, any systematic difference in the lidar ratio will directly affect the
derived extinction profiles. An estimation of the systematic errors
associated with the CALIOP extinction retrieval in the Saharan dust transport
region is presented in Tesche et al. (2013). Based on a comparison between a
ground-based Raman lidar deployed on the Cabo Verde region during SAMUM-2 and
different CALIOP overpasses, this study concluded that CALIOP extinction
profile retrievals of the SAL exhibit an average systematic underestimation
of around 15 % during the summer season, while in some cases the difference
reached 30 %. This systematic underestimation of CALIOP extinction
retrievals can be explained by the fact that the CALIOP retrieval scheme
assumes a dust lidar ratio of 40 sr, while Raman lidar measurements
conducted during SAMUM-2 (Groß et al., 2011) and SALTRACE (Groß et
al., 2015) indicate values close to 55 sr.
According to Wandinger et al. (2010), the dust lidar ratio of 40 sr used by
the CALIOP algorithms is an effective value which takes into account the effect
of multiple scattering and leads to backscatter coefficient profiles which
are in good agreement with ground-based lidar measurements. Nevertheless, the
use of this effective dust lidar for the calculation of the SAL extinction
coefficients leads to their systematic underestimation. Although different
techniques to correct this systematic error were proposed (e.g., Wandinger et
al., 2010; Amiridis et al., 2013), the CALIOP retrievals shown in this study
are presented in their original form. In cases where this effect could alter
the derived conclusions, relevant comments are included (Sect. 3.3).
The MACC model
As part of the formerly Global Monitoring for Environment and Security (GMES)
initiative (now Copernicus), intended to improve our understanding of the
environment and climate change, the European Centre for Medium-Range Weather
Forecasts (ECMWF) developed the MACC model, a forecasting and reanalysis
system for aerosols, greenhouse gases and reactive gases based on the
assimilation of satellite and in situ observations (Hollingsworth et al.,
2008). This project extends the capabilities of the operational ECMWF
Integrated Forecast System (IFS) by including a new set of forecasted
variables. A detailed description of the model and parameterizations is given
in Morcrette et al. (2009), while the assimilation process is explained in
Benedetti et al. (2009) and a companion paper by Mangold et al. (2011)
provides a first validation of the model results. Additional validation of
the aerosol MACC products in northern Africa and the Middle East can be found in
the work by Cuevas et al. (2015).
The MACC aerosol parameterization is based on the LOA/LMD-Z (Laboratoire
d'Optique Atmosphérique/Laboratoire de Météorologie
Dynamique-Zoom) model (Boucher et al., 2002; Reddy et al., 2005) and includes
five types of tropospheric aerosols: dust, sea salt, organic, black carbon
and sulfate. The first two correspond to natural sources and are represented
in the model by three size bins for dust (0.03–0.55, 0.55–0.9 and
0.9–20 µm) and other three for sea salt (0.03–0.5, 0.5–5 and
5–20 µm). Currently, stratospheric aerosols are based on the
climatology already included in the operational IFS as no prognostic fields
are included in the model.
The sea salt emission parameterization is based on the model 10 m winds and a
source function based on the works by Guelle et al. (2001) and Schulz et
al. (2004). The emission, calculated for a relative humidity of 80 %, is
integrated for the three sea salt model bins previously described. Emissions
of dust depend on the 10 m wind, soil moisture, the UV-visible component of
the surface albedo and the fraction of land covered by vegetation when the
surface is snow free, adapted from Ginoux et al. (2001). A correction of the
10 m wind to account for gustiness is also included (Morcrette et al.,
2008). The model includes aerosol transport by diffusion, convection and
advection treated with a semi-Lagrangian approach.
A set of different removal processes are included in the model, namely, dry
deposition, sedimentation and wet deposition. Wet and dry deposition were
directly adapted from the LOA/LMD-Z model, while the sedimentation scheme
follows the work from Tompkins (2005a) on ice sedimentation.
One of the distinctive characteristics of the MACC model is the full
integration of the aerosol model to the forecasting model. The 4D-Var system
regularly employed in the IFS was extended to assimilate AOD observations
from the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and
Aqua satellites at 550 nm, including the total aerosol mixing ratio as
an additional control variable (Benedetti et al., 2009). This assimilation
process is based on the adjustment of the model control variables (e.g.,
initial conditions) in order to minimize a cost function. This function
depends on the difference between the observations and its model equivalent,
and the relative weight assigned to each of them based on the estimated
observational and model uncertainties. In the case of the MODIS AOD
assimilation, the observations are compared with a model-derived AOD. The AOD
observation operator derives the optical depth based on precomputed aerosol
optical properties and model relative humidity for the aerosol species
included in the model. After assimilation, the model output represents the
best statistical compromise between the model background (forecast running
without assimilation) and observations.
The MACC reanalysis was not available for 2013, having stopped in 2012, hence
the operational run at the time of the campaign (June–August 2013) was used
in this study. The model run with a time resolution of 3 h at T255L60, which
corresponds to a horizontal resolution of approximately
0.8∘× 0.8∘ (78 km × 78 km) and 60
vertical levels, with the top at 0.1 hPa. The assimilation window is 12 h.
