Observations addressing effects of aerosol particles on summertime
Arctic clouds are limited. An airborne study, carried out during July 2014
from Resolute Bay, Nunavut, Canada, as part of the Canadian NETCARE project,
provides a comprehensive in situ look into some effects of aerosol particles
on liquid clouds in the clean environment of the Arctic summer. Median cloud
droplet number concentrations (CDNC) from 62 cloud samples are 10 cm
Mass concentrations of the atmospheric aerosol in the Arctic are higher during winter than in summer due to differences in transport of anthropogenic particles and wet scavenging (e.g. Barrie, 1986; Stohl, 2006). Atmospheric chemistry and aerosol cloud Arctic research has largely focussed on the springtime. The winter-to-summer transition offers the opportunity to examine changes in chemistry as the sun rises over the polluted polar atmosphere (e.g. Barrie et al., 1988) and to study impacts of anthropogenic aerosol on the Arctic solar radiation balance (e.g. Law and Stohl, 2007; Quinn et al., 2008). Greater-than-expected warming of the Arctic (e.g. Christensen et al., 2013) and rapidly diminishing Arctic sea ice extent (e.g. Maslanik et al., 2011) have drawn considerable attention to the role of anthropogenic and biomass burning (BB) particles as warming agents for the Arctic (e.g. Law and Stohl, 2007; Quinn et al., 2008; Shindell et al., 2008; Brock et al., 2011; Jacob et al., 2010; UNEP, 2011; Stohl et al., 2013). Recent evidence indicates that the net impact of aerosol particles on the Arctic over the past century has been one of cooling rather than warming (Najafi et al., 2015).
Low-level liquid water clouds are frequent in the sunlit Arctic summer (e.g.
Intrieri et al., 2001), and these clouds can have a net cooling effect (e.g.
Brenner et al., 2001; Garret et al., 2004; Lubin and Vogelmann, 2010; Zhao
and Garrett, 2015; Zamora et al., 2016). Knowledge of the influence of the
atmospheric aerosol on climatic aspects of these clouds is complicated by
the relatively large potential differences in the albedo of the underlying
surface (e.g. Herman, 1977; Lubin and Vogelmann, 2010) and the fact that the
Arctic is relatively free of anthropogenic influence in summer, which means
that particles from natural sources can be the most significant nuclei for
cloud droplets. Those sources shift the number distribution toward particles
smaller than 100 nm (e.g. Heintzenberg and Leck, 1994; Ström et al.,
2003; Heintzenberg et al., 2006; Engvall et al., 2008; Tunved et al., 2013;
Leaitch et al., 2013; Heintzenberg et al., 2015). Particles smaller than 100 nm are often dismissed as being too small to nucleate cloud droplets due to
the assumption that the cooling mechanisms are too slow to generate the
supersaturation (
Effects of pollution on clouds may also lead to warming, but a reference to
clean clouds is still required (e.g. Garrett et al., 2009). Mauritsen et al. (2011) modelled cloud radiative forcing for low clouds using CCN number
concentrations derived from shipborne observations over the Arctic Ocean
(Tjernström et al., 2004, 2014). They found the
impact from changes in CCN for ultra-low values (< 10 cm
Past studies of Arctic aerosols and clouds have emphasized the areas of the
Beaufort and Chukchi seas (e.g. Hobbs and Rango, 1998; Curry, 2001,
and references therein; Lohmann et al., 2001; Yum and Hudson, 2001; Peng et
al., 2002; Wylie and Hudson, 2002; Earle et al., 2011; Lance et al., 2011;
Jouan et al., 2014; Klingebiel et al., 2015). Most of those studies have
focused on springtime when the aerosol can be influenced by anthropogenic or
BB sources. As well, there has been considerable interest in
mixed-phase clouds in the lower Arctic troposphere (e.g. Shupe et al., 2004;
Sandvik et al., 2007; Morrison et al., 2012), but a notable lack of in situ
aerosol observations in combination with liquid water clouds over the
summertime Arctic. Among the studies that have considered in situ aerosol
measurements and summertime Arctic clouds, Zamora et al. (2016) examined the
efficiency of BB plumes on indirect forcing. They
estimated half of the possible maximum forcing from these plumes, mostly due
to the reduction in cloud-base
Motivated by limited knowledge of aerosol effects on summertime Arctic
clouds and particle activation details, the Canadian Network on Climate and
Aerosols: Addressing Key Uncertainties in Remote Canadian Environments
(NETCARE – Given the scarcity of data, what are the characteristics of clouds in the
summertime Arctic, and do clouds near the surface have characteristics
different from those aloft? (Sect. 3.2) What are the sizes of particles that act as nuclei for cloud droplets? Will this allow a closer connection between aerosol processes, particle sizes and
climate effects? (Sect. 3.3) What is the relationship between droplet size and droplet number? In
particular, what is the aerosol influence on cloud below the
Mauritsen limit, and is it possible to assess a background influence of the
aerosol on clouds in the Arctic summer? (Sect. 3.4)
The instrument platform was the Alfred Wegener Institute (AWI) Polar 6 aircraft, a DC-3 aircraft converted to a Basler BT-67 (see Herber et al., 2008).
