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3, 3319–3344, 2010
Intercomparison of
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aerosol optical depth
retrievals
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Atmos. Meas. Tech. Discuss., 3, 3319–3344, 2010
www.atmos-meas-tech-discuss.net/3/3319/2010/
doi:10.5194/amtd-3-3319-2010
© Author(s) 2010. CC Attribution 3.0 License.
Atmospheric
Measurement
Techniques
Discussions
This discussion paper is/has been under review for the journal Atmospheric Measure-
ment Techniques (AMT). Please refer to the corresponding final paper in AMT
if available.
Intercomparison of CALIOP and MODIS
aerosol optical depth retrievals
C. Kittaka1,†, D. M. Winker2, M. A. Vaughan2, A. Omar2, and L. A. Remer3
1Science Systems and Applications Inc., Hampton, VA, USA
2NASA Langley Research Center, Hampton, VA, USA
3NASA Goddard Spaceflight Center, Greenbelt, MD, USA
†deceased
Received: 7 July 2010 – Accepted: 9 July 2010 – Published: 9 August 2010
Correspondence to: D. M. Winker (david.m.winker@nasa.gov)
Published by Copernicus Publications on behalf of the European Geosciences Union.
3319

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Intercomparison of
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Abstract
The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) is carried on the
CALIPSO satellite and has acquired global aerosol profiles since June 2006. CALIPSO
is flown in formation with the Aqua satellite as part of the A-train satellite constellation,
so that a large number of coincident aerosol observations are available from CALIOP5
and the MODIS-Aqua instrument. This study compares column aerosol optical depth
at 0.532 µm derived from CALIOP aerosol profiles with MODIS-Aqua 0.55 µm aerosol
optical depth over the period June 2006 through August 2008. The study is based on
the CALIOP Version 2 Aerosol Layer Product and MODIS Collection 5. While CALIOP
is first and foremost a profiling instrument, this comparison of column aerosol optical10
depth provides insight into quality of CALIOP aerosol data. It is found that daytime
aerosol optical depth from the CALIOP Version 2 product has a small global mean bias
relative to MODIS Collection 5. Regional biases, of both signs, are larger and biases
are seen to vary somewhat with season. In northern mid-latitudes, aerosol optical
depth from CALIOP is lower, on average, than from MODIS. This may be partly due to15
a latitude-dependent calibration error in Version 2 CALIOP Level 1 daytime 0.532 µm
profiles. This comparison of CALIOP and MODIS also provides insight into possible
biases in the MODIS aerosol optical depth product due to cloud masking and errors in
modeling land surface reflectance.
1 Introduction20
Aerosols have important effects on Earth’s radiation budget through the scattering and
absorption of sunlight, as well as through influences on cloud properties through a
variety of different physical mechanisms. Aerosols have many different sources, both
natural and anthropogenic, and can be transported on hemispheric scales. Limitations
in our ability to observe and characterize aerosols globally are responsible in part for25
the current uncertainties in predicting global climate change (Yu et al., 2006). We have
3320

AMTD
3, 3319–3344, 2010
Intercomparison of
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greatly advanced our understanding of aerosol horizontal distributions using satellite
observations from sensors such as AVHRR, TOMS, MODIS, and MISR. However, the
vertical profile of aerosol still remains uncertain. The CALIPSO satellite was developed
to provide a global profiling capability to complement current capabilities to observe
aerosol and cloud from space.5
The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, onboard
the CALIPSO satellite, provides detection and characterization of aerosols and clouds
using profiles of laser depolarization and 2-wavelength laser backscatter. The active
laser technique provides high vertical resolution and allows retrievals of aerosol pro-
files under both cloud-free conditions and above lower-lying clouds. CALIOP has now10
acquired a four-year record of global aerosol and cloud vertical distributions since
June 2006 (Winker et al., 2010). These observations reveal the vertical profile of
aerosol on a global basis for the first time. CALIPSO flies as part of the A-Train con-
stellation along with the PARASOL, Aqua, Aura, and Cloudsat satellites (Stephens et
al., 2003). The A-train orbit is sun-synchronous, with a 1:30 p.m. orbit crossing time15
and a 98◦ inclination.
While the strength of CALIOP is aerosol profile measurements, there are no in-
dependent aerosol datasets which can be used to validate CALIOP profiles globally.