Among others, the MACC model provides as output vertically resolved total AOD
(natural plus anthropogenic aerosols) corresponding to each of the layers
bound by the model levels. Since this study focuses on the comparison of
the model with lidar observations, extinction coefficient profiles were
calculated dividing the layer AOD by the layer thickness.
MACC model evaluation
The wind profile is a key parameter which determines the characteristics of the Saharan dust long-range transport. Although many studies were conducted to address the
specific role of the trade winds, the AEJ and the
AEWs in the dust lifting, transport and deposition,
many questions remain still open (Ansmann et al., 2011; Schulz et al.,
2012). As the Saharan dust transport path is mainly over the North Atlantic
Ocean, the number of assimilated wind observations into a global model is
very limited, which in turn affects their accuracy. Since many long-range
transport studies use wind information provided by models, the evaluation of
the accuracy of these simulations is of great importance. In this context,
the wind dataset acquired by the DWL during SALTRACE provides a unique
opportunity to evaluate the wind fields by the MACC model which are
ultimately responsible for the Saharan dust long-range transport.
Comparison between the DWL and the MACC model horizontal
wind measurements for the flights performed in the west African (right) and
Caribbean (left) regions. Panels (a, c) show the mean of the DWL and MACC wind speed
measurements in the Caribbean and west African region, respectively; (b, d)
show the difference between the mean DWL and MACC wind speed in the Caribbean and
west African region, respectively (dots, black), together with the standard
deviation of the difference (shaded, grey). Panels (e, g) are the same as (a, c) but for the
wind direction. Panels (f, h) are the same as (b, d) but for wind direction. Panels (i, j)
show the distribution of compared points as a function of altitude in the west African
(right) and Caribbean (left) regions, respectively.
Comparison of CALIOP and MACC zonally averaged AOD and
extinction coefficient for June–July 2013 in the regions of the study
defined in Fig. 1. Panels (a, b) indicate CALIOP and MACC AOD zonal mean; (c, d) CALIOP
extinction coefficient zonal mean; (e, f) MACC extinction coefficient zonal
mean. Panels (g, h) show the difference between the zonally averaged extinction coefficient
measured by CALIOP and simulated by MACC.
The assimilation of AOD from MODIS into the MACC model constrains the total
aerosol mass, which is a great advantage considering the large uncertainties
associated with the dust emission quantification (Huneeus et al., 2011).
Nevertheless, since the assimilated variable is a column-integrated
measurement, no independent constraints are introduced for each aerosol type
and their vertical distributions. For that reason, the ability of the model
to simulate the vertical distribution of each aerosol type still has to be
evaluated. While CALIPSO provides regular backscatter and extinction
coefficient measurements, which can be used to evaluate the model output and
eventually provide data for assimilation, the aerosol detection sensitivity
of CALIOP is limited compared to ground-based or airborne lidars. The DWL
extinction profiles, simultaneously retrieved with the horizontal wind
measurements, allow an independent evaluation of the simulated aerosol
vertical distribution as well as the possibility to study the interaction
between wind and aerosol distributions.
Since most of the flights were conducted either close to the west coast of
Africa or in the Caribbean region, two regions were defined to study the
model results with the DWL and CALIOP dataset. The first region is located at
the west coast of Africa (0–30∘ N, 10–30∘ W), while the
second region encloses the flights in the Caribbean (0–30∘ N,
50–70∘ W).
Method
Because the MACC model provides an output every 3 h, the horizontal
resolution is approximately 80 km (T255) and the vertical levels are not
homogeneously distributed as a function of altitude, a re-binning and
interpolation process is necessary to compare the model output with the DWL
and CALIOP observations. First, the observational data are re-binned to a grid
with a horizontal resolution of 80 km and a vertical grid defined according
to the 60 model levels for the US Standard Atmosphere, 1976
(http://www.ecmwf.int/en/forecasts/documentation-and-support/60-model-levels).
Only bins with more than 50 % of the expected amount of values are used,
otherwise, the bin is filled with a missing value flag. Then, the MACC model
is linearly interpolated in space and time to match the re-binned observation
data grid. Once observations and model data are in a comparable grid,
different comparison techniques were applied. In the case of the horizontal
winds, the re-gridded DWL measurements and model output corresponding to
flights in each region were studied to evaluate the ability of the model to
reproduce the main features of the wind in these two regions.
In the case of the CALIOP extinction retrievals, 2 months of measurements
corresponding to June and July 2013 were included in the comparison due to
the relatively low amount of AOD and extinction retrievals available after the
quality check process (Sect. 2.3). The measurements of CALIOP inside the
regions defined in Sect. 3 and the corresponding MACC profiles were then,
after re-gridding, zonally averaged in each region to provide a statistically
relevant result. Extinction coefficient and AOD are reported by CALIOP and
MACC at 532 nm.
Horizontal wind
The spatially averaged DWL wind retrievals were compared with the
interpolated MACC winds in the west Africa and Caribbean regions defined in
Sect. 3. In the case of the west African region, a total of seven flights
conducted between 11 and 17 June 2013 are included in the comparison, which
corresponds to 1202 speed–direction pairs. In the Caribbean region, 13
measurement flights conducted between 20 June and 11 July 2013 are compared
with a total of 1532 speed–direction measurement pairs. In order to
investigate possible correlations between the altitude and speed and the
differences between the lidar and the model, the mean and standard deviation
of the difference between the DWL and MACC as a function of the altitude, the
number of compared measurements and the mean speed and direction
corresponding to the African and Caribbean regions are shown in Fig. 4.
