ACPAtmospheric Chemistry and PhysicsACPAtmos. Chem. Phys.1680-7324Copernicus GmbHGöttingen, Germany10.5194/acp-15-3719-2015Observations and comparisons of cloud microphysical properties in spring and summertime Arctic stratocumulus clouds during the ACCACIA
campaignLloydG.gary.lloyd@manchester.ac.ukChoulartonT. W.BowerK. N.https://orcid.org/0000-0002-9802-3264CrosierJ.JonesH.DorseyJ. R.GallagherM. W.https://orcid.org/0000-0002-4968-6088ConnollyP.KirchgaessnerA. C. R.https://orcid.org/0000-0001-7483-3652Lachlan-CopeT.Centre for Atmospheric Science, University of Manchester, Manchester, UKBritish Antarctic Survey, NERC, High Cross, Madingley Rd, Cambridge CB3 0ET, UKG. Lloyd (gary.lloyd@manchester.ac.uk)2April2015157371937371September201419November201425February201511March2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://acp.copernicus.org/articles/15/3719/2015/acp-15-3719-2015.htmlThe full text article is available as a PDF file from https://acp.copernicus.org/articles/15/3719/2015/acp-15-3719-2015.pdf
Measurements from four case studies in spring and summer-time Arctic
stratocumulus clouds during the Aerosol-Cloud Coupling And Climate
Interactions in the Arctic (ACCACIA) campaign are presented. We compare
microphysics observations between cases and with previous measurements made
in the Arctic and Antarctic. During ACCACIA, stratocumulus clouds were
observed to consist of liquid at cloud tops, often at distinct temperature
inversions. The cloud top regions precipitated low concentrations of ice
into the cloud below. During the spring cases median ice number
concentrations (∼ 0.5 L-1) were found to be lower by
about a factor of 5 than observations from the summer campaign
(∼ 3 L-1). Cloud layers in the summer spanned a warmer
temperature regime than in the spring and enhancement of ice concentrations
in these cases was found to be due to secondary ice production through the
Hallett–Mossop (H–M) process. Aerosol concentrations during spring ranged
from ∼ 300–400 cm-3 in one case to lower values of
∼ 50–100 cm-3 in the other. The concentration of aerosol
with sizes Dp > 0.5 µm was used in a primary ice
nucleus (IN) prediction scheme (DeMott et al., 2010). Predicted IN values
varied depending on aerosol measurement periods but were generally greater
than maximum observed median values of ice crystal concentrations in the
spring cases, and less than the observed ice concentrations in the summer
due to the influence of secondary ice production. Comparison with recent
cloud observations in the Antarctic summer (Grosvenor et al., 2012), reveals
lower ice concentrations in Antarctic clouds in comparable seasons. An
enhancement of ice crystal number concentrations (when compared with
predicted IN numbers) was also found in Antarctic stratocumulus clouds
spanning the H–M temperature zone; however, concentrations were
about an order of magnitude lower than those observed in the Arctic summer
cases but were similar to the peak values observed in the colder Arctic
spring cases, where the H–M mechanism did not operate.
Introduction
The Arctic is a region that has experienced rapid climate perturbation in
recent decades, with warming rates there being almost twice the global
average over the past 100 years (ACIA, 2005; IPCC, 2007). The most striking
consequence of this warming has been the decline in the extent and area of
sea ice, especially in the warm season. The lowest sea ice extent and area
on record were both observed on 13 September 2012 (Parkinson and Comiso,
2013) and despite some uncertainty ice-free Arctic summers could become a
reality by 2030 (Overland and Wang, 2013). The underlying warming is very
likely caused by increasing anthropogenic greenhouse gases and Arctic
amplification, which is a well-established feature of global climate models
(GCMs; see for example IPCC 5th Assessment Report, 2014). However, the details of
Arctic climate are complex with interactions between the atmospheric
boundary layer, clouds, overlying sea ice and water leading to a number of
feedback mechanisms. These interactions are not well understood due to
variability in the spatial and temporal extent of feedback mechanisms, and
the fact that those that are included in GCMs may
not be accurately parameterised (Callaghan et al., 2012). Clouds play an
important role in a number of proposed feedback processes that may be active
in the Arctic (Curry et al., 1996; Walsh et al., 2009), Arctic clouds are
the dominant factor controlling the surface energy budget, producing a
mostly positive forcing throughout the year, apart from a brief cooling
period during the middle of summer (Intrieri, 2002). These clouds
affect both the long-wave (year-round) and short-wave (summer-only)
radiation budgets and influence turbulent surface exchange. Cloud
microphysical influence on cloud radiative properties depends on the amount
of condensed water and the size, phase and habit of the cloud particles
(Curry et al., 1996). These factors are controlled in part by the cloud
condensation nuclei (CCN) and ice nuclei (IN) concentrations and properties.
