Testing the MODIS satellite retrieval of aerosol fine-mode fraction

Theodore L. Anderson,1 Yonghua Wu,1 D. Allen Chu,2,3 Beat Schmid,4 Jens Redemann,4

and Oleg Dubovik5,6

Received 15 March 2005; revised 10 June 2005; accepted 30 June 2005; published 22 September 2005.

[1] Satellite retrievals of the fine-mode fraction (FMF) of midvisible aerosol opticaldepth, t, are potentially valuable for constraining chemical transport models and forassessing the global distribution of anthropogenic aerosols. Here we compare satelliteretrievals of FMF from the Moderate Resolution Imaging Spectroradiometer (MODIS) tosuborbital data on the submicrometer fraction (SMF) of t. SMF is a closely relatedparameter that is directly measurable by in situ techniques. The primary suborbital methoduses in situ profiling of SMF combined with airborne Sun photometry both to validate thein situ estimate of ambient extinction and to take into account the aerosol above thehighest flight level. This method is independent of the satellite retrieval and has well-known accuracy but entails considerable logistical and technical difficulties. An alternatemethod uses Sun photometer measurements near the surface and an empirical relationbetween SMF and the Angstrom exponent, a, a measure of the wavelength dependence ofoptical depth or extinction. Eleven primary and fifteen alternate comparisons are examinedinvolving varying mixtures of dust, sea salt, and pollution in the vicinity of Korea andJapan. MODIS ocean retrievals of FMF are shown to be systematically higher thansuborbital estimates of SMF by about 0.2. The most significant cause of this discrepancyinvolves the relationship between a and fine-mode partitioning; in situ measurementsindicate a systematically different relationship from what is assumed in the satelliteretrievals. Based on these findings, we recommend: (1) satellite programs shouldconcentrate on retrieving and validating a since an excellent validation program is in placefor doing this, and (2) suborbital measurements should be used to derive relationshipsbetween a and fine-mode partitioning to allow interpretation of the satellite data in termsof fine-mode aerosol optical depth.

Citation: Anderson, T. L., Y. Wu, D. A. Chu, B. Schmid, J. Redemann, and O. Dubovik (2005), Testing the MODIS satellite retrieval

of aerosol fine-mode fraction, J. Geophys. Res., 110, D18204, doi:10.1029/2005JD005978.

1. Introduction

[2] Assessing the climate impact of anthropogenic aero-sols requires at a minimum (1) global-scale knowledge ofaerosol amount and (2) an ability to discriminate naturalfrom anthropogenic aerosol constituents. As discussed byKaufman et al. [2002], satellite measurements offer apotential solution to this challenge, wherein aerosol amountis represented as midvisible optical depth, t, and naturalaerosols (largely, mechanically-generated dust and sea salt)

are discriminated from anthropogenic ones (largely, com-bustion-generated sulfates, organics, and black carbon)using the fine-mode fraction of optical depth, FMF.(MODIS papers usually refer to this parameter as h. Herewe use FMF to distinguish it from submicron fraction,SMF). Implementing this solution requires that the uncer-tainty of these satellite-derived parameters be establishedvia independent measurements of known accuracy. Such‘‘validation’’ experiments need to cover the full range ofviewing conditions and aerosol types. Validation of t iswell advanced for all major aerosol types and for both land[Chu et al., 2002] and ocean [Remer et al., 2002, 2005]surfaces, largely as a result of the global network ofSun photometer/radiometer stations operated under theAERONET program [Holben et al., 2001], but also as aresult of airborne Sun photometer measurements obtainedduring field campaigns [Livingston et al., 2003; Schmid etal., 2003a; Redemann et al., 2005].[3] In contrast, the FMF product lacks a comprehensive

validation program and its accuracy has been assessed byindirect means only. Chu et al. [2005] examined spatialpatterns in the Moderate Resolution Imaging Spectroradi-ometer (MODIS) ocean retrievals of FMF for physical

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 110, D18204, doi:10.1029/2005JD005978, 2005

1Department of Atmospheric Sciences, University of Washington,Seattle, Washington, USA.

2Joint Center for Earth Systems Technology, University of Maryland,Baltimore, Maryland, USA.

3Laboratory for Atmospheres, NASA Goddard Space Flight Center,Greenbelt, Maryland, USA.

4Bay Area Environmental Research Institute, Sonoma, California, USA.5Goddard Earth Sciences and Technology Center, University of

Maryland, Greenbelt, Maryland, USA.6Laboratory for Terrestrial Physics, NASA Goddard Space Flight

Center, Greenbelt, Maryland, USA.

Copyright 2005 by the American Geophysical Union.0148-0227/05/2005JD005978

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plausibility. They find similar values of FMF for Asianregions where dust and biomass burning aerosols wereexpected. From this, they conclude that FMF was biasedhigh in the dust-impacted region and that this was likely dueto the assumption of sphericity in the dust aerosol modelsused in the MODIS retrieval. Results herein apply to thissame dust-impacted region and support the suggestion byChu et al. that the MODIS ocean retrievals are biased high.Levy et al. [2003] and Livingston et al. [2003] found that theMODIS ocean retrieval can severely overestimate the spec-tral dependence of t in measurements near Puerto Rico oftransported Saharan dust. This result implies overestimationof FMF. Finally, Remer et al. [2005] compared the MODISretrieval of FMF to a similar retrieval based on AERONETmeasurements. AERONET measurements of spectral opti-cal depth and spectral sky radiances are routinely inverted toestimate the effective size distribution and refractive indexof the column aerosol [Dubovik and King, 2000; Dubovik etal., 2002]. From this inversion, one can derive the fractionof t caused by particles smaller than some arbitrary cut-point. We refer to this quantity as the submicron fraction oft (SMF), noting that in studies to date with AERONETdata, the cut point has been set at 1.2 mm ambient, geometricdiameter (an alternate method of deriving FMF fromAERONET spectral optical depths has been proposed byO’Neill et al. [2001, 2003]). Examination of monthlyaveraged data from eight sites [Remer et al., 2005] showedgenerally good agreement for both the land and oceanretrievals of FMF, with substantial discrepancies (>0.2)occurring almost exclusively at low values of t (around0.1), where both the MODIS and AERONET retrievals areinherently more uncertain.[4] What has been missing in the assessments to date is

an ability to compare the MODIS retrieval of FMF (or,indeed, the AERONET retrieval of SMF) to an indepen-dent measurement of known accuracy. Here we examinethe potential for airborne, in situ optical measurements tofill this gap. In situ methods allow the accurate measure-ment of light extinction by aerosols and the accurateseparation of this quantity into sub- and super-mm portionsby means of an impactor. There are several challengesinvolved with applying these methods to derive the fine-mode portion of t, primarily (1) sampling the super-mmaerosol from aircraft, (2) adjusting the in situ scatteringmeasurements for the effects of relative humidity andangular truncation, and (3) accounting for aerosol abovethe highest flight level. The next section describes howthese challenges are addressed.

