Such closure measurements, consisting of spectral sunpho- tometer measurements of direct solar radiation, angular and spectral sky radiance in the almucantar have been made dur- ing SAMUM using a CIMEL CE 318 sunphotometer at the site 'Porte au Sahara' (30.237 • N, 5.607 • W), a desert like plane with free horizon in South Morocco, 30 km south of the city Zagora.

The measurements have been made within the time period 12 May 2006 07 to June 2006.


The CIMEL instrument has a field of view (FOV) of 1.2 • .

The instrument is equipped with original interference filters and also with additional filters to block light outside the band-pass region.

The additional blocking filters have been essential es- pecially for the two ultraviolet (UV) channels (0.34 and 0.38 μm) and the near infrared (NIR) channel at 1.02 μm.

The in- strument was calibrated by numerous Langley-plot measure- ments at various locations and at various temperature conditions.

Since the CIMEL instrument has no temperature stabilization, Langley plots have been made at Mt. Zugspitze and in Bre- men and the extraterrestrial instrument intensity i 0 (λ) has been obtained as a function of instrument temperature.

Thus, a temperature-dependent calibration function was derived, to min- imize virtual diurnal cycles.

Linear temperature sensitivities have to be accounted for all channels.

The largest temperature sensitivities are in the UV and the NIR channels.


Direct solar light has been measured for the determination of spectral AOT.

Sky radiance measurements have been started specifically for low as possible Sun elevations to obtain infor- mation on large scattering angles.

The automatic CIMEL mea- surement protocol does not support sky measurements at such low Sun elevations, therefore such measurements have been per- formed manually.

For intercomparisons and retrievals of AOT (cf.

Dinter et al., 2008) the TOA reflectance of Medium Resolu- tion Imaging Spectrometer (MERIS) observations in the reduced resolution (RR) mode of 13 spectral channels from blue to NIR from ESA near real time server at Kiruna have been used.

The available spectral channels for all three types of measurements are presented in Table 1.


The results of the measurements and their application in the intercomparisons are described in the next sections.


Sunphotometer measurements of direct solar radiation have been performed to derive spectral AOT as basic information for (1) the validation of AOT retrievals from MERIS observations (Dinter et al., 2008) and (2) the radiative transfer calculations to retrieve further optical aerosol characteristics of desert dust.


Desert dust observed at low Sun elevations gives rise to sig- nificant light contribution from the aureole into the FOV.

This effect of scattered light needs to be considered, since the aureole contribution leads to a significant reduction of AOT for large air mass factors M, leading to a virtual diurnal cycle.

With the used phase function the aureole effect in the NIR channels (at 1.02 and 0.87 μm) is about 5% of the measured signal at an air mass of 3.2 and negligible for an air mass of 1.2.

In the UV (at 0.34 μm) it is 17% for the air mass of 3.2 and 2% at 1.2.

Under Tellus 61B (2009), 1 these desert conditions and an air mass of 3.2 an unconsidered aureole reduces the AOT in the UV at 0.34 μm by 11%.


Instead of the apparent total optical thickness δ app (λ) δ app (λ) = 1 M ln i 0 (λ) i(λ) , (1) the aureole corrected optical thickness is determined, using a single scattering approximation for the aureole.


i(λ) is the measured solar intensity by the instrument at air mass Mi 0 (λ) is the extraterrestrial intensity, derived from Langley plots.

i diff (λ) is the diffuse sky radiation according the approx- imative calculation of diffuse radiation for the given apparent optical thickness and air mass factor range within the FOV of the CIMEL instrument of 1.2 • with the solid angle d .

p H (θ) is the atmospheric phase function with the scattering angle θ .

The estimate for the phase function has been taken from the averaged phase function, derived from the almucantar measurements in Section 4.

For the approximation of the diffuse sky light we used the simple sky light equation for almucantar geometry given by Volz (1954).

This aureole correction is for a wide range of AOT and M comparable with that of Kinne et al. ( 1997) and Russell et al. ( 2004).


Since the CIMEL has no temperature stabilization, the mea- sured signal is also a function of instrument temperature t. We need to correct the measured values to a defined reference tem- perature t ref , for which the Langley-plot calibration is valid.


The t c values are characteristic for the single spectral chan- nels and have values from 0.03% per • C for visible channels and increase to 0.3% per • C for 1.02 μm and even 0.5% per • C for 0.340 μm.

For measurements in the desert region of Morocco with diurnal temperature changes from 20 to 45 • C the tempera- ture correction was essential to get correct spectral behaviour of AOT.

The AERONET processing only considers the temperature sensibility of the 1.02 μm channel with 0.25 ±0.05% per • C. For other channels no temperature correction is applied (Holben et al., 1998).


The air mass factor M is obtained with Kasten and Young (1989) considering atmospheric curvature and refraction.


The AOT δ Aer is derived from corrected total optical thickness δ by making corrections for Rayleigh scattering δ Ray and gas absorption.


Gas absorption is considered for ozone for the channels 0.5 and 0.67 μm.

The channel 0.94 μm is not considered for AOT determination because of its contamination with strong wa- ter vapour absorption.

For the desert case in Morocco NO 2 absorption is not considered.


The estimation for the error of AOT measurements gives 0.02.

Thus, the relative error is 10% for clean days and drops to 2% for very dusty cases.


With this approach spectral AOT is determined for the time period of SAMUM.

The time-series of AOT is presented in Fig. 1.

As an example of spectral behaviour of AOT the data of 19 May 2006 are presented in Fig. 2.


All days of the period have been characterized by desert dust aerosol with more or less different AOTs.

As can be seen in Fig. 1 strong dust events appeared between 22 May and 26 May.

Also cleaner days show the typical flat spectral slope of dust aerosol.

The Ångström parameter α is also shown in Fig. 1.

For the most days Ångström α is low (0.03-0.4).

Few days with advection of different air masses make exceptions and are characterized by larger α.

The values of α show that the AOT of this period is mainly determined by the mineral dust.


Thus, the data can be used to derive further optical characteristics of desert dust, such as phase function and single scattering albedo.


For the retrieval of aerosol phase functions three steps are re- quired: (1) measurements of sky radiance in the almucantar and their preparation for the comparison with results of radiative transfer calculations; (2) spectral AOT data (Section 3) and (3) a retrieval procedure for the inversion of aerosol phase func- tions.

For the latter one the coupled inversion radiation transfer (CIRATRA; Wendisch and von Hoyningen-Huenen, 1994; von Hoyningen-Huene and Posse, 1997) approach is used.


In addition to the measurements of the spectral optical thickness of aerosol δ Aer (λ) four channels of the instrument, see Table 1, are used to measure the sky brightness and the aureole in the almucantar (that means at the same elevation as the Sun) at 27 different azimuth angles ψ in the range of 3 • -180 • .

Almucantar measurements can only be evaluated, if the sky in all directions is totally free of clouds.

In the first step the so-called unnormalized sky brightness can be determined from the measured sky signals of the instrument i Sky L Sky (λ, θ) = 1 M ξi Sky (λ, θ) i 0 (λ) exp(−δ(λ)M) , (6) where ξ is the product of the ratio of FOV of instrument to that of Sun with the absolute calibration constant ω Obj ω Sun C cal (λ).

It is not important, if normalized functions (eq. 8) are used.

i Sky (λ, θ) is the measured sky brightness, i 0 (λ)-the instrument solar calibration, δ (λ) is the total optical thickness from Section 3 and M the air mass factor.

θ is the scattering angle, obtained as θ = arccos sin 2 (h s ) + cos 2 (h s ) cos(ψ) (7) from solar elevation h s and azimuth ψ.


There are two reasons for the use of a normalization of sky radiance data: (1) absolute sky radiance requires a precise ab- solute calibration.

Because of different unknown properties of the instrument this may be a significant source of errors.

( 2) The results of calculation of sky radiance using radiative transfer codes depend on the accuracy of input data (e.g. solar spectrum, simulated filter bands).


To compare such measurements with radiative transfer cal- culations both the radiometer and the radiative transfer model must have the same 'calibration' conditions.

To avoid discrep- ancies from different 'calibration' conditions, we normalize the measured sky brightness.

p Sky (θ, λ) = L Sky (θ, λ) π 0 L Sky (θ, λ) sin θ dθ (8) from the measured sky radiances L Sky (θ, λ).

The normalization removes the influence of calibration, uncertainties in knowledge of FOV and relative optical air mass.

Therefore, the normal- ization makes all brightness measurements comparable.

This function contains the scattering properties of the sky including the multiple scattering.

However, the normalization leads to a loss of information on single scattering albedo.

Therefore, sin- gle scattering albedo needs to be determined from a comparison with well-calibrated radiation quantities in a separate step, see Section 5.


The normalization requires the integration of the sky radiance in the complete interval of scattering angles between 0 • and 180 • .

The CIMEL instrument performs the measurements in the azimuth range of 3 • and 180 • , for example, scattering angle θ = 180 • −2h o , with h o -the solar elevation.

To extend the measured range of scattering angles to the required one of 0 • and 180 • , the measured sky brightness has to be extrapolated in the forward and backward scattering regions.

To extrapolate the forward range to θ = 0 • we fit a Henyey-Greenstein function to the measurements in the θ-range of 3-10 • .

To extrapolate the backscattering range to θ = 180 • we fit the Heney-Greenstein function from the minimum value of the sky measurement (at about 120 • ) to the largest measurable scattering angle at θ Max = 180 • −2h s .


To reach large scattering angles covered by the measurements low as possible Sun elevations have been selected.

The almu- cantar measurements have been started at about h s = 5 • , if clear sky conditions for measurements prevailed.

The maxi- mum scattering angles close to 170 • were obtained.

This is an essential increase in angular information compared with stan- dard CIMEL operation, used in AERONET and starting at M ≤ 4, which is reaching 150 • in both, almucantar and principle plane.


Some examples of normalized sky brightness measurement for all four sky wavelengths of the CIMEL instrument are shown in Fig. 3 for the 19 May 2006.

If normalization conditions are fulfilled and the sky conditions during the day are stable all measurements for the same wavelength should have the same curve.


For the retrieval of the phase functions from almucantar and spectral AOT the CIRATRA approach (Wendisch and von Hoyningen-Huenen, 1994; von Hoyningen-Huene and Posse, 1997) is used.

The approach consists of several main steps:


(1) Inversion of an optically equivalent aerosol size distribu- tion from spectral AOT and sky brightness aureole for a range of refractive indices from 1.31 to 1.70.


(2) Calculation of aerosol phase function, using the inverted size distributions and a selected scattering database.

Available scattering databases are: Mie theory with spherical particles, the semi-empirical scattering theory of Pollack and Cuzzi (1980) and T-matrix data of Mishchenko et al. ( 2000).