The impact of CCN and IN on cloud properties is significant. A number of
hypothesis explain how variation in the availability of CCN and IN may go on
to alter microphysical structure. Firstly the thermodynamic indirect effect
describes how an increase in CCN leads to a reduction in droplet size,
inhibiting the development of drizzle needed for rime splintering, reducing
the efficiency of the process, which may have a significant impact on cloud
glaciation around -5 ∘C. Secondly the glaciation indirect effect
states that an increase in IN leads to an increase in the number of ice
crystals. Finally the riming indirect effect inhibits ice mass growth as
increasing CCN leads to smaller drops with lower collection efficiencies
that reduces the riming rate (Lohmann and Feichter, 2005).
In relation to these three hypotheses there have been a range of results
presented in the literature in recent years investigating the impact of
aerosol on Arctic clouds. For example, Lance et al. (2011) presented aircraft
data from the Arctic mixed-phase clouds gathered in the Alaska region from
the Aerosol, Radiation, and Cloud Processes affecting Arctic Climate
(ARCPAC) experiment. They reported that the concentration of ice particles
greater than 400 µm is correlated with the concentration of droplets
larger than 30 µm, providing support for the riming indirect effect. They
found that mixed-phase clouds in polluted conditions with a high aerosol
population due to long-range transported biomass burning aerosol contained a
narrower droplet size distribution and 1–2 orders of magnitude fewer
precipitating ice particles than clean clouds at the same temperature.
Although this finding is not consistent with the glaciation indirect it is
likely due to the increase in aerosol not providing active IN in clouds over
the temperature range that was investigated.
Jackson et al. (2012) presented data from the Indirect and Semi-Direct
Aerosol Campaign (ISDAC) and from the Mixed-Phase Arctic Cloud Experiment.
They found no evidence for a riming-indirect effect but did find a
correlation between ice crystal number concentration and above-cloud aerosol
concentration in this case. This finding, together with sub-adiabatic liquid
water contents suggested that ice nuclei were being entrained from above
cloud top in their studies, which is consistent with the glaciation
indirect effect. They also reported lower ice crystal number concentrations
and lower effective radius in more polluted cases compared to data collected
in cleaner single-layer stratocumulus conditions during the Mixed-Phase
Arctic Cloud Experiment (M-PACE) (Verlinde et al., 2007), which is consistent
with the operation of the thermodynamic indirect effect. They concluded that
a wider range of Arctic clouds need to be studied to investigate the
generality of their results.
A paucity of observations in the Arctic means that neither the aerosol
processes, nor cloud properties are well understood or accurately
represented within models, with the result that aerosol and cloud-forcing of
Arctic climate is poorly constrained. An important aspect of modelling
Arctic clouds is the use of primary IN parameterisations to initiate the ice
phase in these clouds. The measurements made in this study of both aerosol
properties and ice number concentrations allowed us to compare predicted ice
nuclei concentrations from the DeMott et al. (2010) IN parameterisation and
cloud ice concentrations measured by microphysics probes.
In the Arctic lower troposphere low cloud dominates the variability in
Arctic cloud cover (Curry et al., 1996), with temperature and humidity
profiles showing a high frequency of one or more temperature inversions
(Kahl, 1990) below which stratocumulus clouds form. During the Arctic
summer, therefore, these low clouds often consist of multiple layers, with a
number of theories describing their vertical separation (Herman and Goody,
1976; Tsay and Jayaweera, 1984; McInnes and Curry, 1995). Such cloud layers
have been observed during different seasons but the relationship between
temperature and the formation of ice in them is not well understood.
Jayaweera and Ohtake (1973) observed very little ice above -20 ∘C,
but Curry et al. (1997) observed ice to be present in clouds at
temperatures (T) between -8 and -14 ∘C
during the Beaufort Arctic Storms Experiment (BASE). It
is possible that the large variation in temperature at which glaciation is
observed is caused by changes in the concentration and composition of
aerosol (Curry, 1995). Recent work, such as in the Arctic Cloud Experiment
(ACE) (Uttal et al., 2002) has improved our knowledge of Arctic mixed-phase
clouds, which dominate in the coldest 9 months of the Arctic year. ACE
reported that clouds were mainly comprised of liquid tops, tended to be very
long lived and continually precipitated ice. The longevity of these clouds
might be considered unusual as the formation of ice leads to loss of water
through the Wegener–Bergeron–Findeison process. More recently, the M-PACE
investigated the Arctic autumn transition season on the north slope of
Alaska, in the area to the east of Barrow. Again, predominantly mixed-phase
clouds were observed with liquid layers present at temperatures as low as
-30 ∘C. Here we present detailed airborne microphysical and
aerosol measurements made in stratocumulus cloud regions in the European
Arctic during the recent Aerosol-Cloud Coupling And Climate Interactions in
the Arctic (ACCACIA) campaigns. We present data from two aircraft during
early spring, in March and April 2013, and from a single aircraft during the
following Arctic summer, in July 2013.
The objectives of this paper are
to report the microphysics and cloud particle properties of Arctic
clouds and the properties, number and size distributions of aerosols in the vicinity of
these;
to identify the origin of the ice phase in these clouds and to compare ice
crystal number concentrations with the parameterisation of primary IN concentrations of DeMott et
al. (2010);
to compare the cloud physics in spring and summer conditions and to identify
any contributions of secondary ice particle production;
to compare and contrast the mixed-phase cloud microphysics of Arctic clouds
with clouds observed in the Antarctic.