2. Methods

2.1. Scope of Study and Parameter Definitions

[5] We examine satellite and suborbital observations inApril 2001, over the ocean and land, in the vicinity of Japanand Korea. The atmosphere in this region and season isheavily impacted by a combination of dust and pollutionaerosols in varying mixtures. As a result, the case studiespresented here exhibit relatively large optical depth andrange from fine-mode to coarse-mode dominated. Suborbitalmeasurements were obtained as part of the Aerosol Char-acterization Experiment (ACE)-Asia [Huebert et al., 2003],which included a large number of surface and airborne

platforms. We use in situ and Sun photometer measurementsobtained on board the National Center for AtmosphericResearch C-130 aircraft as well as Sun photometer measure-ments obtained on board the Office of Naval Research TwinOtter aircraft. Satellite observations are from the MODerateresolution Imaging Spectroradiometer (MODIS) onboardthe Terra satellite.[6] Through a small set of case studies, we compare

satellite and suborbital data on three aerosol properties:aerosol optical depth at 550 nm, t550, the wavelengthdependence of optical depth as expressed in the Angstromexponent, a, and the fine-mode fraction of optical depth at550 nm, FMF. In particular, we examine the meaning andthe accuracy of MODIS-derived FMF.[7] For a given optical property, y, and wavelength range,

Dl, the Angstrom exponent describes the slope of the log ofthat property with respect to the log of wavelength,

�ay Dlð Þ ¼ � d log yð Þ

d log lð Þ ð1Þ

where y can be optical depth, scattering, absorption, etc. ForMODIS retrievals over ocean, we examine the parameterat(550–865), meaning the Angstrom exponent of aerosoloptical depth defined with respect to t550 and t865. ForMODIS retrievals over land, the operative wavelengths areslightly different and we use at(470–660). For the airborneSun photometer data, we determine at by linear regressionusing all wavelengths for which aerosol optical depth dataare available. On the C-130, there were generally four suchwavelengths from 380 to 1021 nm, while on the TwinOtter there were generally 13 such wavelengths from 354 to1558 nm. Finally, for the in situ data, we use the parameteradryscat(450–700), which is the Angstrom exponent of theaerosol scattering coefficient at low RH using measure-ments at 450 and 700 nm. Since scattering dominatesextinction and a has only a small dependence on aerosolhydration so long as RH is below 90% (see Figure 1 anddiscussion below), adryscat is expected to be a good proxy forthe Angstrom exponent of extinction at ambient RH. Thiswas confirmed by comparisons between the in situ and Sunphotometer measurements on the C-130 [Redemann et al.,2003].[8] The meaning and utility of the FMF parameter stems

from the decades old observation [Whitby et al., 1972] thataerosol mass in the atmosphere generally consists of twomodes: (1) a mechanically produced coarse mode and (2) afine mode produced by combustion and/or gas-to-particleconversion. The size distribution of aerosol surface area andlight extinction are closely related to mass and so followthis same general bi-modal pattern. The bi-modal nature ofthe aerosol in the ACE-Asia region was confirmed byAnderson et al. [2003], who showed that, in terms of drylight scattering, the two modes vary independently in theatmosphere and are effectively separated using a low-RHaerodynamic cut diameter of 1 mm. This last statementimplies an operational definition which we shall denotesubmicron fraction, SMF, to distinguish it from the theo-retical concept of fine-mode fraction, FMF. If the fine andcoarse modes each consist of lognormal size distributions,as is commonly assumed, then some portion of the fine-mode will exist at diameters larger than 1 mm and some

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portion of the coarse-mode will exist at diameters smallerthan 1 mm. Thus,

FMF ¼ t550;finet550

ð2Þ

whereas,

SMF ¼ t550;D<1

t550ð3Þ

In the above, the subscript ‘‘fine’’ refers to the complete(theoretical) size distribution of fine-mode particles and thesubscript ‘‘D < 1’’ refers to the portion of the actual aerosolthat exists at low-RH aerodynamic diameters smaller than

1 mm. Table 1 shows the value of SMF characterizing eachof the fine- and coarse-mode aerosol types used in theMODIS retrieval algorithm over the ocean. These SMFvalues are derived from Mie calculations that requireknowledge of the geometrical equivalent cut diameter,Dgeo,cut, that corresponds to the aerodynamic cut of 1 mm.We estimate this from

Dgeo;cut ¼ Daero;cut

ffiffiffiffiffik�r

qð4Þ

where Daero,cut is 1 mm, k is the particle dynamic shapefactor, and r is the particle density. Assumed values of theseparameters are also given in Table 1. Note that SMF isalways within 22% of FMF and usually much closer.[9] Both FMF and SMF can be retrieved from remote

measurements, given assumptions about the shape of theaerosol size distribution. These retrievals depend on the factthat there is a strong wavelength dependence of visible lightextinction (and optical depth) for fine-mode aerosols but notfor coarse-mode aerosols. (Thus, FMF and SMF are closelyrelated to a.) As discussed in next section, the SMFparameter has the advantage that it can be directly andindependently measured using in situ techniques.[10] It is important to consider the effect of RH on the

definitions herein. The in situ measurement of SMF(equation (3)) involves size-separation at low RH. Thisdefinition has the advantages that (1) aerosol characteristicsare measured with respect to a uniform reference conditionand (2) this low-RH condition corresponds closely toaerosol chemical measurements and chemical transportmodels, both of which work in terms of dry componentmass. However, this low-RH separation creates a lack ofcorrespondence with respect to remote measurementswhenever ambient RH is high. Figure 1 shows the hydra-tion effect on aerosol properties for typical, hygroscopic,fine-mode aerosols. Note that the variation of a and SMF isquite small as long as RH is below about 90% but thatthese properties change dramatically for RH above 95%. Inother words, the same aerosol plume observed remotely atbelow-90% RH and above-95% RH would manifest verydifferent spectral behavior and fine-mode partitioning.Clearly, the notion that remotely sensed fine-mode parti-tioning allows one to diagnose the intrinsic nature orsources of the aerosol breaks down at high ambient RH.[11] Time or space averages of intensive properties like a,

FMF, or SMF can be calculated using either (1) the averagevalue of the intensive property or (2) the average values ofthe extensive properties. In the case of a ratio like FMF orSMF, this amounts to calculating either (1) the average ratioor (2) the ratio of the averages. The former method givesequal weighting to data points with low and high values oft550. This tends to amplify noise and can introduce bias aswell, since the derived intensive properties are highlyuncertain when there is little aerosol present to be measured.With this in mind, we use method 2 exclusively in analyzingboth the MODIS and suborbital data.

2.2. Suborbital (Airborne) Data

[12] During the ACE-Asia intensive operating period(March 28 through May 6, 2001), nephelometer and ab-sorption photometer instruments were used on the NCARC-130 aircraft to measure aerosol scattering and absorbing

Figure 1. Variation of fine-mode optical properties as afunction of relative humidity (RH). Results of Miecalculations for unimodal, lognormal size distributions withgeometric standard deviations of 2 and initial (dry) volume-mean diameters (Dgv) intended to span the typical range ofpossibilities. Particles are modeled as a mixture of solubleammonium bisulfate plus an insoluble component with thesame dry refractive index of 1.47. Hydration of the solublecomponent follows the upper (hydrated) hysteresis branch ofdata from Tang and Munkelwitz [1994]. (a) Hydration effecton 550 nm extinction. We note that the ratios of scattering at85% RH to that at 40% RH are 1.89, 1.78, and 1.71 for thethree Dgv values of 0.2, 0.3, and 0.4 mm. (b) Hydration effecton the extinction Angstrom exponent (a) using the MODISwavelengths of 865 and 550 nm. (c) Hydration effect on thesub-mm fraction of 550 nm extinction (SMF). Note that botha and SMF depart rapidly from their dry values above about90% RH.

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properties at visible wavelengths. The instruments andmeasurement strategy are described in Anderson et al.[2003]. Key aspects include (1) separate analysis of thesub-mm aerosol using a cut point of 1 mm aerodynamicdiameter at low RH, (2) most measurements performed atlow RH (below 40%) in order to reduce the effects of RHchanges as a source of variation, (3) RH-induced effects onlight scattering studied separately using deliberate humidi-fication, and (4) frequent measurement of particle-free airand frequent operation of redundant instruments in parallelin order to assess instrumental noise, measurement preci-sion, and calibration stability.[13] Total scattering, ssp, at three wavelengths (450, 550