(3) Radiative transfer calculations with the corresponding spectral optical thickness, composed from AOT and Rayleigh scattering, the atmospheric phase function, consisting of calcu- lated aerosol phase function of the previous step and Rayleigh phase function, an assessment for the surface albedo and a sin- gle scattering albedo.

For the radiative transfer calculations the approach of Nakajima and Tanaka (1988) is used.

The radiative transfer calculation can be made either for the geometry of the almucantar or the satellite observation.

In the case of retrieval of aerosol phase function the almucantar geometry is selected.

The results of the radiative transfer calculation is normalized in the same way as described in equation (8).


(4) Comparison of the results of radiative transfer calculation with the normalized sky brightness from almucantar measure- ment.


The above steps are made in a loop, varying the real part of refractive index, and parameters for the selected scattering theory looking for the best approximation between measured and calculated normalized sky brightness.

The result with the minimal root mean square deviation (RMSD) between both sky brightness distributions lead to the aerosol phase function, rep- resenting the existing radiation field.


The approach used by us deviates not in a significant way of the standard AERONET approach (Dubovik and King, 2000).


(1) We use normalized sky brightness data instead of abso- lute ones, because no absolute radiometric calibration of the sun-/sky-radiometer is required (The absolute calibration is a difficult task and may be not stable under all working conditions of the radiometer).

With the normalization of the sky radiance data in the measurements and radiative calculations we remove a significant error source.


(2) The size distribution is inverted by both approaches.

AERONET uses bi-modal lognormal dis- tribution.

This approach uses a 24-bin frequency distribution in a range of r low − r up with the step d log r for a given refractive index, fitted to spectral AOT and aureole measurements.

The 24-bin frequency distribution is more general than the bi-modal size distribution.

In both cases the size distributions are fitted to the measured data and should be representative for the optical data.


(3) In both approaches aerosol phase function is calculated, using Mie theory for spherical particles.


(4) In the case of non- spherical particles (in our case RMSD for the Mie theory >0.1) other scattering theories are used: AERONET uses a mixture of spheroids with different aspect ratios.

The frequency of aspect ratios is the empirical tuning of the AERONET approach to get a closer approximation to the measured sky radiance data.

This approach uses the theory of Pollack and Cuzzi (1980), where three parameters are used to tune a closer approximation to the normalized sky brightness data of the measurements.

In both approaches the closest approximation of measured data is used.

Thus, both approaches come to similar results for the phase function.


The phase functions used here are normalized to the unit sphere, for example, divided by 4π and have the unit sr −1 .


Mie theory gave only large RMSD of about 20% compared with the other non-spherical scattering theories: Pollak and Cuzzi approach gave RMSD < 5% for the most cases.

The T-matrix approach also gives lower RMSD than Mie theory.

In our case the implemented database for T-matrix calculation, however is restricted in the range of size parameters and aspect ratio.

Thus, the results here have larger RMSD than the Pollak and Cuzzi approach.

Since Dubovik et al. ( 2006) use a database with extended size parameter range and larger range of aspect ratios we do not report results of the T-matrix approximation as it is made by Müller et al. ( 2008b).


The error for the retrieval of aerosol phase function is esti- mated with 0.003 sr −1 for the backscattering region, which is for the values of 0.013 about 25%.

The most retrievals have been made for the CIMEL channel 2, e.g. wavelength 0.87 μm.

The aerosol phase functions of desert dust for this wavelength, obtained for the smallest RMSD are presented in Fig. 4 and the average of the campaign is listed in Table 3.

Table 2 gives the statistics of useful almucantar measurements of the different days.


All functions are almost flat in the backscattering region.

This is confirmed by the lidar ratio of LR= 55 . . .

60, which is in- Retrievals of phase function, using spheroids show a small peak at backscattering toward 180 • (Dubovik et al., 2006; Levy et al., 2007).

We do not find this peak, if we combine lidar ratio and single scattering albedo of Section 5 with our retrievals, see Fig. 4.

Within the error limits of 4% of the satellite data a backscattering peak is also not confirmed.


For radiative transfer calculations of smaller wavelength down to the UV the question for the spectral dependence of the aerosol phase function arises.

Therefore, for selected days also data of the channel 0.440 μm have been used.

The results of the both wavelength 0.870 and 0.440 μm are presented in Fig. 5 in comparison with the spectral results of Dubovik et al. ( 2006).

Within the error limits of the inversions at both wavelengths no significant difference could be found, as well with the results of these inversions and the results of Dubovik et al. ( 2006).

Therefore, we decide to use the aerosol phase functions derived for radiative transfer studies for shorter wavelength too.


The determination of the spectral single scattering albedo re- quires measured calibrated radiances, which can be compared with radiative model calculations, using measured spectral AOT and the obtained phase functions of desert dust.

The reflectance measured by the MERIS instrument on board of ENVISAT is given with an accuracy of 4%.

MERIS has 15 channels within the range of 0.412-0.900 μm, where 13 channels are outside of strong gas absorption bands.

The spatial resolution of MERIS is 1.2 × 1.2 km 2 .

Thus, comparison between modelled TOA re- flectance, using ground-based aerosol characteristics from Sec- tions 3 and 4 and measured TOA reflectance from satellite data can be performed.

The geometry conditions for the overflights are known.


If there are data of spectral surface reflectance, the only free aerosol parameter to achieve closure between modelled and measured TOA reflectance is the single scattering albedo.

Since our normalized phase functions in the LUTs do not con- tain single scattering albedo ω 0 , we get a retrieval correctly for the 'scattering part' on AOT, without any information of ω 0 . And the same is valid for the surface reflectance.


Using these data in RT modelling with ω 0 = 1 leads to an overestimation of the TOA reflectance compared with the satellite measurements.

We explained this difference as effect of absorption, because ω 0 is a linear factor in front of all scattering terms of the radiative transfer equation.


The spectral surface reflectance for the modelling is taken from retrievals by Dinter et al. ( 2008) for the site Porte au Sa- hara, using atmospheric correction of measured MERIS TOA reflectance.

The results of the retrieval of the surface reflectance are compared with results of spectral albedo measurements in the spectral range of 0.370-1.0 μm provided by air-borne spectral albedometer (Bierwirth et al., 2008).


For the calculation of Rayleigh scattering exact surface pres- sure and temperature have been considered, because surface elevation and temperature conditions change the contribution of Rayleigh scattering in the blue and UV significantly.


Finally the spectral single scattering albedo has been varied until modelled TOA reflectance agreed within 0.001.

The values of used spectral single scattering albedo can be taken as estimates of the desert dust.

Table 2 gives an overview of days, where ground-based data and MERIS overflights existed.

Useful days have been 19, 22, 29 May and 07 June 2006.

22 May was the day with the largest AOT (1.17), and 29 May has the lowest AOT (0.13).

The results of the estimation of spectral single scattering albedo are presented in Fig. 6.

Numerical values of spectral single scattering albedo are given in Table 4.

Single scattering albedo is changing with wavelength.

The lowest values have been found for the channel 0.412 μm with 0.95.

Single scattering albedo increases with increasing wavelength to 0.98.

For strong dust events (at 22 May 2006) significantly decreased values have been obtained, see corresponding column in Table 4 or dashed lines in Fig. 6.

Similar values one obtains for 25 May 2006, Tellus 61B (2009), 1 213 The error bars in Fig. 6 and in Table 4 are estimated from standard deviation of all retrievals of spectral single scattering albedo.


Since the SSA is determined from the fit of modelled TOA reflectance to measured ones (MERIS), this impact on SSA is 4%.

The larger error sources are in the input data for the radiative modelling, such as surface reflectance as the main error source.

Assuming an error of 10% for the error of surface reflectance data, the effect in TOA reflectance is spectrally dif- ferent: about 2% in the blue and about 5% in the red, if we do not consider errors in AOT and phase function.

According to error propagation we would come to 6% in the blue and 9% in the red part of the spectrum.


The same method is also applied to TOA reflectance ob- servations of the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY)instrument on board of ENVISAT.

The SCIAMACHY reflectance in the range of 0.443-0.753 μm is compared with that of the MERIS instru- ment to ensure a correct calibration.


Since SCIAMACHY gives TOA reflectance within the spectral range of 0.240-2.3 μm with a spatial resolution of 30 × 60 km 2 , the radiative transfer cal- culations are made starting at 0.340 μm and are compared with the SCIAMACHY data, cf.

Fig. 7.

We choose three additional channels at 0.340, 0.360 and 0.380 μm for the determination of single scattering albedo.


The large footprint of SCIAMACHY includes different surface conditions, thus the selection of repre- sentative spectral surface albedo from air-borne measurements for the UV wavelength is difficult.

The values decrease to the UV to a value of 0.91.

However, the uncertainty of surface albedo for 0.340 nm of the large footprint of SCIAMACHY gives error estimates of ±0.03.


The main uncertainty within this approach is the hetero- geneity of the spectral surface albedo.

The values have been taken from retrievals of MERIS observations and air-borne mea- surement and should correspond with the location of the site, where the ground-based AOT and phase function have been ob- tained.

Within the spectral range of 0.412-0.865 μm satellite re- trieval and air-borne data are coinciding.

For wavelength below 0.412 μm the spectrum is extended using air-borne data.


The found values are significantly higher than values of Sokolik and Toon (1999).

The found values are closer to data of Catrall et al. ( 2003).

They show a decrease of single scattering albedo to the UV.


Based on the combination of ground-based sky radiance, spec- tral AOT and space-borne TOA reflectance measurements the main optical aerosol characteristics of desert dust for the radia- tive transfer have been derived for the application with MERIS observations (Dinter et al., 2008).


For the retrieval of phase functions of desert dust non- spherical light scattering needed to be considered.

The use of spherical particles (Mie theory), as it is made in the OPAC dust models (Hess et al., 1998), gives strong deviations of phase functions in the range of 120 • -180 • scattering angle.

This has consequences on quantities derived by remote sensing, like sin- gle scattering albedo of aerosol and BRDF of the ground.


The light scattering of non-spherical particles, approximated by the semi-empirical theory of Pollack and Cuzzi (1980), gives similar results as T-matrix approaches, assuming mixtures of spheroids as it is done by Dubovik et al. ( 2006), Levy et al. ( 2007) and Müller et al. ( 2008b).


The phase functions of all approaches do not give the strong asymmetric behaviour of Mie theory.

With Tellus 61B (2009), 1 our approach we found no indication for a significant peak at the scattering angle = 180 • , as it is given by the spheroids.


Especially sky brightness measurements at low Sun elevations below 10 • and the lidar ratio of 60 (cf.