Methodology
The ACCACIA campaigns took place during March–April and July 2013. They
were conducted in the region between Greenland and Norway mainly in the
vicinity of Svalbard. The overarching theme of the project was to reduce the
large uncertainty in the effects of aerosols and clouds on the Arctic
surface energy balance and climate. Key to the work presented here is an
understanding of the microphysical properties of Arctic clouds and their
dependence on aerosol properties. To this end, the FAAM (Facility for Airborne Atmospheric Measurements) BAe-146 (British Aerospace-146, or 146) aircraft
performed a number flights incorporating profiled ascents, descents and
constant altitude runs below, within and above cloud during the spring
period. This provided high-resolution measurements of the vertical structure
of the cloud microphysics and the aerosol properties in and out of cloud
regions. The British Antarctic Survey (BAS) Twin Otter aircraft flew during
both campaign periods, providing a subset of the BAe-146 measurements. It
was the only aircraft present during the summer period. A total of 9 science
flights were conducted during the spring period with complementary flights
from the BAS twin otter and 6 flights by the BAS twin otter alone during the
summer period.
Two case studies are selected from both the early spring and summer
campaigns. The spring campaign case studies were selected for having quite
different aerosol loadings within the boundary layer. One was in relatively
clean Arctic air with low total aerosol numbers, while the second had higher
aerosol loadings in the boundary layer. Summer flight cases were selected
for being the cases with higher cloud layer temperatures in a range suitable
for secondary ice production through the Hallett–Mossop Process (Hallett and
Mossop, 1974) to take place. This process is known to operate under
particular conditions, and so could greatly enhance ice crystal number
concentrations. Temperature profiles in the spring cases revealed
stratocumulus cloud temperatures generally between -10 ∘C < T < -20 ∘C,
outside of the H–M zone.
Instrumentation
Instrumentation onboard the FAAM BAe-146 aircraft used for making
measurements of the cloud and aerosol microphysics reported in this paper
included the Cloud Imaging Probe models 15 and 100 (CIP-15 and CIP-100,
Droplet Measurement Technologies (DMT), Boulder, USA) (Baumgardner et al.,
2001), the Cloud Droplet Probe (CDP-100 Version 2, DMT) (Lance et al., 2010)
and the Two-Dimensional Stereoscopic Probe (2D-S, Stratton Park Engineering
Company Inc. Boulder, USA) (Lawson, 2006). The CIP-15 and CIP-100 are
optical array shadow probes consisting of 64-element photodiode arrays
providing image resolutions of 15 and 100 µm, respectively. The
2D-S is a higher-resolution optical array shadow probe which consists of a
128-element photodiode array with image resolution of 10 µm. The CDP
measures the liquid droplet size distribution over the particle size range of
3 < dp < 50 µm. The intensity of forward
scattered laser light in the range 4–12∘ is collected and particle
diameter calculated from this information using Mie scattering solutions
(Lance et al., 2010).
A Cloud Aerosol Spectrometer (CAS, DMT) and a Passive Cavity Aerosol
Spectrometer Probe (PCASP-100X, DMT) were both used to measure aerosol size
distributions onboard the 146. The CAS measures particles in the size range
of 0.51 < dp < 50 µm using forward scattered
light from single particles in the 4–13∘ range and backscattered
light in the 5–13∘ range. Particle size can be determined from
both the forward- and back-scattered light intensity using Mie scattering
solutions (Baumgardner et al., 2001). The PCASP is another optical particle
counter (OPC) and measures aerosol particles in the size range of
0.1 < dp < 3 µm. In this instrument, particles are sized
through measurement of the intensity of laser light scattered within the
35–120∘ range (Rosenberg et al., 2012). All the above instruments
were mounted externally on the FAAM aircraft. Examples of additional core data measurements that were
also used in this paper include temperature (Rosemount/Goodrich type 102
temperature sensors) and altitude measured by the GPS-aided Inertial
Navigation system (GIN).
Flight numbers, run numbers, and their associated time
intervals, altitude and temperature range for the four ACCACIA case studies
presented.
FlightRun numberTime (UTC)Altitude (m)Temperature (∘C)B761 B761A1 A213:13:26–13:16:43 13:04:40–13:10:331850–50 300–1850-19 to -5 -8 to -19B761A313:23:20–13:33:191700–50-19 to -7B768 B768 B768 B768B1 B2 B3 B411:45:16–11:54:02 11:38:39–11:44:59 12:01:30–12:19:08 12:32:20–12:48:141600–50 50–1600 400–50 1300–1050-17 to -9 -17 to -4 -12 to -9 -16 to -14M191 M191 M191 M191 M191C1.1 C1.2 C1.3 C1.4 C208:53:45–09:00:00 09:00:00–09:06:50 09:06:50–09:13:35 09:13:35–09:21:09 10:14:58–10:33:51∼ 2950 ∼ 2900 ∼ 2750 2750–2250 3350–2300∼-7 ∼-6 ∼-5 -4 to -2 -7 to -3M192 M192D1 D212:58:58–13:06:02 12:19:10–12:48:163100–3750 3100–3750-5 to -1 -5 to -1
Instrumentation onboard the Twin Otter Meteorological Airborne Science
INstrumentation (MASIN) aircraft, relevant to measurements reported in this
paper included a CDP-100 for drop size distributions and a 2D-S (summer only),
both similar to those on the FAAM aircraft; a CIP-25 (as on FAAM except
consisting of a 64-element photodiode array providing an image resolution of
25 µm) and core data including temperature measured by Goodrich
Rosemount probes (models; 102E4AL and 102AU1AG for non-deiced, and deiced
temperatures, respectively, similar to those used on the FAAM aircraft) and
altitude derived from the aircraft avionics (Litef AHRS) system.