and 700 nm) was measured with a pair of TSI (St. Paul,MN) model 3563 nephelometers. Light absorption, sap, at550 nm was measured with a pair of Radiance Research(Seattle, WA) particle soot absorption photometers (orPSAPs). For both ssp and sap, one instrument sampled thetotal aerosol while, simultaneously, the other sampled onlythe sub-mm portion of the aerosol. To sample the sub-mmportion, super-mm particles were removed with a multi-orifice impactor following the design of Berner et al.[1979]. A greased substrate was used to prevent particlebounce. To derive extinction at ambient RH, scatteringmeasurements were adjusted for angular nonidealities, fol-lowing Anderson and Ogren [1998], and for hydrationeffects, using an on-board, continuous measurement ofaerosol hygroscopicity. The most important angular non-ideality is truncation of forward scattering, which requires acorrection factor for super-mm scattering of 1.51 ± 0.28. Thehydration adjustments were based on continuous measure-ments of scattering at low (<40%) and high (85%) RH usinga pair of Radiance Research (Seattle, WA) model M903nephelometers. The M903 nephelometers normally mea-sured the total aerosol but were switched, periodically, tomeasure hydration of the sub-mm aerosol. Data reductionprocedures to derive aerosol optical properties and theiruncertainties are described by Anderson et al. [2003]. Keyproperties for this study are the extinction coefficient atambient RH (which can be vertically integrated to obtain

t550 for a layer), adryscat(450–700), and SMF. Examplevertical profiles are shown in Figure 3.[14] Efficient sampling of coarse-mode particles has

proven extremely challenging in previous campaigns [e.g.,Huebert et al., 1990; Blomquist et al., 2001]. For the mostpart, investigators content themselves with estimating theupper cut size of their sampling system and studying theproperties of the portion of the aerosol below this cut size.This severely limits the ability of airborne in situ measure-ments to be compared with remote measurements, since thelatter inherently sense the total aerosol. In particular, itprevents testing of the satellite retrieval of FMF.[15] For ACE-Asia, where coarse-mode dust was

expected to be a major contributor to aerosol opticalproperties, the C-130 was equipped with a newly developedLow Turbulence Inlet (LTI [Lafleur, 1998; Huebert et al.,2004; Wilson et al., 2004]). Unlike traditional solid diffus-ers, the LTI maintains laminar flow during deceleration ofthe sample flow as it enters the aircraft. It does this bysucking away a major fraction (ca. 70%) of the incoming airthrough porous walls of the diffuser. Three lines of evidenceindicate that the overall sampling system (inlet plus sampleplumbing) caused a small enhancement (about 10%) ofcoarse-mode light scattering at 550 nm. These are asfollows: theoretical and empirical estimation of size-depen-dent sampling efficiencies [Anderson et al., 2003], compar-ison of in situ optical properties during fly-bys of surface-based sampling sites [Doherty et al., 2005], and comparisonof extinction profiles with profiles determined by airborneSun photometry [Redemann et al., 2003]. In the presentstudy, coarse mode extinction measurements on the C-130have been reduced by 10% to correct for this samplingartifact.[16] Both the NCAR C-130 and the ONR Twin Otter

were equipped with airborne Sun photometers for measur-ing aerosol optical depth at multiple wavelengths. Thesemeasurements are described by Redemann et al. [2003] andSchmid et al. [2003b], respectively. When these instrumentswere measuring the total column (i.e. the airplane was nearthe surface) near the time of the MODIS overpass, they

Table 1. Properties of Aerosol Models Used in MODIS Ocean Retrievals

Type Dgv,a mm Sg

a r,b g/cc kc Dgeo,cut,d um FMF (550 nm) SMF (550 nm) a (550/700) a (550/865)

Fine1 0.23 1.49 1.79 1.1 0.78 1.00 1.00 2.7 2.92 0.35 1.82 1.79 1.1 0.78 1.00 0.91 1.8 1.93 0.47 1.82 1.39 1.0 0.85 1.00 0.85 1.5 1.74 0.59 1.82 1.39 1.0 0.85 1.00 0.78 1.2 1.4

Coarse5 2.36 1.82 1.24 1.0 0.90 0.00 0.21 �0.2 �0.26 3.53 1.82 1.24 1.0 0.90 0.00 0.07 �0.2 �0.27 4.71 1.82 1.24 1.0 0.90 0.00 0.02 �0.1 �0.28 3.53 1.82 2.6 1.4 0.72 0.00 0.03 �0.2 �0.29 6.82 2.23 2.6 1.4 0.72 0.00 0.03 �0.1 �0.1aLognormal size distributions are assumed. Dgv and Sg are the geometric mean diameter and geometric standard deviation

(derived from size parameters given by Remer et al. [2005]).bHere r is dry density. Explanation of choices: types 1–2: ammonium sulfate at low RH; types 3–4: hydrated ammonium

sulfate at 70% RH; types 5–7: hydrated sea salt at 70% RH; types 8–9: dry dust [Gillette and Goodwin, 1974].cHere k is dynamic shape factor. Explanation of choices: types 1–2: slightly nonspherical; types 3–7: hydrated, thus spherical;

types 8–9: nonspherical.dDgeo,cut gives the geometrical (spherical) diameter corresponding to an aerodynamic inertial separation diameter of 1 mm.

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provide suborbital measurements of t550 and a for directvalidation of MODIS. When combined with an empiricalformula connecting a and SMF (see below), these data canalso generate an estimate of SMF.[17] To test the MODIS retrieval of FMF, we combine the

in situ and Sun photometer measurements on the C-130.From the surface to the highest flight level, in situ measure-ments are used to derive t550, adryscat, and SMF. Note thatt550 and SMF refer to the aerosol at ambient RH. Since wedid not measure the wavelength dependence of aerosolhydration, our in situ instruments do not provide an estimatea at ambient RH. However, Redemann et al. [2003] foundthat adryscat provided an essentially unbiased (within 5%)

proxy for the ambient value of a as measured by the Sunphotometer during the ACE-Asia experiment. For the aero-sol above the highest flight level, we use the Sun photom-eter measurements of t550 and a directly and weparameterize SMF as a function of a. This parameterizationis based on the empirical relationship between SMF andadryscat from C-130 measurements throughout the ACE-Asiacampaign. A quadratic fit to the data yields,

SMF ¼ �0:0512�a2 þ 0:5089

�aþ 0:02 ð5Þ

with a 70% confidence uncertainty of ±0.06, as shown onFigure 2a.[18] We designate the method using low-altitude Sun

photometer data as SP and the combined in situ/Sunphotometer method as I/SP. For the I/SP method, themajority of the column optical depth is characterized bythe in situ techniques (mean 78%, range 55–96%). Thus,these two suborbital methods provide estimates of t550 anda that are largely independent of each other.

2.3. Satellite Data

[19] We use MODIS level-2, 10-km resolution (retrievalboxes are 10-km squares at nadir but expand in the cross-track dimension, reaching �30 km at the edges of theswath) data (MOD04_L2, version 004), which comes in5-minute blocks that cover roughly 2000 km cross-track and1350 km along-track. Land and ocean retrievals are sub-stantially different and are studied separately herein. Thesedata are publicly available from NASA via the web (http://modis.gsfc.nasa.gov/data/). For a detailed description of theMODIS products, retrieval algorithms, and validation sta-tus, we refer the reader to Remer et al. [2005]. Key pointsfor this paper are discussed in this section.[20] Following cloud-clearing procedures, the MODIS

algorithm derives aerosol properties for each 10-km retrievalbox by comparing measured radiances (reflected sunlight) tocalculated radiances for the known viewing geometry andfor specified values of surface reflectivity, aerosol type, andaerosol amount. A finite number of aerosol types areconsidered, each of which has a specified, lognormal sizedistribution and refractive index [see Remer et al., 2005,Tables 1 and 2]. The optical properties (most importantly,the scattering phase function and single scatter albedo) ofeach aerosol type are calculated from Mie theory and theseproperties are used in a large set of radiative transfercalculations to generate look-up tables for the retrievalalgorithm.[21] Aerosol retrieval algorithms for land and ocean are

different in the following, major ways: (1) the land algo-rithm deduces surface reflectivity from the radiance mea-sured at 2.13 mm whereas the ocean algorithm assumesknowledge of surface reflectivity, (2) the land algorithm fitsradiances at two wavelengths whereas the ocean algorithmfits radiances at six wavelengths, and (3) the land algorithmdistinguishes between dust and nondust but otherwise usesprescribed combinations of coarse- and fine-mode aerosolfor each region whereas the ocean algorithm solves for boththe type and relative amount of coarse- and fine-modeaerosol. Thus, the land and ocean retrieval products arelargely independent of each other and, in general, the oceanproducts are much more accurate [Remer et al., 2005]. Note

Figure 2. Empirical verses Mie theory relationshipsamong optical properties. (a) In situ measurement of SMFversus a. (b) Relationship between FMF and a for MODISocean models. Dashed curve gives the empirical fitrelationship from Figure 2a. (c) Relationship betweenSMF and a for MODIS ocean models. Dashed curve as inFigure 2b.

