Aerosol Characterization and Direct Radiative Forcing Assessment over the Ocean. Part I: Methodology...

1818 VOLUME 43J O U R N A L O F A P P L I E D M E T E O R O L O G Y

q 2004 American Meteorological Society

Aerosol Characterization and Direct Radiative Forcing Assessment over the Ocean.Part II: Application to Test Cases and Validation

MARIA JOAO COSTA

Department of Physics, and Evora Geophysics Centre, University of Evora, Evora, Portugal, and National Research Council,Institute of Atmospheric Sciences and Climate (ISAC-CNR), Bologna, Italy

VINCENZO LEVIZZANI

National Research Council, Institute of Atmospheric Sciences and Climate (ISAC-CNR), Bologna, Italy

ANA MARIA SILVA

Department of Physics, and Evora Geophysics Centre, University of Evora, Evora, Portugal

(Manuscript received 18 July 2003, in final form 19 May 2004)

ABSTRACT

A method based on the synergistic use of low earth orbit and geostationary earth orbit satellite data for aerosol-type characterization and aerosol optical thickness (AOT: ta) retrieval and monitoring over the ocean is presentedin Part I of this paper. The method is now applied to a strong dust outbreak over the Atlantic Ocean in June1997 and to two other relevant transport events of biomass burning and desert dust aerosol that occurred in2000 over the Atlantic and Indian Oceans, respectively. The retrievals of the aerosol optical properties arechecked against retrievals from sun and sky radiance measurements from the ground-based Aerosol RoboticNetwork (AERONET). The single-scattering albedo values obtained from AERONET are always within the errorbars presented for Global Ozone Monitoring Experiment (GOME) retrievals, resulting in differences lower than0.041. The retrieved AOT values are compared with the independent space–time-collocated measurements fromthe AERONET, as well as to the satellite aerosol official products of the Polarization and Directionality of theEarth Reflectances (POLDER) and the Moderate Resolution Imaging Spectroradiometer (MODIS). A first estimateof the AOT accuracy derived from comparisons with AERONET data leads to 60.02 6 0.22ta when all AOTvalues are retained or to 60.02 6 0.16ta for aerosol transport events (AOT . 0.4). The upwelling flux at thetop of the atmosphere (TOA) was computed with radiative transfer calculations and used to estimate the TOAdirect shortwave aerosol radiative forcing; a comparison with space–time-collocated measurements from theClouds and the Earth’s Radiant Energy System (CERES) TOA flux product was also done. It was found thatmore than 90% of the values differ from CERES fluxes by less than 615%.

1. Introduction

The importance of strong aerosol mobilization andtransport episodes is becoming increasingly clear to sci-entists since these events are usually connected withhigher aerosol concentrations in the atmosphere, thusaltering the atmospheric composition and affecting del-icate mechanisms such as the water cycle (Haywoodand Boucher 2000; Ramanathan et al. 2001; Kaufmanet al. 2002). This may cause an enhancement/suppres-sion of many related atmospheric processes affectingnot only the global, but also the regional and local,climate. It is therefore of extreme importance that suchevents be accurately detected, characterized, and mon-

Corresponding author address: Vincenzo Levizzani, ISAC-CNR,Via Gobetti 101, I-40129 Bologna, Italy.E-mail: [email protected]

itored. The primary natural source of aerosol particleson a global scale is sea salt, followed by soil dust, whichis a major contributor especially in subtropical and trop-ical regions (Houghton et al. 2001). Another substantialnatural source of aerosols on a global scale is the bio-mass burning in Africa, Asia, Siberia, and South Amer-ica, particularly in the Amazon. For example, smokefrom forest fires is a source of strong absorbing aerosols,which reduce the amount of sunlight scattered back tospace and lead to absorption of solar radiation withinthe atmospheric column (Kaufman et al. 2002; Raman-athan et al. 2001).

Satellite-based methods are undoubtedly the only wayto proceed for global aerosol studies (King et al. 1999).However, the assessment of the reliability of the retriev-als depends on the comparison with independent mea-surements that allow for the error estimation and even-tually the validation of the method.

DECEMBER 2004 1819C O S T A E T A L .

The low earth orbit–geostationary earth orbit (LEO–GEO) satellite-based method presented in Costa et al.(2004, hereinafter Part I) discussed in detail by Costa(2004) is now applied to three case studies of strongaerosol transport events that occurred over the ocean.The potential of the LEO–GEO synergy had alreadybeen discussed by Costa et al. (2002). The aim of themethod is to overcome the limitations inherent in LEOand GEO systems by improving the accuracy of theaerosol characterization over that used by methodsbased exclusively on GEO satellite data and by extend-ing the spatial and temporal coverage of the LEO sat-ellite retrievals to the GEO spatial–temporal scale. Thislatter point is instrumental for monitoring purposes. Theaerosol characterization is derived from the comparisonbetween the Global Ozone Monitoring Experiment(GOME) spectral reflectance measurements and the cor-responding simulated spectral reflectances contained inlookup tables (LUTs). LUTs are derived for differentaerosol climatological models (Dubovik et al. 2002) andare refined through the variation of some of the sizedistribution parameters (fine-mode modal radius andfine-mode percentage density of particles), as well asthe imaginary part of the refractive index in two spectralregions (0.35–0.50 and 0.70–0.86 mm) and the aerosoloptical thickness (AOT). The aerosol characterizationthat best fits the measurements is considered to be thederived aerosol model. The aerosol optical quantities(single-scattering albedo, phase function, and extinctioncoefficient) are obtained from Mie calculations consid-ering spherical aerosol shapes. These quantities are usedto derive the AOT from GEO satellite measurements,avoiding the use of aerosol models from the literature.The AOT at the GEO spatial–temporal scale togetherwith the aerosol optical quantities characterizing a cer-tain aerosol event are applied to estimate the top-of-atmosphere direct shortwave aerosol radiative forcing(TOA DSWARF).

GEO meteorological satellite sensors normally onlyhost a broadband channel in the visible (VIS) spectralrange. However, the method is open to the possible fu-ture use of GEO satellite measurements from new-gen-eration sensors such as the Spinning Enhanced Visibleand Infrared Imager (SEVIRI) flying on board the Me-teosat Second Generation (MSG) (Schmetz et al. 2002).These sensors are expected to bring improvements tothe retrievals because they are equipped with narrowerVIS spectral bands, and additional spectral informationis anticipated from the channels in the near-infrared(NIR) spectral region, which are complementary tothose from GOME that is limited to the ultraviolet(UV)–VIS (Burrows et al. 1999).