There are a relatively small number of groundbased lidars suitable for providing data
for aerosol validation and the existing systems are far from ideally located for provid-20
ing measurements of important aerosol source regions. Field campaigns involving air-
borne lidars are useful, but provide very limited spatial and temporal coverage. Aerosol
optical depth (AOD) data from MODIS-Aqua can be compared with AOD derived from
CALIOP daytime profiles of aerosol extinction. While this is less than ideal, the MODIS
Collection 5 AOD product has undergone extensive validation and data quality is well25
understood, and flying the CALIPSO and Aqua satellites in formation provides a large
number of near-simultaneous, coincident aerosol observations with global coverage.
Comparisons of AOD from MODIS and CALIOP characterize the CALIOP AOD product
and also provide valuable insights into the performance of the CALIOP profile retrievals.
3321

AMTD
3, 3319–3344, 2010
Intercomparison of
CALIOP and MODIS
aerosol optical depth
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Further investigation can identify sources of error in the CALIOP retrievals.
AOD at 0.532 µm derived from the CALIOP Version 2.01 5-km Aerosol Layer Prod-
uct has been compared with AOD at 0.55 µm from MODIS-Aqua Collection 5. This
paper presents an initial, statistical comparison, which illuminates characteristics of
the CALIOP Version 2.01 AOD product and also serves as a benchmark against which5
to compare the CALIOP Version 3 product. Other validation studies are underway,
utilizing AOD measurements from AERONET and direct aerosol extinction profile mea-
surements from airborne HSRL operated by NASA Langley Research Center (Hair et
al., 2009). These studies will provide additional perspectives on CALIOP AOD data
quality.10
2 Measurements
Since the launch of the MODIS and MISR instruments in 1999, advanced satellite mea-
surements have greatly increased our knowledge of the global distribution and prop-
erties of aerosols (Kaufman et al., 2002). MODIS provides daily near-global coverage
and retrievals of AOD at several wavelengths over both ocean and land. Relative to15
previous satellite sensors used to retrieve aerosol, MODIS provided improved spatial
resolution (500m), better spectral coverage, and improved calibration. Development
of the AERONET network of groundbased sunphotometers has allowed an unprece-
dented degree of validation of aerosol retrievals from MODIS.
CALIOP, acquiring global aerosol observations since 2006, is complementary to20
MODIS in several ways. While CALIOP has a swath with essentially zero width, ob-
serving only along the sub-satellite point it acquires vertical profiles at two wavelengths
(0.532 µm and 1.064 µm) and two orthogonal polarizations, with a vertical resolution
of 30–60m (Hunt et al., 2009). Analysis of the spectral and polarization diversity of
the return signals, as a function of altitude, provides some skill in identifying aerosol25
type and also allows identification of columns which are inhomogeneous in terms of
aerosol type (Omar et al., 2009). While the MODIS and CALIOP retrievals rely on
3322

AMTD
3, 3319–3344, 2010
Intercomparison of
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several assumptions and are subject to several sources of error, the retrieval methods
are completely different and the CALIOP assumptions and sources of error are inde-
pendent of those of MODIS. Thus, a comparison of the two AOD datasets can lead to
insights into the strengths and limitations of both datasets.
2.1 MODIS5
The Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite
measures scattered radiances at 36 wavelengths from 0.41 to 14 µm. A 2330-km swath
provides near-global coverage every day. Different algorithms are used to retrieve AOD
over ocean and over land. Over ocean, seven wavelengths (0.47, 0.55, 0.66, 0.86, 1.2,
1.6, and 2.12 µm) are used to retrieve aerosol optical depth and other aerosol proper-10
ties (Tanre´ et al., 1997). These channels have spatial resolutions of 250m or 500m
and calibration of the radiances is believed to be accurate to 2% or better. Radiances
are grouped into nominal 10-km cells containing 20×20 pixels at 500-m resolution. All
400 pixels must be identified as ocean pixels for the ocean algorithm to be applied. If
any land is contained within the cell the land algorithm is applied (Remer et al., 2005).15
After screening for clouds and marine sediments, the brightest 25% and darkest 25%
of the remaining 500-m pixels are discarded. Retrievals are performed on the remain-
ing pixels. To avoid errors due to sunglint, retrievals are performed only for pixels where
the glint angle is greater than 40◦. Outside the glint regions the water-leaving radiance
is assumed to be negligible except at 550 nm where the surface reflectance is assumed20
to be 0.005. Wind speed is assumed to be 6m/s everywhere.