The following measurements are relevant to this discussion:
Particle number concentrations > 5 nm diameter were measured with
a TSI 3787 water-based ultrafine condensation particle counter (UCPC),
sampling at a flow rate of 0.6 L min Aerosol particle size distributions from 20 to 100 nm (45 s up scans and
15 s down scans) were measured using a Brechtel Manufacturing Incorporated
(BMI) scanning mobility system (SMS) coupled with a TSI 3010 condensation
particle counter (CPC). The sheath and sample flows were set to 6 and 1 L min Aerosol particle size distributions from 70 nm to 1 CCNC (0.6 %) were measured using a DMT CCN model 100 counter operating
behind a DMT low-pressure inlet at approximately 650 hPa. For the nominal
water Droplet size distributions from 2 to 45 Two-dimensional cloud particle images from about 50 to 800 Carbon monoxide (CO) is used here as a relative indicator of aerosol
influenced by pollution sources and as a potential tracer for aerosol
particles entering cloud. CO was measured with an Aerolaser ultra-fast
CO monitor model AL 5002 based on vacuum ultraviolet fluorimetry, employing
the excitation of CO at 150 nm. This instrument was modified such that
in situ calibrations could be conducted in flight.
Details of the instrument calibration and evaluations are given in the
Supplement (Sect. S1).
State parameters and meteorological measurements were made with an AIMMS-20,
manufactured by Aventech Research Inc. This instrument consists of three
modules: (1) an air data probe that measures the three-dimensional
aircraft-relative flow vector (true air speed, angle-of-attack and
sideslip), temperature, and relative humidity and includes a three-axis
accelerometer pack for turbulence measurement; (2) an inertial measurement
unit that consists of three gyros and three accelerometers providing the
aircraft angular rate and acceleration; (3) a global positioning system for
aircraft 3-D position and inertial velocity. Horizontal and vertical wind
speeds were measured with accuracies of 0.50 and 0.75 m s
Summary of averaged cloud observations with
LWC > 0.01 g m
Aerosol particles were sampled through a shrouded inlet diffuser (diameter
0.35 cm at intake point), which is the same inlet discussed by Leaitch et al. (2010). For the airspeeds during this study, particle transmission by
the inlet is near unity for particles from 20 nm to < 1
CO was sampled through a separate inlet consisting of a 0.40 cm OD Teflon
tube using aircraft forward motion to push air into the line in combination
with a rear-facing 0.95 cm OD Teflon exhaust line that reduced the line
pressure. The continuously measured sample flow was approximately 12 L min
Compilation of the flight tracks. All flights originated from
Resolute Bay (74
Eleven research flights were conducted from Resolute Bay, Nunavut
(74
A summary of all flight tracks is shown in Fig. 1. Flights mostly consisted
of vertical profiles and low-level transits over ice, water and melt ponds
that contributed to the formation of low cloud; low cloud is defined
here as cloud tops below 200 m m.s.l. Higher-level cloud was also sampled
during the profiles and transits. The polynyas that were sampled are
shown in the top centre of each panel of Fig. 2. Cloud was sampled on 8
of the 11 flights, more frequently during period 1 because of overall better
visual contrast between clouds and surfaces. Furthermore, period 2 was
marked by the presence of the Canadian Coast Guard Ship
Satellite images from 5 July when LA clouds were sampled over the
two polynyas to the north and from 8 July when LA clouds were sampled along
Lancaster Sound. Lancaster Sound is cloud free on 5 July and mostly
covered by cloud on 8 July. Resolute Bay is marked with a “X”. Images are
courtesy of NASA Worldview:
Four examples of profiles through higher-altitude clouds.