Data analysis
During each science flight, measurements of aerosol and cloud microphysical
properties were made. The techniques used to interpret these data are
described below. The flights and the conditions during some of the measurement periods can be found in Table 1.
Cloud microphysics measurements
In this paper, 1 Hz data from all cloud and aerosol instruments have been
further averaged over 10 s periods for presentation. Measurements from
the 2D-S probe have been presented in preference to other 2-D probe data due
to this probe's significantly faster response time (by > a factor of
10) and greater resolution. When comparing CIP-15 and 2D-S size
distributions we found good agreement over their respective size ranges.
During the spring cases it was possible to combine 2D-S data with
measurements from the CIP-100 to extend the cloud particle size range.
Analysis of imagery from these optical array probes (OAPs) was used to
calculate number concentrations and discriminate particle phase.
Identification of irregular particles, assumed to be ice, was achieved
through examination of each particle's circularity (Crosier et al., 2011).
Ice water contents (IWCs) were determined using the Brown and Francis (1995)
mass dimensional relationship. This mass dimensional relationship is widely
used in the literature for mixed-phase clouds (e.g. Crosier et al., 2011).
Baker and Lawson (2006) found discrepancies between their treatments of data
using habit recognition and the Brown and Francis scheme. In our case
studies where the IWC is high, most of the mass is dominated by small ice
crystals, for which good agreement is found between Brown and Francis and
Baker and Lawson.
Measurements of aerosol concentrations > 0.5 µm
from the CAS and PCASP probes, together with predicted primary IN
number using the DeMott et al. (2010) (D10) scheme (with either CAS or PCASP
aerosol concentration data as input). Observed minimum median cloud
temperatures were input to D10, and IN predictions were compared with observed
maximum median ice concentrations.
All cloud microphysics probes were fitted with “anti-shatter” tips
(Korolev et al., 2011, 2013) to mitigate particle shattering
on the probe . However, even with these modifications shattering artifacts
may still be present, particularly under some cloud conditions, and these
need to be corrected for (Field et al., 2006). To minimise such artifacts,
inter-arrival time (IAT) histograms were analysed in an attempt to identify
and remove these additional particles, i.e. by removing particles with very
short IATs that are indicative of shattered ice crystals.
Crosier et al. (2013) reported that careful analysis of IAT histograms for different cloud
microphysical conditions is needed to determine the most appropriate IAT
threshold for best case elimination of such artifacts. For example, in
regions of naturally high ice crystal number concentrations, such as in the
H–M secondary ice production temperature zone, the minimum IAT threshold may
need to be reduced more than is usual so as not to exclude too many
naturally generated ice crystals with short IATs. In this study, we found a
minimum IAT threshold of 1×10-5 and 2×10-5 s for the 2D-S and
CIP-15 instruments, respectively, to be appropriate IAT values for the
majority of cloud region data presented.
It was found that the CIP probes and 2D-S ice crystal number concentrations
differed by less than 20 % over their common size range. In this paper we
present the data from the 2D-S due to its larger size range, higher
resolution and faster response time.
Aerosol measurements
We did not directly measure IN concentrations during each flight, however
information in each case study, about aerosol concentration and size was
used to calculate the predicted primary IN concentrations from
the DeMott et al. (2010, hereafter D10) parameterisation of primary ice
nuclei numbers, which is dependent on the number concentration of aerosol
particles with diameters > 0.5 µm. Combined measurements of
the aerosol concentration using the PCASP and CAS for spring, and CAS for
summer, were used from cloud-free regions selected by applying maximum
relative humidity (RH) thresholds. This was done to reduce the contribution
of any haze aerosol particles smaller than 0.5 µm in size growing into the
size range at higher humidities and being incorrectly included. The CAS
instrument has a lower size threshold of 0.51 µm. D10 notes that the
maximum possible aerosol size that could be measured and included in their
D10 parameterisation was 1.6 µm. However, due to the size bins utilised
by the CAS instrument this upper threshold had to be relaxed to 2 µm,
although the extra contribution to the aerosol concentrations used in the
calculations is likely to be small. Measurements from the higher-resolution
PCASP were selected from the size range of 0.5–1.6 µm, in
keeping with the D10 scheme. The D10-predicted IN concentrations were then
compared directly as a function of temperature with the observed ice crystal
concentrations. The minimum-observed median temperature was input to D10 and
predicted IN numbers compared with the maximum-observed median ice crystal
number concentrations (Fig. 11) for the clouds during each of the four cases.