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that level-2 retrieval boxes that have a mixture of land andocean are analyzed using the MODIS land algorithm[Remer et al., 2005.][22] Over land, the MODIS algorithm decides (based on

the ratio of t470 to t660 in a preliminary retrieval) whetherthe aerosol type is pure dust, pure nondust, or mixed. Thefinal retrieval then proceeds using either the dust aerosolmodel, the nondust aerosol model assigned to that geo-graphical location, or a mixture of the two. (Table 1 ofRemer et al. [2005] gives the properties of the dust andnondust aerosol models.) FMF is set to 0 for the pure dustcase, 1 for the nondust case, and is calculated from the ratioof t470 to t660 in the mixed case. Two points are worthnoting. First, the mixed criterion is rarely met such thatFMF values over land are generally either 1 or 0 [Remer etal., 2005]. Second, the nondust aerosol types actuallyinclude coarse-mode components. Therefore, the FMF pa-rameter over land has a different meaning than it does overthe ocean and would more appropriately be called the‘‘nondust fraction’’.[23] Over the ocean, the MODIS algorithm generates, for

each 10-km retrieval box, 20 candidate solutionscorresponding to all possible combinations of 4 fine-modeand 5 coarse-mode aerosol types (Table 1). Each solutionoptimizes the fit between measured and calculated radiancesby adjusting the ratio of the fine and coarse modes. Twotypes of retrieval products are reported in the level-2 dataset: (1) the ‘‘best’’ products, which represent the single,best-fit solution, and (2) the ‘‘average’’ products, whichrepresent the average of all solutions that match the mea-sured radiances to within 3%. Since radiance uncertainty isestimated to be about ±2% [Remer et al., 2005], all solutionscontributing to the ‘‘average’’ products can be consideredplausible. It is generally thought that the ‘‘average’’ prod-ucts are more accurate and realistic. The ‘‘best’’ product, forexample, could exhibit spatial discontinuities as the retrievalswitches from one solution to another but these wouldpresumably be smoothed over in the ‘‘average’’ products.[24] For each of the 20 combinations of fine and coarse

mode used in the ocean algorithm, Mie theory defines aspecific relationship between the FMF and a, as shown inFigure 2b. Note that the coarse mode aerosol types all havevery similar (and negative) values of a such that all 20curves converge when FMF = 0. When FMF is high, thecurves separate into four groups based on fine-mode aerosoltype. This results from the fact that the fine-mode typeshave very different values of a, ranging from >2.5 for type 1to <1.5 for type 4 (Table 1).[25] For a given value of a and a given choice of fine- and

coarse-mode aerosol, Mie theory allows us to calculate notonly the value of FMF that MODIS will retrieve (Figure 2b)but also the value of SMF that corresponds to this sameretrieval and that more closely matches the quantity deter-mined by the in situ measurements. The relationship be-tween a and SMF is shown in Figure 2c. On this plot, SMFgenerally does not reach values of 0 or 1 because theMODIS aerosol types do not separate perfectly at 1 mmaerodynamic diameter. (See SMF values for each aerosoltype in Table 1.) On both Figures 2b and 2c, the quadratic fitto the empirical in situ measurements (Figure 2a) is shownas a dashed line for reference. It is evident that, for a givenvalue of a, the MODIS aerosol models used in the ocean

retrieval predict a higher value of both FMF and SMF thanis predicted by the in situ, empirical relationship. Thisgeneral result is consistent with the case-study analysispresented here.

2.4. Uncertainties

[26] For suborbital measurements, all uncertainties arereported at 70% confidence. For satellite data, previousstudies have established the uncertainties in t550 but notin a or FMF. Indeed, the purpose of this study is, in part, toattempt to quantify these uncertainties. Therefore, we do notreport satellite uncertainties but, rather, standard deviationsof the satellite products over the data points included in eachcomparison. Thus, we are able to test whether the uncer-tainty range of the suborbital data encompasses the vari-ability range of the satellite observations.

2.5. Logic of This Test

[27] Testing the satellite retrieval of FMF requires acarefully designed set of measurements. It is worth summa-rizing the logic of the present test. In situ measurements ofambient extinction were verified by airborne Sun photom-etry [Redemann et al., 2003]. This helps to establish theuncertainty of the in situ measurements and to confirm thatthe major sources of potential error (sampling efficiency forsuper-mm particles, correction of scattering from low-RH toambient RH, and correction of super-mm scattering fornephelometer truncation) did not introduce systematic bias.In situ measurements of sub-mm extinction are based oncalibrated nephelometric and photometric methods withwell-known uncertainties [Anderson et al., 1996; Andersonand Ogren, 1998; Bond et al., 1999]. Sub-mm separationrelies on inertial impaction, making this method indepen-dent from the satellite method. The great majority of thecolumn aerosol (55–96%) is characterized by this in situtechnique. The sub-mm fraction of t550 for the aerosol abovethe highest flight level uses airborne Sun photometry andan empirical relationship between a and SMF (Figure 2a).The good correspondence that is found between adryscatand aambient (in situ versus Sun photometer [Redemannet al., 2003] shows that humidity effects do not affect theAngstrom exponent significantly. Thus, the empirical rela-tionship observed between adryscat and SMF should hold foraambient as well, at least for the conditions and aerosol typesobserved in this study. (Note in Table 2 that ambient RHwas generally below 85% in our comparisons and neverexceeded 95%.) Thus, we can derive a measurement ofSMF for the entire atmospheric column that has a well-known uncertainty and is independent of the satelliteretrieval of FMF. However, the definitions of FMF andSMF are slightly incompatible, which could cause a dis-crepancy between the two that is not related to satelliteinaccuracy. This source of discrepancy can be examinedusing Mie theory and knowledge of the specific aerosoltypes that were used in the MODIS retrieval.

3. Results

3.1. Case Study Selection

[28] All research flights by both the C-130 and the TwinOtter aircrafts were examined (19 flights each) for suitablecomparisons with MODIS. Requirements were (1) properly

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Table

2.ComparisonLogistics

a

DOY

I/SP

SP

MODIS

Begin

Tim

e,hh:m

mEndTim

e,hh:m

mAveLat,

deg

AveLon,

deg

TopAlt.,

mMax

RH,

%Beg

Tim

e,hh:m

mEndTim

e,hh:m

mAveLat,

deg

AveLon,

deg

Min

Alt.,

mOverpassTim

e,hh:m

mAveLat,

deg

AveLon,

deg

No.of10-km

Boxes

C-130,Ocean

96

2:13

2:58

33.783

126.163

3131

89

0:34

0:36

34.133

132.232

82:00

33.262

126.078

10

98

3:48

4:10

36.439

133.497

4101

85

––

––

–1:45

36.443

133.541

53

102

1:18

1:53

33.372

126.602

5770

69

1:45

1:53

33.582

126.170

40

3:00

33.443

127.305

14

103

1:04

2:00

35.786

131.747

3972

67

1:51

2:00

35.780

132.265

46

2:05

35.790

131.747

56

110

2:09

2:16

34.857

140.470

1892

84

2:15

2:16

34.970

140.602

32

2:10

34.810

140.480

15

113

1:05

1:48

33.241

139.012

5518

83

1:05

1:25

32.600

139.088

30

1:05

32.776

139.095

42

C-130,Land

96

0:35

0:45

34.100

132.266

3131

92

0:35

0:36

34.133

132.233

92:00

34.101

132.268

28

98

3:16

3:41

34.114

132.298

4087

91

2:03

2:10

34.138

132.234

17

1:50

34.482

132.486

44

102

1:18

1:53

33.372

126.602

5770

69

1:45

1:53

33.582

126.170

40

3:00

33.397

126.557

16

121

1:50

4:18

39.496

139.353

7380

76

1:50

1:55

38.957

139.147

54

1:50

40.339

139.908

15

122

1:44

2:45

33.052

125.798

6293

94

2:35

2:45

33.089

125.689

46

2:35

33.340

126.400

6

Twin

Otter,Ocean

96

––

––

––

1:44

1:46

32.883

127.531

43

2:00

32.885

127.581

12

102

––

––

––

3:07

3:09

32.980

127.602

49

3:00

32.973

127.596

10

109

––

––

––

1:36

1:38

36.817

133.302

54

1:30

36.795

133.292

6113

––

––

––

2:58

3:00

33.051

133.962

29

2:45

33.048

133.926

9

Twin

Otter,Land

98

––

––

––

2:09

2:11

34.149

132.229

12

1:50

34.158

132.212

16

aDOY,day-of-year(January1=1).Alltimes

arein

UTC.