In the case of the west African region, Fig. 4c and g indicate a good
agreement in the profile shape between the mean measured and simulated wind
speed and direction, respectively, with the altitude of the wind maxima and
minima being well reproduced by the model. Regarding the wind speed
magnitude, Fig. 4d indicates an underestimation of the wind speed by the
model between 0.5 and 6 km, with a maximum difference of
5 m s-1 at around
5 km. This is approximately coincident with the altitude of the maximum
simulated (13.2 m s-1) and measured wind speeds (17 m s-1),
which corresponds to the presence of the AEJ in the region. The
underestimation of the AEJ by the ECMWF model was already reported in
previous studies, like the one conducted during the JET2000 campaign in
August 2000 (Thorncroft et al., 2003; Tompkins et al., 2005b). The
comparison, performed against a set of dropsonde measurements, indicated a
similar difference profile, with a maximum difference of around
5 m s-1. As in the case of the comparison between the lidar and the
dropsondes, the distribution of points included in the comparison (Fig. 4j)
is representative of the lidar coverage, which in turn is determined by the
aerosol load distribution and cloud coverage. Most of the measurements are
available below 6 km, in coincidence with the SAL upper bound.
The left row of Fig. 4 presents the results for the Caribbean region. In
contrast to the previous case, some differences in the mean wind speed and
direction structures are recognizable in Fig. 4a and e. Both the DWL and the
model show a similar behavior below 0.8 km, characterized by an increasing
wind speed as a function of altitude, reaching its maximum at 0.8 km. Although
the simulated and measured wind gradients are similar, the simulated speeds
are around 1 m s-1 larger than the measured ones. Above the boundary
layer, the model shows a decrease in the wind speed and a general
underestimation of the wind speed compared to the DWL measurements. As in the
previous case, the distribution of compared points as a function of the
altitude (Fig. 4i) is correlated with the dust load and cloud coverage. The
strong reduction of measurement points above 4 km is related with the
general decrease in the altitude of the SAL top boundary as the dust moves
westward.
Aerosol extinction coefficient
In order to analyze the accuracy of the MACC model vertical aerosol
distribution, the extinction coefficient profiles were compared to those
retrieved by CALIOP during the months of June and July 2013 for a wavelength
of 532 nm. An overview of the comparison is presented in Fig. 5, where the
zonal mean of the simulated and measured AOD and extinction coefficient is
presented, together with the difference between the model and measurement,
for the west African and Caribbean regions indicated in Fig. 1.
Figure 5a and b show the zonal mean of the AOD for the two regions. The
simulated and measured AOD close to the African coast (Fig. 5b) exhibit a
similar bell shape, with the model maxima located at 18.5∘ N and the
weighted mean of the CALIOP AOD at 15∘ N. In the Caribbean region,
the model and the CALIOP measurements show a better agreement, with the
center of the dust plume located at 16∘ N in both cases. The change
in the AOD between both regions, a reduction by one half due to the transport
between the African coast and Barbados, is in relatively good agreement.
Nevertheless, the AOD north and south of the dust plume show consistent
higher values in the model. This bias is consistent with the study presented
in Kim et al. (2013), which showed that MODIS AOD values corresponding to
clean marine aerosols approximately double the AOD reported by CALIOP.
While a relatively good agreement of the measured and simulated AOD is expected
due to the constraints introduced by the assimilation of MODIS measurements,
the vertical distribution of the dust, which plays a crucial role in
atmospheric radiative transfer studies (Zhang et al., 2013), has to be
evaluated. The zonal averaged extinction coefficient measured by CALIOP in
west Africa (Fig. 5d) shows an elevated dust plume between 5 and
30∘ N, with its lower bound at 1 km and its upper bound at
approximately 6 km. Below 1 km, an aerosol-loaded boundary layer is
recognizable, with higher extinction coefficients below the SAL, probably due
to dust entrainment into the atmospheric boundary layer (ABL). In the
Caribbean, the dust plume top sinks to around 4 km, and the extinction
decreases to about half of the values measured close to the source region. As
in the previous case, the ABL shows higher extinction below the SAL than
north or south of it; the characteristic wedge shape as we move from higher
to lower latitudes can also be noted.
The modeled aerosols' vertical distribution close to the dust source region
is presented, together with the difference with the CALIOP measurements, in
Fig. 5f and h, respectively. The modeled dust plume shows relatively good
agreement in spatial distribution with respect to the CALIOP measurements,
extending between 10 and 30∘ N. Coincident with the AOD measurements
presented in Fig. 5b, the simulated plume is slightly displaced in the north
direction and exhibits a higher maximum extinction at around 2 km. This
displacement, clearly visible in the difference plot, could lead to a change
in the interaction between the SAL and the AEJ, which in turn will promote
different dust transport patterns. However, the major difference between
CALIOP and MACC is visible in the boundary layer and above the SAL. In the
ABL, the model strongly underestimates the extinction coefficient. The model
average extinction in the ABL (< 1 km) is 0.045 km-1 in the
Caribbean region and 0.065 km-1 in the west Africa region, while the
CALIOP average retrievals are 0.145 and 0.13 km-1, respectively.