Tesche et al., 2008) support this finding.


Spectral single scattering albedo has been estimated from modelling TOA reflectance and intercomparison with satellite observations.

The UV value at 0.340 μm is found with 0.91 and 0.95 for 0.412 μm, rising up to 0.98 at 0.753 μm.

Strong dust events give decreased single scattering albedo.

Our values are at the upper limit of data, presented by Petzold et al. ( 2008), but they agree in spectral behaviour and magnitude with results of desert dust, given by Catrall et al. ( 2003).

Compared with our findings the OPAC desert dust models underestimate the single scattering albedo significantly.


Vertical profiles of dust key optical properties are presented from measurements during the Saharan Mineral Dust Experiment (SAMUM) by Raman and depolarization lidar at two ground-based sites and by airborne high spectral resolution lidar.

One of the sites, Tinfou, is located close to the border of the Sahara in Southern Morocco and was the main in situ site during SAMUM.

The other site was Ouarzazate airport, the main lidar site.

From the lidar measurements the spatial distribution of the dust between Tinfou and Ouarzazate was derived for 1 d. The retrieved profiles of backscatter and extinction coefficients and particle depolarization ratios show comparable dust optical properties, a similar vertical structure of the dust layer, and a height of about 4 km asl at both sites.

The airborne cross-section of the extinction coefficient at the two sites confirms the low variability in dust properties.

Although the general picture of the dust layer was similar, the lidar measurements reveal a higher dust load closer to the dust source.

Nevertheless, the observed intensive optical properties were the same.

These results indicate that the lidar measurements at two sites close to the dust source are both representative for the SAMUM dust conditions.


1. Introduction


The radiative impact of mineral dust particles – one of the main uncertainties in climate forcing – is strongly controlled by their optical properties and their spatial distribution [1].

One of the main sources for mineral dust is the North African desert, the Sahara.

Saharan dust has been studied when transported over short ranges to Europe [2-5] or over long ranges to the Caribbean Sea [6-8] and also during various field campaigns over North Africa.

Most recently, the Saharan Dust Experiment (SHADE; [9]) in 2000, the Southern African Regional Science Initiative (SAFARI–2000), also in 2000 [10], and the African Monsoon Multidisciplinary Analyses (AMMA; [11]), in 2006, have been carried out.


In most cases the dust was mixed with aerosol types of biomass burning or urban origin.

During the SHADE campaign airborne lidar measurements allowed a characterization of mineral dust particles [12] between Dakar (Senegal) and Cape Verde Islands.

Biomass burning aerosol has been characterized during the SAFARI–2000 campaign in Southern Africa.

During the AMMA dry season special observation period in January 2006 Saharan dust and biomass burning particles were characterized by lidar profiling south of the Sahara [13-15] and were observed by aircraft in situ measurements [16].

Mineral dust was mainly present in the lowermost 2 km while biomass burning aerosol mixed with varying amounts of dust was observed in elevated layers up to 5 km.


But pure dust conditions have rarely been met during those field experiments.

To assure that pure dust is probed one has to place the instruments as close as possible to a source of mineral dust, that is, the Saharan desert [1].


This was the subject of the Saharan Mineral Dust Experiment (SAMUM): to characterize mineral dust particles close to their source and to quantify their radiative effects [17].


The first field campaign was carried out in May and June 2006 in Southern Morocco to assure measurements of pure, not aged dust.

Two field sites were chosen for the ground-based measurements.

One of the sites was located at Tinfou, close to the town Zagora.

Tinfou is one of the last posts before the Saharan desert in Morocco and offers almost pure dust conditions.

It was the main site for in situ measurements of optical, microphysical and mineralogical properties of Saharan dust particles.


The other site was Ouarzazate airport that lies about 100 km to the northwest in the Anti-Atlas Mountains where a small research aircraft for radiative and in situ measurements was deployed.

A map showing these locations can be found in the introductory paper [17] and is shown by several other companion papers [18-20].


Due to logistical reasons, all ground-based lidar systems were operated from Ouarzazate.

These systems were three Raman and backscatter lidars of different sizes operating at different numbers of wavelengths and covering different measurement ranges.

Thus, these lidars were complementing one another so that the dust optical properties of interest could be studied comprehensively at different wavelengths and ranges.


Due to financial limitations, no additional lidar could be installed at Tinfou.

To have at least a few examples of the vertical distribution of the dust and its diurnal variation, one of the lidars the small, portable Raman lidar system (POLIS) was moved from Ouarzazate to Tinfou for a short stay.

The measurements at Tinfou allow to investigate if the distance to Ouarzazate and the orographic differences between the two sites has an impact on the results obtained at Ouarzazate. Are the dust particles probed at both sites of the same type? And thus, is it possible to combine the results from both sites for the vertical closure study that SAMUM aimed at? Or have the mineral particles already undergone a significant change in any of their optical properties?


To study the regional variability of the dust layer we compare simultaneous lidar profiles of dust optical properties at both sites and connect them with a corresponding airborne lidar cross-section.

In Section 2, we introduce the SAMUM field campaign and present the instruments used in this study.

In Section 3, the lidar evaluation methods are described and in Section 4, the results of our case study are presented and discussed.

Section 5 gives a short summary and conclusion.


2. Field campaign and instrumentation


Tinfou


The vertical probing of desert dust optical properties presented in this paper took place at Tinfou.

The site is located on the property of the Hotel Porte au Sahara (30.2°N, 5.6°W) 30 km southeast of Zagora, Morocco, at the border of the Saharan desert.

This remote place was the main SAMUM site for in situ measurements of the Saharan dust properties because it has two main advantages: it is close to the desert without disturbing settlements in-between, so that pure dust conditions were expected there.

The site is easily accessible by car so that mid-size equipment – as the small, portable lidar POLIS – can be transported there.

The altitude is 680 m above sea level (asl).

Lidar measurements at Tinfou were conducted on 3 d from the evening of 26 May to mid-day of 28 May 2006.


The lidar used for the measurements in Tinfou was the portable Raman and polarization lidar POLIS which was developed at the Meteorological Institute at the University of Munich.

POLIS is a small, rugged, two channel lidar.

It emits pulses of linear polarized light at the wavelength of 355 nm.

By choosing the wavelength in the ultraviolet region, where the eye is less sensitive, the lidar is eye-safe beyond a distance of 30 m from the laser.

Two detection channels are available and the data acquisition allows a vertical sampling with 7.5 m resolution.

The laser is mounted directly onto the receiving telescope to minimize the distance between the laser axis and the telescope axis.

As a consequence the overlap between the emitting and receiving fields of view of POLIS is completed at 120 m. More technical details of this lidar system are described by Heese et al. [ 21, 22].


POLIS can be operated in two modes: either in the depolarization mode or in the Raman mode.

In the depolarization mode, the two channels of the lidar are used for measuring the parallel- and cross-polarized components of the backscattered light to determine the depolarization ratio at 355 nm.

In the Raman mode, measurements at 355 nm and at the nitrogen Raman shifted wavelength at 387 nm are performed.

Since two different detection units exist, one for depolarization and one for Raman measurements, switching between the measurement modes is easily done by replacing the complete detector block.

Due to precise manufacturing of the mechanical components no optical re-alignment of the system is necessary.


The aerosol optical depth (AOD) measured by sun photometry is an optical property that can be used to evaluate lidar retrievals.

At Tinfou a Cimel CE 318 sun photometer owned by the University of Bremen was operated during SAMUM.

This sun photometer was equipped with additional channels in the ultraviolet at 341 and 379 nm and in the near infrared at 1020 nm.

Measurements of the direct solar radiation and the angular and spectral sky radiance in the almucantar regime were performed regularly.

The AOD was determined from the direct sun measurements at eight channels by the coupled inversion radiation transfer (CIRATRA; [23, 24]) approach.

This algorithm has been improved by an aureole correction for additional light in the instruments field of view for desert cases and is described by von Hoyningen-Huene et al. [ 25].

For the comparison with the lidar wavelength at 355 nm, the two additional channels in the ultraviolet are used.


To cover the lowermost heights, where the overlap of the lidars emitter and receiver is not complete yet, extinction data from a visibility meter was used.

The visibility meter (model VPF-710, Biral, Bristol UK) was operated at Tinfou by IfT and measures the extinction coefficient at 880 nm.

The principle operation is to measure the forward scattered light in a small undisturbed sample volume of about 400 cm3 at a scattering angle of 45°.

The scattered intensity is a direct measure of the extinction coefficient.

The extrapolation from 880 to 355 nm was done using an Ångström coefficient of 0.2.

This value coincides with the mean Ångström coefficient observed by the sun photometer in Tinfou.


Ouarzazate


While POLIS was in Tinfou the two other SAMUM lidar systems were continuing measurements at Ouarzazate airport (30.9°N, 6.9°W].

The airport lies at 1133 m asl between the high Atlas Mountain ridge to the northwest and the lower Anti-Atlas to the southeast.


Those two lidars were the mobile, scanning multiwavelength lidar MULIS of the University of Munich and the six-wavelength backscatter extinction lidar-ratio temperature humidity profiling apparatus (BERTHA) of the IfT [26].


MULIS is emitting the three Nd:YAG laser wavelengths 355, 532 and 1064 nm and has six receiving channels including two nitrogen Raman channels at 387, 607 nm and a depolarization channel at 532 nm.


More details of this lidar system and an analysis of dust depolarization properties during SAMUM are described by Freudenthaler et al. [ 27].


The six wavelengths emitted by BERTHA are 355, 400, 532, 710, 800 and 1064 nm.

In this study, the extinction profiles derived at the ultraviolet and the visible wavelengths are used.


BERTHA is a scanning lidar system.


During daytime measurements were conducted at the elevation angle of 45° and – to avoid specular reflections from cirrus clouds [28] – at an angle of 5° off the zenith during nighttime.


A comprehensive analysis of BERTHA data is given by Tesche et al. [ 29].


For the measurements of the AOD at Ouarzazate the Aerosol Robotic Network (AERONET; [30]) sun photometer of the Leipzig lidar group was deployed.

It is equipped with an additional long wavelength channel at 1640 nm for improved dust observations.

The AERONET sun -photometer measures direct sunlight at eight channels: 339, 379, 441, 501, 675, 869, 940, 1021 and 1638 nm wavelength.

The AOD data used in this study are quality assured AERONET retrievals.


Aircraft


Finally, the DLR Falcon-20 research aircraft was deployed at the airport of Casablanca.

Onboard, besides numerous particle collecting and in situ experiments, a high spectral resolution lidar (HSRL; [31]) was operated during SAMUM.

Several overflights over the ground-based sites gave the opportunity of intercomparisons between airborne and ground-based lidar profiles and allow to study the spatial distribution of the dust.