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operating instruments, (2) sufficient measurements undercloud-free conditions, and (3) flight tracks that were suffi-ciently close to the MODIS measurements in terms of bothspace and time. Eight suitable flights yielding elevencomparison cases (six ocean and five land) were identifiedfor the C-130 and five suitable flights yielding five com-parison cases (four ocean and one land) were identified forthe Twin Otter. Logistical data for all cases are shown inTable 2. Note that SMF was not measured on the Twin Ottersuch that this aircraft only yields comparisons using the SPmethod. For all comparisons, we selected MODIS level-2data that was within 0.25 degrees of the flight track, asillustrated by the pluses in Figure 4. In addition, we onlyused MODIS aerosol data when the cloud fraction for that10-km retrieval box was less than 0.8. Because of the timerequired to perform an airborne profile and other logisticalmatters, time offsets between I/SP and MODIS data wereoften larger than one would desire. The average temporaloffset from the MODIS overpass time to the midpoint of theI/SP data is 1.0 hour and the maximum is 2.25 hours. On theother hand, the comparisons in terms of t550 (Table 3 andFigure 5d) provide strong evidence that the same amountand type of aerosol were being sensed by the satellite andsuborbital instruments, despite these offsets.

3.2. Case Studies

[29] We illustrate the nature of the comparison data byconsidering two cases in detail. DOY 113 (April 23, 2001)provides a fairly ideal case, with complete satellite coverageof the flight region, homogeneous conditions, no spatialoffset, and a small time offset. (See Table 2 for space/timeinformation.) DOY 102 (April 12, 2001) represents a moreproblematic case, where a large portion of the MODISocean data is unavailable due to Sun glint and there is asubstantial offset in time.

3.2.1. DOY 113[30] On this day the C-130 flew a series of profiles and

stacked ‘‘L’’ patterns over the ocean south of Tokyo Bay.Conditions were essentially cloud-free (Figure 4a) and quitehomogeneous both horizontally (Figures 4a–4d) and intime. The in situ profile data (Figures 3a and 3b) reveal aboundary layer height of �1000 m, modest humidity (max-imum is 83% at the top of the boundary layer), a boundarylayer aerosol that is a mixture of coarse and fine modes and isquite hygroscopic, and a free-tropospheric aerosol that ispredominantly coarse mode and only slightly hygroscopic.Chemical measurements in the boundary layer (not shown)by an external, Total Aerosol Sampler (TAS [Kline et al.,2004]) indicate substantial sea salt, a moderate amount ofnon-sea-salt sulfate, and little dust. Taken together, the in situmeasurements indicate that the column aerosol consistedprimarily of sea salt and pollution in the boundary layer anddust in the free troposphere. The existence of dust in the freetroposphere is supported by lidar data from Tokyo (�250 kmto the north) showing high levels of aerosol depolarization(indicative of nonspherical particles) between 3 and 6 kmaltitude [Murayama et al., 2003].[31] The maximum altitude of this profile (5500 m) did

not encompass the full extent of the free tropospheric dust asevidenced by the substantial amount of aerosol optical depthabove the highest flight level (0.1 out of a total of 0.3). Thisprofile was the second of four profiles flown in the sameregion in which in situ and Sun photometer measurementswere compared in terms of ambient extinction and a[Redemann et al., 2003, Figures 4j–4m and 5j–5m]. Thesefour profiles indicate consistent aerosol properties in timeand very good overall agreement between the two methods.[32] Key level-2 satellite data from this case are shown in

Figures 4a–4d. The C-130 flight track is indicated on thesefigures with a green line for near-surface sampling and a red

Table 3. Comparison Results

t550 a SMF or FMFa

I/SP Mean(unc)

SP Mean(unc)

MODIS Mean(std)

I/SP Mean(unc)

SP Mean(unc)

MODIS Mean(std)

I/SP Mean(unc)

SP Mean(unc)

MODIS Mean(std)

C-130, Ocean96 0.35 (0.03) 0.36 (0.02) 0.43 (0.02) 0.92 (0.13) 1.12 (0.09) 1.18 (0.07) 0.53 (0.11) 0.53 (0.07) 0.86 (0.03)98 0.37 (0.04) – 0.34 (0.02) 1.39 (0.16) – 1.36 (0.03) 0.73 (0.14) – 0.89 (0.01)102 0.42 (0.04) 0.42 (0.02) 0.46 (0.03) 0.64 (0.16) 0.57 (0.14) 0.57 (0.02) 0.35 (0.05) 0.29 (0.09) 0.53 (0.01)103 0.24 (0.03) 0.26 (0.02) 0.24 (0.02) 1.1 (0.2) 1.0 (0.2) 1.06 (0.04) 0.60 (0.15) 0.49 (0.10) 0.71 (0.02)110 0.33 (0.04) 0.36 (0.03) 0.31 (0.02) 1.4 (0.3) 1.2 (0.2) 1.09 (0.11) 0.63 (0.17) 0.55 (0.10) 0.75 (0.04)113 0.29 (0.04) 0.30 (0.03) 0.30 (0.02) 0.9 (0.2) 0.7 (0.2) 1.03 (0.03) 0.45 (0.12) 0.37 (0.11) 0.75 (0.01)

C-130, Land96 0.36 (0.04) 0.36 (0.02) 0.47 (0.04) 0.97 (0.14) 1.12 (0.09) 1.5 (0.3) 0.54 (0.11) 0.53 (0.07) 1.00 (0.00)98 0.32 (0.04) 0.36 (0.02) 0.40 (0.07) 1.37 (0.14) 1.48 (0.14) 1.8 (0.4) 0.68 (0.14) 0.66 (0.08) 1.00 (0.00)102 0.42 (0.04) 0.42 (0.02) 0.42 (0.04) 0.64 (0.16) 0.57 (0.14) 1.00 (0.13) 0.35 (0.05) 0.29 (0.09) 1.00 (0.00)121 0.46 (0.05) 0.44 (0.02) 0.49 (0.10) 1.1 (0.2) 0.98 (0.09) 0.9 (0.4) 0.56 (0.11) 0.47 (0.07) 1.00 (0.00)122 0.32 (0.04) 0.36 (0.03) 0.39 (0.10) 1.56 (0.19) 1.54 (0.18) 2.1 (0.6) 0.81 (0.17) 0.68 (0.09) 1.00 (0.00)

Twin Otter, Ocean96 – 0.35 (0.01) 0.39 (0.05) – 1.05 (0.03) 1.08 (0.06) – 0.50 (0.06) 0.80 (0.02102 – 0.32 (0.01) 0.44 (0.02) – 0.52 (0.04) 0.59 (0.01) – 0.27 (0.06) 0.54 (0.01)109 – 0.40 (0.01) 0.42 (0.01) – 1.00 (0.05) 1.20 (0.01) – 0.48 (0.06) 0.84 (0.01)113 – 0.25 (0.01) 0.28 (0.03) – 0.65 (0.05) 0.85 (0.05) – 0.33 (0.07) 0.67 (0.02)

Twin Otter, Land98 – 0.38 (0.01) 0.44 (0.05) – 1.33 (0.03) 1.7 (0.2) – 0.61 (0.06) 1.00 (0.00)

aI/SP and SP measurements derive SMF (equation (3)), while MODIS measurements derive FMF (equation (2)).