All aerosol number concentrations are given in terms of standard atmospheric
pressure and temperature (STP: 1 atm and 15
Clouds were sampled during a flight whenever possible, mostly by ascending
or descending through them. It was not possible to sample below the
low-altitude (LA) cloud bases. Most clouds were liquid phase, based on the
2D-C grey images of cloud particles > 50
The pre-cloud aerosol for the HA clouds is mostly derived from averages of values collected within about 50 m of cloud base when a cloud base was visible and achievable. In some cases, as discussed in Sects. 2.4.1 and 2.4.2, the pre-cloud aerosol concentrations include contributions from above cloud (19 July) or are from similar or lower altitudes in the clear air upwind of the cloud. For the aerosol measurements made with the 1 min averaged number concentrations from the SMS, values from further below cloud are necessary in some cases. These values are, however, consistent with the 1 s aerosol measurements closer to cloud base.
Every possible liquid cloud was sampled along a flight path, and some cloud
layers were sampled more than once. That will bias the sample numbers to
clouds of greater spatial extent. However, that bias is appropriate from a
climate perspective since cloud extent is a major factor for the impacts of
clouds on climate. A total of 62 liquid water cloud samples, or averages of
individual cloud penetrations, were averaged with the constraint that the
mean LWC is > 0.01 g m
In Sects. 2.4.1 and 2.4.2, a range of detailed examples are used to show how the aerosol observations relate to the cloud observations for the HA cloud (clouds based above 200 m) and LA cloud (clouds topped below 200 m), to (1) demonstrate how the pre-cloud aerosol concentrations were assessed for the 62 samples and to (2) note where effects of entrainment may be a factor and how multiple cloud layers are considered. At 200 m or below, the LA clouds were in the boundary layer, in flight indistinguishable from the surface (i.e. some were possibly fog). Thus, sampling below such clouds was not possible due to proximity to the surface. Besides cloud microphysics, the only in-cloud measurements considered valid are the CO and thermodynamics. For completeness, the aerosol measurements within cloud are included in the plots associated with Sects. 2.4.1 and 2.4.2, but such measurements, including the CCN, are unreliable due to issues of drying and partial drying associated with the inlet and a particular instrument as well as droplet shattering on the inlet (e.g. Hudson and Frisbie, 1991, and Hallett and Christensen, 1984). The in-cloud aerosol measurements are not part of the subsequent analysis.
Four examples of profiles through HA clouds are shown in Fig. 3. There are
two panels for each profile: the left-hand panel shows CO, CDNC and particle
number concentrations (N5, Nx-100, N100, CCNC (0.6 %)); the right-hand
panel shows temperature, equivalent potential temperature (
One of several similar profiles
through a stratocumulus layer during the transits to and from the
polynyas north of Resolute Bay. The CDNC (at STP) are relatively constant
with altitude while LWC and VMD both increase steadily with altitude. These
features characterize cloud formation by lifting of air, and they indicate
that
the cloud droplets were nucleated on particles from below cloud base. The
cloud top is relatively sharply capped by a temperature inversion of about
2
The maximum and mean CDNC (STP) of
about 75 and 55 cm
The July 19 profile includes two
cloud layers, one from 1200 to 1400 m and a second from 1400 to 1500 m. The layer
separation appears in the CO concentrations, which are approximately uniform
through the lower layer and increasing in the upper layer. The CO levels of
100
Time series during the sampling of low-altitude (LA) cloud or fog over the
polynyas north of Resolute Bay.
