The effect of smoke, dust, and pollution aerosol on
shallow cloud development over the Atlantic Ocean
Yoram J. Kaufman*†, Ilan Koren*‡, Lorraine A. Remer*, Daniel Rosenfeld§, and Yinon Rudich¶
*National Aeronautics and Space Administration Goddard Space Flight Center, Greenbelt, MD 20771;‡Joint Center for Earth Systems Technology, University
of Maryland, Baltimore County, Baltimore, MD 21228-4664;§Institute of Earth Sciences, Hebrew University of Jerusalem, Jerusalem 91904, Israel; and
¶Department of Environmental Sciences, Weizmann Institute, Rehovot 76100, Israel
Communicated by Veerabhadran Ramanathan, Scripps Institution of Oceanography, La Jolla, CA, June 21, 2005 (received for review January 21, 2005)
Clouds developing in a polluted environment tend to have more
numerous but smaller droplets. This property may lead to suppres-
sion of precipitation and longer cloud lifetime. Absorption of
incoming solar radiation by aerosols, however, can reduce the
uncertainty in evaluating climate forcing. Using large statistics of
1-km resolution MODIS (Moderate Resolution Imaging Spectrora-
diometer) satellite data, we study the aerosol effect on shallow
water clouds, separately in four regions of the Atlantic Ocean, for
June through August 2002: marine aerosol (30°S–20°S), smoke
(20°S–5°N), mineral dust (5°N–25°N), and pollution aerosols (30°N–
60°N). All four aerosol types affect the cloud droplet size. We also
by 0.2–0.4 from clean to polluted, smoky, or dusty conditions.
Covariability analysis with meteorological parameters associates
most of this change to aerosol, for each of the four regions and 3
aerosol effect can be explained by coincidental, unresolved,
or errors in the data, although further in situ measurements and
The radiative effect at the top of the atmosphere incurred by the
aerosol effect on the shallow clouds and solar radiation is ?11 ?
3 W?m2for the 3 months studied; 2?3 of it is due to the aerosol-
induced cloud changes, and 1?3 is due to aerosol direct radiative
cloud cover ? cloud height ? indirect effect ? radiative forcing ? air quality
covering a separate latitude belt (see Fig. 1). The Southern
Tropical Atlantic (30°S–20°S) is dominated by clean maritime
air. The region between 20°S and 5°N is a relatively well defined
region covered by smoke from biomass burning in Africa (1, 2).
The Northern Tropical Atlantic (5°N–30°N) is under heavy
influx of dust from Africa (3), and the Northern Atlantic
(30°N–60°N) is impacted by anthropogenic pollution aerosol
from North America and Europe. These aerosols absorb and
reflect solar radiation to space (4), thereby affecting the regional
atmospheric energy balance. Clouds that form in air laden with
high aerosol concentrations tend to contain more numerous but
smaller droplets that reflect sunlight and cool the Earth (5). The
smaller cloud droplets reduce the efficiency of droplet growth by
collision coalescence, which at least under some conditions (6)
However, there is a second pathway for aerosols to affect clouds:
Smoke, pollution, and dust aerosols absorb solar radiation, heat
the atmosphere, and reduce evaporation from the surface (9–
11). As a result, smoke over the Amazon or pollution aerosol
over the Indian Ocean can inhibit cloud formation (12, 13). This
global warming effect, but recent studies questioned this con-
clusion (16, 17). Cloud-resolving models show that absorbing
aerosols located above stratiform clouds can strengthen the
uring June through August, the Atlantic Ocean is covered
by varying concentrations of several aerosol types, each
temperature inversion, thus increasing the moisture and liquid
water content of the cloud layer (18). Here we present obser-
vations of yet a stronger effect of aerosols on clouds and climate,
namely, a substantial increase in shallow cloud coverage due to
high aerosol concentrations.
The contradictory pathways by which aerosols can affect
clouds, and the large natural variability of cloud properties,
represent the largest uncertainty in understanding climate
change forcing. A better understanding of the effect requires
large-scale systematic measurements to resolve the effect of
aerosol on the hydrological cycle and distinguish it from natural
variability. Aerosol–cloud interactions over the Atlantic Ocean
and in other regions were explored in field experiments (19, 20).