The spectral aerosol single-scattering albedo andaerosol phase function derived from GOME high spec-tral resolution measurements are used to characterizethe aerosol transport events and to model the atmo-spheric radiation. They are successively compared withsimultaneous and collocated retrievals from the ground-

based sun–sky photometer Aerosol Robotic Network(AERONET; Dubovik and King 2000).

The AOT values retrieved at the temporal and spatialscales of the GEO satellite Meteosat are also comparedwith AERONET measurements and with the officialaerosol products from the Polarization and Direction-ality of the Earth Reflectances (POLDER) instrument(Goloub et al. 1999; Deuze et al. 2000) on board theAdvanced Earth Observing Satellite (ADEOS) and withthe Moderate Resolution Imaging Spectroradiometer(MODIS) (Tanre et al. 1997) on board the Terra space-craft. In addition, the AOT values are checked againstresults derived from aerosol models available in the lit-erature. This not only validates the results of the newmethod, but also shows that there is a notable improve-ment when considering the GOME-derived aerosolquantities instead of relying on a climatologically basedcharacterization.

The TOA shortwave (SW) flux is in turn comparedwith the TOA flux product (dataset CERES Terra FM1Edition1 ES8) of the Clouds and the Earth’s RadiantEnergy System (CERES; Wielicki et al. 1996), on boardTerra, with the purpose of controlling the flux modelingquality and indirectly the estimated TOA DSWARF, assuggested by Christopher and Zhang (2002).

The following section illustrates the selected casestudies. Section 3 describes results and their validation,and section 4 summarizes conclusions from the test andvalidation exercise.

2. Case studies

Three case studies of aerosol transport over the oceanwere selected: 1) dust transport over the Atlantic Ocean,2) dust transport over the Indian Ocean (Arabian Sea),and 3) a smoke transport event over the South AtlanticOcean. The geographical areas of each of the case stud-ies are illustrated in the maps in Fig. 1. The blacksquares indicate the locations of the AERONET stationsused as ground reference.

The event of the first case study occurred at the be-ginning of June 1997 over the Atlantic Ocean (Fig. 1a),where massive amounts of dust are frequently blownwestward out of the African Sahara Desert, especiallyduring the Northern Hemisphere summer. This is dueto the almost complete absence of rainout during thisseason, which prevents the deposition of dust particlesand allows their long-distance transport. The Meteosat-6 full-disk image corresponding to the VIS spectralchannel shown in Fig. 2a demonstrates the extent andintensity of the dust event, as evident from the widebrighter region over the North Atlantic Ocean cloud-free region. Figure 2b shows the corresponding AOTmap obtained from the present methodology using theGOME-derived aerosol properties. Higher AOT valuesare distinguished in the region where the dust aerosolplume is located. The dust aerosol absorption map fromthe Total Ozone Mapping Spectrometer (TOMS) on


FIG. 1. Maps of the geographical areas for each of the selectedaerosol case studies: (a) dust transport event over the North AtlanticOcean, (b) dust transport event over the Arabian Sea, and (c) biomassburning event over the South Atlantic Ocean. The black squares in-dicate the location of the AERONET stations used for comparison:(a) CV, Cape Verde; DK, Dakar; BZ, Banizoumbou; (b) BA, Bahrain;KA, Kaashidhoo; NZ, Nes Ziona; and (c) AI, Ascension Island; EP,Etosha-Pan; SW, Swakopmund; and ZA, Zambezi.

FIG. 2. (a) Meteosat-6 full-disk VIS imagery from 8 Jun 1997, slot25 (1200–1230 UTC), when the dust was blowing off the SaharaDesert and crossing the Atlantic Ocean (courtesy of EUMETSAT).(b) The corresponding aerosol optical thickness map derived usingthe present methodology.

board the Earth Probe (Fig. 3a) allows for the detectionof absorbing aerosol particles, such as dust and smoke,based on their absorption properties in the UV spectralregion. The grayish spots over the dominating back-ground color delimit the aerosol absorption areas andtherefore the presence of absorbing particles. The cor-responding selected AERONET stations for the above-mentioned case study are the Cape Verde Islands


FIG. 3. Absorbing aerosol particles detected by the Earth ProbeTOMS on (a) 8 Jun 1997, (b) 14 Jul 2000, and (c) 9 Sep 2000. TOMSdata allow for distinguishing between different types of aerosol par-ticles based on their absorbing properties in the UV. The brighterregions over land and darker regions over the ocean represent strongaerosol absorption.

(16.7338N, 22.9358W); Dakar, Senegal (14.3948N,16.9598W); and Banizoumbou, Niger (13.5418N,2.6658E). VIS (0.30–1.05 mm) and infrared (IR: 10.0–13.1 mm) images of Meteosat-6 positioned over the At-lantic Ocean (08, 08) from 1 to 30 June 1997 are col-lected hourly between 0800 and 1400 UTC. The nearest

space–time GOME data are collected for the same pe-riod. Although the main event took place in the firstpart of June, the entire month’s worth of data were an-alyzed.

The second case study took place from 10 to 16 July2000 over the Arabian Sea (see Fig. 1b). Figure 3bshows the aerosol absorption detected from TOMS: thebrighter areas over the Arabian Sea correspond to thedust transport over the area in this period. Data fromMeteosat-5 (same spectral channels as Meteosat-6), po-sitioned over the Indian Ocean (08, 638E), were collectedonce more with an hourly frequency from 0430 to 0830UTC. The corresponding GOME orbits were also pro-cessed. Measurements from the AERONET stations lo-cated in Bahrain (26.3338N, 50.5008E); Kaashidhoo,Republic of Maldives (4.9658N, 73.4668E); and NesZiona, Israel (31.9228N, 34.7898E), were used for com-parison.