Although the CALIOP retrievals of the ABL extinction are affected by the
uncertainty in the lidar ratios and the underestimation of the SAL
extinction, these effects cannot explain the large discrepancy observed
between the model and the CALIOP retrieval.
The underestimation of the SAL extinction due to an underestimation of the
dust lidar ratio would lead to an underestimation of the CALIOP backscatter
in the boundary layer, which in turn would lead to an even larger CALIOP
retrieval. On the other hand, since the aerosol load found in the ABL
below the SAL is dominated by a mixture of marine aerosol and dust, the
expected average CALIOP lidar ratio will oscillate between the lidar ratio
values corresponding to pure marine (20 sr) and pure dust (40 sr). In the
case of the retrievals presented in Fig. 5c and d, the average lidar ratio
used by CALIOP for the calculation of the ABL (< 1 km) extinction
coefficient was found to be between 33 sr in the west African coast region
and 37 sr in the Caribbean region. These values are similar to those
presented in Groß et al. (2016), where the average lidar ratio observed
in the ABL was 26 ± 5 sr, with values ranging from 22 ± 5 sr in
the case of pure marine aerosol to 35 ± 3 sr for the case of a
dust-dominated ABL. These results, corresponding to June–July 2013, are in
agreement with the CALIOP retrievals presented in Cuevas et al. (2015), where
a similar difference in the ABL extinction in the west African region
(M'Bour) was also observed during the summer seasons of 2007 and 2008.
The comparison of the CALIOP extinction retrievals and the corresponding
model results indicate a relatively small overestimation of the SAL extinction
by the model. Even if the CALIOP extinction retrievals of the SAL are
multiplied by a correction factor of 1.375 (55 sr/40 sr) to take into account
the underestimation of the lidar ratio by CALIOP discussed in Sect. 2.3, most
of the MACC results are still above the CALIOP retrievals (not shown). The
SAL AOD derived from MACC is still larger than the SAL AOD derived from
CALIOP extinction. Based on SAL lower and upper bounds between 2 and 5 km
in the Caribbean and between 1 and 6 km in the African region, the SAL AOD
values based on MACC are 50 and 10 % larger than the CALIOP retrievals,
respectively. Additionally, although the pure dust lidar ratio used for
CALIOP is 40 sr, sometimes the algorithm identifies part of the SAL as
polluted dust, with an associated lidar ratio of 55 sr. This leads to an
average lidar ratio larger than 40 sr, which in turn leads to a higher
extinction and to a smaller systematic bias. If instead of correcting the
CALIOP extinction retrievals by using the correction factor suggested by
Wandinger et al. (2010) the mean underestimation reported by Tesche et
al. (2013) from Table 5 is used (1/0.858=1.165), the differences are even
larger.
Above the SAL, the model indicates the presence of a very thin aerosol layer
extending up to 20 km which is not visible in the CALIOP measurements. Since
the extinction coefficients predicted by the model above the SAL are in the
order of the sensitivity threshold of CALIOP (∼ 0.01 km-1), a
direct validation of these features is not possible only by means of CALIOP
measurements. Recent studies (e.g., Rogers et al., 2014) indicate that the
lack of detection of weakly backscattering aerosol layers in the free
troposphere leads to an underestimation of approximately 0.02 in the CALIOP
column AOD. This effect can partially explain the systematically lower CALIOP
AOD values observed in Fig. 5a and b. In order to further investigate this
feature, a comparison of the model with the DWL measurements performed
during the transfer flight between Cabo Verde and South America is presented
in the next section.
Characteristics of the Saharan dust long-range transport
The study presented in the previous section provided a general overview of
the performance of the model. In this section, a set of three selected
flights form the SALTRACE campaign are used to provide a deeper insight into
some characteristic features of the Saharan dust long-range transport
mechanism. The first case study, corresponding to a flight between Cabo
Verde and Dakar, is included to further investigate the differences observed
in the AEJ intensity as well as the ability of the model to reproduce the
generation of AEWs. The second case study presents measurements over the
North Atlantic Ocean, which provides a second comparison of the AEJ speed
and the opportunity to analyze the interaction of the dust with the ITCZ.
Finally, the third case presents the measurements of a dust outbreak in the
Caribbean region after the long-range transport across the North Atlantic.
In order to facilitate the interpretation of these case studies, the
corresponding synoptic situation is presented in Fig. 6. These charts, which
include the wind direction and wind speed at 700 hPa and the total AOD, are
based on the MACC model results. Additionally, in order to situate the case
studies within the context of the SALTRACE campaign, a Hovmöller diagram
with the MACC meridional winds and AOD averaged between 0 and 30∘ N
is presented in Fig. 7. This diagram simplifies the visualization of some
features associated with the Saharan dust long-range transport, like the dust
outbreaks, the AEWs and the passage of the tropical storm Chantal. A period
of 3 to 5 days between outbreaks and a transport time of around 5 days
between Dakar and Barbados can be easily noted in the AOD diagram (Fig. 7,
right). In order to highlight the strong correlation of these outbreaks with
the propagation of AEWs, the wave troughs relevant for the presented case
studies are indicated in Fig. 7.