Over land, AOD is retrieved at 0.47, 0.55, and 0.66 µm (Kaufman et al., 1997). As
described above, the land algorithm is also used in coastal areas. The land algorithm
only retrieves AOD over dark surfaces. Pixels containing snow/ice and cloudy pixels
are masked out. Cloud mask quality flags (cf land, cf ocean) are included in the data25
product to indicate the fraction of cloudy pixels within the 10×10 km2 grid cells. cf x=3
indicates greater than 90% cloudy pixels, while cf x=0 indicates fewer than 30% cloud
pixels. After masking, dark pixels are selected based on their reflectance at 2.12 µm.
3323

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Intercomparison of
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Surface reflectance must fall within the range 0.01 to 0.25 to be selected. Pixels are
then sorted according to their reflectance at 0.66 µm and the darkest 20% and brightest
50% within each 10-km cell are discarded. Retrievals are performed on the remaining
30% of pixels.
A number of validation studies have characterized uncertainties of the MODIS AOD5
product. Relative to AERONET AOD measurements, Remer et al. (2005) found that
one standard deviation of MODIS-Terra AOD fell within the expected uncertainties of
∆τ =±0.03±0.05τ over ocean and ∆τ =±0.05±0.15τ over land. Ichoku et al. (2005)
compared AOD from MODIS-Terra and MODIS-Aqua averaged over 50×50 km2 boxes
with Aeronet AOD. Redemann et al. (2006) compared MODIS AOD at the 10×10 km210
scale of the Level 2 product with AERONET. Kahn et al. (2007) look at sources of sys-
tematic bias in AOD retrievals over the ocean from the MODIS and MISR instruments
on the Terra satellite.
2.2 CALIOP
CALIOP measures elastic laser backscatter at 1.064 µm and the parallel and cross-15
polarized components of the 0.532 µm return signal, from which the linear depolariza-
tion is derived (Hunt et al., 2009). At the Earth’s surface, the diameter of the laser
footprint is 70m, with successive footprints spaced by 333m along the orbit track. The
instrument has a fixed near-nadir view angle, so the measurements map a vertical
curtain along the orbital path. The 0.532 µm backscatter signal is sampled every 30m20
vertically from −0.5 km to 8.2 km. Between 8.2 km and 20.2 km altitude profiles are av-
eraged to 60m in the vertical and every three successive shots are averaged together
to give a horizontal resolution of 1 km. The geolocated and altitude-registered Level 1
data are calibrated before being processed for Level 2 data products. Daytime mea-
surements have a lower signal-to-noise ratio than at night owing to the noise added by25
the solar background illumination. Subtle diurnal differences in retrievals are caused
by the use of different calibration algorithms for day and for night. Briefly, extinction is
retrieved in three steps: (1) backscatter profiles are searched for layers with horizontal
3324

AMTD
3, 3319–3344, 2010
Intercomparison of
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averaging varying from 1/3 km to 80 km; (2) identified layers are classified as cloud or
aerosol; and (3) aerosol and cloud extinction profiles are retrieved, starting with the
highest layers detected and working down to the Earth’s surface (Winker et al., 2009
and references therein). Aerosol retrievals are performed on layers which have been
horizontally averaged over 5 km, 20 km, or 80 km. Retrieval results are reported at 5-5
km horizontal scale in the 5-km Aerosol Layer Product. Retrieval results from 20-km or
80-km layers are repeated 4 times, or 16 times, in the 5-km product.
Extinction retrieval from a backscatter lidar such as CALIOP is under-determined
and an additional constraint is required. When the layer transmittance can be accu-
rately measured, from clear-air signals on either side of a layer, the measured trans-10
mittance yields the layer optical depth directly and can be used as a constraint on the
extinction retrieval (Young, 1995). This occurs rarely during daytime, when the SNR of
clear-air returns is lower than at night. Therefore, an algorithm is used to estimate the
“lidar ratio” (the ratio of particle extinction to 180-degree backscatter) from the 0.532 µm
backscatter and depolarization signals (Omar et al., 2009), which provides the neces-15
sary constraint for the retrieval. Aerosol extinction is retrieved above clouds and below
optically thin clouds, as well as in cloudfree columns, but only within identified aerosol
layers (Young and Vaughan, 2009).