In the Atlantic Ocean region, these studies demonstrated con-
nections between aerosol concentration and cloud microphysics.
The experiments were intensive in aerosol and cloud physical
and chemical characterizations, but were limited in their spatial
and temporal extents. Satellite data were used on a global scale
liquid water content and cloud cover (23). Sekiguchi et al. (23)
found a 0.10 increase in global cloud cover between pristine and
hazy (high aerosol concentration) conditions. However, these
studies used satellite data with limited spatial resolution (4–6
km) that cannot resolve smaller clouds, more susceptible to the
aerosol effect. They also left open the question of whether the
changes in the cloud cover are due to the aerosol effect or to
other atmospheric changes that can influence both clouds and
aerosol. Here, using the new Moderate Resolution Imaging
Spectroradiometer (MODIS)-Terra satellite data of aerosol and
clouds with resolution of 1 km, we analyze 3 months (June–
August 2002) of data covering millions of km2of shallow
(stratiform and trade cumulus) clouds, and the aerosol in their
immediate vicinity, and apply multiple regression to distinguish
the aerosol impact on clouds from that of coincidentally chang-
ing meteorological conditions.
Shallow water clouds have a critical role in the climate system;
2–3 K of greenhouse warming (24). By reflecting sunlight back
to space, stratiform clouds are ‘‘the vast climate refrigerator of the
tropics and subtropics’’ (ref. 25, see also ref. 26). They are
difficult to model because they are only a few hundred meters
thick, capped by a strong temperature inversion, and controlled
by small-scale physical processes. Using state-of-the-art satellite
data, we show that the aerosol concentration is linked to the
development, microphysics, and coverage of shallow clouds,
thereby generating a large radiative forcing of climate.
Analysis of the Satellite Data
We use the MODIS data on the Terra satellite to measure the
daily aerosol column concentration and its correlation to the
Freely available online through the PNAS open access option.
Abbreviations: MODIS, Moderate Resolution Imaging Spectroradiometer; AOT, aerosol
optical thickness; LWP, liquid water path; AERONET, Aerosol Robotic Network.
†To whom correspondence should be addressed. E-mail: email@example.com.
© 2005 by The National Academy of Sciences of the USA
August 9, 2005 ?
vol. 102 ?
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local stratiform and trade cumulus cloud cover and properties.
MODIS observes detailed aerosol and cloud properties with
resolution of 0.5–1 km. The data are summarized into a daily
1° ? 1° latitude and longitude grid. Simultaneous observations
of aerosols in cloud-free regions of the grid box and clouds in the
cloudy regions of the grid box are possible (see http:??modis-
atmos.gsfc.nasa.gov?). Aerosol nonhomogeneity has a spatial
scale of 50–400 km (27), allowing the 1° resolution study.
MODIS measures the aerosol optical thickness, ? (in cloud-free,
sun-glint-free conditions), representing the aerosol column con-
centration (28), which we use as a surrogate for the concentra-
tion of aerosol that interacts with the cloud layer. MODIS also
measures the following cloud properties: cloud cover, optical
depth, liquid water content, cloud top effective radius, and cloud
top pressure (29–31).
The 1° ? 1° latitude and longitude data were classified as
shallow water clouds if the average cloud top pressure is higher
than 640 hPa and all of the clouds in the given grid box and in
its surrounding neighboring pixels are water clouds (no ice). The
average cloud top pressure of the shallow clouds is 870 hPa,
corresponding to 1,200 m. For the region impacted by smoke,
53% of the 1° ? 1° grid boxes were classified as shallow clouds
(see Table 1). This percentage corresponds to 107km2with
average of 50 daily observations during the 3 months of inves-
tigation. For the region impacted by dust it corresponds to 6 ?
106km2of observations (see definition of the studied region in
During June through August, smoke, dust and pollution aerosols
are confined to separate latitude belts of the Atlantic Ocean (Fig.