The results are shown in Table 2.
The results of this comparison from all four cases can be compared with
previous observations of Arctic clouds and with recent aircraft measurements
of clouds over the Antarctic Peninsula in the summer (Grosvenor et al.,
2012).
Spring case 1 – Friday 22 March 2013 (FAAM flight B761)
The FAAM aircraft flew from Kiruna, Sweden (67.85∘ N,
20.21∘ E),
to Svalbard, Norway, landing at Longyearbyen,
(78.22∘ N, 15.65∘ E) to refuel. After takeoff at
∼ 11:45 UTC a ∼ 2 h science flight was
undertaken to the south-east of Svalbard (Fig. 1) before returning to
Kiruna. The objective was to investigate stratocumulus clouds over a north–south line in this area. The flight focused on a series of
profiled descents and ascents to enable measurements to be made of the cloud
layer from below the cloud base to above the cloud top and into the inversion layer
above. During the flight there were three significant penetrations through the
inversion at cloud top and in each case there was a marked temperature
increase of ∼ 5 ∘C. Microphysical time series data for
this case are presented, with the relevant runs highlighted in Fig. 2. A
description of one cloud profile is given here, with further profiles
described in the Supplement.
AVHRR visible satellite imagery for spring case 1 (a), spring
case 2 (b), summer case 1 (c) and summer case 2 (d). The science flight area
is highlighted by purple boxes in each figure.
Boundary layer aerosol number concentrations (from the PCASP) were found to
be relatively low at ∼ 50–100 cm-3. A blocking high-pressure system east of Greenland was present, with a trough over eastern
Scandinavia. The area of operation was situated on the north-eastern side of
the anticyclone with widespread low cloud observed south and east of
Svalbard (Fig. 1), with winds from the north advecting from over the sea ice
towards open sea. Earlier dropsonde measurements (on the transit into
Longyearbyen prior to refuelling) showed surface winds of ∼ 3 m s-1
increasing to 15 m s-1 at 500 mb. The cloud layers during
this flight were found to contain generally uniform liquid water content
profiles, which were found to be approximately adiabatic. The clouds were
situated over the temperature range of -15 ∘C < T < -20 ∘C.
Generally low concentrations of ice, often in isolated
pockets, were observed in these clouds.
Microphysics time series for spring case 1. Data includes
temperature (∘C) and altitude (m) (lower panel) together with 1
and 10 s data sets for CDP liquid water content (g m-3) (panel 2
from bottom), CDP cloud particle number concentration (cm-3) (panel 3)
and ice water content (g m-3) and ice number concentrations (L-1)
(top panel). Profiles A2 and A3 are described in the Supplement.
Profiled descent A1
During profile A1 the aircraft (now travelling north) descended from the
inversion layer. Cloud top was encountered at 1650 m (T=-18.6∘C).
The highest values of Nice were observed in the cloud
top region, at ∼ 4 L-1. Particles here consisted of small
irregular ice particles (mean size ∼ 360 µm) that showed
evidence of riming, together with small droplets. LWC at cloud top increased
to 0.3 g m3 with Ndrop∼ 55 cm-3 (mean diameter
∼ 17 µm). As the aircraft descended (∼ 250 m
below cloud top) Nice decreased to ∼ 1 L-1, while
mean ice particle size increased to ∼ 395 µm.
Ndrop increased to ∼ 70 cm-3, while mean size
decreased slightly (∼ 16 µm), while LWCs generally
decreased somewhat to ∼ 0.2 g m-3. In spring cases
this pattern of steadily reducing LWC with an increase in droplet number
towards cloud base was frequently observed (Fig. 10). As the aircraft
descended to an altitude of ∼ 1150 m, Nice increased by
approximately a factor of 2 (to ∼ 2 L-1). At around 13:15 UTC
a number of rapid transitions from liquid to predominantly glaciated
conditions were observed in the mid cloud region at 730 m and T=-12∘C.
2D-S imagery (Fig. 3c) highlights these changes taking place
as small droplets are quickly replaced by small irregular ice crystals and
eventually larger snow particles (mean diameter ∼ 610 µm)
that consisted of heavily rimed ice crystals and aggregates, some of which
can be identified as exhibiting a dendritic habit. Three further swift phase
transitions were observed as the aircraft approached cloud base. LWC in the
liquid-dominated regions was between ∼ 0.15 and 0.25 g m-3
while Ndrop peaked at ∼ 130 cm-3. During
the ice-phase sections of the transition cycle, mean particle sizes were
∼ 615 µm and Nice was a few per litre. The
contribution of these glaciated cloud regions to the IWC was considerable,
with values around 0.1 g m-3 recorded. These transitions ended as the
aircraft descended below cloud base (T=-12∘C) at 700 m
a.s.l., and precipitating snow was observed (mean size ∼ 710 µm).
Measurements of the ice phase during spring cases often showed
increasing ice crystal size towards cloud base, with the largest ice
particles measured in precipitation from the cloud layers above.
Images from the 2D-S cloud probe during spring case 1 from
(a) a cloud top region during A1, (b) 500 m below cloud top during
A2, (c) region of swift transitions between ice and liquid, and (d) a precipitation
region below cloud base.
