Mineral dust particles originate mainly from arid anddesert regions of North Africa, Middle and East Asia,and the Arabian Peninsula, and can be frequentlytransported more than a thousand kilometers by at-mospheric circulations.1 These aerosols are known tobe mainly composed of nonspherical particles andexhibit strong mass and time variations dependingon the surface properties as well as the weather con-ditions. Like other particles, dust aerosols affect theEarth’s climate through direct extinction of solar ra-diation and indirect modification of cloud formation.2Those effects, however, are not actually entirely char-acterized, partly due to their highly variable and com-plex geometric shape.
Several theoretical3–5 and experimental6 studieshave demonstrated the effect of the particle’s shapeon its optical properties. The theoretical computationof scattering properties for realistic nonspherical par-ticles still remains a difficult task. For example, thesimulated optical and radiative parameters of silicate
samples obtained through their microphysical prop-erties do not fully fit the laboratory measurements.6Indeed, the simulations with the use of microphysicalproperties are not as effective as those we can expectfor the assumed spherical particles (with a good ap-proximation) belonging to the accumulation mode.Therefore the new remote sensing retrievals of aero-sol optical properties, for example, presented in thisstudy, as well as laboratory measurements, are es-sential complementary tools to improve the aerosoloptical characterization.
The continuous observations of the ground-basedsunphotometer network have tremendous potential tomonitor regional and global aerosol particles as well asto comprehensively retrieve particle properties. Cur-rent routine aerosol retrieval algorithms commonly as-sume a fixed shape, e.g., sphere or spheroid, to providea group of retrieved microphysical parameters leadingto the computation of optical properties. However, thismethod usually leads to a loss of accuracy for dustaerosols. In previous work, we have established apolarimetry-based retrieval algorithm that derivesaerosol optical properties directly from sky radianceand polarized radiance measurements.7–10 We haveshown that the retrieved optical properties are notsensitive to the initial shape assumption and can re-veal nonspherical properties of aerosol particles. Thisdemonstration has been performed using a spheroiddust model.10
In this paper, we mainly present the retrieval ofoptical properties for natural dust aerosols andpostpone the investigation on their microphysical
Z. Li ([email protected]), P. Goloub, L. Blarel, T.Podvin, and I. Jankowiak are with Laboratoire d’Optique Atmo-sphérique, Université des Sciences et Techniques de Lille, Ville-neuve d’Ascq, France. B. Damiri is with CIMEL electronique,Paris, France.
Received 7 September 2006; revised 9 December 2006; accepted14 December 2006; posted 15 December 2006 (Doc. ID 74823);published 1 March 2007.
properties. We consider sunphotometer polarizedmeasurements acquired at several potential dustsites in Africa, Europe, and East Asia. This datasetis contributed mainly by the PHOTONS network,the French part of the AERONET global sunpho-tometer network. A total of 16 sites with potentialdust occurrences are initially considered. Amongthem, Agoufou, Banizoumbou, Dakar, Institute ofRural Economy (Cinzana), and Ouagadougou (Fig.1), with a sufficient amount of dust events in 2005,are finally selected for further investigations. Sincethese sites were involved in the African MonsoonMultidisciplinary Analysis (AMMA) experiment from2005, carefully maintained instruments have pro-vided quality-assured data.
2. Items and Method
Equation (1) describes the scattering of an incidentwave on randomly oriented particles,
�IQUV��
�s
4�r2 F�I0
Q0
U0
V0
�, (1)
where the optical characteristics of the particles aredescribed by a scattering phase matrix F. Two vectors�I0, Q0, U0, V0�T and �I, Q, U, V �T composed of fourStokes parameters (T means transpose) representthe incident and scattered waves, respectively, and ris the distance between the scattering particle andthe observer. The quantity �s is the scattering crosssection that denotes the scattered energy by parti-cles. The total energy removed from the incidentwave is described by �c.11 The ratio �s��c is calledsingle-scattering albedo �0, which describes the radi-ation absorption property of aerosols. In practice, themeasured total radiance L equals I, and the polarizedradiance Lp equals �Q2 � U2 � V2�1�2. The influence ofV is usually insignificant in the Earth’s atmosphere.Moreover, the first element of the scattering matrixF11, also called phase function, is normalized as
�0
�
F11���sin �d� � 2, (2)
where � is the scattering angle.