1), allowing separate analysis of their effect and the effect of pure
marine air on the prevailing clouds (see Table 1). Fig. 2 shows the
longitudinal distribution of changes in the shallow cloud cover and
The fraction of the shallow clouds decreases from east to west
The largest changes in cloud cover and Reffare observed in regions
with high aerosol concentrations near the continental sources. The
cloud liquid water path (LWP) increases in all but the biomass-
burning zone, in agreement with theory (7). In the smoke zone the
The satellite data show a systematic increase in the shallow
cloud coverage as a function of the aerosol concentration across
the Atlantic Ocean for all four aerosol types (see Table 1). For
a given value of cloud fraction (0.30), the spatial coverage of
shallow clouds extends ?2,000 km further to the west for heavy
smoke or dust in comparison with the clean conditions (Fig. 2).
Table 1. Results of the analysis for four regions in the Atlantic Ocean
Radiative effects (W?m2) due to
0.20 ? 0.06 0.19 ? 0.03
0.36 ? 0.12 0.25 ? 0.04
0.31 ? 0.07 0.31 ? 0.04
?12 ? 10
?12 ? 13
?32 ? 3
6 ? 34
9 ? 34
?21 ? 8
?39 ? 20
?66 ? 13
?55 ? 11
Marine30°S-20°S0.47 0.27 0.02–0.240.085 0.45 ? 0.10 0.45 ? 0.04
?19 ? 735 ? 22
?72 ? 18—————
change in the cloud top pressure (CLTP). For each value the variability among the three months of analysis (June-August) is given. The average radiative effects due
to change in the aerosol optical thickness from the base oceanic value of 0.06 associated with the following: increase in cloud droplet concentration (?Nc) due to
uncertainty of 50%. No calculations are given for the marine region, because the average AOT is too close to the baseline value.
as the optical thickness) and type (given by the fraction of the aerosol in the
sub-?m mode) over the Atlantic Ocean for the June–August period. The optical
thickness is represented by the brightness of the image. The aerosol type is
represented by the color: red, dominance by sub-?m particles, smoke from
central Africa and pollution from Europe and North America, and green, domi-
nance by dust from Africa or sea salt in regions with high winds. (Lower) Spatial
distribution of shallow (red), deep convective (green), and mixed (blue) cloud
The data are averaged for June–August 2002.
Spatial distribution of aerosol and clouds over the Atlantic Ocean from
www.pnas.org?cgi?doi?10.1073?pnas.0505191102Kaufman et al.
The shallow clouds also form closer to the African coast in
smoke-laden conditions. Can the observed changes in the cloud
cover be associated with aerosol effects?
Cause and Effect
In Fig. 2 and Table 1 we show the relationship between shallow
cloud cover and the presence of aerosols in all four geographical
zones analyzed separately for each of the 3 months of this study.
Cloud resolving models predict an increase in stratiform cloud
cover with an increase in the aerosol concentration (32). How-
ever, cloud properties also change because of variation in
large-scale atmospheric circulation that may also affect aerosol
concentrations. For example, regions of low atmospheric pres-
sures are convergence zones that tend to accumulate aerosol and
water vapor and generate conditions favorable for cloud forma-
To untangle the effect of aerosol and large-scale meteorology
on cloud properties, we use linear multiple regression. Note that
the aerosol indirect effect cannot be untangled with high degree
of confidence until regional models can predict cloud evolution
with high precision. Here we are mainly trying to eliminate the
influence of large-scale meteorological parameters that can
impact simultaneously both aerosol concentration and cloud
development, generating false correlation between them. The
regression analyzes the dependence of the measured cloud
properties (cover, droplet effective radius, and optical thickness)
on (i) MODIS measurements: aerosol optical thickness (AOT)
and total precipitable water vapor (indicator of convergence);
and (ii) National Center for Environmental Prediction (NCEP)-
generated meteorological fields that include air temperature at
1,000 hPa, temperature difference of 850 and 1,000 hPa and
750–1,000 hPa, winds at three altitudes (1,000, 750, and 500
hPa), broad-scale vertical motion at 850 and 500 hPa based on
the continuity equation, sea surface temperature, equivalent
potential temperature difference between 500 and 950 hPa (34),
and low static stability, (1??e)(d?e?dz), where the differential is
defined as a finite difference between 850 and 950 hPa. The
logarithm of the AOT is used to reduce nonlinearity in the
regression. Logarithmic dependence is expected from cloud
condensation theory (35), and it was found to be appropriate
here. Nonlinearity in the relationships among the parameters
is used to address the following questions:
Y What is the sensitivity of the cloud cover to independent varia-
tions in meteorological and aerosol parameters? We find (Table
2) that cloud cover is affected mainly by air temperature at
1,000 hPa, temperature difference 1,000–750 hPa, the AOT,
sea surface temperature, and the winds. The influence of
aerosol is similar to the influence of these meteorological
parameters. This influence of meteorological parameters on
MODIS clouds, as expected, shows that the National Center
for Environmental Prediction data are relevant to assess
simultaneous effects of synoptic meteorological variables on
clouds and aerosol.