3. Evaluation of POLIS data


The optical properties measured by aerosol lidar are depolarization ratio, particle backscatter and extinction coefficients and lidar ratio.

Depolarization is a parameter that depends on the shape of the particles.

Extinction coefficient depends on scattering and absorbing properties of the particles but also on the number and size distribution of the particles.

This is also valid for the vertically integrated extinction, the optical depth.

Finally, the extinction-to-backscatter ratio, the lidar ratio, is again characteristic for the various particle types.


In the following subsections, the derivation of these optical properties from the lidar data is explained in more detail.


3.1. Depolarization ratio


The depolarization ratio characterizes atmospheric particles and identifies aspherical particles as, for example, mineral dust particles or cirrus clouds.

Two types of depolarization can be determined from the lidar signal: the total or volume depolarization and the particle depolarization.


The volume depolarization is the direct ratio of the backscatter signal received in the plane that is cross-polarized to the laser’s polarization to the signal received in the plane parallel to it.

It can be derived with a high temporal resolution of 30 s. The volume depolarization comprises the relative contribution of particles and air molecules in terms of backscatter coefficients.

For an accurate retrieval the relative sensitivity of the two channels against each other has been determined.

This is done by a calibration of the channels by rotating the polarizing beam splitter cube by 45° in both directions from its normal position.

At these positions the polarizing beam splitter cube transmits both polarization planes of the incoming light equally.

From the ratio of these signals the relative sensitivities of the channels can be determined.

A calibration using both rotations minimizes the error in positioning the polarizing beam splitter cube.


To get a measure only depending on particle properties, the particle depolarization ratio must be calculated.

The particle depolarization is an intensive optical property that characterizes the particles itself in composition and shape and is independent of the number of observed particles.

For this purpose, the volume depolarization must be converted into particle depolarization using the corresponding molecular and particle backscatter coefficients [32, 33].

To calculate the molecular backscatter coefficient radio soundings performed at Ouarzazate airport were used.

The particle backscatter profiles are derived from the lidar measurements.


Backscatter and extinction coefficient and lidar ratio


An extensive aerosol optical property derived from lidar measurements is the particle extinction coefficient.

An extensive optical property depends not only on the particles composition and shape but increases with the number of observed particles.

Particle extinction is one of the key input parameters for radiative transfer calculations.

It can be derived from lidar signals in two ways: either from the elastic signal at the emitted laser wavelength, which is 355 nm in the case of POLIS, or from the inelastic Raman signal at 387 nm.


From the inelastic Raman signal the direct determination of the particle extinction coefficient without a priori assumptions is possible [34].

This is due to the fact that the Raman signal at 387 nm scattered back by nitrogen molecules is only affected by particle extinction and known optical properties of the air molecules.

From the Raman signal and the corresponding elastic signal at 355 nm the backscatter coefficient and thus the backscatter-to-extinction ratio, the lidar ratio, can be derived.

The lidar ratio is again an intensive optical property that is specific for the observed particle type and does not depend on the number of particles.

The nighttime Raman measurements are averaged over at least 1 h to achieve an extinction profile up to the upper troposphere with an error of less than 25%.

Due to the relatively low Raman signal compared to the sky background during daytime Raman measurements are restricted to nighttime.


During daytime the retrieval of the extinction coefficient from the elastic signal is done by the method described by Fernald [35] assuming a realistic value for the lidar ratio, to solve the underdetermined lidar equation.

This lidar ratio can be derived from nighttime Raman measurements.

As will be shown later, the lidar ratio for dust inside the nighttime boundary layer was found to be 55 sr.

This value coincides with lidar ratios observed earlier in dust layers.

During AMMA the lidar ratio observed in the dust layer by POLIS was 55 ± 5 sr [14]. And from an episode, when Saharan dust particles were transported towards Europe [3] the observed lidar ratio was 59 ± 11 sr.

Also from the SAMUM lidar measurements at Ouarzazate the lidar ratio of dust particles was determined as 55 ± 6 sr [36, 29].

Thus, a mean lidar ratio of 55 sr was applied to derive the particle extinction by the Fernald method for all daytime measurements from POLIS during SAMUM.


Aerosol optical depth


Aerosol optical depth can be derived from the lidar measurements by vertical integration of the extinction coefficient profile.

The profiles are integrated from the lowermost lidar height up to a height well above the dust layer, which was chosen at 7.5 km asl.

In the absence of clouds, above this height no contribution to the AOD needs to be added.

This is justified by the fact that in all retrieved lidar profiles the extinction coefficients are below 0.01 above the dust layer.


One exception is a 15 min period on 28 May 2006 where a thin cirrus was observed at 11 km height.

The contribution of this cirrus to the AOD is discussed by Kahn et al. [ 18].

Close to the ground the extinction coefficient is extrapolated to a ground-level extinction value measured by the visibility meter.


Finally, the resulting AOD is compared to the AOD obtained from sun photometer measurements at the wavelength 341 and 379 nm and interpolated to the lidar wavelength at 355 nm.


4. Lidar profiles


On 26 May 2006 POLIS was transported to the site at Tinfou to stay there until 28 May 2006.

Raman lidar measurements were performed on the evenings and depolarization measurements were performed during daytime.

After about noon the measurements have been stopped because air temperatures exceeded 35°C and the water cooling circuit of the laser became too weak.


In the following, we present examples of Raman and Fernald derived backscatter and extinction coefficients, corresponding lidar ratios and the particle depolarization observed inside the dust layer.

From the high temporal resolution volume depolarization data the monitoring of the mostly undisturbed development of the dust layer is shown during one morning.

To determine the spatial distribution of the dust a case study was conducted on 28 May 2006.

The lidar profiles measured in Tinfou are compared to measurements performed at Ouarzazate and interpreted in conjunction with the airborne HSRL profiles from a Falcon overflight over both sites.

These profiles are then related to the dust distribution observed during SAMUM at Ouarzazate and during the POLIS measurement period at Tinfou.


4.1. Raman measurements and lidar ratio


Extinction coefficient profiles and extinction-to-backscatter or lidar ratio were derived from POLIS Raman measurements taken in the late evenings.

On 26 May 2006 a significant fraction of dust has been washed out by heavy rain showers in the afternoon.

On 27 May 2006 the dust layer has recovered quickly.


The extinction coefficient profiles, backscatter profiles and lidar ratios derived from the Raman measurement are shown in Fig. 1.

The extinction and backscatter profiles show a well-developed dust layer that reaches up to approximately 4.3 km.

The lidar ratio resulting from these measurements is quite constant inside the dust layer and the mean value is 55 ± 8 sr.


For comparison, the backscatter and extinction profiles retrieved from the same raw signal using the Fernald method with the constant lidar ratio of 55 sr are plotted.

The agreement of the profiles is very good: the same structure of the dust layer is resolved as by the Raman measurement, especially in the backscatter profile.

The differences in the upper part of the extinction profile is due to different height averagings.

This comprises an increasing height interval with altitude for the Raman measurements to account for the decreasing signal-to-noise ratio with altitude: At 1 km altitude the Raman signal is derived with vertical smoothing with a window lengths of 400 m, at 2 km of 600 m and at 4 km of 1 km.

The profiles by the Fernald method are vertically smoothed over a constant height interval of 300 m.


The extinction coefficient profile shows values up to 0.2 km−1 throughout the whole dust layer.

The AOD integrated from this extinction profile is 0.52, which is close to the AOD of 0.55 measured by the sun photometer in the evening just before sunset.

The AOD measured by the sun photometer did decrease from around 1 in the morning to around 0.5 in the course of this day.

These values are fully comparable to dust extinction coefficient measured earlier.


For example, during AMMA the mean extinction coefficients for dust measured by POLIS in the Sahel region were around 0.2 km−1.

For 1 d with direct import of dust loaded air masses from the Saharan desert, the extinction coefficient could exceed 1.5 km−1.

However, the vertical extent of this layer was only a few 10 m [14].

Extinction values in the same order are presented by Johnson et al. [ 15], who show airborne nephelometer measurements compared to airborne lidar measurements [13] with ground-based measurements from POLIS and an MPL lidar stationed at Niamey Airport.

Further south in Benin a microlidar also measured extinction coefficient in the order of 0.2 km−1 in the dust layer close to the ground [37].


Daytime extinction coefficients


During daytime, when the sky background is too high for the weak Raman signal depolarization ratio measurements were performed.

The extinction and backscatter profiles were derived from the total lidar signal by combining both depolarization channels.

The profiles were calculated using the Fernald method with a lidar ratio of 55 sr, as determined from the nighttime Raman measurements.


Fig. 2 shows a two-layer structure of dust on 27 May.

The upper boundary of the dust layer on this day is at around 3.8 km.

The extinction coefficient in the lower part of the newly developing dust layer is reaching values of 0.4 km−1.

Above this layer the residual layer from the night before is still present.

Here the extinction values are around 0.08 km−1.


At ground level the extinction coefficient measured by the visibility meter is between 0.68 km−1 at 10:00 UTC and 0.54 km−1 at 10:30 UTC.

The integration of the lidar profile and extrapolation to the ground values gives an AOD of 0.75, which is in good agreement with the values measured by the sun photometer of around 0.79 at 10:00 UTC.

This difference in AOD is only about 5 %, which is inside the uncertainty of the extinction coefficient imposed by the lidar-ratio error.

Thus, we can conclude that the mean lidar ratio from the night is also valid for the morning hours.


The comparably high value of the AOD was caused by high surface winds.

Around 10:00 UTC the surface wind speed was rising up to 10 ms−1, and dust from local sources was mobilized and mixed into the lower boundary layer.


Depolarization


Despite the two layers observed in the extinction and backscatter profiles, on 27 May the particle depolarization ratio throughout the whole boundary layer is constant and has a value of 30% ± 6% (see Fig. 2, right-hand panel).


This value was also measured the next day and is shown in Fig. 4 (right-hand panel).

Here high particle depolarization ratios with values between 26% and 36% throughout the dust layer were observed.


Since the particle depolarization is an intensive optical property these measurements imply that the particles in the dust layer and in the residual layer above are of the same type.


Observations in Ouarzazate from all lidar systems show that these values are representative for the dust layer close to the source region.


Freudenthaler et al. [ 27] have studied the depolarization ratio at four wavelengths (355, 532, 710 and 1064 nm) and found very low wavelength dependence of the depolarization and mean values around 30% during dust episodes.


To visualize the temporal development of the dust layer during the day the high resolution volume depolarization measurements are very useful.

On 28 May 2006 the measurements started early in the morning (Fig. 3).

This was done to achieve a long measurement series in parallel with co-located sun photometer measurements by the University of Bremen.