A totally different third case study concerned an ep-isode of smoke transport over the South Atlantic Oceanfrom the biomass fires that raged across southern Africain early September 2000 (results refer to the period from6 to 13 September). The geographical areas are shownin Fig. 1c and the AERONET stations used for the com-parisons were Ascension Island (7.9768S, 14.4158W);Zambezi, Zambia (13.5338S, 23.1078E); Etosha-Pan,Namibia (19.1758S, 15.9148E); and Swakopmund, Na-mibia (22.6588S, 14.5648E). Hourly data from Meteo-sat-7 (same spectral channels as Meteosat-6) were usedfrom 6 to 13 September 2000, between 0800 and 1400UTC, together with GOME data from the same period.The darker regions over the sea in Fig. 3c delimit a widearea of absorbing aerosol (smoke particles), as detectedby TOMS being transported off the west coasts of An-gola and Namibia. Note also in the same map the dusttransport originating from the Sahara Desert, which wasnot considered in the present study.

Besides the aerosol models obtained with the presentmethod, three climatological aerosol models from theliterature (Dubovik et al. 2002) were also examined fortheir aerosol characterization: 1) desert type for CapeVerde, 2) desert type for Bahrain, and 3) biomass burn-ing type (African savannah).

3. Results and validation

a. Aerosol properties retrieved from GOME

A spatial and temporal analysis of the GOME-derivedaerosol optical properties (see Part I for details) resultsin case-specific average dust/biomass burning aerosolquantities, such as spectral extinction, single-scatteringalbedo, and phase function, assuming the aerosol plumesmaintained their physical characteristics during the du-ration of each one of the case studies. These resultswere compared with ground measurements from AERO-NET’s official inversion product (Dubovik and King2000). The AERONET algorithm derives the aerosol


FIG. 4. Spectral aerosol single-scattering albedo values for (a) Sa-haran dust, (b) Arabian dust, and (c) biomass burning. The verticalerror bars represent the standard deviation of the GOME-derivedsingle-scattering albedo (around 0.04).

size distribution, the complex refractive index, and thesingle-scattering albedo from spectral sun and sky ra-diances measured by the network’s sun–sky photome-ters. Level-1.0 data are used in this case since no level-2.0 inversion products were available for the presentcase studies. The AERONET size distribution and com-plex refractive index were used as input for Mie cal-culations in order to obtain the aerosol optical proper-ties, such as the phase function, characteristic of theaerosol event under study according to the recommen-dations of Dubovik et al. (2000). The Angstrom ex-ponent is also calculated from the AERONET spectralAOT values and compared with the value obtained fromGOME.

Figure 4 shows the values of the single-scatteringalbedo for the three case studies together with thosefrom aerosol models in the literature. The vertical errorbars represent the standard deviation of the GOME-derived single-scattering albedo (around 0.04). AERO-NET single-scattering albedo values have an accuracyof the order of 0.03 for dust and biomass burning eventswith AOT at 0.44 mm . 0.5 (Dubovik et al. 2000).These error bars are not reported in the graphs in Fig.4 for clarity. In Fig. 4a the GOME-derived values forthe Sahara dust event are compared with AERONET’svalues taken in Dakar and Banizoumbou, sites that wereoverpassed by dust plumes several times during thisperiod; results from the AERONET inversion algorithmwere not available from Cape Verde and they are notshown. The single-scattering albedo is in good agree-ment with the AERONET measurements, especially forthe Dakar site in the red spectral region with differenceslower than 0.01, whereas there is a slight underesti-mation in the blue region, reflecting higher aerosol ab-sorption than that reported by the AERONET Dakarmeasurements (differences of 0.016 at 0.4 mm and of0.013 at 0.488 mm). The climatological desert dust mod-el derived from the AERONET data at Cape Verde (Du-bovik et al. 2002) presents considerably higher spectralsingle-scattering albedo values outside the error barsassociated with GOME-derived results, with differencesranging between 0.05 at 0.4 mm and 0.07 at 0.694 mm.The fact that the AERONET single-scattering albedovalues in Banizoumbou are lower, particularly in the redspectral region (higher aerosol absorption) with differ-ences that reach 0.035 at 0.86 mm, is probably connectedwith the site location being well inland, where the aero-sol load might have been higher and the land surfaceproperties are quite different from those of the oceansurface. The desert plume mixes over the ocean withmarine aerosol particles characterized by very low ab-sorption, which is reflected in higher single-scatteringalbedo results. Nevertheless, the values correspondingto the Banizoumbou AERONET site are still within theGOME-derived error bars.

In the dust transport case illustrated in Fig. 4b, theGOME-derived spectral single-scattering albedo valuesare in between measurements taken at Bahrain and

Kaashidhoo AERONET sites. The Bahrain site registersthe lowest single-scattering albedo values in this case,differing from the GOME results of 0.01 in the blueand of 0.02–0.03 in the red. Numbers referring to Kaash-idhoo are higher, hinting to a less absorbing aerosol type,with differences from the GOME results being between0.04 (blue) and 0.02–0.01 (red). A possible explanationof this difference is that the Kaashidhoo site, situatedat the extreme southwest part of the area, was less af-fected by the dust plume than the other site and thesingle-scattering albedo values in reality characterize amixture of dust and marine particles. Once again the


FIG. 5. Same as in Fig. 4 but for the Angstrom exponent.

climatological model representative of desert dust overBahrain (Dubovik et al. 2002) induces higher single-scattering albedo values (less absorbing aerosol), withdifferences from the GOME-derived values of around0.08.

A comparison between the single-scattering albedofor the dust aerosol in the two cases indicates that thedesert dust from the Middle East absorbs more than thatwhich originated from the Sahara Desert: the differenceis 0.03 in the blue and 0.05 in the red.

The results for the biomass burning episode are re-ported in Fig. 4c. Note that the aerosol properties fromthe Swakopmund AERONET site do not correspond tothe period of study (6–13 September 2000) but to a fewdays later (15–24 September 2000) because of problemswith data availability: the comparison was thereforedone assuming the smoke plume maintained its char-acteristics during the second period, which is not nec-essarily true. GOME-derived values are in good agree-ment with AERONET measurements in Ascension Is-land, differing by 0.005 in the blue and by 0.017–0.01in the red. Yet, AERONET results for Zambezi andSwakopmund are a little lower, with greater differencesfor the lower wavelengths (always less than 0.03).Again, these sites are located inland and closer to thefires, especially Swakopmund. Moreover, the twoground and satellite datasets are close in time but notcoincident. The biomass burning case displays an op-timal agreement with the AERONET values reportedfor the African savannah (Dubovik et al. 2002), withdifferences being lower than 0.004, except at 0.86 mmwhere a difference of 0.02 is observed. Note that thisdifference is lower than the accuracy limit of AERO-NET retrievals and of GOME-derived standard devia-tions and therefore these results are considered quitegood.