Y Can changes in the meteorological parameters increase the cloud
cover while increasing the aerosol concentration? We check the
systematic change of the meteorological parameters from
clean to hazy conditions. The main systematic residual is in the
(Upper) and southern tropical Atlantic with smoke intrusion (Lower). The results are shown for four ranges of the aerosol optical thickness (AOT). The dots are
average of 50–200 1° ? 1° grid boxes located in similar longitude location and for the same AOT range.
Longitudinal dependence of the shallow cloud fraction (Left) and droplet effective radius (Right) for the northern tropical Atlantic with dust intrusions
Kaufman et al. PNAS ?
August 9, 2005 ?
vol. 102 ?
no. 32 ?
dust region (Table 2) by the air temperature difference
1,000–750 hPa and the strength of the Easterly winds at 750
hPa. As a result, the multiple regression suggests that 70% of
the change in the cloud cover between clean and dusty
conditions is due to the actual dust influence. In the other
regions the change in the cloud cover from clean to hazy
conditions is similar to the change associated with aerosol (see
The associated error in the net aerosol effect within the 95th
percentile confidence level, based on the multiple regression, is
4–8% of the effects mentioned. Errors in the meteorological
parameters or nonlinearity in the effects could shift some of the
dependencies of the cloud cover to aerosol; however, from the
Here we compute the radiative impact resulting from the aerosol
enhancement of cloud cover, and we compare it with the aerosol
indirect radiative effects due to the increase in cloud droplet
concentration and LWP. Note that cloud droplet concentration
is proportional to (5) Reff?1/3for fixed LWP. Results are sum-
marized in Table 1. The calculations are done in several sequen-
tial steps: Preparatory stage. The cloud droplet density, LWP, and
the cover are all scaled to the baseline clean conditions (36) of
AOT ? 0.06 from the actual AOT in each grid box of 1° ? 1°.
The scaling uses the multiple regression-derived dependences of
these cloud properties on the AOT. Then, using the M.-D. Chou
radiative transfer model (37), we calculate the reflected sunlight
at the top of the atmosphere for the clean conditions. Step 1. For
each grid box of 1° ? 1°, we replace Reffand the cloud droplet
density from their values for the clean conditions to the actual
values, and compute the change in the reflected sunlight (col-
umn ?Ncin Table 1). Step 2. We replace the clean condition
LWP with the actual value (column ?Nc? ?LWP in Table 1).
Step 3. We replace the cloud cover with the actual value (column
?Nc? ?LWP ? ?cl in Table 1). Step 4. We add the direct aerosol
effect, assuming that most of the aerosol is above the shallow
clouds, because both the dust and the smoke are observed to be
at 3-km altitude in this period of the year (1–3). The aerosol
properties were taken from the aerosol climatology of Dubovik
et al. (4). The aerosol effect for the entire study area is shown in
The results in Table 1 show that the effect of the aerosol-
induced change in the cloud cover generates a radiative effect of
?3 to ?8 W?m2, or 3–8 times larger than the effect of aerosol-
induced changes in the droplet concentration and LWP. The
results are comparable to the radiative effects over the Medi-
terranean Sea derived from field experiment data of ?7 W?m2
at the top of the atmosphere (11). Including aerosol direct effect
on solar radiation, the total aerosol radiative effect in the North
Atlantic is ?8 to ?14 W?m2. This strong radiative effect is not
counteracted by the thermal radiative effect due to the low
altitude of the clouds. The thermal effect is ?0.2 W?m2.