Spring case 2 – Wednesday 3 April 2013 (FAAM flight B768)
The FAAM aircraft departed Longyearbyen at around 11:00 UTC and conducted
measurements to the NW of Svalbard to investigate low-level clouds over the
sea ice (moving from NW to SE in the target area – Fig. 1). A low pressure
(1004 mb) region was centred south of Svalbard with an associated band of
cloud and precipitation. To the NW of Svalbard, within the measurement area,
surface winds were ENE and < 10 m s-1. Measurements revealed
an air mass containing significantly more aerosol than in Spring case 1, with
PCASP concentrations typically ∼ 300–400 cm-3 in the
boundary layer. During the flight the aircraft made two distinct sawtooth
profiles through the cloud layer and into the inversion above cloud top
where temperatures in each instance increased by ∼ 2 ∘C.
Figure 4 shows time series of the microphysical measurements made during
this science flight. Further profile descriptions can be found in the
Supplement. Despite the contrast in aerosol loadings when
compared with the first spring case, where aerosol concentrations were much
lower, the cloud layers were similar with generally uniform structure and
low concentrations of primary ice. Despite the cloud layers being situated
in slightly higher temperatures
(-12 ∘C < T < -16 ∘C),
the concentrations of ice were similar to spring case 1.
Microphysics time series data for spring case 2. Data includes
temperature (∘C) and altitude (m) (lower panel) 1 and 10 s
data sets for CDP liquid water content (g m-3) and CDP concentration
(cm-3) (middle panels), and ice water content (g m-3) and ice
number concentrations (L-1) (top panel). Profiles B2, B3 and B4 are
described in the Supplement.
Profiled descent B1
Flying NW, the aircraft performed a profiled descent from the inversion
layer (T=-16.5∘C) into cloud top, ∼ 1550 m a.s.l.,
where the measured temperature was -17 ∘C. LWCs rose
to ∼ 0.9 g m-3 and Ndrop (mean diameter
∼ 15 µm) peaked at ∼ 320 cm-3. The
highest values of Nice never exceeded 0.5 L-1 in this cloud top
region and imagery from the 2D-S probe revealed many small droplets with
isolated small (mean size ∼ 223 µm) irregular ice
crystals (Fig. 5a). After descending through this brief cloud top region
Nice increased to ∼ 0.5 L-1. As the aircraft
descended over the next 500 m mean droplet concentrations gradually
increased from 300 to 370 cm-3 with mean diameters
decreasing slightly to 12.5 µm. LWCs fell from 0.7 to 0.2 g m-3
over the same period, a pattern consistent with spring case 1.
Nice values remained fairly constant and IWCs were < 0.02 g m-3.
2D-S imagery showed ice crystals (mean diameter 295 µm) to be
mainly dendritic in nature. During the last 160 m depth of the cloud, before
cloud base, Nice remained similar to the mid cloud region. However,
concentrations of liquid droplets measured by the CDP showed greater
variability. Peaks in number concentrations reached up to 430 cm-3,
with rapid changes down to 110 cm-3.
Images from the 2D-S cloud probe from spring case 2 for
(a) cloud top during B1, (b) profiled ascent during B2, (c) dendritic ice in
the cloud base region during B2, and (d) columnar ice above the sea surface
during B2.
The aircraft passed cloud base at 700 m a.s.l. encountering low concentrations
(< 0.5 L-1) of precipitating snow. Interestingly, as the
aircraft continued its descent (to 50 m a.s.l.) a significant increase in
Nice was observed (T=-9∘C), with 10 s mean values
of 2 L-1. Images from the 2D-S revealed (Fig. 5d) snow precipitation
co-existing with small columnar ice crystals. CDP LWC was very low,
< 0.01 g m-3; however, examination of the 2D-S imagery showed
the presence of spherical drizzle droplets larger than the maximum
detectable size of the CDP. Size distribution data from the 2D-S in this
region revealed an additional mode dominated by these smaller columnar ice
crystals, typically 80 µm in size. As the aircraft ascended again,
these higher concentrations of ice crystals diminished.
Summer case 1 – Tuesday 18 July 2013 (flight number M191)
The BAS Twin Otter aircraft departed Longyearbyen airport at ∼ 07:00 UTC
to conduct a ∼ 2 h science flight to the north of
Svalbard (Fig. 1). Examination of surface pressure charts showed a slack low
pressure around Svalbard, with an occluded front to the east. Extensive low
clouds were present in the area with light winds < 5 m s-1 from
the north. The objectives of the flight were to measure aerosol
concentrations and composition in the vicinity of clouds, together with the
microphysical properties of the clouds by undertaking a combination of
profiles and straight and level runs through stratocumulus cloud layers to
capture the microphysical structure. Time series of data collected during
this flight are presented in Fig. 6. Profile C2 is described below, with
details of the measurements made during C1 found in the Supplement. Cloud
layers during this case were found to be situated in the H–M temperature
zone with greater variability in microphysical structure when compared with
the spring cases. At cloud top, ice concentrations were found to be similar
to the spring cases. However, at times, in the body of the cloud secondary ice
production caused significant areas of glaciated cloud, which appeared
to lead to greater variability in the liquid water profile of the clouds
when compared to the colder layers observed in the spring.