Two layers can be identified: The lowermost layer with the highest volume depolarization ratio with values of up to 10% – shown in red and yellow colours – has reached a height of about 1.2 km asl at 7:00 UTC which corresponds to 500 m above ground level (agl).

The dust layer extends with the solar elevation and its upper boundary is already at about 2 km at 9:20 UTC.

Note the wave-like structure of the upper boundary caused by turbulent mixing.

The size of the eddies can be approximated from their vertical extent, which reached about 1 km above ground around 9:00 UTC and is growing on over the course of the day.


Above this newly developing dust layer a residual layer with volume depolarization ratios around 5% can be identified up to a height of approximately 2.5 km asl.

The upper boundary of the residual layer is stable throughout the morning.

That the depolarization ratio is a good tracer for boundary layer dynamics has been shown previously by Gibert et al. [ 38].


Dust distribution between Tinfou and Ouarzazate


The aim of this study is to find out if the choice of two different sites for the SAMUM field campaign is valid in terms of comparable retrieved dust optical properties.

For this the lidar profiles measured at Tinfou shall be compared to those measured at Ouarzazate.

Unfortunately, due to heavy rain on 26 May and some rain showers and cloudiness on 27 May, no lidar measurements were possible at Ouarzazate. But finally the intercomparison could be performed on 28 May, when POLIS was still operating at Tinfou and the two other SAMUM lidars were again measuring at Ouarzazate.

An additional advantage on this day is that an overflight over both sites with the DLR Falcon was conducted.

Onboard the HSRL was measuring backscatter and extinction profiles at the wavelength 532 nm and the backscatter coefficient at 1064 nm.

One of the Falcons flight legs was crossing over Ouarzazate at 10:43 UTC and flew on directly to the other site at Tinfou where it arrived at 10:53 UTC.

This case study also supports investigations on the spatial representativeness of the lidar measurements.


The corresponding backscatter and extinction profiles at 532 nm measured over Tinfou are plotted together with POLIS profiles of backscatter and extinction coefficients at 355 nm in Fig. 4 (left-hand and middle panel).

The profiles from POLIS agree well with the HSRL profiles in shape and also in magnitude, especially at heights above 2 km.


Below this altitude in the lower boundary the backscatter coefficient from the HSRL is higher but the extinction profiles are quite similar.

These differences are due to different spatial coverages and a limited time averaging period by the aircraft.

The measurement by the HSRL is spatially averaged over 30.37°–30.31°N and 5.72°–5.75°W, corresponding to a flight path of about 20 km and a time period from 10:53:22 to 10:54:06 UTC.


The freshly raised dust particles in the lower boundary layer are subject to higher spatial variability than in the more settled residual layer from the night.

In the present case the airborne measurements were averaged over a region that lies to the west of Tinfou where the dust concentration was slightly higher.

This can be seen also in the upper panel of Fig. 6.


The wavelength dependence of the backscatter coefficient is very low for dust particles.

Therefore, the different wavelengths of the HSRL and POLIS signals should not contribute to the observed discrepancies.


This low wavelength dependance can be demonstrated by considering the measurements from a sun photometer.

At Tinfou those measurements show that the columnar Ångström coefficient of the AOD is almost wavelength independent: it lies between 0 and 0.2 [25].

This is also in agreement with the Ångström coefficient measured at Ouarzazate by the SAMUM lidar systems [29], and with previous measurements of Saharan dust outbreaks observed over Europe [4, 3, 5].

However, parts of the observed differences may still due to different lines of vision of the two lidars.


The differences in backscatter are also reflected in a differing lidar ratio at the lower altitudes.

The mean lidar ratio derived from the backscatter and extinction profiles measured by the HSRL at the lower altitudes is around 38 ± 5 sr at 532 nm.

As for all daytime measurements POLIS profiles at 355 nm were derived with the lidar ratio of 55 sr.

To examine if this lidar ratio was also valid on this day, the resulting extinction profile was integrated to an AOD of 0.39.

This AOD compares well with the value of 0.40 measured by the sun photometer at Tinfou. Since we do not see a significant difference in AOD we can assume that the extinction profile from POLIS derived by the Fernald method delivers reasonable results for this day.


The comparison of the profiles of extinction coefficients taken by MULIS and BERTHA at Ouarzazate during the Falcon overflight also coincides well with the profile from the airborne HSRL.

Figure 5 (left-hand panel) shows the extinction profiles from BERTHA at 355 and 532 nm, and from MULIS and the HSRL at 532 nm (MULIS data were provided by V. Freudenthaler, Meteorological Institute at the University of Munich).

For direct comparison the profiles observed at Tinfou are plotted again in Fig. 5 (right-hand panel).

The profiles measured at Ouarzazate resemble in shape and magnitude to the profiles measured at Tinfou.


A similar two-level dust layer is reaching up to altitudes around 4–4.2 km asl.

The residual dust layer from the night is again present above 2.6 km and shows extinction values around 0.08 km−1, compared to 0.06 km−1 at Tinfou.

Below 2.6 km, inside the newly developed dust layer, the profiles from MULIS and the HSRL show extinction values of up to 0.15 km−1, compared to 0.2 km−1 at Tinfou.


The profiles from BERTHA are not shown below 2.2 km asl, because the overlap between laser and receiving telescope is not complete before 1.1 km above ground (see also Fig. 2, [29]).

The ground-based lidars have all different geometrical factors.

The smaller MULIS has a complete overlap at 250 m above ground.

For comparison, POLIS overlap is already complete at 120 m above ground.

Since the HSRL is measuring downward looking its profiles always reach the ground.


A disagreement in the profiles at Ouarzazate is a differing boundary layer top.

It results mainly from different vertical resolutions and smoothings: BERTHA data are vertically smoothed over 660 m. The HSRL has a vertical resolution of 530 m. MULIS data were calculated from backscatter coefficients using the lidar ratio from the HSRL and are smoothed with a sliding average of 75 m. The larger smoothing window from BERTHA and HSRL leads to a less pronounced upper boundary than in the profile by MULIS. But also the averaging times and different spatial resolutions of the HSRL compared to the stationary measurement of the ground-based lidar are different.

The HSRL profile was averaged from 30.9°–30.0°N and 6.9°–6.8°W which corresponds to a temporal average of 86 s. The ground-based measurements are averaged over about 1.5 h to achieve a low-noise lidar signal. But independently of the slightly differing observed boundary layer heights by the lidar systems the determined particle properties are still comparable.


Although the profiles from Ouarzazate and Tinfou only represent a snapshot of the dust optical properties during one morning these results imply that the spatial variability of the dust layer over the distance of 100 km between Tinfou and Ouarzazate is rather low.


An overview over the dust optical properties measured by lidar at Ouarzazate is presented by Tesche et al. [ 29]: They conducted a height resolved statistical analysis that revealed a dust layer depth of typically 4–6 km height asl.

A vertically inhomogeneous dust plume with internal dust layers was usually observed in the morning, before the evolution of the convective boundary layer.

The Saharan dust layer was then well mixed in the early evening.

The 500 nm dust optical depth ranged from 0.2 to 0.8 at Ouarzazate, Ångström exponents derived from photometer and lidar data were mainly between 0 and 0.4.

The volume extinction coefficients varied from 0.03 to 0.3 km−1 with a mean value of 0.1 km−1 in the lowest 3 km agl.

Mean extinction–to–backscatter ratios of 53–55 sr (±7–13 sr) were obtained at 355, 532 and 1064 nm.

A significant wavelength dependence of the lidar ratio was not observed close to the source region of atmospheric desert dust.


The values of the optical properties of the dust layer measured at Tinfou during the three lidar measurement days lay within these margins.

The dust layer height at Tinfou was 4 km asl, the extinction coefficients in the dust layer were between 0.1 and 0.2 km−1, and the AOD was around 0.4.

During the whole SAMUM campaign the AOD at Tinfou was varying between 0.2 and 1.2 [25], slightly higher values than at Ouarzazate. But only a few days with a high AOD greater than 1 were observed and they were again caused by local dust activation when the wind speed was above 10 m s−1.

For most days the Ångström exponent is low (0.03–0.4).

These results encourage us to conclude that we observe the same typical optical properties for pure dust at both sides.


To further study the spatial variability of the dust layer cross-sections of backscatter ratio and extinction coefficient derived from the airborne lidar measurements are shown in Fig. 6.

These cross-sections give a good overview over the dust distribution between Tinfou and Ouarzazate on 28 May 2006.

This was a day of moderate dust load with AODs up to 0.5.


The extinction values east of the mountain ridge at 30.6°N show the developing dust layer with the highest values up to 2.5 km a.s.l., the same structure as observed by POLIS over Tinfou.

West of the mountains the dust load is decreasing and starts to disperse into the upper boundary layer.

The lidar extinction profiles measured at Ouarzazate show values of about 0.05 km−1 lower than at Tinfou.

This is consistent with the slightly lower dust load observed over Ouarzazate.

The differing amount of dust is also reflected in the lower backscatter ratio west of the mountains.

The AOD measured by sun photometry at Ouarzazate at 11:0 UTC was 0.35, compared to 0.39 at Tinfou.


HYSPLIT backtrajectories [39] ending at Tinfou and Ouarzazate on 28 May 2006 at 11 UTC (not shown) support the assumption that the same air masses were advected at both sites.

The backtrajectory arriving at 1 km asl at both sites came from the southeast and originated from Algeria.

The backtrajectories arriving at 2 and 3 km asl at both sites follow a cyclonic circulation from the south and southwest.


The meteorological situation during the whole SAMUM campaign was intensively analysed by Knippertz et al. [ 20] using backtrajectories.

They show that several high dust and intermediate phases with lower dust impact did alternate during SAMUM.

The high dust phases were dominated by air mass advection from the east and southeast, that is, northern and central Algeria. But also during the low dust phases advection from the east occurs, for example, in connection with a high pressure systems over the Atlas Mountains.


28 May was the last day of the second high dust phase of SAMUM.

It was characterized by a cut-off low over northwestern Africa.

The corresponding circulation is reflected in the mid-level HYSPLIT trajectories for both sites in our study.

At lower levels there is still an easterly inflow of dust from Algeria, before the next intermediate low dust phase started later on that day.

Due to the geographical location closer to Algeria, the dust load at these lower levels is higher at Tinfou than at Ouarzazate (see Fig. 5).

From this trajectory analysis we can conclude that the same air mass accounts for the same structure of the dust layer observed over Tinfou and Ouarzazate on this day.

From the common easterly advection of dust during the high dust phases we can conclude that in these cases comparable dust conditions were present at both sites and thus similar dust optical properties were observed.