Table 2. Multiple regression analysis of the influence of meteorological parameters and dust
optical thickness on the cloud fraction analyzed in the 5°N–30°N region of the Atlantic Ocean
to cloud fraction
Change in cloud
fraction clean to hazy
Temperature at 1,000 hPa
Temperature difference, 1,000–750 hPa
Sea surface temperature
Northern wind at 1,000 hPa
Temperature difference, 1,000–850 hPa
Difference in potential temperature at 500–950 hPa
Low static stability at 850 and 950 hPa
Eastern wind at 1,000 hPa
Northern wind at 750 hPa
Eastern wind at 750 hPa
Total column precipitable water vapor
Absolute vorticity at 1,000 hPa
Eastern wind at 500 hPa
?0.32 ? 0.09
?0.31 ? 0.27
0.29 ? 0.14
?0.28 ? 0.09
?0.28 ? 0.26
?0.21 ? 0.15
0.19 ? 0.07
?0.17 ? 0.05
?0.10 ? 0.08
?0.09 ? 0.11
?0.08 ? 0.07
?0.05 ? 0.08
0.04 ? 0.06
?0.02 ? 0.05
?0.04 ? 0.08
0.05 ? 0.07
0.25 ? 0.03
0.00 ? 0.03
0.01 ? 0.01
?0.01 ? 0.01
0.01 ? 0.01
?0.01 ? 0.02
0.00 ? 0.01
0.00 ? 0.00
0.06 ? 0.02
0.01 ? 0.01
0.00 ? 0.00
?0.01 ? 0.03
The analysis was carried for 3 months independently, June through August, and the table shows the average
and variability among the 3 months. The parameters influencing the cloud fraction are ordered by order of
importance based on the correlation with the cloud cover (second column). The next two columns give the
correlation of the parameter with the AOT and the change in the cloud fraction associated by the multiple
Note that while the AOT is one among seven parameters affecting the cloud fraction, it is by factor five the
dominant parameter affecting the change in the cloud fraction from clean (AOT ? 0.03) to hazy (AOT ? 0.40)
conditions. In the smoke, pollution, or marine regions the aerosol effects were even stronger. The main
meteorological parameters that affected the difference in the cloud cover from clean to hazy conditions are the
speed at 750 hPa.
combined effect on cloud cover and microphysics and on reflection of solar
radiation. The radiative effect is calculated as the difference of MODIS obser-
The results are weighted by the frequency of detection of shallow clouds in
the 1° latitude ? longitude daily grid boxes. The color bar shows the values
The aerosol reflected solar flux at the top of the atmosphere due to
www.pnas.org?cgi?doi?10.1073?pnas.0505191102 Kaufman et al.
The satellite measurements are performed at 10:30 a.m. ? 30
min, local time. However the diurnal cycle of the shallow clouds in
this region was shown to be of amplitude of 0.03 in cloud fraction,
corresponding to an error in the diurnal average (38) of 7%.
The radiative effect at the surface due to the aerosol and
aerosol–cloud interaction is a combination of the radiative effect
at the top of the atmosphere ? absorption by the aerosol. We
estimate the aerosol absorption by using the aerosol climatology
of Dubovik et al. (4). The results, shown in Table 1, indicate that
the surface radiative effect is ?9 to ?14 W?m2.
Note that these large radiative effects are found for the season
with highest aerosol loading at this region. Myhre et al. (G.
Myhre, F. Stordall, M. Johnsrud, Y.J.K., D.R., T. K. Bernsten,
T. F. Berglen, A. M. Fjærå, and I. S. A. Isaksen, unpublished
a global aerosol indirect forcing of ?1.8 W?m2through similar
Understanding the Processes
The satellite analysis shows that in all four geographical zones of
the Atlantic Ocean, and independently for the 3 months, each
with different aerosol properties and meteorology, aerosols
systematically increase the shallow cloud cover. In the marine
aerosol zone, in the very clean conditions, clouds have difficul-
ties forming. Cloud-resolving models that simulate (32) this
condition show an increase in stratiform cloud cover with the
increase of aerosol concentration. Aerosols supply the conden-
sation nuclei needed to form cloud droplets. Further increases in
aerosol concentrations reduce the size of the droplets and delay
or inhibit the formation of precipitation, increasing the cloud
cover in the process.