Horizontal winds at 700 hPa and AOD derived from the MACC model for
the regions corresponding to the three cases: (a) 12 June 2013
09:00 UTC, flight between Sal and Dakar; (b) 17 June 2013
15:00 UTC: flight between Cabo Verde and South America; (c)
11 July 2013 18:00 UTC: flight between Barbados and Puerto Rico. The
sections of the flight tracks shown in Figs. 8, 9 and 11 (blue, solid), wind
streamlines (in m s-1) and AOD (grey color scale) are shown.
MACC model meridional wind (left) and AOD (right) presented in form
of a Hovmöller diagram averaged for latitudes between 0 and
30∘ N and 700 hPa pressure level. The flights corresponding to each
case (black, thick, solid), the longitude of Dakar and Barbados (black,
dashed), relevant AEWs troughs (black, solid) and the position of the
tropical storm Chantal (black, crosses) are indicated.
DWL measurements (left column) and MACC model (right
column) along the measurement track for the flight on 12 June 2013. Panels (a, b)
show the extinction coefficient; (c, d) the horizontal wind speed; (e, f) the horizontal wind
direction; (g, h) the zonal wind component; (i, j) the meridional wind component.
Regions where no atmospheric signal is available (e.g., below clouds, low
laser energy, low aerosol load) are colored white in panels (a), (c), (e) and grey
in panels (g), (i).
Dust plume at the west African coast
On 12 June 2013 the Falcon performed a research flight at the west coast of
Africa, departing from Cabo Verde at 08:52 UTC and landing in Dakar at
12:08 UTC. The model winds at 700 hPa are presented, together with the AOD,
in Fig. 6a. Wind speeds around 15 to 25 m s-1 can be observed between
10 and 15∘ N, which is compatible with the presence of the AEJ. The
inverted V-shape disturbance in the AEJ flow in the Dakar region, suggests
the passage of an AEW during the observation period. The observation of the
change in the meridional wind flow direction at pressure levels between 850
and 700 hPa is a typical way to detect AEWs, with the wave trough
defined as the point of zero meridional wind (change from northerly to
southerly flow) (e.g., Reed et al., 1977). According to this definition, the
wave trough can be recognized at 17∘ W during the observation period
(AEW 1; Fig. 7). This wave, sampled during the flight on 12 June 2013,
propagated further to the west at an approximate speed of 8∘
(∼ 900 km) per day, reaching Barbados on 17 June 2013. Several other
waves can be also observed in the presented period. All wave cases propagate
westward with a similar speed, which gives a mean travel time of
around 5 days between the African west coast and Barbados. This result is
consistent with observations and previous studies on the AEW behavior
(Zipser et al., 2009).
The AOD for the Dakar region presented in Fig. 6a shows a dust-loaded air
mass on the leading edge of the AEW and a region of less dust load behind the
trough. Satellite images (not shown), indicate the presence of strong
convective activity behind the trough, which is a typical feature of the AEWs
(Fink et al., 2003; Cifelli et al., 2010). The propagation of the dust
outbreak as it leaves the west African coast can be observed in Fig. 7
(right). According to the model results, this outbreak was the largest one
(highest AOD) during the SALTRACE observation period. The modeled passage of
the AEW seen in Fig. 6a is coincident with a reduction in the amount of
exported dust behind the trough (AEW 1). This could be the result of the
enhanced wet deposition associated with the convective cell activity
(Desboeufs et al., 2010).
The DWL measurements corresponding to the selected case study are presented
in Fig. 8. The extinction coefficient profiles derived from the DWL
measurements presented in Fig. 8a are in qualitative agreement with the
distribution simulated by the model (Fig. 8b), with an elevated dust plume
between 1 and 6 km riding on top of the marine boundary layer as it leaves
the African continent (17∘ W). These results are compatible with the
BERTHA ground-based measurements carried out in Cabo Verde during the
SAMUM-2b campaign (Tesche et al., 2011) in summer 2008, where a 0.5–1.0 km
deep maritime boundary layer topped by a 4–5 km deep mineral dust layer was
typically observed. As has been noted in the previous section, the model
underestimates the extinction of the marine boundary layer and overestimates
the extinction of the SAL. The average SAL extinction retrieved from the DWL
for altitudes between 1 and 6 km and longitudes between 16.17 and
15∘ W is 0.11 km-1, while the corresponding MACC average
extinction is 0.4 km-1. This difference is much larger than the
systematic error of ±20 % estimated for the DWL backscatter
retrievals. Although in this case the compared values are extinction
coefficients and not backscatter coefficients, the lidar ratios used in the
DWL retrieval (55 sr for the SAL, 35 sr for the marine-dust mixed layer and
30 sr for the marine boundary layer) are in agreement with those found in the
literature and small local variations cannot explain the large difference
observed in this case study.
DWL measurements (left column) and MACC model (right
column) along the measurement track for the flight on 17 June 2013. Panels (a, b) show the extinction coefficient; (c, d) the extinction coefficient plotted in logarithmic
scale; (e, f) the horizontal wind speed; (g, h) the horizontal wind direction. The
white color indicates regions were no atmospheric signal is available (e.g.,
below clouds, low laser energy, low aerosol load). The dropsondes' launch
time (dashed, red) is indicated in (a) and (b).