In 1998, Devaux et al. published a relationship [Eq.(3)] between the measured and the simulated (markedwith*) atmospheric radiative parameters,7
�0
��0F11
�0*sin �d� ��
0
�
�L � �L* � L0*�L0*
F11*
�L � L*
L0*�m
�0*�apm�sin �d�,
(3)
where �0* and F11* are the estimated aerosol single-scattering albedo and phase function, respectively,�a is the aerosol optical thickness, and �m and pm
correspond to the molecular optical thickness andphase function, respectively. We call L the measuredsky radiance, L* the calculated radiance, and L0*the calculated radiance in the case of a black surface(the reflectance equals zero). These radiative quanti-ties are computed by using successive-orders-of-scattering (SOS) radiative transfer code,12 assuminga plane-parallel atmosphere and taking into accountmultiple scattering processes within the atmosphereas well as interactions with the ground. In this work,we use a Lambertian surface assumption and groundreflectance derived from five-year bimonthly aver-aged Moderate Resolution Imaging Spectroradiom-eter (MODIS) observations.13
By substituting Eq. (2) into Eq. (3), the left-handintegral is reduced to 2�0��0*. Hereafter, �0 is com-puted with a simple interpolation method as follows.Given several �0* and a fixed F11*, when the right-hand integral reaches 2, the left-hand �0* convergesto �0 (the measured single-scattering albedo). Once�0 is known, F11 can be calculated with Eq. (3). Givenpolarimetric measurements, the second element ofthe scattering matrix F12, or the polarized phase func-tion �F12, can be computed as
F12 � F12*Lp
Lp*��0��
Lp � Lp*��0�Lp*��0�
�m
�0�aqm, (4)
where qm is the second element of the molecularscattering matrix, and Lp*��0� means the polarizedsky radiance calculated with the measured single-scattering albedo.
Systematic sensitivity studies have shown the max-imum retrieval errors are 0.03 on �0, 10% on F11, 0.01on F12, and 0.02 on the �F12�F11 ratio at 0.87 m.10
These accuracy assessments are performed at a solarzenith angle of 45°, and atmospheric particles areassumed to be spherical with a coarse-mode domi-nated size distribution. Benefiting from the retrievalalgorithm, we expect a similar accuracy for retrievingoptical properties of natural dust particles.10
3. Data and Results
The initial dataset used in this study is composed ofsolar-principle-plane sky radiances at 0.44, 0.67, 0.87,and 1.02 m, polarized sky radiances at 0.87 m, and
Fig. 1. Map of the selected sunphotometer locations in Africa.
spectral aerosol optical thickness �a measured by theCimel CE318 polarized version sunphotometer. Thefirst step before retrieving the particle’s optical prop-erties is to select cloud-free measurements. We useAERONET level 1.5 �a measurements. In this level,most of cloud-contaminated records have beenremoved.14 In addition, we check the symmetry ofaureole measurements as well as the angular skyradiance smoothness to reject the cases perturbed byany cloud located distinctly away from a direct sunbeam. Among the various CE-318 polarized versions,the most recent version provides the best polarimet-ric accuracy. In order to obtain more consistent andcomparable results, before retrieving optical proper-ties, we smooth the polarized radiance by a movingaverage smooth algorithm with a slide window offive-point width. The maximum difference betweenthe smoothed and the initial Lp is generally less than4% by considering only scattering angles largerthan 20°.
A. Selection and Classification of Dust Dataset
To select dust cases from cloud-free measurements, weconsider a simple double threshold with �a�0.87 m�larger than 0.5 and an Ångström exponent � lowerthan 0.5. Moreover, for a more accurate retrieval, weselect measurements with solar zenith angles largerthan 62° to obtain F11 and F12 in a wide scatteringrange.10 The numbers of the selected dust cases arelisted in Table 1.