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line for vertical profiling. The MODIS 10-km data pointsthat were used in calculating satellite average values andstandard deviations (Table 3 and Figure 5) are indicated bypluses. Examining Table 3, we see that comparison in termsof t550 is excellent for all three methods and that the I/SPand SP methods are in reasonable agreement (within uncer-tainties) for both a and SMF. The MODIS retrieval of a issomewhat higher than the suborbital measurements but onlyslightly beyond the suborbital uncertainty ranges. However,the MODIS retrieval of FMF (0.75) is substantially higherthan the suborbital estimates of SMF (0.45 and 0.37 for I/SPand SP, respectively). Some portion of this difference arisesfrom the difference in definition; however, Mie calculations(not shown) performed on the aerosol types used in theMODIS ‘‘best’’ retrieval for this case indicate that aretrieval of SMF would be only 0.02 lower than the retrievalof FMF. In short, the MODIS retrieval indicates fine-modedominance over a broad region of the ocean while subor-

bital data acquired over a small portion of that regionindicates that coarse-mode dust (aloft) and coarse-modesea salt (in the boundary layer) were the dominant contrib-utors to optical depth.3.2.2. DOY 102[33] On this day both the C-130 and the Twin Otter

operated in the vicinity of the Gosan surface station on JejuIsland, just south of the Korean Peninsula. (Jeju is the islandin the center of Figures 4e–4h). This was a post-frontalsituation with mostly clear skies and continental outflowfrom China occurring in the boundary layer. An extensiveplume of dust and pollution was observed to be blanketingthe Yellow Sea, Korean Peninsula, and Korean Strait.MODIS data over the ocean in the vicinity of Jeju indicateslittle cloud cover (Figure 4e), modest gradients in t550(Figure 4f), and quite homogeneous conditions with respectto the aerosol intensive properties (Figures 4g and 4h). Interms of t550, MODIS indicates close agreement between

Figure 3. In situ aerosol measurements for two case studies. Extensive properties were first averagedinto 200 m layers and intensive properties were calculated from these. ‘‘totTSGdry’’ and ‘‘subTSGdry’’are low-RH total scattering at 550 nm for sub-mm and total aerosol, respectively; ‘‘totTSGamb’’ is totalscattering at 550 nm and at ambient RH, ‘‘totABS’’ and ‘‘subABS’’ are absorption at 550 nm by the totaland sub-mm aerosol, respectively. (a) Extensive and (b) intensive properties for DOY 113 (April 23,2001). (c) Extensive and (d) intensive properties for DOY 102 (April 12, 2001).

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the land values and those over the adjacent ocean; however,there is a strong discontinuity between the retrieved valuesof FMF over the Jeju land mass (1.0) and those over theadjacent ocean (�0.5).

[34] To the north, south, and west of Jeju Island, MODISaerosol data are not available over the ocean due to Sunglint. Unfortunately, the C-130 was operating in this Sunglint region at overpass time. Therefore, we compare the

Figure 4. Satellite observations (MODIS level 2) for two case studies. Pluses, asterisks, and opencircles show the MODIS data used in our analysis over ocean for the C-130, over land for the C-130, andover ocean for the Twin Otter, respectively. The red curve gives the C-130 flight path. Green colorindicates the C-130 low leg measurement. For DOY 113, Figures 4a–4d display Fcld (fraction of cloud),t, FMF, and a, respectively. For DOY 102, Figures 4e–4h display the same four parameters.

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MODIS retrievals to C-130 data obtained 1–2 hours earlierin the vicinity of Jeju, specifically, a profile descent overJeju followed by a surface leg just west of it (passingwithin a few kilometers of the Gosan station). These data(Figures 3c and 3d) indicate a relatively dry boundary layer(maximum RH is 69%) extending to �2500 m and con-taining virtually all the column optical depth. Chemical datafrom the TAS are available from the surface leg and from asubsequent level leg flown at 350 m. These indicate that

dust comprised the overwhelming majority of aerosol drymass, although sulfate concentrations are also very high(relative to clean conditions) and there was a small amountof sea salt. Consistent with this chemistry, the opticalmeasurements shown in Figures 3c and 3d indicate thatthe coarse-mode dominates extinction (SMF is �0.3) andthat the aerosol hygroscopicity is low but not quite as low aswould be expected for pure dust. Simultaneous opticalmeasurements at the Gosan station confirm the coarse-mode

Figure 5. Summary of comparisons among in situ/Sun photometer (I/SP), Sun photometer (SP), andMODIS. The SP versus I/SP comparisons for (a) t, (b) SMF, and (c) a show that these two largelyindependent methods produce comparable results. The t comparison between MODIS and I/SP inFigure 5d shows that the satellite and airborne sensors were responding to essentially the same aerosolphenomena, despite offsets in space and time for some cases. The validation tests for MODIS intensiveoptical properties are shown in Figure 5e for a and in Figure 5f for FMF. Error bars representmeasurement uncertainty (70% confidence) for the SP and I/SP variables and represent variability (onestandard deviation) over the comparison domain for the MODIS variables.

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dominance, showing a local SMF value of 0.34 [Doherty etal., 2005].[35] As mentioned, we assume temporal homogeneity

over 1–2 hours for this comparison. Evidence that this isreasonable comes from (1) lidar observations at Gosanwhich show that the aerosol vertical structure remained inplace for several hours before and after the overpass time[Kim et al., 2005], (2) Twin Otter SP measurements madenear Jeju and at the exact overpass time which show thesame value of a as was obtained earlier by the C-130 (seeTable 3), and (3) C-130 profile data acquired near Jeju fourhours after overpass time which indicate very similar aerosolproperties, especially in terms of SMF.[36] Table 3 indicates very good comparisons in terms of

t550 and the ocean retrieval of a. The MODIS land retrievalof a and ocean retrieval of FMF are both significantlyhigher than the suborbital estimates, yet the satellite andsuborbital values are correlated in a way that implies aphysical connection. In contrast, the MODIS land retrievalof FMF (1.0, implying no coarse mode at all), is inconsis-tent with both the MODIS ocean retrieval and the suborbitalmeasurements.[37] The matter of parameter definition is rather signif-

icant in this case. Mie calculations made on the aerosoltypes used in the ‘‘best’’ retrieval over the ocean indicatethat a MODIS retrieval of SMF would be lower by 0.07.Thus, the retrieved FMF value of 0.53 corresponds to anSMF retrieval of something like 0.46, which is only

slightly beyond the uncertainty range of the I/SP estimate(0.35 ± 0.05).

3.3. Comparison Summary

[38] Sixteen cases were identified in the ACE-Asia datafor testing the MODIS level 2 aerosol products. The resultsfor the two suborbital methods (I/SP and SP) as well as forMODIS are summarized in Table 3 and Figure 5. Weprovide uncertainty estimates for the suborbital methodsbut, for MODIS, we simply present the standard deviationover the 10-km data points that were used in the compar-ison. This is because for a and FMF, it is unclear what theuncertainty for MODIS ought to be. The informationprovided allows assessment of whether the uncertaintyrange of the suborbital measurements overlaps with thevariability of the MODIS retrieval, all to 70% confidence.Figure 5 also shows the root mean square error (RMSE) foreach comparison.[39] The suborbital methods are compared to each other

in Figures 5a–5c. Good correlation (R � 0.92) andagreement within uncertainties is found for all cases andall three parameters. The RMS errors are 0.03 for t550, 0.12for a, and 0.08 for SMF. These results provide the context,in terms of suborbital measurement precision, for evaluat-ing the comparisons with MODIS, which are shown inFigures 5d–5f. As in previous studies, we find the satelliteretrieval of t550 (Figure 5d) agrees reasonably well withsuborbital estimates (RMSE = 0.06 over both land and

Figure 6. Frequency distribution of aerosol properties for ACE-Asia region and time from four datasets. For MODIS, only ocean retrievals are considered. Further details on the data sets are given inTable 4. (a) t, (b) a, and (c) fine-mode partitioning (FMF or SMF).