The primary products used in this paper are the 0.55 µm Opti-
cal Depth Land and Ocean from the MODIS-Aqua Level 2 aerosol data product20
(MYD04 L2), and the Feature Optical Depth 532 from the CALIOP Level 2 5-km
Aerosol Layer Product. Feature Optical Depth is summed over each aerosol layer in a
5-km the column to obtain the column AOD.
Figure 1 shows seasonally-averaged AOD from MODIS and from CALIOP observa-
tions, plotted on the same 5×5 degree equal-angle grid. Daytime and nighttime AOD25
distributions from CALIOP are generally similar. Differences are due to a combination
of differences between day and night sensitivity, differences in systematic calibration
errors for day and night, differences in spatial sampling, and diurnal changes in the
aerosol. Even though the MODIS and daytime CALIOP observations are simultane-
3325

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Intercomparison of
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ous, a number of differences can be seen, due in part to differences in sampling of
the two instruments. CALIOP retrieves AOD over the Sahara desert and other bright
surfaces where the MODIS product has no data. Daytime CALIOP measurements ex-
tend to higher southern latitudes than MODIS. Because CALIOP measurements are at
nadir only, many fewer samples are acquired than from MODIS and many grid cells are5
sampled only about once per week, causing CALIOP AOD to appear to be noisier than
MODIS AOD. Intense but intermittent aerosol events – such as dust storms or forest
fires – may be missed by CALIOP, resulting in smaller grid-cell averages than MODIS
AOD which better represents the seasonal-mean AOD at smaller spatial scales due to
its daily coverage.10
3 Method
Because of the large differences in spatial sampling, the remainder of the comparisons
in this paper will be based on simultaneous, co-located daytime CALIOP and MODIS
observations. The comparison of matched observations reduces uncertainties from
spatial and temporal differences of the observations, but greatly reduces the number15
of observations and so may compromise the geophysical representivity. First, MODIS
10-km cells coincident with CALIOP 5-km pixels are identified. After applying quality
screening to the CALIOP aerosol data, layer optical depths are summed to derive
0.532 µm column AOD. Coincident CALIOP and MODIS AOD are then stored, along
with cloud masking information.20
3.1 Sampling geometry and co-location
CALIOP laser footprints have a diameter of 70m with a center-center separation of
about 330m. Thus there are about 30 footprints within the 10×10 km2 MODIS Level 2
cell. The orbits of the CALIPSO and Aqua satellites are controlled to keep the along-
track separation at about 2 min and the relative cross-track error of the two satellite25
3326

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groundtracks to about 10 km. MODIS AOD is not retrieved for pixels over water where
the sunglint angle is less than 40◦. Therefore the CALIPSO orbit was shifted relative to
the Aqua orbit to minimize the occurrence of MODIS sunglint at the CALIOP footprint.
On the day side of the orbit at the equator the CALIPSO subsatellite point falls 215 km
to the east of the Aqua subsatellite point. At the orbit turning points (82◦ N and 82◦ S)5
the cross-track bias is zero and increases to 215 km at the equator. Thus the CALIOP
footprint is continually moving cross-track with respect to the MODIS 10×10 km2 grid
(Fig. 2). Spatially coincident CALIOP and MODIS AOD observations are identified
when the distance between the center of a CALIPSO 5-km “pixel” and that of a MODIS
pixel is less than 10 km. This criterion automatically selects time-coincident measure-10
ments (within 2 min).
3.2 Data screening
Additional quality screening is applied to CALIOP Level 2 aerosol data before use. In
a small number of cases, the initial lidar ratio is automatically reduced to avoid a di-
verging solution (Winker et al., 2009). It has been found that these retrievals are not15
reliable, so columns containing aerosol layers where the final lidar ratio is different from
the initial lidar ratio are screened out. Also, in Version 2 data, a small number of aerosol
layers are found to have anomalously large layer-integrated attenuated backscatter val-
ues, most often due to overcorrection of the attenuation of overlying layers. Therefore,
columns containing aerosol layers with integrated attenuated backscatter greater than20
0.01 sr−1 are also screened out.