We plot the retrieved �F12�90°��F11�90°� in Fig. 2.The relationship between linear polarization degree
and � confirms that polarization is sensitive to aero-sol size parameters. In addition, most of the data�85%� are located within � range from �0.05 to 0.25.We split this large interval into four subintervals inorder to facilitate the classification analysis. Defini-tion of classes, numbers of samples, and the averagedÅngström exponents are all listed in Table 2.
B. Dust Optical Properties
The retrieved aerosol optical properties do not exhibitlarge site-to-site variability in any size class. To keepthe consistency with other studies,15 we present inFig. 3, for each size class, the averaged �a��, �0��,F11�0.87 m�, and �F12�0.87 m� quantities. Usingthese results, we can observe these main features ofdust optical properties:
(i) Mineral dust shows a significant increase inthe trend of the single-scattering albedo versus �,which is also shown in other previous studies.15 How-ever, in the case of nondust dominated aerosol parti-cles, we expect �0�� to exhibit a tendency to decrease.At 0.87 m, the average �0 value over all size classes��0.05 � � � 0.25� reaches 0.95.
(ii) Mineral dust phase function F11 exhibits rathersmall variability and shows, as expected, strong for-ward scattering as well as weak and rather flat back-ward scattering. We also show a modeled F11 obtainedthrough Mie code with an assumed dust refractiveindex of (1.5 � i0.001) and a lognormal size distribu-tion fitting the laboratory measured size of the felds-par sample with the laser diffraction method. This F11is also employed by other authors to compare withlaboratory measurements of feldspar sample’s phasefunction.6 In our study, we consider this F11 a typicalmodel for spherical coarse particles, and therefore ithelps illustrate the difference between our retrievaland retrieval for spherical particles. Within a scat-tering angle range from 15° to 80°, our retrievedF11 is smaller than the one of spherical coarse parti-cles. From 80° to 140°, our retrieval is larger thanthat of spherical particles. This systematic distinctangular behavior was also observed in previous find-ings16 and can be considered as evidence of non-spherical particles.
(iii) The retrieved polarized phase function �F12also differs significantly from the one of sphericalcoarse particles obtained through Mie theory, andincreases regularly together with an increase of �,i.e., a diminution of the aerosol size. The maximumvalue of �F12 in the 50°–140° range varies from 0.034to 0.053, while a local minimum is found in the range20°–50°. Detailed data files corresponding to Fig. 3as well as F11 retrieved at additional wavelengths,e.g., 0.44, 0.67, and 1.02 m, can be found on thePHOTONS web site (http://www-loa.univ-lille1.fr/photons).
4. Comparison with Laboratory Results
Volten et al. published several scattering phase matrix-es of mineral samples measured in the laboratory.17
Fig. 2. (Color online) Degree of linear polarization for single scat-tering of dust aerosols at a fixed scattering angle (90 degrees)versus Ångström exponent. Classification of the retrievals and abest linear fitting of all points are also shown.
Table 1. Numbers of Cloud-Free, Total Dust [�a(0.87 �m) > 0.5 and� < 0.5], and Selected Dust (Plus a Limitation of Solar Zenith
In Fig. 4 we compare the retrieved �F12�F11 ratio withthat for the experimental feldspar sample and anaverage of several samples (feldspar, red clay, quartz,loess, Pinatubo volcanic ash, Lokon volcanic ash, andSahara sand). Moreover, the parameterized feldsparsize distribution and refractive index6 are used tocompute �F12�F11 through Mie theory by assumingspheres. For comparison, we also show these com-puted Mie results at 0.63 and 0.87 m in the samefigure.
Figure 4 provides some general features for themineral dust �F12�F11 ratio. Several points should bekept in mind:
(i) There are probably differences in the micro-physical properties between laboratory samples andnatural dusts, e.g., size distribution, refractive index,particle composition, and humidity.
(ii) Laboratory measurements and our retrievalsare not performed at the same wavelength due todistinct instrument designs. However, this spectraldifference shows no significant importance, in thecase of large nonspherical particles.18
Regardless of these differences, our retrievals stillexhibit a good consistency with laboratory measure-ments in this quasi-quantitative comparison, becausethe determining factor inside the comparison is thatboth of the investigated samples are nonsphericallarge particles. Our results also agree with severalprevious studies in the way that spherical particlesproduce very different angular features,3,6,18 as illus-trated by Fig. 4. This consistency demonstrates thereliability of our algorithm to detect the radiative andoptical effect of nonspherical particles.