The Angstrom exponent obtained from AERONETmeasurements and the GOME-derived values are plottedin Fig. 5. The numbers from the satellite-based algo-rithm are relative to the mean aerosol properties re-trieved over the area; therefore, a constant value wasderived for each case. The Angstrom exponent valuesare very low in the first case (Fig. 5a), which is typicalof dust aerosol particles presenting a dominant largerparticle mode, unlike biomass burning aerosols wherethe Angstrom exponent values are larger. The GOME-derived value was 0.04, which is generally in goodagreement with results from Cape Verde, Dakar, andBanizoumbou. Also for the Arabian dust, although thevalues are higher (0.20), the accordance with the AERO-NET values taken at Bahrain and Kaashidoo sites isquite acceptable (Fig. 5b). The values of the Angstromexponent from AERONET increase significantly for thebiomass burning aerosol type (Fig. 5c) as was expectedand again the GOME retrieval matches this increasewith a value of 1.55.

Figure 6 presents the graphs of the phase function at0.4 mm. GOME-based retrievals are reported together

with AERONET values and models taken from Duboviket al. (2002). Figure 6a shows that the phase functionobtained from GOME is lower than the AERONET val-ues for scattering angles between 808 and 1508, and thesame tendency is found for the Cape Verde literaturemodel. In the Arabian dust case the underestimation ofthe GOME-derived phase function, as well as of theBahrain literature phase function values, is still appre-ciable although less marked. This could be connectedwith artifacts arising from considering in both aerosolmodels (ours and Dubovik’s) spherical aerosol shapesfor desert dust particles. As pointed out by Dubovik etal. (2002), the nonspherical shape for desert dust par-ticles is responsible for deviations of the phase functionat scattering angles $908. On the contrary, the biomass-


FIG. 6. Same as in Fig. 4 but for the normalized phase function at0.4 mm.

FIG. 7. Frequency histogram of the AOT derived from Meteosatusing GOME-derived aerosol properties and the aerosol model de-rived from AERONET data for Cape Verde (Dubovik et al. 2002).

burning case shows a good agreement between GOME-derived values and AERONET aerosol phase functionretrievals for the Zambezi and Swakopmund sites, wherethe spherical aerosol shape is suitable. The African sa-vannah literature model is also in good agreement, es-pecially for scattering angles ,1508.

b. Aerosol optical thickness retrieved from GEOsatellite measurements

1) SAHARA DUST EVENT

The AOT is derived from Meteosat broadband VISmeasurements using both the GOME-derived aerosol

properties and the desert dust model described by Du-bovik et al. (2002) derived from AERONET measure-ments in Cape Verde. The results are compared in Fig.7, where the frequency histogram of the AOT values isshown. The processing of about 5 million Meteosat pix-els during the event in the first half of June 1997 overthe area shown in Fig. 1a supports the histogram in Fig.7. Clearly, for both aerosol models a bimodal distri-bution of the AOT can be distinguished, which corre-sponds to a background marine situation and to the Sa-haran dust transport event. While the modalities cor-respondent to the background marine particles (lowAOT values) are very similar, substantial differencescan be noted for optical thickness values related to thedust event where larger AOT values are obtained. Thisshows how significant the impact that the choice of theadequate aerosol properties can be on the AOT in thepresence of high aerosol loads in the atmosphere.

The AOT derived from Meteosat data was comparedwith measurements from the selected AERONET sites.The AERONET AOT values used in the comparisonsare level 2.0 (quality assured) and have an accuracy ofabout 0.02 (Holben et al. 1998). The Meteosat AOTpixels were enclosed in a box of 0.58 3 0.58 centeredon the geographical location of the ground-based sta-tion, then spatially averaged, and the respective standarddeviation computed, discarding all cloud–land-contam-inated pixels. AOT values from the AERONET stationswere taken for about 1 h before and 1 h after the Me-teosat scan time over the area. Values were time aver-aged and the standard deviation over the 2-h period


FIG. 8. Scatterplots of the AOT retrieved from the Meteosat vsAERONET values for the Cape Verde and Dakar sites during Jun1997. The optical thickness from Meteosat is retrieved assuming (a)GOME-derived aerosol properties and (b) a literature aerosol modelfor Cape Verde (Dubovik et al. 2002). Horizontal error bars refer tothe standard deviation of AERONET measurements over the 2-h pe-riod and the vertical ones the spatial variation in optical thicknessover the area. The dotted lines delimit the 615% error.

computed. The AERONET averaged optical thicknesswas taken for comparisons if the correspondent standarddeviation was ,0.2. With regard to the spatially aver-aged AOT derived from Meteosat, values . 1.0 areretained if the correspondent standard deviation is ,0.5.

Figure 8 shows the scatterplots of the optical thick-ness retrieved from Meteosat using GOME-derivedaerosol properties (Fig. 8a) and the Cape Verde literatureaerosol model (Dubovik et al. 2002; Fig. 8b), versus theAERONET measurements taken in Cape Verde and Da-kar, for the first half of June 1997 after the screeningof data. The horizontal error bars represent the standarddeviation of AERONET measurements over the 2-h pe-riod, whereas the vertical error bars represent the spatialvariation in the optical thickness over the chosen area.The dotted lines delimit the 615% error, representativeof the Meteosat instrumental error (Part I). In general,there is quite good agreement between the AOT valuesretrieved from Meteosat using GOME-derived aerosolproperties and the ones measured by the AERONETsites. Differences are attributed to the scatter of Meteo-sat-retrieved values within the averaged area. Never-theless, the accordance is better than in the case of theaerosol models from the literature, which seems to showa tendency to underestimate the AOT values. In fact,74% of the AOT values retrieved from Meteosat usingGOME-derived aerosol properties have an agreement ofbetter than 15% with AERONET AOT measurements,whereas for the AOT values derived using the CapeVerde desert dust model (Dubovik et al. 2002) only 62%of the values fall within this error limit. This fact provesthat, although Meteosat has only a broadband channelin the VIS spectral region, its data can be used for aero-sol studies when associated with the GOME-derivedaerosol properties. The retrieval accuracy improves sig-nificantly over that which can be achieved by usingliterature aerosol models, as is shown by the compari-sons with AERONET measurements.