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ocean). Similarly, we find reasonably good satellite/subor-bital agreement in terms of a (Figure 5e), better over theocean (RMSE = 0.14) than over the land (RMSE = 0.37).Results in terms of these two parameters lend confidence tothe validity of our test despite the low sample number andthe spatio-temporal offsets that characterized some of thecases. The comparison of satellite FMF to suborbital SMF(Figure 5f) shows, in the first place, that the MODIS landretrieval does not appear to provide useful information -that is, over a wide range of suborbital values, the satelliteretrieval is always 1.0. In the second place, the satelliteocean retrieval is always higher than the suborbital value,with an RMSE of 0.22. As discussed in the next section, nomore than half of this discrepancy can be explained interms of parameter definition or temporary satellite errorduring early 2001. The remainder, therefore, would appear torepresent a systematic overestimation of FMF by MODIS.

3.4. Campaign-Wide Statistics

[40] Satellite observations, long-term monitoring pro-grams, and intensive field campaigns all share the goal ofbeing able to characterize aerosol properties over an entireregion. Figure 6 shows the frequency distributions of t, a,and fine-mode partitioning for the ACE-Asia region accord-ing to four different measurement approaches. These are(1) column-averaged in situ measurements (the opticaldepth comparison does not include the in situ method sinceit applies to only part of the atmospheric column and is thussystematically biased low) from the C-130, (2) airborne Sunphotometry (SP) from both the C-130 and Twin Otter,

(3) ground-based AERONET observations from 4 stations,and (4) ocean-only satellite observations from MODIS.Summary statistics as well as data set descriptions are givenin Table 4. Each mode of observation is subject to samplebias. It is of interest, therefore, that the frequency distribu-tions for t and a are very similar. This implies that a similarspectrum of aerosol amount and type were sampled by allfour approaches over the course of the experiment. It alsoimplies that the four methods provide mutually consistentmeasurements of the a parameter.[41] In contrast, the distributions of fine-mode partition-

ing are distinctly different. The mean AERONET value ishigher by about 0.2 and the mean MODIS value is higher byabout 0.3 than the mean values derived from the in situ andSP approaches. (These latter two are not independent sinceSMF from the SP approach uses the in situ derivedrelationship with a given in equation (5).) This result isvery similar to the case-study result. Both suggest that theprimary cause of discrepancy is not the ability to measure abut, rather, involves the relationship between a and fine-mode partitioning.

4. Discussion

4.1. Causes of Observed Discrepancies

[42] We find that, in the Asian outflow region, t550 and acan be retrieved by MODIS with good fidelity over theocean and with less but still reasonable fidelity over theland. In contrast, the MODIS retrieval of FMF appears to besystematically high over the oceans and to be unrealisticover the land.[43] To further investigate the land retrieval of FMF, we

examined all land data points that were (1) within any ofthe 5-minute MODIS data blocks from the case studies and(2) within the ACE-Asia study region of 20–50�N and100–150�E. This yielded a total of 8621 land data points ofwhich 97% were found to have an FMF value of 1.0. Thisimplies a virtual absence of dust from the ACE-Asia regionon those days - an implication that is radically at odds with ahost of airborne and surface measurements. We thereforesuggest that the land retrieval of FMF is unreliable.[44] Regarding the ocean retrieval of FMF, two possible

causes for the systematically higher values need to beevaluated: (1) difference in definition and (2) MODIS errorrelated to side-B electronics. Any remaining discrepancyafter taking these into account is likely due to MODISretrieval error.[45] To evaluate the issue of parameter definition, we

calculated the difference between the retrieval of FMF andthe retrieval of SMF (using Mie calculations and the aerosoltypes involved in the ‘‘best’’ retrievals) for all six C-130comparisons over the ocean. On average, FMF was higherby 0.06, indicating that parameter definition accounts for asignificant but small fraction of the overall discrepancy of0.20.[46] In October 2000, the MODIS detector electronics

were switched to ‘‘side-B’’ and in June, 2001, following an‘‘anomaly,’’ the detector electronics were switched back to‘‘side-A.’’ Chu et al. [2005] suggests that during the ‘‘side-B’’ era (i.e. during ACE-Asia), FMF may be exaggerated,especially at low optical depth. Remer et al. [2005], incontrast, suggest that FMF may be underestimated just after

Table 4. Comparison of Regional Statistics Among Various Data

Sets for Optical Depth, Angstrom Exponent, and the Fine-Mode

Partitioning of Aerosol Optical Depth During ACE-Asia, April 1 to

May 4, 2001a

CountIn Situ Columnb

137SPc,d

23216AERONETe,d

185MODISf

30247

Optical Depth (550 nm)Mean – 0.349 0.326 0.358S.D. – 0.145 0.155 0.167

Angstrom ExponentMean 0.99 0.94 0.97 1.12S.D. 0.38 0.28 0.32 0.25

Fine-Mode Partitioning (FMF or SMF)Mean 0.47 0.45 0.66 0.76S.D. 0.16 0.12 0.12 0.10

aFrequency distributions are shown in Figure 6.bProfile measurements from C-130 aircraft as described in text.

Restricted to vertical profiles with minimum altitude below 800 m andmaximum altitude above 3000 m.

cAirborne Sun photometer data from the Twin Otter and C-130 with3-second resolution, as described in text. Cloud-screened data for altitudesbelow 200 m are used. SMF has been derived from a according toequation (5).

dRestricted to cases with 550 nm optical depth between 0.05 and 0.8.eBased on data from 4 AERONET stations: Anmyon and Jeju in South

Korea and Noto and Shirahama in Japan. a is determined by regressing 7optical depths from 340 to 1020 nm wavelength. SMF is determined by thestandard Dubovik inversion [Dubovik and King, 2000] of clear-sky opticaldepths and radiances and defined as the portion of 550 nm optical depthcaused by particles smaller than 1.2 mm diameter.

fMODIS level-2, ocean data at 10-km resolution for 30�–39�N and123�–136�E. Restricted to retrieval boxes with cloud fraction less than 0.8and 550 nm optical depth between 0.1 and 0.8.

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the ‘‘side-B’’ era (that is, just after the ‘‘anomaly’’). Neitherstudy finds evidence of effects at moderate to high opticaldepth, such as characterized the cases herein. To investigatethis matter, we examine monthly-averaged, level-3, pureocean MODIS data (such analysis can easily be done by thereader using the ‘‘MOVAS’’ website: lake.nascom.nasa.gov/www/online_analysis/movas/monthly/index.shtml) from2001 to 2004 for three regions of Asian outflow and oneregion of the southern, remote ocean. For each region, FMFand t550 were averaged over March-April-May for 2001(‘‘side B’’ era) and this was compared to March-April-Mayaverage values over the subsequent three years, 2002–2004.In agreement with the findings of Chu et al. [2005], theremote ocean region manifested much higher FMF during2001 (0.51) compared to the mean and standard deviation ofthe subsequent years (0.32 ± 0.05). The Asian outflowregions were the Sea of Japan, the Yellow Sea, and theEast China Sea. Seasonal/regional mean optical depth ismuch higher (0.4 to 0.8) and the interannual differences inFMF are much more subtle. Averaged over the threeregions, FMF is 0.72 for 2001, which is slightly but notsignificantly higher than in subsequent years (0.69 ± 0.03).It has been noted that 2003 had lower than normal Asiandust outflow, which would tend to raise FMF (J. T. Mao,personal communication). However, if we consider only2002 and 2004, the mean FMF in these Asian outflowregions is only marginally lower at 0.68. Based on this latterresult, it appears possible that around 0.04 of the FMFdiscrepancy observed herein could be due to anomalousbehavior in the ‘‘side-B’’ era.[47] The above two factors could explain up to half of the

observed discrepancy such that the MODIS retrievalappears to exaggerate fine-mode partitioning in this regionby at least 0.1. This is consistent with the findings of Chu etal. [2005] for the same region and time. The fact that thedust models in the current MODIS retrieval assume spher-ical geometry may be responsible for this overestimate ofFMF, as suggested previously [Levy et al., 2003; Remer etal., 2005; Chu et al., 2005]. Our ocean case studies tend tosupport this. The three cases with discrepancies that are wellbeyond the uncertainties are DOYs 96, 102, and 113. Theseare also the three cases with the lowest values of SMF and,thus, the ones most dominated by dust.