The enhanced cloud coverage associated with the previously mentioned
convective system can be seen starting at 09:35 UTC (behind the wave trough)
as white regions in the DWL extinction plot (Fig. 8a). These clouds, visible
at altitudes between 6 and 8 km, completely blocked the DWL laser, which in
turn led to missing data below them (white regions). An associated decrease
in the aerosol load in this clouds region can also be noted in the DWL
retrievals starting at 09:47 UTC. Since the MACC model extinction product
does not include clouds, the enhanced cloud coverage cannot be seen in
Fig. 8b.
The horizontal wind profiles retrieved by the DWL and simulated by MACC are
presented as speed–direction and u–v components in Fig. 8c–j. The
presence of the AEJ can be recognized on both: the DWL speed measurements
(Fig. 8c) and the corresponding MACC speed profiles (Fig. 8d) for altitudes
between 3 and 6 km. The magnitude of the jet is, nevertheless, strongly
underestimated by the model by almost 10 m s-1, which is above the
mean difference of 5 m s-1 observed in the previous section for the
mean of all flights in the AEJ region. The underestimation of the AEJ impacts
not only in the amount of transported Saharan dust but also in the
propagation and development of AEWs (Leroux and Hall, 2009). Below 2 km, a
land–sea breeze system located over Dakar (-15∘ N, 18∘ W)
can be recognized in the DWL and MACC wind speed–direction profiles. The
passages of the AEWs are easier to recognize when the wind vector is
presented as u and v components. The u component of the measured (Fig. 8g)
and simulated (Fig. 8h) wind profiles is dominated by the AEJ, while the v
component captures the wave trough observed in Figs. 7 and 8. Both the
position of the trough and the amplitude of the wind meridional component are
well reproduced by the model. A strong coincidence between the dust plume
border and trough is also visible in both cases.
Dust long-range transport across the Atlantic
The second case corresponds to a flight between Cabo Verde and South America
performed on 17 June 2017 between 13:24 and 17:21 UTC. This flight gives the
opportunity to study the interface between the SAL and the ITCZ, as well as
the AEJ, the tropical easterly jet (TEJ) (Chen and Loon, 1987) and the
ability of the model to reproduce them. The synoptic situation, presented in
Figs. 6b and 9, shows a dust plume laterally bound by an AEW trough located
at 15∘ W (AEW 2, Fig. 7) and an AEW crest located at 40∘ W
and south bound by the ITCZ, located between 3 and 8∘ N. In the
DWL measurements, the ITCZ can be recognized by the presence of strong
convective activity and the associated development of convective clouds at
6 km (white areas) and between 2 and 7∘ N.
Temperature (upper row) and water vapor mixing ratio
(lower row) measured by the dropsondes launched during the flight on 17 June 2013 (dots, red) and the corresponding MACC model values (crosses, black).
Same as Fig. 8, but for the flight on 11 July 2013.
Zonal and meridional wind components are omitted.
The DWL and MACC extinction and horizontal wind profiles are presented in
Fig. 9. The MACC model is able to reproduce the main characteristics of the
aerosol vertical distribution. North of the ITCZ, a dust plume with its upper
bound at 6 km is visible by both the model and the DWL. In the case of the
DWL measurements, the SAL is lower bound by a characteristic wedge-shaped
marine boundary layer topped by low-level clouds, while in the case of the
MACC model, the lower bound seems to be lower and constant as a function of the
latitude. The model and dropsonde temperature and water vapor mixing ratio
vertical profiles presented in Fig. 10 show a generally good agreement,
although a consistent underestimation of the model temperature of around
2∘ K below 1 km can be observed. In the case of the first dropsonde
(DS 1), the temperature and mixing ratio profiles are compatible with the
differences observed by the DWL, with the model showing an ABL top inversion
approximately 500 m below the measured one. Although in the case of the DWL
the coverage in the ITCZ is limited by the presence of clouds, the dust load
south of it is clearly reduced by the effect of wet deposition on both the
DWL and the MACC model simulation. As in the previous section, the model
indicates the presence of aerosols above the SAL, especially in the ITCZ
region, which is not captured by the lidar. Since the extinction coefficients
shown by the model are quite low, an additional set of extinction plots in
logarithmic scale were added to highlight this feature (Fig. 7c and d). The
average extinction coefficient shown in Fig. 7d for an altitude of 9.2 km
range from 0.003 km-1 between 14:35 and 14:50 UTC to 0.01 km-1
between 15:05 and 15:35 UTC. Because the DWL relies on the atmospheric
aerosols for the retrieval of wind measurements, such change in the aerosol
load should result in a change in the wind retrieval coverage. Nevertheless,
this is not observed in Fig. 7e and g, where the wind retrieval coverage is
limited to a band of approximately 2 km below the Falcon, independently of
the geographical location. While the extinction coefficients shown by MACC
above the SAL are normally below 0.01 km-1, its detection by the DWL,
especially close to the Falcon, would be expected in the case of a real
feature. The aerosols shown by the model in the upper troposphere are likely
to be an artifact introduced by the model in order to compensate the lack of
extinction in the ABL and hence balance the assimilated AOD from MODIS.