5. Summary and conclusions


In this study, lidar profiles of dust backscatter and extinction coefficients and of volume and particle depolarization ratios are presented.

The profiles were measured by several lidar systems in the frame of the first field campaign of the German SAMUM project in Southern Morocco.


Lidar profiles at the two SAMUM ground sites, Tinfou and Ouarzazate, and from an airborne lidar were used for a case study of the spatial variability of the dust.


The comparison of the derived particle properties at both sites show good agreement in particle depolarization, which lets us conclude that dust particles of the same type and shape were observed.

The comparison also revealed excellent agreement in extinction coefficient with the profiles obtained from an airborne HSRL during the overpasses over the sites.


However, the typical extinction coefficients and the resulting AODs were slightly higher in Tinfou compared to Ouarzazate.

This is mainly due to more local dust sources and thus a higher amount of dust mixed into the boundary layer east of the Anti-Atlas Mountains.


A similar structure and height of the dust layer was observed at both sites.


During daytime the new dust layer is developing while the residual layer from the night is still present at higher altitudes.

In the course of the day the dust layer height is raised by vertical mixing by convective processes like dust devils and convective dust plumes (see also [40]).

In the evenings the lidar profiles show a well-mixed dust layer extending up to 4 km asl.


Though the time period of the POLIS measurement at Tinfou was limited and thus the comparison is not based on statistics we can conclude that there are no indications of significant differences in the mineral dust characteristics over a spatial scale of 100 km.

During this comparison, the meteorological conditions were providing that the same dust layer was observable at both sites.

The pure and fresh dust layer probed in Tinfou was essentially consisting of the same dust particle type that has been observed over Ouarzazate.

This encourages us to assume that results found at one site are valid for the other site as well and both sites together can be used to describe dust particles close to their source region.


Certainly, dissimilarities in the dust layer occur due to regional orographic features.

In the case of Ouarzazate and Tinfou, which are separated by the lower Anti-Atlas Mountains, these are minor differences.

In contrast, the high Atlas Mountains west of Ouarzazate may cause a significant change in the optical properties by mixing marine aerosol with the dust particles [31].

From this, we can conclude that although the dust load is higher closer to the desert, the observed two-layer structure of the dust layer is in principle the same, and, more important, the dust optical properties measured at both sites are comparable.

Finally, we can conclude that Ouarzazate was close enough to the North African sources of mineral dust to allow the characterization of pure mineral dust particles by lidar profiling.

The choice of the main lidar site at Ouarzazate airport – where the necessary logistical conditions for the big lidar systems were available – away from the in situ site was an appropriate alternative.


Acknowledgments


The SAMUM researcher group was funded by the German Science Foundation (DFG) under Grant FOR539.


The authors gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model used in this publication.


Approximately 30% of the land surface is arid, having desert or semi-desert conditions.

Aerosol originating from these regions plays a significant role in climate and atmospheric chemistry of the atmosphere.

Retrieving aerosol properties from space-borne platforms above desert conditions, where the surface reflectance is usually very bright, is a challenging task.

The proportion of the surface to top of atmosphere (TOA) reflectance can reach values over 90%, especially for wavelength above 500 nm.

For these reasons detailed knowledge of aerosol and surface optical properties from these regions is required to separate atmosphere from intrinsically bright surfaces.

An approach to retrieve aerosol properties over arid and semi-arid regions based on the Bremen Aerosol Retrieval (BAER) has been developed and validated within the Dust Aerosol Retrievals from Space-Born Instruments (DREAMS) Project, which is part of the Saharan Mineral Dust Experiment (SAMUM, 2006).

Combining measurements of the backscattered radiation from the Medium Resolution Imaging Spectrometer (MERIS) instrument aboard Environmental Satellite (ENVISAT) and ground-based measurements in Morocco in radiation closure experiments yields the aerosol optical properties of mineral dust at selected locations.


The recognition that anthropogenic activity directly and indirectly is modulating climate (IPCC, 2007), and the observation of increasing desertification, which, as a consequence, results in increasing amounts of atmospheric dust, has turned the attention of the scientific community on the importance of improving our understanding of aerosol.

In this context airborne mineral dust plays an important role, having bio-geochemical impact on the ecosystem and influencing locally and globally atmospheric radiative forcing [1][2][3].

As described in several studies [4], the dust from the Sahara is often transported out of the boundary layer into free troposphere and then travels thousands of kilometres across the Atlantic or into northern Europe.

For this reason, it is especially important to understand the processes controlling the formation, transport and fate of dust aerosols originating from Saharan source regions.

Therefore, adequate satellite remote sensing observation techniques for mineral dust are required, which can be used over a wide variety of surface conditions, especially in source regions.


The Bremen aerosol retrieval algorithm (BAER) has been developed to retrieve aerosol optical properties above land and ocean surfaces.

A detailed description of the BAER algorithm and its application for the retrieval of aerosol properties are discussed elsewhere [5].

Predominantly existing retrieval approaches for aerosol optical thickness work for known low reflecting surface conditions.

The bright surface of desert and semi-arid regions is the most challenging application for BAER.

In desert regions, the spectral surface reflectance is very high in the red part of visible spectrum and near infrared, but decreases relatively fast in the blue for wavelengths shorter 500 nm.

This behaviour contrasts to that of, for example, clouds or snow, which are predominantly spectral neutral.

To account for increased surface reflectance, associated with these very bright surfaces types, BAER needed to be modified.

The radiation closures of the SAMUM experiment have been used to investigate aerosol [6] and surface [7] properties and their interaction with the retrieval of aerosol optical thickness.

A brief overview of the used satellite instrument and the usual aerosol retrieval techniques in the UV/VIS region will be given in Section 2.

A description of the optimization of BAER for desert conditions will be discussed in Section 2.2 and validated in Section 4.

Examples of aerosol optical thickness derived by using the BAER algorithm over Sahara region during SAMUM campaign in South Morocco will be shown in this paper.


The evaluations reveal various dust sources, which are important contributors to airborne dust transported over long distances.

The aerosol optical thickness and surface reflectance are determined simultaneously in the algorithm using look-up tables to match the satellite observed spectral top of atmosphere (TOA) radiance.

Reduced Resolution Level 1 data of the Medium Resolution Imaging Spectrometer (MERIS), which is a radiometer on the Environmental Satellite (ENVISAT), are used.

The instrument gives TOA radiance at 15 channels in the wavelength range of 400–1000 nm.

Several algorithms for remote sensing of aerosol properties over land using different kind of sensors have already been developed.

The BAER algorithm is generic and can be applied to any calibrated measurement of backscattered radiation, yielding the TOA spectral reflectance as a function of wavelength, especially those having sufficient channels in the short-wave region.

In this context, it has been applied to the data from the sensors: Sea-Viewing Wide Field-of-View Sensor (SeaWiFS; http://oceancolor.gsfc.nasa.gov/SeaWiFS/), Moderate-Resolution Imaging Spectroradiometer (MODIS; http://modis.gsfc.nasa.gov/), MERIS [8][9] and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY; [10][11]).


The standard MODIS aerosol retrieval algorithm over land uses the dark target approach [12][13] and assumes a fixed relation between 0.47, 0.64 and the 2.1 μm channels, respectively.

This is a valid assumption for most vegetated land surfaces.

But over desert regions these values deviates significantly from this assumption.

For these conditions, there are substantial areas with data gaps in the standard MODIS aerosol product over land.

The BAER algorithm as well as the ‘Deep Blue’ algorithm from [14] uses the blue channels of satellite instruments for separation between surface and atmosphere.

This is possible, because of the decreasing surface reflectance in this spectral regions.

For dark surfaces (vegetation, ‘brown’ bare soil) this is an appropriate approach, whereas over desert and other bright reflecting surfaces this leads to an not negligible overestimation of the aerosol optical thickness.

To avoid this problem [14] use as an a priori knowledge a surface reflectance determined from a clear-scene database for a given geolocation.

Following this approach, this study is focusing on an improvement of the model for the spectral and bidirectional reflecting surface properties and its integration within the retrieval procedure.

For this a surface reflectance data set for the SAMUM region based on atmospheric corrected MERIS data has been build up.

Comparisons of this database with aircraft measurements are shown in Section 4.3.


In this paper, retrievals of aerosol optical properties have been inverted from measurements made by the MERIS instrument, which flies on the European satellite ENVISAT.

Environmental Satellite was launched on the 1 March 2002.

It flies in a sun synchronous orbit in descending mode, having an inclination of 82° and a resulting equator crossing time of around 10 a.m. The MERIS, medium resolution instrument, is a hyper-spectral instrument.

The backscatterd upwelling radiation from atmosphere and surface is directed into the instrument, which comprises a spectrometer and a 2-D array detector arrangement.

Observations of the Earth shine and the extraterrestrial solar irradiance yield the spectral reflectance at the TOA for the particular viewing direction.

The instrument has 15 spectral channels, which operate between 400 and 1000 nm.

The spatial resolution of one pixel is 1.04 × 1.2 km reduced and 260 × 300 m full resolved for all 15 channels.

The swath width amounts 1150 km and yields to a global coverage every 3 d. MERIS is a well-calibrated instrument and is qualified for evaluations over bright reflecting surfaces, because there is no saturation problem with high radiation input in each of the spectral channels up to an albedo of 1.0 [9].

Furthermore it offers a successful mixture of spectral and spatial resolution and coverage.


An overview of the steps within the extended BAER approach is presented in Fig. 1.

The BAER method determines an aerosol reflectance by eq. ( 1) and has been extended for the purpose of retrievals over desert: (1) Subtracting the path reflectance produced by the Rayleigh scattering for the geometry of illumination and observation.

Correcting air masses by ground pressure using a digital elevation model for the surface elevation.

( 2) Correcting the surface reflectance.

Over land: using a model of a linear mixture of reflectance spectra of vegetation and bare soil, tuned by Normalized Differential Vegetation Index (NDVI).

Over ocean: linear mixing of coastal water and clean ocean using Normalized Differential Phytoplankton Index (NDPI). ( 3) A new land class ‘Desert’ has been implemented, using brighter bare soil spectra, if NDVI is close to zero.

( 4) The use of constraints for the spectral aerosol optical thickness as a function of wavelength.

In this manner, BAER retrieves spectral AOT by separating the effect of aerosol on the backscattered radiation from those of surfaces.

As a result the spectral surface reflectance is generated simultaneously for a given ground scene.

The main problem is the selection and consideration of the variability of bare soil spectra.


To distinguish between cloudy and cloud free pixels from MERIS observations we use a three step approach.

This based on the following three assumptions: (1) First we use a simple threshold approach.

That means if the TOA reflectance of channels 2, 3 and 4 (443, 490 and 510 nm) exceeds a limit (ρ TOA > 0.3) we assign this pixel as cloudy.