The AOT values retrieved from Meteosat-6 are alsocompared to the corresponding POLDER product (Gol-oub et al. 1999). For this purpose, the values of AOT, 2.0 are averaged over coincident cells of 0.58 3 0.58and compared within the time coincidence window ,15min. The cell is retained for comparison if at least 40%of its pixels fulfill the AOT , 2.0 condition.

The scatterplots of Meteosat versus POLDER AOTfor the aerosol characterization with the GOME-derivedaerosol properties are displayed in Fig. 9a for the wholeof June 1997. Error limits are 615% (dotted) and 630%(dashed). Data are somehow scattered, and this may bedue to differences in the algorithms. If all AOT valuesare compared, 23% of the values lay within the 615%limit and 44% within 630%. If only values of AOT .0.4 are considered (aerosol event situation), percentagesincrease to 36% (615% error limit) and 70% (630%error). When the Cape Verde literature dust model isconsidered, a higher number of cases is obtained withinthe same limits: 29% and 53% for the 615% and 630%

error limits, respectively, when all values are consid-ered; 45% and 80% for the 615% and 630% errorlimits, respectively, if only AOT . 0.4 values are re-tained. Note that the LUTs built for the retrieval of theoptical thickness from POLDER have 0.6 as the largest


FIG. 9. Scatterplots of the AOT retrieved from Meteosat vs POL-DER retrievals. Optical thickness from Meteosat is retrieved assum-ing (a) GOME-derived aerosol properties and (b) Meteosat resultsmatching the conditions of POLDER (assuming a pure scatteringapproximation and thus multiplying the optical thickness by the sin-gle-scattering albedo at 0.55 mm). For the GOME-derived desert aero-sol the value is 0.88 and for the Cape Verde literature desert modelthe value is 0.96. The 615% (dotted) and the 630% (dashed) errorlimits are indicated.

AOT value (Goloub et al. 1999). This means that higherAOT values are obtained by linear extrapolation, pos-sibly leading to an under- or overestimation of the val-ues. The highest value considered acceptable for thevalidation and shown in the figure is 2.0, since it maybe considered representative of a typical desert aerosoldust load for these events (Tanre et al. 1997). On the

other hand, aerosol absorption is taken into account inthe present method, but not considered in the POLDERalgorithm, and this may be the cause of the systematicdifferences observed in the plots. In order to compareresults on the same ground, that is, the POLDER situ-ation, the values of the present method were reprocessedassuming a pure scattering approximation. In this case,the optical thickness was multiplied by the single-scat-tering albedo at 0.55 mm. The value obtained from Miecalculations of the single-scattering albedo from theGOME retrieval is 0.88 while that from the literaturedesert class is 0.96. The new results are now illustratedin the scatterplot of Fig. 9b After matching the retrievalconditions of the GEO-retrieved AOT values to thoseof POLDER, the two sets of AOT values come closerto each other when using the GOME-derived aerosolproperties (see Fig. 9b). Thirty-four percent of the val-ues in the scatterplot agree within 615% and when onlyAOT . 0.4 values are taken, the percentage increasesto 55%. As for the 630% limit (dashed lines in thegraphs in Fig. 9), 55% and 86% are obtained, respec-tively, when all the AOT values are considered and onlyAOT . 0.4 are taken. When using the desert dust lit-erature model, the agreement between Meteosat andPOLDER AOT is worse with an underestimation trendof the optical thickness: 26% and 52% for the 615%and 630% error limits, respectively, when all valuesare considered; 38% and 77% for the 615% and 630%error limits, respectively, if only AOT . 0.4 values areconsidered.

The frequency distributions of the ratio between theAOT obtained from POLDER and that from Meteosatdisplayed in Fig. 10 summarize the results for June1997. The left column refers to the optical thicknessderived from Meteosat using the GOME aerosol prop-erties plotted (a) considering aerosol absorption and (b)matching its values to the conditions of POLDER, thatis, multiplying them by the single-scattering albedo. Incase a it seems that there is a systematic overestimationtendency of Meteosat data. This difference is minimizedin case b when the results are matched to POLDERconditions, which means considering nonabsorbingaerosols and using GOME-derived properties as illus-trated in Fig. 10b.

The graphs in Fig. 11 show the frequency percentageof the ratio between POLDER and Meteosat AOTs dur-ing June 1997. Even though the desert dust propertiesare derived from GOME data gathered in the first halfof June, the results refer to the whole month. The aimis to detect significant differences and set a temporallimit on the validity of the aerosol optical propertiesretrieved from GOME spectral reflectance fitting. Theinspection of the graphs, which show once more Me-teosat results with and without aerosol absorption (Figs.11a and 11b, respectively), suggests that the agreementbetween Meteosat and POLDER retrievals is slightlyworse for the last week of June than for the rest of themonth. This may be an indication that retrieved aerosol


FIG. 10. Frequency distribution of the ratio between POLDER andMeteosat AOTs. Meteosat values were computed from the GOME-derived aerosol properties (a) considering aerosol absorption and (b)omitting it as in the POLDER algorithm.

FIG. 11. Same as in Fig. 10 but for the daily frequency percentage.

classes at that time were no longer representative of theaerosol-loaded atmospheric situation and should havebeen updated.

2) ARABIAN DUST EVENT

The AOT retrieved from Meteosat-5 pixel radiancesin July 2000 over the area in the Arabian Sea depicted

in Fig. 1b are compared with AERONET measurementstaken at Bahrain and Nes Ziona. Results are reportedin the scatterplot in Fig. 12. The conditions imposed forthe comparisons are those applied to the Sahara dust


FIG. 12. Same as in Fig. 8 but for the Bahrain and Nes ZionaAERONET sites during Jul 2000.

FIG. 13. Scatterplots of the AOT derived from Meteosat using theGOME-derived aerosol properties vs MODIS retrievals for the casestudy of the Arabian dust during Jul 2000. The dotted lines representa 615% error limit and the dashed lines a 630% error limit.

event. In general, the agreement between ground-basedmeasurements and satellite retrievals using the aerosolproperties derived from GOME spectral measurementsis good, with 40% of the values within 615% (dottedlines in Fig. 12) and 54% of the cases within the samelimit if only AOT . 0.4 values are considered. Fur-thermore, the agreement is better than that resultingfrom the application of the literature aerosol model (notshown), which once again discloses a tendency to un-derestimate the AOT values. In fact only 32% of theAOT values derived using the literature aerosol modelare within the agreement limit of 615%, and this totalrises up to 45% if only AOT . 0.4 are considered.