The horizontal wind speed profiles are presented in Fig. 7e and f for the DWL
and the MACC model, respectively. The AEJ, visible in the DWL measurements on
the north of the ITCZ for altitudes 2 km and almost 7 km can also be seen
in the model, although slightly displaced to the north and with a lower mean
speed. Below 1.5 km, northerly and southerly trade winds are visible in the
model and DWL profiles. A third feature, located to the south of the ITCZ and
at around 10 km is the TEJ. While the position of the TEJ is well captured
by the model, the DWL measurements suggest a model underestimation of the
wind speed of around 5 m s-1.
Dust plume in the Caribbean region
The synoptic situation presented in Figs. 6c and 7 shows a dust-loaded air
mass reaching Barbados on 11 July 2013. This Saharan dust outbreak was the
first to reach Barbados after the passage of the tropical storm Chantal over
the Barbados region, between 8 and 9 July 2013. According to the results from
the MACC model, this outbreak left the African continent 5 days before, on
6 July 2013, together with an AEW. In contrast to the 12 June and 17 June
cases, the dust moved behind the AEW (AEW 3; Fig. 7) trough in this case and
almost no dust was visible in front of the trough. This change is likely to
be due to the influence of the tropical storm Chantal and the associated wet
deposition which can be clearly seen in Fig. 7 as a decrease in the AOD. On
11 July 2013, two research flights were performed. This case study focuses on
the second flight, which departed from Barbados at 18:04 UTC and landed in
Puerto Rico at 21:05 UTC. The DWL extinction and horizontal wind
measurements are presented, together with the MACC model, in Fig. 10. A
comparison between the DWL retrievals for the first flight on 11 July 2013
and the corresponding ground-based POLIS measurements is presented as part of
the DWL calibration validation in Chouza et al. (2015).
As in the previous cases, the modeled SAL shape and extinction is in relatively
good agreement with the DWL measurements, suggesting an adequate treatment of
the Saharan dust long-range transport and deposition processes by the model.
Both measurements and models show a dust plume with a descending upper bound
and a rising lower bound as it moves westwards together with higher
extinction coefficients in its lower half. The model results corresponding to
the measurements conducted close after the takeoff from Barbados shows an
aerosol plume extending from approximately 1.7 km up to 5 km bound by two
temperature inversions (not shown). This is compatible with the
radio-sounding and POLIS ground-based lidar measurements presented in
Groß et al. (2015), where the lidar measurements conducted on
11 July 2013 (23:00–24:00 UTC), 5 h after takeoff, show the SAL
between 1.5 and 4.8 km. In the same way as the model, the sounding
temperature profiles exhibit inversions at its lower and upper bounds. In
coincidence with previous measurements, the ABL extinction is strongly
underestimated by the model and a thin aerosol layer above the SAL is
modeled, but not seen by the DWL.
As can be seen in Fig. 6c, the general circulation in the region is dominated
by the Bermuda high pressure system, which leads to an anti-cyclonic flow
over the Caribbean (Fig. 6c). The modeled winds are in relatively good
agreement with the measurements. The high wind speeds found between 4 and
5 km are underestimated by the model by approximately 3 m s-1, while
its wedge shape and direction are well reproduced. The influence on the lee
side of Dominica and the Guadeloupe islands can be seen in the DWL retrievals for
latitudes between 15 and 16∘ N. These islands, with surfaces of 750
and 1600 km2 and elevations of up to 1447 and 1467 m, respectively,
introduce relatively large disturbances in the low-level flow. This effect,
characterized by a relatively sudden decrease in the wind speed and a change in
the direction for altitudes below 1.5 km cannot be captured by the MACC
model due to its relatively coarse grid of 80 km.
Summary and conclusions
Aerosol global models are of key importance not only for environmental and
climate change studies but also as air quality monitoring tools. The
evaluation of the model capabilities by mean of comparisons with
observations is of great importance for improvement of the models. In this
study, the ability of the MACC model to reproduce the Saharan dust
long-range transport across the Atlantic Ocean was investigated by means of
a comparison with DWL, CALIOP and dropsonde observations conducted during
SALTRACE. For the first time a DWL was used to characterize the Saharan dust
transport and its associated features.
First, the horizontal wind vector retrievals by the DLR airborne DWL during
SALTRACE were evaluated with a comparison with collocated dropsonde
measurements. The comparison shows a very good agreement, with a
DWL–dropsonde mean difference of 0.08 m s-1 and a standard deviation
of 0.92 m s-1 for the wind speed. For the case of the wind direction,
the mean difference was 0.5∘ and the standard deviation 10∘.
These estimated accuracies are in agreement with previous studies (e.g.,
Weissmann et al., 2005).