Fig. 3. (Color online) Averaged dust optical properties retrieved from ground-based sunphotometer polarimetric measurements: (a) spectraloptical thickness, (b) spectral single-scattering albedo, (c) phase function, and (d) polarized phase function. Error bars show the standarddeviation of the variability of sample values. We also show modeled F11 and �F12 for spherical coarse particles obtained through Mie theorywith a lognormal size distribution fitting the laboratory measured size of the feldspar sample and an estimated refractive index (Nousiainenet al., 2006) in (c) and (d) to illustrate the difference of optical properties between spherical and natural nonspherical dust particles.
Table 2. Classification of Dust Measurements at Five African Aeronet Sites in 2005a
We consider sunphotometer measurements at fiveAfrican AERONET sites and derive dust optical prop-erties with the use of a polarimetry-based algorithm.Retrieved single-scattering albedo shows an increas-ing trend versus wavelength with an average of 0.95at 0.87 m. Phase function F11 illustrates strong for-ward scattering as well as weak and flat backward�� 100°� scattering with a typical value of 0.18 at120°. Retrieved polarized phase function �F12 andlinear polarization degree �F12�F11 for single scatter-ing of unpolarized incident light increase when thesize of the particle decreases, while the maximumvalues observed at scattering angles of 100° rangebetween 0.14 and 0.21. Compared with the results ofMie code for spheres, the retrieved angular behaviorof the scattering matrix elements differs significantly.
Since accurate modeling of polarized optical prop-erties of natural mineral dust from its microphysicalproperties remains a difficult task, we choose an al-ternative strategy to validate our retrievals. We per-form the comparison with the existing laboratorymeasurements of linear polarization degree of silicatesamples, in order to check the reliability and effi-ciency of our method in the assessment of opticalproperties for nonspherical particles. Although ex-perimental limitations restrict the quantitative as-pect of the comparison, the reliability of our retrievalsis confirmed by the good consistency with laboratoryresults as well as the significant difference from Mieresults for spherical particles. Furthermore, our re-sults provide valuable information for the spaceborneremote sensing based upon multi-angular, spectral,and polarized observations. For example, the impor-tant issue of aerosol retrieval from space, as is donewith POLDER1-2�PARASOL directional and polari-metric measurements, is the necessary use of opticalproperties since the algorithm is based on aerosol F11
and �F12.19 From the angular information measuredby POLDER1-2�PARASOL, one can detect the pres-ence of nonspherical particles to select the most con-venient F11 and �F12 (i.e., nonspherical particles) interms of the spectral �a retrieval. Over the ocean, inmany dust cases, the use of F11 and �F12 derived fromnonspherical particles has greatly improved the in-terpretation of angular radiance and polarized radi-ance, and consequently the retrieved aerosol opticalthickness.20 In this context also, our results provideuseful information to improve these satellite algo-rithms.
This work was supported by Centre Nationald’Etudes Spatiales (CNES) and Fonds Européen deDéveloppement Régional (FEDER). We thank D.Tanré, B. Chatenet, F. Lavenu, and correspondingsite managers for maintaining sunphotometer sitesused in this research. We would like to thank theAERONET (http://aeronet.gsfc.nasa.gov) team atGoddard Space Flight Center for supplying data ac-cess and optical thickness calculations. We also wishto thank E. Cuevas from INM, Izana (Spain) and J. P.Morel from Météo France, Carpentras (France) forcontributing to PHOTONS sunphotometer calibra-tion. We are grateful to L. Gonzalez and C. Oudardfor providing MODIS ground reflectance. The au-thors are also very grateful to M. Kacenelenbogen,M. Deng, and S. Wang for improving the English ofthis manuscript. PHOTONS Service d’Observation isfunded by CNES, INSU (Institut National des Sci-ences de l’Univers), CNRS (Centre National de laRecherche Scientifique), and USTL (Université desSciences et Techniques de Lille).
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