Microphysics time series data for summer case 1. Data includes
temperature (∘C) and altitude (m) (lower panel) together with 1 and
10 s data sets for CDP liquid water content (g m-3) (second panel
up), CDP concentrations (cm-3), ice water content (g m-3) and ice
number concentrations (L-1) (top panels). Flight segments C1.1, C1.2,
C1.3 and C1.4 are described in the Supplement.
Profile C2
The aircraft performed a sawtooth profile, descending from cloud top at
∼ 3300 m down to a minimum altitude of ∼ 2300 m
followed by a profiled ascent to complete the sawtooth. During the descent
into cloud top (T=-9∘C), LWCs rose sharply to peak values of 0.3 g m-3
and Ndrop (mean diameter 19 µm) increased to 155 cm-3.
Nice in the cloud top regions peaked at 1 L-1. With
decreasing altitude, LWC declined gradually to values close to 0.01 g m-3.
As the temperature increased to above -8 ∘C, ice
crystal number concentrations (mean diameter 210 µm) increased to 5 L-1,
with peaks at ∼ 12 L-1. 2D-S imagery revealed
the presence of small columnar ice crystals together with small liquid
droplets (CDP mean diameter 8.5 µm) and some irregular ice particles.
Low concentrations of ice at cloud top was consistent in both summer cases,
with periods of enhanced concentrations due to rime splintering lower
in the clouds.
At 2880 m (T=-6.5∘ C) the cloud dissipated until the next cloud
layer was encountered 200 m below (T=-5∘ C). In this region CDP
LWC and Ndrop were more variable than in the cloud layer above.
Generally, LWCs were < 0.1 g m-3 with peaks in Ndrop up to
∼ 155 cm-3 and transitions between liquid cloud and
predominantly glaciated cloud were observed. During glaciated periods 2D-S
imagery showed many columnar ice crystals, typical of the growth regime at
this temperature (∼-5∘ C) and consistent
with the enhancement of Nice through the H–M process. Greater variation
in microphysical structure, with broken cloud layers and transitions between
liquid and glaciated phases, was evident in the summer cases, which was in
contrast to the uniform spring cloud layers.
Summer case 2 – Wednesday 19 July 2013 (M192)
The BAS aircraft departed Longyearbyen at ∼ 09:00 UTC intending
to investigate cloud microphysics and aerosol properties to the north of
Svalbard (Fig. 1). On arrival at the observation area the forecasted cloud
was not present so the flight was diverted to the south-east of Svalbard to
meet an approaching cloud system. Surface pressure charts showed a low
pressure system over Scandinavia (central pressure 1002 mb), with a warm
front south-east of Svalbard that was moving to the north-west. Surface winds in
this area were ∼ 13 m s-1 from the north-east. In situ
cloud microphysics measurements were made for approximately 1.5 h in
total. To meet the objectives of the flight, straight and level runs and sawtooth profiles were performed through the cloud layers. Microphysics time
series data from the flight are shown in Fig. 8. Profile D2 is described
below, with the additional profile D1 discussed in the Supplement.
This second summer case was again found to have different microphysical
characteristics when compared with spring cases. Higher ice number
concentrations and the domination of the ice phase by secondary ice
formation caused much greater variability in the structure of the clouds
observed.
Images from the 2D-S cloud probe from summer case 1 for
(a) small irregular ice during C1.2, (b) and (c) secondary ice production
during C1.3 and C1.4, respectively, and (d) ice together with drizzle during
C2.
Microphysics time series data for summer case 2. Data includes
temperature (∘C) and altitude (m) (lower panel) together with 1 and
10 s data sets for CDP liquid water content (g m-3), CDP
concentration (cm-3) (middle panels), ice water content (g m-3)
and ice number concentrations (L-1) (top panel). Profile D1 is
described in the Supplement.
Profile D2
During period D2, the aircraft performed a number of straight and level runs
combined with sawtooth profiles to capture the microphysical structure of
the cloud layers present. At 3100 m the aircraft flew a straight and level
run below cloud base and encountered a region of snow precipitation at
temperatures between -2 and -3 ∘C.
Nice peaked at 5 L-1 giving peaks in calculated IWCs of
∼ 0.1 g m-3. Probe imagery showed ice crystals (mean
diameter 410 µm) dominated by irregular particles, with some evidence
of plate-like and dendritic structures. Observation of snow precipitation
below some cloud layers is a common observation in both spring and summer
cases.
During a profiled ascent up to 3400 m (to begin an extended SLR – straight and level run) the
aircraft penetrated cloud base at 3300 m (T=-4∘C). LWCs rose to
∼ 0.1 g m-3 with Ndrop generally observed to be
between 10 and 50 cm-3 (mean diameter 12 µm). Nice in this
region was between 0 and 1 L-1 and crystals consisted of irregular ice
particles, columnar ice and small liquid droplets. The mean diameter of the
ice particles in this region was 470 µm. Continuing at 3400 m altitude,
the aircraft encountered a break in the cloud layer that lasted for around 1 min
(∼ 6 km), before a subsequent cloud layer was observed
that had similar LWCs to the previous cloud layer (∼ 0.1 g m-3)
but with generally lower droplet concentrations (of mean
diameter 17.5 µm) with mean Ndrop values of 15–30 cm-3.