The retrieved AOT values are also compared with thecorresponding values out of the MODIS official aerosolproduct (version 004). Coincident areas of 0.58 3 0.58are averaged and compared, keeping the best time co-incidence (maximum 15-min difference). Figure 13shows the scatterplots of Meteosat versus MODIS AOTsfor the case of aerosol characterization with GOME-derived aerosol properties. Results refer to the periodfrom 10 to 16 July 2000. There is again better agreementbetween the results from both algorithms when the aero-sol properties obtained from the GOME spectral mea-surements’ inversion are used in the Meteosat retrievals:55% of data agree within 615%, whereas the agreementdrops down to only 45% when the Bahrain desert dustmodel is used. If the limit is relaxed to 630%, then thenumbers are 75% and 70% for the GOME-derived prop-erties and the literature model, respectively. If only val-ues with AOT . 0.4 when the GOME-derived prop-erties are considered, 70% and 90% of the cases are

within 615% and 630%, respectively. Under the sameconditions, the Bahrain desert models results in 62% ofthe cases being within 615% and 90% of the caseswithin 630%. Note that the greatest differences stem-ming from the use of the different aerosol models(GOME derived and literature) are obtained for the low-est error limit (615%). This indicates that the use ofthe GOME-derived aerosol properties improves the ac-curacy of the retrieved AOT values.

3) BIOMASS BURNING EVENT

AERONET measurements from Swakopmund werenot available during the period of the event, and Etosha-Pan and Zambezi are located inland. Therefore, therewere no coincident Meteosat AOT results since pres-ently the method is limited to retrievals only over theocean. The only AERONET site used for AOT com-parisons is Ascension Island (see Fig. 1c) and resultsare shown in Fig. 14. Only a limited number of coin-cident data points are available for AERONET values, 0.7. If only AOT . 0.4 values are considered, 78%of them are within 615%, against a 54% resulting fromthe use of the African savannah literature model. If allvalues are retained, 34% are confined within the 615%limit for the GOME-derived properties and 27% for theliterature aerosol model.

AOT values computed from Meteosat VIS radiancesare also compared with the official MODIS AOT prod-uct during the period of the event (6–13 September2000). Once again, coincident areas of 0.58 3 0.58 are


FIG. 14. Same as in Fig. 8 but for the Ascension IslandAERONET site during Sep 2000.

FIG. 15. Same as in Fig. 13 but for the biomass burning casestudy, during Sep 2000.

averaged and compared, thus ensuring the best temporalmatch between MODIS and Meteosat image acquisi-tions. Figure 15 shows these comparisons for the caseof aerosol characterization with GOME-derived prop-erties. When using the GOME-derived properties, 48%and 60% of the cases are within the 615% and 630%error limits, respectively, when all values are consid-ered. If only values with AOT . 0.4 are considered,70% and 96% of the cases are within the 615% and630% error limits, respectively. As for the African sa-vannah literature model, 32% (within 615%) and 57%(within 630%) are the figures when all the AOT valuesare considered, and 40% (within 615%) and 87% (with-in 630%), if only AOT . 0.4 results are taken.

A first estimate of the accuracy of the GOME/Me-teosat-derived AOTs at 0.55 mm inferred from AERO-NET comparisons is 60.02 6 0.22ta when all AOTvalues are examined. For aerosol event situations whereAOT . 0.4, the estimate of the AOT accuracy is 60.026 0.16ta. The accuracy is not as good as that publishedfor MODIS AOT (60.03 6 0.05ta, dust excluded) byTanre et al. (1997), and this is probably due to inherentproblems in the satellite data used (GOME pixel di-mension, Meteosat calibration; see Part I for details).Nevertheless, the proposed methodology is not merelysuited for AOT monitoring, but also for deriving theTOA direct SW aerosol radiative forcing at the GEOtemporal scale. Other methods based exclusively onLEO satellite data lack this feature that is relevant forclimate applications. On the other hand, if the meth-odology is applied to better calibrated and high space–

time resolution MSG SEVIRI data, it is conceivable thatthe AOT accuracy of the present method will signifi-cantly improve.

c. DSWARF assessment from GEO satellitemeasurements

The TOA SW flux modeled with the Second Simu-lation of the Satellite Signal in the Solar Spectrum (6S;Vermote et al. 1997) radiative transfer code is comparedto the CERES TOA SW flux product as a way of ver-ifying the radiative transfer calculations and checkingthe validity of the calculated LUTs (see details in PartI). The fluxes are modeled considering a tropical verticalatmospheric profile (McClatchey et al. 1971), a Lam-bertian ocean surface, and the GOME-derived aerosolproperties. The comparison was carried out only for theaerosol events occurred during the year 2000, that is,the dust event over the Arabian Sea and the biomassburning episode since for the 1997 dust event there wereno CERES data available. Results are shown in Fig. 16.The data points correspond to averages over 0.258 30.258 wide areas within the study regions (Figs. 1b and1c) for cloud- and land-free pixels. A slight tendencyof the model to underestimate the values with respectto CERES results is observed. Nevertheless, the agree-ment between the measurements and the correspondentmodeled data is in general quite good. In the first case(Arabian dust event), 96% of the modeled values presentan agreement with CERES data better than 615% (dot-ted lines in the plots), whereas in the second case (bio-mass-burning episode) 93% of the values are within thesame level of agreement.


FIG. 16. Scatterplots of the modeled TOA SW flux vs CERES TOA SW flux for the geographical areas presented in Fig. 1: (a) dusttransport event over the Arabian Sea, 10–16 Jul 2000, and (b) biomass-burning event over the South Atlantic Ocean, 6–13 Sep 2000. Thedotted lines represent the 615% error limit.

FIG. 17. Scatterplots of the TOA DSWARF vs AOT at the reference wavelength of 0.55 mm, for the geographical areas presented in Fig.1: (a) dust transport event over the North Atlantic Ocean, 1–14 Jun 1997; (b) dust transport event over the Arabian Sea, 10–16 Jul 2000,and (c) biomass-burning event over the South Atlantic Ocean, 6–13 Sep 2000. The points in the graphs correspond to pixels in the imageryand what varies is time during the event and the geometry of the illumination.