This is a more complex cloud
with substantial LWC variations that suggest three cloud layers. The values
of mean CDNC at STP are 45, 49 and 65 cm
Time series of altitude, CO, N80-100, N90-100, N100, CCNC (0.6 %) and CDNC from low-altitude (LA) cloud sampling over Lancaster Sound on 8 July. The cloud was deeper over the open water of the Sound (see satellite picture in Fig. 2b). Over the ice to the west, the cloud was not as deep and could not be sampled. Segments over water and ice are indicated at the top of the figure.
Profiles down into cloud showing
The two examples in Fig. 4 are for
cloud or fog over the polynyas north of Resolute Bay on 5 and 7 July. Four
cloud samples were collected on 5 July at altitudes below 200 m. The time
series in Fig. 4a covers the period of collection of the two lowest samples:
16:18:02–16:21:57 UT at 130 m and 16:39:35–16:40:18 UT at 88 m. In the air upwind
of the cloud or fog, the N100, N30 and CCNC (0.6 %) are estimated at 3, 10–14 and 5 cm
Figure 5 shows a time series of altitude, CO, N100,
N80-100, N90-100, CCNC (0.6 %) and CDNC from the sampling above and in the
low cloud over Lancaster Sound on 8 July. The cloud over the open water of
the Sound is visible in the satellite picture in Fig. 2b. Cloud was also
present over the ice to the west, but it was much thinner and reached only
to about 150 m above the surface. Over the water, the cloud was sampled as
high as 230 m by descending into it down to about 150 m between 17:27 and
17:43 UT as shown in Fig. 5. Observations in profiles from two of five
samples are shown in Fig. 6. This cloud deepened as the aircraft approached
the ice edge from over the water and thinned abruptly over the ice with
tops below 150 m, as shown in Fig. 5 (time 17:47 UT). The thicker cloud was
associated with a shift in wind direction to more southerly suggesting an
influence of the Prince Regent Inlet and surrounding terrain on the flow as
well as possibly circulations influenced by the water–ice transition. The
cloud layer was relatively stable and the
Summary statistics for the cloud and aerosol samples are discussed in Sect. 3.1, the microphysics of low-altitude and higher-altitude clouds are contrasted in Sect. 3.2, particle activation is summarized in Sect. 3.3 and in Sect. 3.4 the relationship between VMD and CDNC is used to consider the transition of aerosol indirect effects from potential warming to potential cooling. All analyses are based on the 62 cloud samples discussed in Sect. 2.4. The LA cloud subset is comprised of 24 samples and the HA cloud subset consists of 38 samples.
Summary of averaged observations for low-altitude (LA) and higher-altitude (HA) clouds. Values without parentheses are referenced to ambient volumes and values in parentheses are referenced to STP. 5 and 95 are the 5th and 95th percentiles.
The mean and median values of the microphysical properties of the cloud and pre-cloud aerosols as well as the altitudes and temperatures derived from the 62 cloud samples are given in Table 1, separated between periods 1 and 2. Values of the CDNC and the LWC are given relative to in situ volumes as well as STP. As discussed above, the pre-cloud CCNC (0.6 %), N50 and N100 are averages of those values collected within about 50 m of cloud base where a cloud base was clear and achievable. In other cases the pre-cloud CCNC (0.6 %), N50 and N100 are the values at the similar or lower altitudes in the clear air upwind of the cloud, except in the case of 8 July when the pre-cloud aerosol is based on the measurements in the area downwind plus those immediately above cloud. The CCNC (0.6 %) samples in Table 1 are limited to 44 due to instrument problems, all of which occurred during the early part of 7 July.
Cloud liquid water paths (LWPs) are estimated for 36 of the samples when a complete profile between cloud base and cloud top was possible. The LWPs are shown at the bottom of Table 1. Of the 36 LWP estimates, 34 are above 200 m, and the mean and median altitudes are 1044 and 862 m, respectively. Not included in the summary statistics are the samples from 8 July shown in Figs. 5 and 6. For the minimum altitude reached in that cloud, the LWP ranged from 12 to 25 and thus the total LWP for that cloud exceeded 25.