Figure 4 shows the number of 5-km CALIOP columns with valid data from both in-
struments between 15 June 2006 and 31 August 2008. For MODIS this represents
all of the pixels except for those filled with a missing value due to cloud cover, high
reflectance surface, or sunglint, while the CALIPSO pixels with valid data are those25
remaining after the screening described above. Over this time period there are about
1.8 million coincident AOD retrievals. Over ocean, about 12% of the CALIPSO day-
time footprints have a coincident MODIS AOD value. The co-located measurements
3327

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Intercomparison of
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are heavily weighted toward the Southern Hemisphere due to a combination of cloud
cover, reflective land surfaces, and sunglint. Even with the 215 km offset, the CALIPSO
ground track falls just within the edge of the MODIS sun glint areas at northern mid-
latitudes from May through July. This contributes to fewer coincident samples over
the ocean in the Northern Hemisphere spring and summer. In Collection 5, AOD is5
not retrieved over highly reflective land surfaces such as ice/snow and deserts, which
reduces the number of coincidences over land at mid and high latitudes. Polar night
further reduces the number of MODIS observations at high latitudes and there are
relatively few coincident samples in the tropics due to frequent cloud cover.
4 Effects of cloud screening10
The next few figures show the frequency distributions of AOD values from the two
instruments. These distributions are used to help identify general characteristics of the
two data sets and determine the effects of additional screening. Figure 5 shows the
two-dimensional frequency distributions of the coincident CALIOP and MODIS AOD
values over ocean (a) and over land (b) for the time period from 15 June 2006 to15
31 August 2008. The samples going into these histograms are instantaneous, co-
located MODIS and CALIOP AOD values. The CALIOP AOD data are screened using
the method described in the Sect. 3.2, while MODIS AOD is used regardless of cloud
fraction within the 10-km cell.
Several features of these plots give insight into data quality. MODIS and CALIOP20
AOD over ocean are somewhat correlated, although the scatter is very large. There
is little correlation over land however. CALIOP uses the same retrieval algorithm over
land and ocean. The difference between Fig. 5a and b may be due to larger instanta-
neous uncertainties in the MODIS land algorithm, or may just reflect the higher spatial
variability of aerosol over land. Looking at AOD values smaller than 0.2, CALIOP AOD25
is biased somewhat low relative to MODIS for both land and ocean. A prominent fea-
ture seen in both scatter plots is a high population in the MODIS AOD bins between
3328

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zero and 0.6 for zero CALIOP AOD. This feature extends to −0.05 in the MODIS bins
for land. A similar feature is seen over land for zero MODIS AOD and CALIOP AOD
less than 0.1. A noticeable feature in the ocean plot is an enhanced population in the
CALIOP AOD range between 0.4 and 0.8 for MODIS AOD smaller than 0.2.
The scatter plots in Fig. 6 are produced the same as those in Fig. 5 except for5
more stringent cloud screening, using only coincident AOD from grid cells where less
than 30% of the pixels are cloudy (cf x=0). The area of enhanced CALIOP AOD be-
tween 0.4 and 0.8 corresponding to MODIS AOD less than 0.2, seen in Fig. 5a, has
disappeared. When the locations of this population are mapped, they are seen to pre-
dominantly come from relatively clean ocean regions dominated by trade cumulus, and10
analysis of CALIOP cloud height data shows the population is associated with clouds
having tops below 2 km. Therefore, this population may be an artifact due to a program-
ming error in the CALIOP Version 2 production software where small-scale boundary
layer clouds are not properly cleared from 5-km average profiles. These cloud contam-
inated profiles are most often classified as cloud, but if classified as aerosol they would15
tend contribute to a high bias in AOD. Figure 6a also shows substantial effects of the
additional cloud screening on the population of MODIS bins for zero CALIOP AOD over
ocean. The frequency of large MODIS AOD values is greatly reduced, indicating these
may be due to cloud contamination or possibly side-scattering from clouds. The distri-
bution for land, however, exhibits little change in the general pattern with the exception20
of the high MODIS AOD range.
One additional level of cloud-screening was applied. CALIOP identifies clouds in
roughly 20–30% of MODIS 10×10 km2 grid cells with less than 30% cloudy pixels. The
histograms of Fig. 6 don’t change significantly if these cloudy columns are screened
out, but the mean AOD decreases somewhat. Table 1 summarizes changes in mean25
AOD for the three different levels of cloud screening.
The large MODIS AOD values corresponding to near-zero CALIOP AOD – seen
along the x-axis of Figs. 5b and 6b – are not significantly affected by more stringent
cloud screening. If we map the location of these observations, many are associated
3329

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with arid regions having 2.12 µm surface reflectance greater than 15% (Fig. 7). While
there are a number of possible explanations for high MODIS AOD and near-zero
CALIOP AOD, it is likely that use of incorrect surface reflectivity values in the MODIS
retrievals is one source.