4.2. Implications for Future Satellite/SuborbitalCoordination

[48] Summarizing the previous section, it seems plausiblethat a combination of three factors (parameter definition,side-B electronics, and spherical models for dust) might beable to account for the observed discrepancies with respectto the MODIS ocean retrieval of FMF. However, there is analternate and, we suggest, more useful way to view theresults. Agreement is reasonably good with respect to a. Thechoice of aerosol models establishes a one-to-one relationbetween a and FMF (or SMF). The discrepancy arises,therefore, because the empirical relationship between a andSMF (Figure 2a) is different from the relationship predictedby Mie calculations based on the MODIS aerosol models(Figure 2c). This result is strongly supported by the cam-paign-wide statistics presented in Figure 6 and Table 4. Inaddition, it would appear that the FMF product is muchmore sensitive to inaccuracies in the aerosol model assump-

tions than is the a product. Indeed, the a product appears tohave considerable legitimacy even over land, where theFMF product is clearly unrealistic. Finally, we note that thea product can be rigorously validated by ground-based orairborne Sun photometers, whereas a true validation of FMFrequires considerable expense and logistical difficulties, asdescribed herein.[49] This situation suggests a way to improve the coor-

dination between satellite and suborbital observations. First,the primary satellite retrieval product (after t550) should bea, as recommended by early investigators [Durkee et al.,1986; Higurashi and Nakajima, 1999]. The existing vali-dation program is excellently suited to quantifying theaccuracy with which this parameter can be retrieved,whereas a systematic validation program for FMF doesnot exist. Moreover, there are indications that the a param-eter is poorly retrieved in some situations [Levy et al., 2003;Livingston et al., 2003], indicating that validation of thisparameter is far from complete. At the same time, in situmethods provide robust and accurate measurements of botha and fine-mode partitioning (i.e. SMF). Thus, largeamounts of data have been acquired at the surface for allmajor aerosol types [see, e.g., Delene and Ogren, 2002],and the potential exists for acquiring such data aloft as well,as demonstrated herein. Our second suggestion, therefore, isthat suborbital measurements (in situ combined with remotemethods) be used to establish, empirically, the relationshipbetween a and fine-mode partitioning, including regionalvariations in this relationship. For example, equation (5)captures this relationship for the ACE-Asia region, accord-ing to the in situ measurements on the C-130. Suchinformation, in turn, can be used to convert the satelliteretrieval of a into global maps of SMF. Additional subor-bital studies should be used to examine the potentialrelationships between a, fine-mode partitioning, and theanthropogenic fraction of aerosol optical depth. A specialpoint of emphasis should be testing the inversion-basedretrievals at AERONET stations of size distribution, SMF,and other parameters.[50] Finally, we note that accurate characterization of

fine-mode partitioning by in situ methods may benefit fromrecent advances in instrumentation. A lightweight opticalparticle counter (OPC) has been shown in two recentcampaigns to provide largely equivalent information to themuch bulkier set-up (twin-nephelometers plus impactor)used here [Shinozuka et al., 2004; Clarke et al., 2004].The OPC approach has advantages in terms of cost, capa-bility for deployment on small aircraft, ability to resolvedetails of the size distribution, and ability to providecompositional information via thermal preconditioning.However, it has significant disadvantages as well, includingcalibration uncertainties and the required use of Mie theoryand various assumptions to derive integral optical propertiessuch as SMF. Also of potential value is the measurement ofaerosol extinction by the cavity ring-down (CRD) technique[Smith and Atkinson, 2001; Strawa et al., 2003; Petterssonet al., 2004]. Nephelometer measurements of coarse-modescattering require a large correction (around 50%) forforward angular truncation, which, in turn, is a major sourceof measurement uncertainty [Anderson and Ogren, 1998].The CRD method virtually eliminates this source of errorsuch that accurate measurement of coarse-mode extinction

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may be among its most valuable contributions to aerosolscience. However, we caution that this capability has yet tobe demonstrated in either laboratory or field studies.

5. Conclusions

[51] Airborne profiles in the ACE-Asia region are used toprovide the first test of the MODIS retrieval of fine-modefraction (FMF) against in situ measurements. Logistical andtechnical difficulties limit the number of test cases and meanthat each must be processed with great care. Despite thesmall sample size and despite significant temporal offsets insome cases, the results reveal consistent patterns that appearto be informative. In particular, for level-2, version 4MODISdata over the ocean (1) good agreement is found with respectto aerosol optical depth, t550, and the Angstrom exponent, a,(2) good correlation is found between the MODIS retrievalof FMF and the suborbital estimate of submicron fraction(SMF), but (3) the MODIS retrieval of FMF is systematicallyhigher than suborbital SMF by about 0.2. About one half ofthe observed discrepancy in FMF/SMF can be ascribed to thedifference in parameter definition and anomalous detectorbehavior associated with the MODIS ‘‘side-B’’ electronics.The assumption of spherical shape in the MODIS aerosolmodels for dust could plausibly account for the rest. How-ever, we propose a more useful way to interpret these resultsand use them to advance future research aimed at globalmapping of fine-mode optical depth.[52] First, the good agreement obtained here with respect

to a suggests that this parameter is a more robust retrievalproduct. We note, in addition, that a, unlike FMF, can berigorously validated with existing Sun photometer measure-ments from ground-based networks (e.g. AERONET) aswell as from ships and airborne platforms. Thus, we recom-mend that satellite programs give high priority to developingglobal, validated data sets of a and its uncertainty.[53] Second, in situ techniques provide robust measures

of both a and SMF, and these measurements (both previouswork and herein) demonstrate a strong relationship betweenthe two. Moreover, we have shown that, for the ACE-Asiaregion, this empirical relationship differs systematicallyfrom the relationships that are dictated by the MODISaerosol models. With this in mind, we propose that in situmeasurements be analyzed to establish the regional vari-ability and uncertainty of this relationship and that satelliteretrieval algorithms be developed on this empirical basis.Implementing these recommendations will require carefulattention to exact parameter definitions, which necessarilydiffer among the various modes of measurement.

[54] Acknowledgments. This project depends upon high-quality dataprovided by several research programs, especially aerosol data fromMODIS and AERONET, provided under the auspices of NASA’s EarthObserving System. In addition, we gratefully acknowledge the organizersof the ACE-Asia field campaign, in particular, Barry Huebert and TimBates, as well as the outstanding support staff responsible for the NCAR C-130 research aircraft. This work is supported by NASA’s CALIPSOMission (contract NAS1-99105) and the National Science Foundation(grants ATM-0138250 and ATM-0205198).

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�����������������������T. L. Anderson and Y. Wu, Department of Atmospheric Sciences, Room

408 ATG/Box 351640, University of Washington, Seattle, WA 98195-1640,USA. (tadand@u.washington.edu)D. A. Chu, Laboratory for Atmospheres, NASA Goddard Space Flight

Center, Greenbelt, MD 20771, USA.O. Dubovik, Laboratory for Terrestrial Physics, NASA Goddard Space

Flight Center, Greenbelt, MD 20771, USA.J. Redemann and B. Schmid, Bay Area Environmental Research Institute,

Sonoma, CA 95476, USA.

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