In the smoke-covered zone, the processes are more complex.
Further south, Haywood et al. (1) observed that the stratiform
clouds are detached from the overlaying smoke layer, with a
vertical separation of a few hundred meters. A recent modeling
study (18) showed that under such conditions the absorption of
sunlight by the smoke alone can influence the underlying
stratiform clouds even without physical interaction. Solar radi-
ation heats the smoke layer, increasing the strength of the
inversion that prevents entrainment of dry air into the stratus
clouds below, and thus increases the moisture and the cloud
liquid water content in the stratus deck. However, not all of the
clouds in this latitude zone are shallow stratiform clouds. Some
are trade cumulus clouds that penetrate the smoke layer at 800
hPa. Probably we observe a combination of the increase in cloud
cover predicted by Johnson et al. (18) and microphysical effects
in the trade cumulus as indicated by the strong reduction of the
droplet effective radius. Note that we measure the total aerosol
column and correlate it with the presence of low shallow clouds.
Therefore we can see correlation both in the case of aerosol
modifying the cloud microphysics and in the case of aerosol
affecting the clouds through modifying the radiation field.
Ackerman et al. (40) showed that the inhibition of precipita-
tion is expected to increase entrainment of air from above the
clouds. If the air above the cloud is dry the entrainment may
reduce the cloud water content. However over the Atlantic
Ocean the humid conditions are expected to increase the cloud
liquid water content (40), in agreement with our findings.
The satellite analysis of the AOT was evaluated against inde-
pendent ground-based measurements of the Aerosol Robotic
Network (AERONET) sun photometers (41) for ?30 stations
on islands and coastlines around the world (42). This validation,
using 2,000 points, shows that the standard error in the satellite
The MODIS aerosol cloud screening over the oceans is based on
rigorous spatial variability of the reflectances at 0.86 and 1.38
?m (cirrus channel) (43). Can residual cloud contamination still
affect the data significantly?
We performed two studies to answer the question (44). In the
first we calculated the change in the average aerosol fine fraction
(fraction of the optical thickness contributed by fine aerosols)
between clear and hazy conditions. Cloud contamination, with
its flat spectrum, would have been interpreted by the inversion
as coarse aerosols. For smoke or dust the fine fraction increases
with the transition from clear oceanic air to high dust or smoke
concentrations, contrary to what can be expected because of
cloud contamination. For the pollution zone, the fine fraction
increases with ? until ? ? 0.3, and it decreases for higher ?.
In the second study we check whether the AERONET vali-
dation with the low bias of ?? ? 0.008, mentioned above, could
have missed cases with cloud contamination or cloud illumina-
tion of the aerosol path. In the validation a point is selected if
there are at least 2 AERONET measurements during 1 hr
around the satellite overpass time and at least 5 ocean measure-
ments of 25 possible in a 50-km zone around the AERONET
station. Does this sampling bias the validation to clear skies? We
simulated 900 AERONET validations for different cloud con-
ditions to find out. The simulation shows that for an average
cloud fraction of 50%, the selected validation data set has an
average cloud fraction of only 27%. Therefore, the true cloud
contamination and illumination should be roughly twice the
contamination observed in the validation data set, or on average
doubling the bias to ?? ? 0.016.
We also studied to what degree cloud detection can be
affected by the presence of aerosol. We found it to be indepen-
dent of the presence of aerosols (45) for aerosol optical thickness
? ? 0.5. For ? ? 0.6, the aerosol fields affected the cloud
The methodology to derive the cloud droplet effective radius
and optical thickness is based on calculations for spatially
homogeneous and smooth clouds (30, 31). In reality the cloud
bumpiness and inhomogeneities result in overestimation of the
effective droplet radius and underestimation of the cloud’s
optical thickness (46). However, these effects do not depend
significantly on the presence of aerosol. Therefore the MODIS
retrievals are adequate for studying the correlations between
changes in the cloud cover, droplet size, and cloud optical
thickness and changes in the surrounding aerosol concentration.
properties from the satellite observations. Haywood et al. (1, 2)
evaluated the cloud retrievals in the presence of African dust and
smoke aerosol. They found that the MODIS droplet effective
radius (using the 0.86- and the 2.1-?m channels) is not affected
by overlying aerosol. We expect the cloud optical thicknesses to
be accurately derived (within 10%) in the presence of dust,
because dust does not absorb sunlight at 0.86 ?m. However
smoke can reduce the observed cloud optical thickness by
The point here is to acknowledge several sources of uncer-
tainty in deriving both aerosol and cloud parameters from
satellites. However, none of these sources of error can explain
the systematically significant relationships we find between
aerosol optical thickness and cloud fraction.