( 2) If the TOA reflectance the ratio of two channels (412 and 443 nm) for the first is lower than ρ TOA(412 nm)/ρ TOA(443 nm) < 1.04.

( 3) The standard deviation of a centre pixel of a 5 × 5 pixel mask to the mean of this mask is a value for the gradient of this pixel to the neighbour pixels.

This assign mainly the cloud borders and high reflectance variations within clouds.

If the relation of the standard deviation to the mean of a 5 × 5 pixel mask is lager than σ/AOT(5 × 5) > 0.005 the pixel is masked as cloudy.

These values are working quite well for the region of SAMUM campaign. But improving this cloud parameters for independent retrievals on lager scales (beyond SAMUM region) is subject of further investigations.


The main equation [12][5] used in this work can be formulated as follows: ρAer(λ, z0, zS) = ρTOA(λ, z0, zS) − ρRay(λ, z0, zS, pSurf(z)) − T (λ, M(z0)) · T (λ, M(zS)) · ASurf(λ) 1 − ASurf(λ) · ρHem(λ) (1) , where ρ Aer is the aerosol and ρ TOA the TOA reflectance, calculated by the normalization of measured TOA radiance L(λ) to the extraterrestrial irradiance E 0(λ) multiplied by the airmass factor M0: ρTOA(λ) = π L(λ) E0(λ) · M0.

( 2) ρ Ray(λ, z0, zS, pSurf(z)) is the path reflectance of the Rayleigh scattering whereas pSurf(z) is the surface pressure depending on the elevation of the ground for the corresponding pixel.

The information of the elevation comes from the gtopo30 database (q. v. http://edc.usgs.gov/sitemap.html).

T(λ, M(z0)) and T(λ, M(zS)) are the total atmospheric transmission for the zenith distance of illumination z0 and viewing geometry zS whereas M is the air mass factor.

The transmission factors containing direct and diffuse transmission for both radiation directions z0,S .

ρ Hem(λ) is the hemispheric atmospheric reflectance.

The influence of the hemispheric reflectance over low reflecting surfaces (e.g. ocean or vegetation in the blue spectral region) is less important but not negligible over bright surfaces like desert.

Total transmissions and hemispheric reflectance are determined by parametrization derived from radiative transfer calculations [15][16].

The radiative transfer calculations are made using an Henyey-Greenstein asymmetry parameter of g = 0.7.

The transmissions and hemispheric reflectance are calculated for a AOT range of 0.0–2.5 and parametrized by polynomial coefficients.


The investigations with the SAMUM data have shown that consideration of the surface albedo ASurf(λ) as a Lambert ground is not sufficient.

In this study it has been shown that a simple cosine law does not match the angle dependence of desert ground reflectance.

Therefore, an improved surface bidirectional reflectance distribution function (BRDF) model is implemented in BAER and is described in Section 2.3.

Figure 2 shows several surface spectra, including data for bright bare soil conditions.

Since the bare soil over the Sahara region is more or less the only surface influence, the variability of the soil type directly affects the spectral AOT.

Therefore, a regional data set with an adequate surface spectra is required.

This needs to be established iteratively by the BAER approach, starting with a priori assumptions for the region of interest.

For the SAMUM region, the spectrum from [17] as ρ Soil(λ) and a vegetation spectrum ρ Veg(λ) from closure experiment Lindenberg Aerosol Characterization Experiment (LACE-98) are used (see [5]).


Using MERIS overflights, intercomparisons of retrieved aerosol optical thickness and ground-based sun photometer measurements have been made.

These intercomparisons have shown systematic deviations depending on viewing geometry.

Since the phasefunctions in [6], see Fig. 4, do not support the observed deviations in viewing geometry, the observed effects need to be evoked by surface anisotropy.

Therefore the surface reflectance model used by the BAER approach needs to be extended for anisotropy effects of surface.

The following surface reflectance model is used in this study: ρSurf(λ) = · [CVeg · ρVeg(λ) F BRDF∗ + (1 − CVeg) · ρSoil(λ)] (3) with F as scaling factor, adapting the spectral surface model to the conditions within the scene.

This scaling is made for the wavelength 0.665 μm (MERIS channel 7).

F = ρTOA(665 nm) − ρRay(665 nm) − ρAer(665 nm) CVeg · ρVeg(665 nm) + (1 − CVeg) · ρSoil(665 nm) (4) .

C Veg is the vegetation fraction using an atmospheric corrected NDVI, calculated with channel 13 (0.865 μm) and channel 7 (0.665 μm) of MERIS and BRDF∗ is a normalized function considering the surface anisotropy relative to nadir viewing (see Fig. 3).

BRDF∗(z0, zS, φ) = BRDF(z0, zS, φ) BRDF(z0, zS = 0, φ)


The original approach of [18] does not consider the BRDF effects and F was the only parameter for adapting the surface model.

However, the radiation closure between ground-based results and satellite data within this study showed that significant deviations in AOT occur, if the surface anisotropy is neglected.

To reduce deviations in AOT the surface anisotropy by the Rahman-Pinty-Verstraete BRDF model [19][20][21][22][23] will be introduced as follows: BRDF = k0 · cosk2−1 z0 · cosk2−1 zS (cos z0 + cos zS)1−k2 · P (θ ) · (1 + R(θ)).

( 6) Thereby P (θ) = [ 1 + k2 1 1 − k2 1 − 2 · k1 · cos(π − θ ) ] 3/2 (7) is a function of anisotropic scattering of the surface, where θ is the phase angle cos θ = cos z0 · cos zS + sin z0 · sin zS · cos φ .

( 1 + R(θ)) describes the ‘glint’ region.

R(θ) = 1 − k0 1 + g (8) g = (tan2 z0 + tan2 zS − 2 · tan z0 · tan zS · cos φ)1/2.

( 9) The parameters k0, k1 and k2 have to be determined to minimize the deviations of the retrieved AOT from satellite and ground.

k0 is the parameter for the intensity of the surface reflectance and has less influence on the shape of the BRDF.

As input of this parameter we use the result of [C Veg · ρ Veg(λ) + (1 − C Veg) · ρ Soil(λ)] from eq. ( 3).

For the conditions at the location of ‘Porte au Sahara’ k2 = 0.7 and for k1 = −0.1 have been extracted as optimal parameters.

The same parameters at the site Ouarzazate also lead to a significant reduction of deviations between retrieved satellite and ground-based AOT.


Assuming a ‘black-sky’ albedo, in other words neglecting the diffuse hemispherical part (‘white-sky’ albedo), the resulting surface reflectance ρ Surf(λ) can be treated as equivalent to the albedo ASurf(λ).

The increase of the diffuse hemispherical reflectance along with increasing atmospheric aerosol loading is corrected by ρ Hem(λ) in eq. ( 1).

The present status cannot give experience on the regional variability of these parameters, especially, if different surface types exist.

These parameters are found for dry stone desert type in Southern Morocco.

However, the continuation of the analysis of deviations between retrieved and ground-based AOT and the analysis of POLDER (Polarization and Directionality of the Earth’s Reflectances) data will give also parameters for other surface types [23].


The LUTs describe the relationships between TOA reflectance, aerosol reflectance and the AOT, respectively, for the different channels of the MERIS instrument.

These calculations have been carried out with radiative transfer models (RTM) to establish look-up tables for the retrieval.

This is made by using the radiative transfer code of [24] for the solar illumination and satellite observation geometry within the scene.

Similar results have been obtained using the RTM SCIATRAN [25].

Aerosol reflectance is strongly dependent on illumination and viewing geometry.

Since the RTM include multiple scattering, the effects of multiple scattering are automatically considered in the LUT.

The setup of LUT requires input parameters for the RTM.

These are the aerosol optical thickness, the phasefunction and the single scattering albedo of the aerosol and the spectral surface reflectance.

The aerosol optical thickness, the phasefunction and the single scattering albedo were determined using ground-based measurements [6] and the spectral surface albedo by aircraft measurements [7].

Examples of calculated phasefunctions are shown in Fig. 4.

This phasefunctions are calculated from ground-based CIMEL sky brightness measurements by using an inversion model based on a semi-empirical approach by [26] and was done in [6].

The curve shape shows a very smooth behaviour in the backward scattering region and no back scattering peak which is an outcome of non-spherical particles.

Further information are available in the work of [6].

The results of the radiative transfer calculations are shown in Fig. 5.

The LUT was calculated up to an aerosol optical thickness of 2.5.

The AOT increases strongly with increasing aerosol reflectance, this means low deviation of the retrieved aerosol reflectance leads to a high variation in the AOT.

If we look to the variability of the anisotropy effects of the surface (see Section 2.3) we get differences of ±20% in the considered surface albedo (see Fig. 3).

This makes a difference for lower wavelength, where the surface reflectance is about 0.1 (see Fig. 2), of ±0.32 in the retrieved AOT.

For larger wavelength (>500 nm), where the reflectance of bright surfaces may be greater than 0.3 (see Fig. 2), deviation of ±20% leads to an over- or underestimation of the AOT of 1.15.

Therefore, we retrieve the AOT only for the first seven channels of MERIS (412–665 nm).

The data for lager wavelength are extrapolated with the calculated Ångström coefficient to the six channels above 665 nm (682–885 nm) to recalculate the atmospheric corrected surface reflectance.

Radiative transfer calculations have also shown that a brighter surface reflectance yields to an increase of the multiple scattering fraction as part of the aerosol reflectance.

Thus, the surface has an important influence on the retrieved AOT.

Other than for relative dark surface conditions, systematic LUTs for different surface conditions are required.


The extended BAER approach has been tested over the Sahara region during the SAMUM experiment in Ouarzazate and Zagora (“Port au Sahara”), South Morocco (SAMUM, 2006).

During the SAMUM experiment (12 May–7 June 2006) the following closure measurements have been made: (1) Ground-based measurement for spectral AOT and sky-brightness with a CIMEL 318 sun photometer to derive validation data and required aerosol phasefunctions for the desert dust.

( 2) Spectral albedo measurements from aircraft [7] to compare the retrieved spectral surface reflectance by BAER.

( 3) Top of atmosphere radiance by the MERIS instrument for the retrieval of AOT and surface reflectance by BAER and for further closure studies to derive additional aerosol and surface parameters.

Inter-comparisons with the ground- and satellite-based data will be given in Section 4.

First retrievals over desert region with the modified BAER are presented in this paper.


Using the desert starting conditions described in Sections 2.2, 2.3 and 2.4, first retrievals of AOT and surface reflectance over Morocco and surrounding region have been obtained.

As one example, Fig. 6 gives the regional pattern of AOT for MERIS channel 1 (412 nm) over land and ocean for the MERIS scene of 19 May 2006.