The second part of this work focused on the evaluation of the MACC model
using the wind and aerosol backscatter measurements from the DWL in
combination with CALIOP extinction profiles and dropsondes. Two evaluation
regions were defined: one close to the Saharan dust source on the west coast
of Africa and a second one in the Caribbean region. Although the wind
comparison shows a generally good agreement in both regions, a systematic
underestimation of the AEJ wind speed was observed in the region close to
west Africa. Since the AEJ is one of the main Saharan dust advection
mechanisms, its underestimation would lead to a wrong estimation of the
amount of dust being transported. Additionally, since the AEJ and the
associated vertical and horizontal wind shear serve as an energy source for the
AEWs, the correct modeling of jet speed and position is crucial to correctly
model the AEWs propagation and evolution. As indicated by Tompkins et
al. (2005), a change in the aerosol radiative effect climatology can alter
the AEJ speed. Thus, the observed underestimation in the AEJ wind speed could
be partially due to the lack of radiative coupling between winds and aerosols
in this MACC operational analysis run in 2013. Follow-up studies could
explore this coupling of the aerosol and wind fields in a manner similar to
Rémy et al. (2015), specifically for the SAL. Such a study would allow,
in combination with the results presented in this work, to estimate the
importance of an interactive radiative coupling to correctly simulate the AEJ
intensity, the Saharan dust vertical distribution and its long-range
transport.
Based on CALIOP extinction profiles, the model average aerosol vertical
distribution was evaluated in both regions. Although a generally good
agreement was observed in the position and geometry of the SAL, a strong
systematic underestimation of the marine boundary layer aerosol content was
observed in both regions. Since the MACC model assimilates MODIS AOD
measurements, the total model AOD is generally in good agreement with CALIOP
measurements. A slight overestimation of aerosol in the upper troposphere
was observed in the model, which is likely to be an artifact introduced by
the model to compensate the lack of aerosol in the marine boundary layer and
thus match the assimilated MODIS AOD. An additional confirmation of this
explanation could be investigated in future studies by means of a comparison
between the model and in situ aerosol measurements.
The good agreement between the modeled and measured AOD observed in this
study serves as an indication of the potential of satellite data
assimilation in global aerosol models. Currently, studies are being
conducted in order to assimilate CALIOP attenuated backscatter vertical
profiles in order to constrain the modeled aerosol vertical distribution. In
a similar way, previous studies showed an improvement of modeled winds after
the assimilation of airborne Doppler wind lidar measurements (Weissmann et
al., 2007). Future satellite missions like Aeolus (ESA, 2008) and EarthCARE
(Illingworth et al., 2014) will provide a whole new set of wind and aerosol
vertical profile measurements which are expected to lead to a significant
improvement in weather prediction and global climate models, especially in
regions where observations are sparse.
In addition to the average wind and extinction comparison in both regions,
three case studies were presented. These cases, which correspond to the
initial, middle and final phase of the Saharan dust long-range transport
process, allowed us to investigate the characteristic features of the Saharan
dust transport and the ability of the model to reproduce them. The DWL
measurements carried out close to the west African coast show a SAL extending
from 1 km up to 6 km and the AEJ at altitudes between 3 and 6 km, with
speeds of up to 25 m s-1. Additionally, the passing of an AEW and the
associated convective activity allowed us to investigate its effect on the
dust distribution and transport pattern. As the dust is transported west over
the Atlantic Ocean, the top of the SAL sinks, while its bottom rises. This
typical SAL feature was confirmed by the DWL retrievals corresponding to the
second and third case studies. The measurements conducted over the Atlantic
Ocean, corresponding to the second case study, showed a strong decrease in
the dust load in the ITCZ as well as a rise in the lower edge of the SAL for
low latitudes. The wind measurements carried out over the Atlantic revealed
the presence of the AEJ north of the ITCZ, with speeds between 15 and
20 m s-1 and altitudes between 2 and 5 km. As the dust plume reached
the Caribbean, approximately 5 days after leaving Africa, the top of the SAL
was slightly below 5 km and its bottom at 2 km.
Although in all cases we found a good qualitative agreement between the
measurements and the model, an underestimation of almost 10 m s-1 in the
AEJ speed was observed in the first case study. This is approximately 2
times the observed difference between the mean dropsonde measurements and the
model. As expected, due to the relatively coarse resolution of the model,
some island-induced mesoscale (< 100 km) disturbances in the winds
where observed by the DWL but not reproduced by the model. The analysis of
the extinction coefficient profiles shows similar results to those based on
CALIOP and MACC spatio-temporal averages. The modeled extinction values in
the boundary layer corresponding to the three case studies were far below the
measured ones by the DWL, while above the SAL a thin aerosol layer was
observed in the model but not in the DWL retrievals.
Data availability
Data used in this manuscript can be provided upon request by e-mail to Dr. Oliver Reitebuch (oliver.reitebuch@dlr.de).
Acknowledgements
This work was funded by the Helmholtz Association under grant number
VH-NG-606 (Helmholtz-Hochschul-Nachwuchsforschergruppe AerCARE). The
SALTRACE campaign was mainly funded by the Helmholtz Association, DLR, LMU
and TROPOS. CALIOP/CALIPSO data were obtained from the NASA Langley Research
Center Atmospheric Science Data Center. The SALTRACE flights on Cabo Verde
were funded through the DLR-internal project VolcATS (Volcanic ash impact on
the Air Transport System). The first author thanks the German Academic
Exchange Service (DAAD) for the financial support.
The article processing charges for this open-access publication were covered by a Research Centre of the Helmholtz Association.
Edited by: U. Wandinger
Reviewed by: two anonymous referees
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