Discussion and Conclusions
Three months of daily observations of clouds and aerosol over
the Atlantic Ocean show independently that for each month and
for each of the four regions, each dominated by a different
aerosol type, aerosols have a large effect on the coverage and
properties of shallow clouds. The shallow cloud cover increases
systematically by 0.20–0.40 with increases in the aerosol column
concentration, which is represented by increase in the optical
thickness from 0.03 to 0.5. This increase in cloud cover also
extends the coverage of shallow clouds thousands of kilometers
Kaufman et al. PNAS ?
August 9, 2005 ?
vol. 102 ?
no. 32 ?
west in the smoke- and dust-dominated regions. The changes are
accompanied by reduction in cloud droplet size by 10–30%. In
most of the regions (all but the smoke region) the liquid water
content increases as well. All these observations are in agree-
ment with the suggestion that inhibition of precipitation by
and properties of Atlantic shallow clouds. Multiple regression
analysis associated most of the increase in the cloud cover with
increase in the presence of aerosol and only a small part with
changing large-scale meteorological conditions. However, the
large-scale and linear nature of the multiple regression analysis
leaves uncertainties in the cause and effect that can be resolved
with further development of regional cloud-resolving models.
The 95th percentile confidence limit on the aerosol effect on
cloud fraction is only 4–8% lower than the stated values.
The systematic influence of high aerosol concentrations on
clouds generates large radiative effects over the Atlantic Ocean
that may regionally counteract the greenhouse warming. Here
we can expect that the nonmarine aerosols have doubled in the
last 50–100 years, because of expansion of population and
economic activity by factor of 3, and a doubling in Saharan dust
production (47). The smoke and pollution effect on cloud cover
generates a radiative forcing at the top of atmosphere that is
about half of today’s aerosol effect or ?6 W?m2, and reduction
of sunlight available for evaporation from the ocean by 7 W?m2,
thus dominating climate change in this region. This finding is in
line with the observation of a global dimming of sunlight at the
surface over the land in the last 50 years (48) of 10–20 W?m2,
taking into account the higher aerosol concentrations over the
show that the dimming effect reversed in the mid-1980s and a
brightening resumed (39, 50). This reversal is also associated
with similar reversal in cloud-free transmission of sunlight in
Europe and Japan, which is a measure of the aerosol optical
thickness. A rough estimate based on figure S4 of Wild et al. (39)
gives an increase until the mid-1980s and a decrease until 2000
of AOT of 0.01–0.02 per decade, respectively. Scaling the
radiative effects in Table 1 to these changes in AOT gives
radiative effects of 2–3 W?m2, in agreement with the measure-
ments (39, 48–50). This agreement suggests that the aerosol
indirect effect, and in particular the increase of cloud cover, can
serve as a possible explanation for the observed changes in
The forcing observed by aerosol-induced increase in cloud
coverage exceeds that due to aerosol-induced changes in cloud
drop concentrations alone by a factor of 3–5. These findings
clearly demonstrate that traditional estimates of aerosol-cloud
forcing, which focused on cloud top brightness, may be inade-
quate and severely underestimate the aerosol climatic effects.
The aerosol inhibition of precipitation derived indirectly in
this study, and the drastic influence, in particular of smoke and
dust on the shallow stratiform and trade cumulus clouds, spatial
cover, and radiative forcing, leave open the question to what
extent these aerosols control the circulation and climate of the
We thank Bruce Wielicki for valuable comments that brought significant
improvements in the manuscript. This work was supported by the
National Aeronautics and Space Administration, the Israeli Space
Agency, and the Israel Science Foundation.
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