5 Comparison of spatial averages5
The following analyses are based on fully cloud-screened data, where fewer than 30%
of MODIS pixels are cloudy and CALIOP detects no clouds in the column. Figure 7
compares MODIS and CALIOP zonal mean AOD distributions for ocean and for land,
averaged over the entire 27-month period. Only data passing the most stringent cloud
screening has been used: MODIS flag cf=0 and no cloud identified by CALIOP. Over10
the ocean, zonal mean AOD differences (MODIS–CALIPSO) range from −0.02 to
+0.06. The agreement is reasonably good, except that MODIS AOD is significantly
larger than CALIOP north of 30◦ N and about 0.03 larger than CALIOP between 40◦ –
60◦ S. The range of the AOD difference over land is much larger, from −0.14 to +0.18,
which may be due in part to the much smaller number of co-located samples over land.15
Referring back to Fig. 4, it can be seen that many land regions have few co-located
samples relative to much of the ocean. CALIOP AOD is lower than MODIS at high
northern and southern mid-latitudes, as over ocean, but is also higher than MODIS
between 20◦ S–20◦ N, a region which is likely dominated by smoke from biomass fires.
There is a known Northern Hemisphere bias in the Version 2 daytime CALIOP 0.532 µm20
calibration. The calibration bias causes the attenuated backscatter signal to be low in
northern mid-latitudes and may contribute to the generally smaller CALIOP AOD values
seen in the Northern Hemisphere in Fig. 8.
To provide more insight into these zonal patterns, Fig. 9 illustrates the geographi-
cal distribution of seasonally-averaged differences in co-located MODIS and CALIOP25
AOD. Only CALIOP AOD from cloud-free 5-km columns and MODIS AOD from grid
cells with less than 30% cloud pixels are used. Retrievals over surfaces flagged as
3330

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snow/ice are also screened out. A 5◦ ×5◦ grid is used to provide sufficient statistics for
the nadir-only CALIPSO retrievals without losing regional patterns of the AOD distribu-
tion. A strong hemispheric pattern is seen, with MODIS AOD tending to be higher than
CALIOP AOD in the northern and somewhat lower in the Southern Hemisphere, ex-
cept for 40◦–60◦ S during Austral spring and summer when MODIS AOD is somewhat5
higher. The magnitude of AOD differences is considerably larger over land than that
over ocean, partly because mean AOD tends to be larger over land than over ocean.
Numerous regional biases can also be seen, some which are counter to the overall
north-south pattern. MODIS AOD is consistently lower than CALIOP over India, except
in arid northwest India and Pakistan where MODIS is consistently higher. In this com-10
parison, CALIOP tends to be higher than MODIS over the eastern US and lower over
Western US. CALIOP AOD is generally larger than MODIS over tropical Africa, except
during DJF where MODIS AOD is larger over Niger/Nigeria. In the Southern Hemi-
sphere, CALIOP AOD is consistently higher over central and southern Africa, while
MODIS is consistently higher in the Gulf of Guinea – both regions typically dominated15
by smoke. MODIS AOD is consistently higher in southern Argentina. The seasonal cy-
cle over Brazil is not well sampled, probably because of persistent cloud cover. During
the dry season (SON) CALIOP AOD is higher in eastern Brazil, while MODIS AOD is
significantly higher in western Brazil and Bolivia. There is a degree of consistency in
these regional differences, pointing to the likelihood of underlying causes in algorithms20
and calibration.
6 Summary
This paper has developed a methodology for screening CALIOP AOD data and com-
paring with MODIS AOD. Initial AOD comparisons have been performed based on
CALIOP Version 2 and MODIS Collection 5 data. These comparisons show that global25
mean AOD from CALIOP is somewhat low relative to MODIS-Aqua, but that there are
significant regional biases of both signs. The work reported here forms a basis for
3331

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further comparisons using the recently released CALIOP Version 3 data. Apparent
systematic regional differences identified here, such as between southern Africa and
the Gulf of Guinea, or between eastern and western United States, provide motiva-
tion for more detailed case studies to diagnose the source of these differences at the
algorithm level.5
References
Hair, J. W., Hostetler, C. A., Cook, A., Harper, D. B., Ferrare, R., Mack, T. L., Welch, W., Ramos
Isquierdo, L., and Hovis, F.: Airborne High Spectral Resolution Lidar for Profiling Aerosol
Optical Properties, Appl. Opt., 47, 6734–6752, 2008.