The TOA DSWARF is then retrieved over the studyareas, using the AOT values previously estimated fromMeteosat VIS measurements and LUTs calculated us-ing the aerosol properties obtained from GOME (PartI). Figure 17 shows the variation of the TOA DSWARFwith the AOT at the reference wavelength of 0.55 mmcalculated from Meteosat VIS radiances consideringthe GOME-derived aerosol properties for each of thethree aerosol events considered. The points in thegraphs correspond to pixels in the imagery and what

varies is time during the event and the geometry ofthe illumination. Note how the points fall along well-defined curves that correspond basically to differentsolar zenith angles. The graphs show that the TOADSWARF per unit AOT is greater for the Saharan dustevent than it is in the other cases. This is probablyrelated to the fact that the spectral single-scatteringalbedo values are higher in this case, thus leading tomore radiation reflected at the TOA. For the Arabiandust and biomass-burning cases, the lower single-scat-


FIG. 18. Daily mean AOT and TOA DSWARF during the threeaerosol events presented in the paper. The smaller graphs show thevariation of the daily mean TOA DSWARF vs the daily mean AOT.Results correspond to mean values over the considered areas in Fig.1: (a) dust transport event over the North Atlantic Ocean, 1–14 Jun1997, (b) dust transport event over the Arabian Sea, 10–16 Jul 2000,and (c) biomass-burning event over the South Atlantic Ocean, 6–13Sep 2000. The slope, intercept, and correlation coefficient for eachof the cases are, respectively, (a) 218.4 W m22, 20.57 W m22, and0.96; (b) 215.0 W m22, 20.79 W m22, and 0.98; and (c) 214.3W m22, 21.7 W m22, and 0.92.

tering albedo values result in higher aerosol absorption,possibly leading to atmospheric heating. In these casesthe surface and atmospheric radiative forcings becomemore relevant for climate studies than does the TOAforcing (Satheesh and Ramanathan 2000).

The instantaneous TOA DSWARF values obtainedfrom Meteosat data were averaged for the 24-h periodover the case study regions to obtain the mean dailyTOA DSWARF variation during the events shown inFig. 18 together with the daily mean variation of theAOT values derived from Meteosat pixel radiances con-sidering GOME aerosol optical properties. The variationof the daily mean TOA DSWARF with the daily meanAOT is also shown in the smaller graphs in Fig. 18.Note again that larger negative TOA DSWARF valueswere derived over the Atlantic Ocean for the Saharandust, meaning that in this case the earth–atmospheresystem ‘‘loses’’ more energy, which results in a coolingof the system. In particular, note that the TOA DSWARFis at a maximum on 7 June 1997 when the AOT valueis also the highest (Fig. 18a). For an AOT 5 1.0 thecomputed daily mean TOA DSWARF is 219.0 W m22,which is quite close to the value of 220.7 W m22 pub-lished by Liu et al. (2003) for Saharan dust aerosols. Inthe other two events, lower daily mean TOA DSWARFvalues are observed and therefore the cooling is not sopronounced. The Arabian dust event is associated witha daily mean TOA DSWARF of 215.8 W m22 for anAOT 5 1.0 and the biomass-burning case shows a valueof 216.0 W m22 for the same AOT.

4. Conclusions

Aerosol optical properties were derived from GOMEhigh spectral resolution measurements and used to es-timate the AOT and the TOA DSWARF from MeteosatVIS measurements over selected areas and during sig-nificant aerosol transport episodes. The proposed meth-od is a valid tool for aerosol characterization and op-tical thickness monitoring over the ocean, especiallyfor strong aerosol events, provided that a geostationarysatellite covers the area of interest. This potential isdemonstrated using data from the Meteosat operationalservice (positioned at 08, 08) and from the Indian OceanMeteosat-5 coverage service (positioned at 08, 638E).

Comparisons of model-derived aerosol properties,such as the single-scattering albedo, Angstrom expo-nent, and phase function with independent retrievalsfrom several AERONET sites, show that the agreementis generally quite good. The single-scattering albedovalues obtained from AERONET are in fact alwayswithin the error bars associated with GOME retrievals,resulting in differences being always lower than 0.041.In addition, the spectral behavior of the single-scatteringalbedo is well reproduced from GOME retrievals for allcase studies.

The comparison of the AOT retrieved from Meteosatwith independent measurements from AERONET

shows a good agreement as well, when GOME-derivedaerosol properties representative of the aerosol situationare used. A first estimate of the derived AOT accuracyfor all values is 60.02 6 0.22ta, and 60.02 6 0.16ta


for events when AOT . 0.4. Reasonable agreement isalso found from comparisons with the AOT productsobtained from POLDER and MODIS data. Comparisonswith POLDER show that 34% of the AOT values agreewith POLDER within a 615% limit, whereas withMODIS the agreement increases to 55%. When onlyvalues of AOT . 0.4 are considered, the agreement iseven better, with 55% of the values being within the615% limit for POLDER, and 70% of the values withinthe same limit for MODIS. Results demonstrate that thechoice of the aerosol model is crucial for accurate re-trievals and consequently the atmospheric characteriza-tion should, as much as possible, be representative ofthe actual situation. This implies that the atmosphericcharacterization should be regularly updated while con-ducting studies over long time retrievals. On the otherhand, the great potential of the method for the study ofstrong aerosol transport events is also demonstrated.

The TOA SW fluxes retrieved from Meteosat andthose estimated from the CERES product compare well,with more than 90% of the values differing from CERESfluxes for less than 615%. The DSWARF estimates forthe three aerosol events show that the effect at the TOAis higher for the Saharan dust in June 1997. As expected,the stronger absorption of aerosol particles in the Ara-bian region and over the South Atlantic results in a lowernegative TOA DSWARF probably increasing the radi-ative forcing at the surface. In addition, the daily meanTOA DSWARF per unit optical thickness is estimatedto be 219.0 W m22 for the Saharan dust event (in agree-ment with Liu et al. 2003), 215.8 W m22 for the Arabiandust event, and 216.0 W m22 for the biomass burningepisode.