During period 1, the median sampling altitude is lower and the temperatures are slightly below freezing compared with just above freezing during period 2. The CO mixing ratios are overall low and at approximately background values during period 1. The median CDNC are higher during period 1 than period 2, but the mean values are similar. The CDNC compare more closely with the N50 during period 1, while during period 2 the CDNC are about equally between the N50 and N100. The CCNC (0.6 %) equated with particles between 50 and 100 nm during period 1, whereas during period 2 they were closer to the N100 values. The reduction in particle hygroscopicity during period 2 may be due to an increased presence of organics in the aerosol during that time (Willis et al., 2016).
The LWC plotted as a function of the CDNC
The LA clouds were close to the surface, and all were associated with open water;
some or all may be technically fogs. They may be formed by advection of
warmer moist air over a cooler surface (the 8 July LA cloud that moved from
Baffin Bay westward along Lancaster Sound was likely dominated by that
process), by radiation cooling or by the passage of very cold air over a
warm moist surface. The latter, also known as sea smoke, is the likely
explanation for the clouds over the polynyas; also, it is possible that
there was an advection component associated with the sea smoke moving from
the polynyas over the ice surfaces. In general, the LA clouds are associated
with low-level horizontal advection and heat and water exchange with the
underlying ice or water surface. In contrast, vertical motions are
responsible for some of the HA clouds, and none of the HA clouds interact so
closely with the underlying surface. Due to those differences, the
characteristics of the LA and HA clouds are considered separately. Table 2
shows the mean and median values for the samples separated between LA and HA
clouds; vertical profiles of CDNC, LWC and VMD samples are shown in
Fig. S7. On average, the LA samples have lower CDNC and higher
VMD compared with the HA cases, and the LA clouds are activating on larger
particles relative to the HA clouds (e.g. CDNC/N50). The values of the
CDNC/CCNC (0.6 %) indicate that the
As in Fig. 7a, but identifying the specific LA cases of 5, 7,
8 and 17 July. Linear regressions for each set of samples are also plotted, and
the coefficients of determination are given in the legends. The slopes are
significant at a 95 % confidence level within
Variations in LWC are correlated with those of CDNC for the LA samples (Fig. 7a). The coefficient of determination (
The LWC–CDNC correlation is identifiable for individual flights with
sufficient LA samples: four flights, comprising 20 of the 24 LA samples, had
three or more points as shown in Fig. 8. The regressions for each of the
7, 8 and 17 July cases are approximately linear, and the respective mean
VMDs
are 20.8, 18.8 and 18.2
Plots of CDNC vs.
Here, the sizes and CCN activity of particles that acted as nuclei for cloud
droplets are examined. The CDNC are plotted vs. N100 in Fig. 9a,
separated between LA and HA samples. The CDNC are most often higher than the
N100 and more so for the HA samples, which indicates that particles smaller
than 100 nm activated in most cases and most often in the HA clouds. The
mean and median values of CDNC(STP)/N100 are 2.2 and 1.8 for all 62 samples,
and the 30th percentile of the CDNC/N100 is 1.2, which means that in
about 70 % of the cases droplets nucleated on particles significantly
smaller than 100 nm. Figure 9a can be compared with the results of Hegg et al. (2012), who showed a linear fit of CDNC to N100 for marine stratocumulus with
a slope of 0.72 for which the N100 in 94 % of the samples was > 150 cm
The mean and median values of the CCNC (0.6 %) associated with all cloud
samples (84 and 47 cm
Variations in the measured CCNC (0.6 %) are explained well by variations in
smaller (N50) and larger (N100) particles as shown in Fig. 10b. The slopes
of the power-law fits, for which the exponents are both close to unity,
indicate that the CCNC (0.6 %) at 0.6 %
The relationship between the VMD and CDNC shown in Fig. 11 exhibits a
scattered but clear tendency for smaller VMD with increasing CDNC. The solid
black curve is a reference line based on the study-mean LWC of 0.12 g m
The aerosol influence on clouds with CDNC below the Mauritsen limit is considered in Sect. 3.5 In Sect. 3.5, the potential background influence of the aerosol on clouds with CDNC above the Mauritsen limit is examined.