Hunt, W. H., Winker, D. M., Vaughan, M. A., Powell, K. A., Lucker, P. L., and Weimer, C.:10
CALIPSO Lidar Description and Performance Assessment, J. Atmos. Oceanic Technol., 26,
1214–1228, 2009.
Ichoku, C., Chu, D. A., Mattoo, S., Kaufman, Y. J., Remer, L. A., Tanre´, D. Slutsker, I., and Hol-
ben, B. N.: A spatio-temporal approach for global validation and analysis of MODIS aerosol
products, Geophys. Res. Lett., 29, L8006, doi:10.1029/2001GL013206, 2002.15
Kahn, R. A., Garay, M. J., Nelson, D. L., Yau, K. K., Bull, M. A., Gaitley, B. J., Martonchik, J.
V., and Levy, R. C.: Satellite-derived aerosol optical depth over dark water from MISR and
MODIS: comparisons with AERONET and implications for climatological studies, J. Geophys.
Res., 112, D18205, doi:10.10.1029/2006JD008175, 2007.
Kaufman, Y., Tanre´, D., and Boucher, O.: A satellite view of aerosols in the climate system,20
Nature, 419, 215–223, 2002.
Kaufman, Y. J., Tanre´, D., Remer, L. A., Vermote, E. F., Chu, A., and Holben, B. N.: Operational
remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging
spectroradiometer, J. Geophys. Res., 102, 17051–17067, 1997.
Levy, R. C., Remer, L. A., Kaufman, Y. J., Tanre´, D., Mattoo, S., Vermote, E., and Dubovik, O.:25
Revised Algorithm Theoretical Basis Document: MODIS Aerosol Products MOD/MYD04,
2006.
Liu, Z., Vaughan, M. A., Winker, D. M., Kittaka, C., Kuehn, R. E., Getzewich, B. J., Trepte, C.
R., and Hostetler, C. A.: The CALIPSO Lidar Cloud and Aerosol Discrimination: Version 2
3332

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J I
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iscussion
P
aper
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D
iscussion
P
aper
|
D
iscussion
P
aper
|
D
iscussion
P
aper
|
Algorithm and Initial Assessment of Performance, J. Atmos. Oceanic Technol., 26, 1198–
1213, doi:10.1175/2009JTECHA1229.1, 2009.
Omar, A., Winker, D., Kittaka, C., Vaughan, M., Liu, Z., Hu, Y., Trepte, C., Rogers, R.,
Ferrare, R., Kuehn, R., and Hostetler, C.: The CALIPSO Automated Aerosol Classifi-
cation and Lidar Ratio Selection Algorithm, J. Atmos. Oceanic Technol., 26, 1994–2014,5
doi:10.1175/2009JTECHA1231.1, 2009.
Redemann, J., Zhang, Q., Schmid, B., Russell, P. B., Livingston, J. M., Jonsson, H., and
Remer, L. A.: Assessment of MODIS-derived visible and near-IR aerosol optical properties
and their spatial variability in the presence of mineral dust, Geophys. Res. Lett., 33, L18814,
doi:10.1029/2006GL026626, 2006.10
Remer, L. A., Kaufman, Y. J., Tanre´, D., Mattoo, S., Chu, D. A., Martins, J. V., Li, R.-R., Ichoku,
C., Levy, R. C., Kleidman, R. G., Eck, T. F., Vermote, E., and Holben, B. N.: The MODIS
Aerosol Algorithm, Products, and Validation, J. Atmos. Sci., 62, 947–973, 2005.
Stephens, G. L., Vane, D. G., Boain, R. J., Mace, G. G., et al.: The CloudSat mission and the
A-Train: A new dimension of space-based observations of clouds and precipitation, B. Am.15
Meteorol. Soc., 83, 1771–1790, 2002.
Tanre´, D., Kaufman, Y. J., Herman, M., and Mattoo, S.: Remote sensing of aerosol proper-
ties over oceans using the MODIS/ESO spectral radiances, J. Geophys. Res., 102, 16971–
16988, 1997.