Acknowledgments. Funding was provided by the Por-tuguese Foundation for Science and Technology underGrant POCTI/CTA/42917/2001. One of the authors(VL) acknowledges support by the Italian Space Agencyunder the grant Sinergia GERB-SEVIRI nello studio delbilancio radiativo a scala regionale e locale. The seniorauthor was supported by the Subprograma Ciencia eTecnologia do 28 Quadro Comunitario de Apoio. Me-teosat imagery was kindly made available by EUMET-SAT. AERONET data are available online (http://aero-net.gsfc.nasa.gov/) thanks to NASA, CNES, and CNRS.AERONET investigators and their staff deserve specialthanks for establishing and maintaining the sites wherethe data used in this investigation were obtained. POL-DER aerosol parameters are products derived from thedata of the CNES POLDER instrument on board NAS-DA’s ADEOS. MODIS data are courtesy of NASA EarthScience Enterprise and the official algorithms were de-veloped by the MODIS Science Teams. They were pro-cessed by the MODIS Adaptive Processing System(MODAPS) and Goddard Distributed Active ArchiveCenter (DAAC), the latter being in charge of archivingand distribution. CERES data were provided by the At-mospheric Sciences Data Center at NASA Langley Re-

search Center. Three anonymous reviewers significantlycontributed to the improvement of the manuscript andare gratefully recognized.

REFERENCES

Burrows, J. P., and Coauthors, 1999: The Global Ozone MonitoringExperiment (GOME): Mission concept and first scientific results.J. Atmos. Sci., 56, 151–175.

Christopher, A. S., and J. Zhang, 2002: Daytime variation of short-wave direct radiative forcing of biomass burning aerosols fromGOES-8 imager. J. Atmos. Sci., 59, 681–691.

Costa, M. J., 2004: Aerosol and cloud satellite remote sensing: Mon-itoring and modeling using passive radiometers. Ph.D. thesis,Dept. of Physics, University of Evora, Evora, Portugal, 233 pp.

——, M. Cervino, E. Cattani, F. Torricella, V. Levizzani, A. M. Silva,and S. Melani, 2002: Aerosol characterization and optical thick-ness retrievals using GOME and METEOSAT satellite data. Me-teor. Atmos. Phys., 81, 289–298.

——, A. M. Silva, and V. Levizzani, 2004: Aerosol characterizationand direct radiative forcing assessment over the ocean. Part I:Methodology and sensitivity analysis. J. Appl. Meteor., 43,1799–1817.

Deuze, J.-L., P. Goloub, M. Herman, A. Marchand, G. Perry, S. Su-sana, and D. Tanre, 2000: Estimate of the aerosol properties overthe ocean with POLDER. J. Geophys. Res., 105, 15 329–15 346.

Dubovik, O., and M. D. King, 2000: A flexible inversion algorithmfor retrieval of aerosol optical properties from sun and sky ra-diance measurements. J. Geophys. Res., 105, 20 673–20 696.

——, A. Smirnov, B. Holben, M. D. King, Y. J. Kaufman, T. Eck,and I. Slutsker, 2000: Accuracy assessments of aerosol opticalproperties retrieved from Aerosol Robotic Network (AERONET)sun and sky radiance measurements. J. Geophys. Res., 105,9791–9806.

——, B. N. Holben, T. F. Eck, A. Smirnov, Y. J. Kaufman, M. D.King, D. Tanre, and I. Slutsker, 2002: Variability of absorptionand optical properties of key aerosol types observed in world-wide locations. J. Atmos. Sci., 59, 590–608.

Goloub, P., D. Tanre, J. L. Deuze, M. Herman, A. Marchand, and F.-M. Breon, 1999: Validation of the first algorithm for derivingthe aerosol properties over the ocean using the POLDER/ADEOSmeasurements. IEEE Trans. Geosci. Remote Sens., 37, 1586–1596.

Haywood, J., and O. Boucher, 2000: Estimates of the direct andindirect radiative forcing due to tropospheric aerosols; a review.Rev. Geophys., 38, 513–543.

Holben, B. N., and Coauthors, 1998: AERONET—A federated in-strument network and data archive for aerosol characterization.Remote Sens. Environ., 66, 1–16.

Houghton, J. T., Y. Ding, D. J. Griggs, M. Noguer, P. J. van derLinden, and D. Xiaosu, Eds., 2001: Climate Change 2001. TheScientific Basis. Cambridge University Press, 881 pp.

Kaufman, Y. J., D. Tanre, and O. Boucher, 2002: A satellite view ofaerosols in the climate system. Nature, 419, 215–223.

King, M. D., Y. J. Kaufman, D. Tanre, and T. Nakajima, 1999: Remotesensing of tropospheric aerosols from space: Past, present, andfuture. Bull. Amer. Meteor. Soc., 80, 2229–2259.

Liu, X., J. Wang, and S. A. Christopher, 2003: Shortwave directradiative forcing of Saharan dust aerosols over the AtlanticOcean. Int. J. Remote Sens., 24, 5147–5160.

McClatchey, R. A., W. Fenn, J. E. A. Selby, F. E. Volz, and J. S.Garing, 1971: Optical properties of the atmosphere. Environ-mental Research Paper 354, Air Force Cambridge Research Lab-oratories AFCRL-TR-71-0279, Hanscom Air Force Base, Bed-ford, MA, 85 pp.

Ramanathan, V., P. J. Crutzen, J. T. Kiehl, and D. Rosenfeld, 2001:Aerosols, climate and the hydrological cycle. Science, 294,2119–2124.

Satheesh, S. K., and V. Ramanathan, 2000: Large differences in trop-


ical aerosol forcing at the top of the atmosphere and Earth’ssurface. Nature, 405, 60–63.

Schmetz, J., P. Pili, S. Tjemkes, D. Just, J. Kerkmann, S. Rota, andA. Ratier, 2002: An introduction to Meteosat Second Generation(MSG). Bull. Amer. Meteor. Soc., 83, 977–992.

Tanre, D., Y. J. Kaufman, M. Herman, and S. Mattoo, 1997: Remotesensing of aerosol properties over oceans using the MODIS/EOSspectral radiances. J. Geophys. Res., 102, 16 971–16 988.

Vermote, E. F., D. Tanre, J.-L. Deuze, M. Herman, and J.-J. Morcrette,1997: Second Simulation of the Satellite Signal in the SolarSpectrum: An overview. IEEE Trans. Geosci. Remote Sens., 35,675–686.

Wielicki, B. A., B. R. Barkstrom, E. F. Harrison, R. B. Lee III, G.L. Smith, and J. E. Cooper, 1996: Clouds and the Earth’s RadiantEnergy System (CERES): An Earth Observing System experi-ment. Bull. Amer. Meteor. Soc., 77, 853–868.

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