Seventeen of the 62 samples fall at or below our best estimate of the
Mauritsen limit. Fifteen of those 17 samples are from LA clouds with median
pre-cloud N50 and N100 estimates of 8.2 and 3.0 cm
The mean VMD of all cloud samples plotted vs. the CDNC. All
CDNC are referenced to the ambient pressure. The dashed vertical green line
represents the “CCN-limited” division discussed by Mauritsen et al. (2011)
and estimated here as 16 cm
The LWCs do not correlate with either the N50 or the N100 (Fig. S8). In this low CDNC environment, where cloud droplets may grow large enough to be gravitationally removed from the cloud without the support of collision–coalescence, the absence of a positive correlation of either the CDNC or LWC with the aerosol indicates that small changes in the aerosol did not contribute significantly to the changes in the LWC. Variations in other processes, such as mixing or the rate of cooling, may be responsible for the correlation of CDNC and LWC. It can be argued that some aerosol must exist for these clouds to form, but these observations show no association of changes in either the CDNC or LWC with changes in the aerosol.
Above the estimated Mauritsen limit, the general reduction in the VMD with
the CCNC-associated (0.6 %) increase in CDNC reflects the impact of
increases in aerosol on clouds. In Fig. 11, samples are identified between
those associated with lower CO (green circles; < 81 ppbv, the median
CO value of all samples) and those with highest CO (red circles;
> 90 ppbv); six samples have no CO measurement and the remaining
points have CO falling within 81–90 ppbv. Five of the seven higher-CO
samples are from the 19 July case (e.g. Fig. 3e, f) that has been linked
with BB (Köllner et al., 2015), and the highest CDNC
point (273 cm
Aerosol particle size distributions, CCNC at 0.6 % water
The median pre-cloud N100 of 33 cm
From the median values of CDNC/CCNC (0.6 %; 1.2 for the HA clouds and 0.6
for the LA clouds) and the linear regression of CDNC and CCNC (0.6 %), it
is inferred that the average
In 17 cases, 15 of which are LA clouds, the CDNC fell at or below the CCN
limit discussed by Mauritsen et al. (2011), which is estimated here as 16 cm
Forty-five cloud samples with CDNC above the Mauritsen limit exhibit a clear
influence of changing aerosol. The cloud microphysics for the clouds formed
in cleaner air (smaller particles and lower CO: < 81 ppbv) overlap
with clouds formed in what was likely more polluted air (larger particles
and higher CO: > 90 ppbv) covering a CDNC range of 16–160 cm
The complete data set is available from the NETCARE web site (
The authors acknowledge a large number of people for their contributions to this work. We thank Kenn Borek Air, in particular Kevin Elke and John Bayes, for their skillful piloting that facilitated these cloud observations. We are grateful to John Ford, David Heath and the U of Toronto machine shop, Jim Hodgson and Lake Central Air Services in Muskoka, Jim Watson (Scale Modelbuilders, Inc.), Julia Binder and Martin Gerhmann (AWI), Mike Harwood and Andrew Elford (EC) for their support of the integration of the instrumentation and aircraft. We thank Mohammed Wasey for his support of the instrumentation during the integration and in the field. We are grateful to Carrie Taylor (EC), Bob Christensen (U of T), Kevin Riehl (Kenn Borek Air), Lukas Kandora, Manuel Sellmann and Jens Herrmann (AWI), Desiree Toom, Sangeeta Sharma, Dan Veber, Andrew Platt, Anne Mari Macdonald, Ralf Staebler and Maurice Watt (EC), Kathy Law and Jennie Thomas (LATMOS) for their support of the study. We thank the biogeochemistry department of MPIC for providing the CO instrument and Dieter Scharffe for his support during the preparation phase of the campaign. We thank the Nunavut Research Institute and the Nunavut Impact Review Board for licensing the study. Logistical support in Resolute Bay was provided by the Polar Continental Shelf Project (PCSP) of Natural Resources Canada under PCSP Field Project no. 218-14, and we are particularly grateful to Tim McCagherty and Jodi MacGregor of the PCSP. Funding for this work was provided by the Natural Sciences and Engineering Research Council of Canada through the NETCARE project of the Climate Change and Atmospheric Research Program, the Alfred Wegener Institute and Environment and Climate Change Canada. Edited by: V.-M. Kerminen Reviewed by: J. Hudson and two anonymous referees