Vaughan, M., Powell, K., Kuehn, R., Young, S., Winker, D., Hostetler, C., Hunt, W., Liu, Z.,20
McGill, M., and Getzewich, B.: Fully Automated Detection of Cloud and Aerosol Layers in
the CALIPSO Lidar Measurements, J. Atmos. Ocean. Technol., 26, 2034–2050, 2009.
Winker, D. M., Pelon, J., Coakley, J. A., Ackerman, S. A., et al.: The CALIPSO Mission: a
Global 3-D View of Aerosols and Clouds, B. Am. Meteorol. Soc., 91, August 2010, in press.
Winker, D. M., Vaughan, M. A., Omar, A., Hu, Y., Powell, K. A., Liu, Z., Hunt, W. H., and Young,25
S. A.: Overview of the CALIPSO mission and CALIOP data processing algorithms, J. Atmos.
Ocean Tech., 26, 2310–2323, doi:10.1175/2009JTECHA1281, 2009.
Young, S. A.: Analysis of lidar backscatter profiles in optically thin clouds, Appl. Opt., 34, 7019–
7031, 1995.
Young, S. A. and Vaughan, M. A.: The retrieval of profiles of particulate extinction from Cloud30
Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) data: Algorithm descrip-
tion, J. Atmos. Oceanic Technol., 26, 1105–1119, doi:10.1175/2008 JTECHA1221.1, 2009.
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Yu, H., Kaufman, Y. J., Chin, M., Feingold, G., Remer, L. A., Anderson, T. L., Balkanski, Y.,
Bellouin, N., Boucher, O., Christopher, S., DeCola, P., Kahn, R., Koch, D., Loeb, N., Reddy,
M. S., Schulz, M., Takemura, T., and Zhou, M.: A review of measurement-based assess-
ments of the aerosol direct radiative effect and forcing, Atmos. Chem. Phys., 6, 613–666,
doi:10.5194/acp-6-613-2006, 2006.5
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Table 1. Global-mean AOD for different cloud-screening criteria. Averaging period is JJA
between 15 June 2006 and 31 August 2008.
Ocean Land
MODIS CALIOP MODIS CALIOP
All MODIS AOD 0.120 0.084 0.145 0.089
MODIS<30% cloudy 0.096 0.082 0.126 0.102
CALIOP cloud-free 0.083 0.076 0.082 0.094
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(a) (b)
(c)
Fig. 1. Seasonal-mean AOD distributions for JJA 2006 from (a) CALIOP daytime retrievals;
(b) CALIOP nighttime retrievals; and (c) MODIS retrievals.
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Fig. 2. Geometry of the MODIS 10-km grid vs. the CALIOP “swath”.
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Fig. 3. CALIPSO ground-track superimposed on color-coded MODIS AOD retrievals,
1 July 2006. In northern mid-latitudes, the CALIPSO groundtrack falls within the eastern edge
of the MODIS sunglint region, so MODIS AOD is not retrieved to the west of the CALIPSO
ground-track.
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Fig. 4. Map of the number of the CALIPSO and MODIS coincidences with valid AOD data from
both instruments from 15 June 2006 to 31 August 2008.
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(a)
(b)
Fig. 5. Frequency distributions of AOD values for JJA (between 15 June 2006 and 31 Au-
gust 2008) over the global ocean (a) and land (b) using all coincident CALIOP and MODIS
data.
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(a)
(b)
Fig. 6. Frequency distributions of AOD values for JJA (between 15 June 2006 and 31 Au-
gust 2008) over the global ocean (a) and land (b) using the most stringent MODIS cloud
screening.
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Fig. 7. Number of cloudfree 5-km pixels where CALIOP AOD=0 and MODIS AOD>0.05 for
instantaneous, co-located retrievals, 15 June 2006–31 August 2008.
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(a)
(b)
Fig. 8. Zonal mean AOD from CALIPSO and from MODIS, and zonal mean MODIS-CALIPSO
differences for cloud-free columns for the period 15 June 2006 to 31 August 2008. (a) over
ocean; (b) over land.
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(a) (b)
(c) (d)
Fig. 9. Seasonal-mean differences of MODIS and CALIOP AOD (MODIS–CALIOP), averaged
for seasons over the period of 15 June 2006 to 31 August 2008. Grey indicates grid cells with
insufficient number of samples. (a) March-April-May; (b) June-July-August; (c) September-
October-November; (d) December-January-February.
3344