The corresponding RGB image is given in Fig. 7.

A validation of AOT for all MERIS overflights during the SAMUM campaign (12 May–7 June 2006) in Morocco is given in Fig. 8.

The two CIMEL sun photometers for ground-based AOT measurements were placed at the airport of Ouarzazate as well as 36 km southeast of Zagora at ‘Porte au Sahara’.

The sun photometer in Ouarzazate was part of the AERONET network and the sun photometer in Zagora was contributed by the Institute of Environmental Physics, University of Bremen.

For further information see corresponding publications [6].

First validations have been done by wavelength 440 nm of the sun photometer and 443 nm of the MERIS instrument, respectively.

The retrieved AOT from satellite data is averaged over a 5 × 5 pixel mask of the corresponding geolocation.

The comparisons show qualitative good agreements between retrieved AOTs with a correlation coefficient of 0.84 (see Fig. 8).

The time of measurements and satellite overpass time are synchronized and have maximum deviation of ±20 min.

Nonetheless strong temporal dynamics of aerosol loading in these regions could be responsible for deviations of ground- and satellite-based measurements because of differences in measuring time.

22 and 25 May 2006 show very high AOTs around 1.2 for ground measurements.

The BAER algorithm detects these conditions as cloudy and disregards the relevant pixels from standard AOT retrieval.


In Fig. 9, comparisons of spectral AOT retrieved from satellite (MERIS BAER) and CIMEL ground-based instrument are shown.

The AOTs of 13 MERIS channels are averaged over 5 × 5 pixels for the geolocation of the SAMUM AERONET site in Ouarzazate.

The error-bars are the standard deviation for the 5 × 5 pixel mask.

The sun photometer spectra in Fig. 9 are measured for the same time as the MERIS overpass time with maximum deviations of ±20 min.

The MERIS AOT shows a higher Ångström coefficient than the sun photometer.

For the first four MERIS channels the comparison shows good agreement but for wavelengths above 500 nm the deviation increases.

This behaviour is due to the increasing of total TOA reflectance in relation to the aerosol reflectance, which is a consequence of increasing surface reflectance.

So little deviations in the estimate of surface reflectance have a strong impact on the retrieved AOT.


The Multiangle Imaging Spectroradiometer (MISR) flies aboard the TERRA satellite in a sun synchronous orbit and measures upwelling solar radiation scattered by Earth surface and atmosphere.

The instrument measures for each pixel in a swath of 400 km width four short-wave spectral channels (446, 558, 672 and 866 nm) at nine different viewing angles (forward and backward 70.5°, 60.0°, 45.6°, 26.1° and nadir view).

With this feature the MISR aerosol retrieval algorithms are able to distinguish contributions in TOA reflectance from surface and atmosphere [27][28][29][30].

The MISR standard aerosol product reports AOT and aerosol type at 17.6 km spatial resolution.

With the swath width of 400 km the MISR instrument has a poorer coverage than the MERIS instrument and get a global coverage every 9 d. During SAMUM field campaign there were three dates (19, 28 May and 04 June 2006), where the MISR overpass covers the region of interest (see [31]).

The comparisons between MISR and MERIS show good agreement with little deviation (see Fig. 8) which could be caused by different overpass times (∼30 min).


If the BAER algorithm completes the AOT retrieval successfully, which means with a RMSD lower than 0.05, the standard run is followed by an additional loop: The recalculation of surface albedo by inversion of eq. ( 1) with all retrieved parameters.

In Fig. 10, comparisons of surface reflectance from satellite and aircraft in the region of Ouarzazate for the 19 May 2006 are shown.

For each aircraft measurement the next collocated pixel of MERIS measurement is evaluated.

The TOA reflectance has been corrected by the atmosphere reflectance, in other words by the Rayleigh reflectance ρ Ray(λ, z0, zS, pSurf(z)) and aerosol reflectance ρ Aer(λ).

First retrievals of recalculated surface albedo for the 19 May 2006 in the region of Ouarzazate show qualitative good agreement with air plane measurements from [7].

The BAER algorithm reproduces the shape of the spectral dependence of the albedo in a correct way, but the deviation of the absolute adaptation in wavelength above 550 nm leads to a larger error in the retrieved aerosol optical thickness.


First retrievals of aerosol optical thickness over arid and semi-arid Saharan desert regions of the MERIS instrument aboard ENVISAT are obtained.

These results have been analysed and validated in comparison with the ground-based observations.

It has been shown that the assumption of a Lambert ground leaded to unresolved surface effects in the AOT retrieval.

Especially dependencies of the AOT results on viewing geometry were observed.

Exclusion of the TOA reflectance anisotropy due to aerosol and molecular scattering, leads to the conclusion that further surface directional effects have to be taken into account.

Therefore, following improvements and modifications in the original BAER retrieval have been required to improve AOT results over brighter surfaces.

( 1) The Rayleigh path reflectance ρ Ray(λ, z0, zS, pSurf(z)) needs to be calculated considering the approximate value surface reflectance.

The assumption of ‘black’ surface leads to biased spectral behaviour of AOT.

( 2) The surface cannot be treated as a Lambert ground.

The retrieval results suffered from surface anisotropy, depending on illumination and viewing geometry.

Since the MERIS observations during SAMUM include the ‘glint’ region, clear indications for non Lambertian surface effects have been found.

( 3) For the compensation of surface anisotropy the parameters of a BRDF model [23][19][20][21][22] have been determined to minimize the deviations between retrieved AOT and ground-based observations.

Thus a normalized BRDF model has been obtained, which is implemented into the surface model of BAER.

With these changes in the original BAER approach comparable AOTs with ground-based observations have been obtained.

The results are now comparable within a 25% range in magnitude and in spectral slope (see Figs. 8 and 9).

The correlation of retrieved AOT of 443 nm from ground- and satellite-based measurements improves from 0.22 to 0.84.

First retrievals of recalculated surface albedo for the 19 May 2006 over Ouarzazate show qualitative good agreement with airplane measurements from [7] (see Fig. 10).

The algorithm reproduces the spectral shape of the albedo in a correct way, but the deviation of the absolute adaption for wavelengths above 550 nm leads to a larger error in the retrieved aerosol optical thickness.


This is the first time a retrieval is presented to analyse spectral aerosol properties over bright reflecting desert regions for the MERIS instrument.

To solve such challenging problem closure experiments like SAMUM are essential to get detailed knowledge about local atmosphere aerosol conditions.

With that knowledge we were able to improve the BAER algorithm to those conditions.

The key issue to retrieve aerosol optical thickness from TOA reflectance is the separation between atmosphere and surface reflectance.

Because of high variability and no atmospheric independent characteristic, like the NDVI, we need a priori knowledge about the surface reflectance.

This knowledge comes from experimental measurements like the SAMUM campaign.

To retrieve larger regions from satellite, not everywhere measurements are available, we need to use a database of surface reflectivity using, for example, the minimum reflectivity technique [32][33].

The radiative transfer calculations for the determination of LUT showed that brighter surface reflectance leads to an increased contribution of multiple scattering.

Therefore, LUT calculated for dark (or even ‘black’) surface conditions will underestimate higher AOT.


Demographic and Clinical Characteristics of the MGH Cohort Table 1 and Supplement Table S1 (24) provide demo- graphic, clinical, and laboratory characteristics overall and by obesity (BMI ≥30 or BMI <30) for the MGH cohort.

At PTC, obese patients were more likely to be female (48% vs 41%, P = 0.020), were younger (56.0 vs 65.0 median age, P < 0.001), less likely to have ever smoked (33% vs 42%, P = 0.001) and more likely to be Hispanic (42% vs 32%, P < 0.001) compared with nonobese patients.

They were also more likely to experience a longer time from start of symptoms to PTC, experience more symptoms at PTC, have a reported history of T2DM and be admitted directly to the ICU than nonobese patients.

At 28 days after PTC, obese patients had more complications, including acute respiratory distress syndrome, and were more likely to be mechanically ventilated.


CRP trajectories over time are illustrated in Fig. 2 stratified by obesity.

The individual level trajectories are presented as a function of the number of days before or after peak CRP.

Medians each day by mechanical ventila- tion/death status are provided.

This exploratory figure sug- gests: (1) a shift upwards in CRP within both obesity strata for patients with more severe disease; and (2) a higher median peak CRP for obese compared with nonobese pa- tients.

In unadjusted analysis, median peak biomarker values in obese patients compared with nonobese patients were greater for CRP and ESR.


Findings support systemic inflammatory pathways in obesity-associated severe COVID-19 disease, particularly in patients < 65 years, captured by CRP and ESR.

Contextualized in clinical trial findings, these results reveal therapeutic opportunity to target systemic inflammatory pathways and monitor interventions in high-risk subgroups and particularly obese patients.


Key Words: biomarkers, COVID-19, inflammation, obesity, SARS-CoV-2, severe disease Obesity is one of the strongest risk factors for critical illness among severe acute respiratory syndrome cor- onavirus 2 (SARS-CoV-2)-infected individuals (1-4).

Moreover, emerging evidence suggests that obesity- associated severe disease is more pronounced in younger populations compared with older populations (5-8).

At the same time, studies of multiple biomarkers of pathophysiological processes reveal elevated levels of C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), D-dimer, ferritin, interleukin-6 (IL-6) and white blood cell count (WBC) and its fractions contribute to severe COVID-19 outcomes (4, 9).

Indeed, emerging immunophenotyping data suggest that a marked dysregulation of innate and adaptive immunity is a hall- mark of poor outcomes in COVID-19 (10-12).


As the relationship between obesity and inflammatory markers is well-established in population and clinical based epidemiologic studies of non-SARS-CoV-2-infected individ- uals (13-15), several commentaries have postulated on com- plex mechanisms linking obesity, inflammatory pathways, age, and race/ethnicity to severe disease in COVID-19 (16, 17).

However, the specific role of inflammation in the causal pathways between obesity and severe COVID-19 outcomes remains unknown and the translational clinical utility of dis- ease biomarkers in COVID-19 remains to be fully developed and exploited.

In this work, we hypothesize that biomarkers of obesity-associated systemic inflammation are mediators of severe outcomes in COVID-19.

Through a rigorous in- vestigation of causal mediation by systemic inflammatory responses in the link between obesity and severe COVID-19 outcomes, this research is designed to advance clinical trans- lational opportunities for targeted interventions.


We addressed our hypothesis using data derived from 3828 SARS-CoV-2-infected patients hospitalized at 2 independent quaternary care facilities, Massachusetts General Hospital (MGH) and Columbia University Irving Medical Center/New York Presbyterian Hospital (CUIMC/NYP).