Nice values in this region were lower than before (< 0.5 L-1).
The sampling of this cloudy region was brief before another gap
in cloud was observed that lasted ∼ 2 min. The end of this
second clear region was defined by a sudden transition to columnar ice and
small irregular particles (mean diameter 410 µm) in concentrations up
to a peak of 4 L-1. This region was mostly glaciated with LWC < 0.01 g m-3.
During this SLR there were very swift transitions observed
between predominantly glaciated regions containing ice crystals of a
columnar nature and then mainly liquid regions consisting of low
concentrations (< 30 cm-3) of small liquid droplets (mean
diameter 14 µm) and LWCs (∼ 0.01 g m-3) (Fig. 9c–d).
This predominantly glaciated period ended when the aircraft performed a
profiled ascent and Nice decreased to < 0.5 L-1 while
LWCs increased to a peak of 0.3 g m-3 and Ndrop rose to a maximum
of ∼ 120 cm-3 (mean diameter 14 µm). The aircraft
penetrated cloud top at 3700 m (T=-4.5∘C). During
subsequent passes through the H–M zone during period D2, further peaks in ice
concentrations up to 20 L-1, attributed to rime splintering, were
observed.
Primary IN parameterisation comparison
Ice number concentrations as a function of altitude for science flight
periods have been presented and here these observations are compared to
calculations of the primary IN concentrations predicted using the D10 scheme,
using aerosol concentrations (diameter > 0.5 µm) that were
measured on each flight as input. DeMott et al. (2010) analysed data sets of
IN concentrations over a 14-year period from a number of different locations
and found that these could be related to temperature and the number of
aerosol > 0.5 µm. The parameterisation provided an improved
fit to the data sets and predicted 62 % of the observations to within a
factor of 2. Table 2 shows mean aerosol concentrations for measurement
periods during each case, the input temperature to D10, the maximum median
ice concentration used for comparison and the predicted IN concentration
based on both the PCASP and CAS aerosol measurements (where available).
During the spring measurement campaign it was possible to compare the CAS
and PCASP probe data sets. Despite some variation in concentrations reported
between the two instruments, D10-predicted IN values were found to be fairly
insensitive to these differences. Grosvenor et al. (2012) highlighted that
changes of about a factor of 4 produced a very limited change in the IN
concentrations predicted by the scheme.
2D-S cloud probe imagery for summer case 2 showing (a) columnar
ice during D1, (b) images of columns together with liquid during
D2 and swift transitions between (c) glaciated and (d) liquid phases during
D2.
In spring case 1 the maximum median ice value was 0.61 L-1 so
predicted IN values were generally higher (between a factor of 2 and 4) than
this median ice concentration observation. However, peaks in ice
concentrations of up to ∼ 10 L-1 were also observed
(Fig. 2), so on these occasions D10 significantly underpredicts observed ice
number concentrations when compared to these peak values. During spring case
2, maximum median ice concentration values were similar to spring case 1.
Secondary ice production was observed close to the sea surface in this case
so these higher median concentrations have been disregarded for the purposes
of the D10 primary IN comparison. Aerosol measurements from the CAS were lower
than from the PCASP but predicted IN values were in good agreement (less
than a factor of 2) with the observed maximum median concentration. The peak
concentrations observed during the flight were ∼ 5 L-1
(Fig. 4) and as in the first spring case D10 underpredicted these peak
concentrations by about a factor of 10.
During summer case 1 the minimum cloud temperatures were higher (T=-10∘C)
than in the spring cases. The maximum median ice concentrations
observed were also higher (3.35 L-1). The origin of these enhanced
concentrations is attributed to SIP (secondary ice production), making a direct comparison with the
D10 primary IN scheme difficult. Predicted IN concentrations from D10 were
found to underestimate the maximum median ice concentrations observed in
this summer case (due to secondary ice production), but were in agreement
with the concentrations observed near cloud top, where the ice phase is
likely to represent primary heterogeneous ice nucleation. Observed ice
concentrations in summer case 2 were also higher than in the previous spring
cases and similar to the first summer case. The second case had higher
minimum cloud temperatures than in the first summer case (T=-4.3∘C).
Due to effect of SIP at this temperature, it was not
possible to compare D10 with the concentrations of ice observed in these
clouds.
Discussion
Summaries of typical profiles during each case have been presented, with
microphysics data encompassing all cloud penetrations during the science
flights presented as a function of altitude shown in Figs. 10, 11 and 12.
Figure 10 shows the cloud liquid droplet parameters, Fig. 11 the ice
crystal concentration statistics and Fig. 12 the ice mass and diameter
parameters. In each case (a) is spring case 1, (b) spring case 2, (c) summer
case 1 and (d) summer case 2. The yellow lines on the ice plots (Fig. 8)
show the approximate location of cloud top and cloud base altitudes deduced
from liquid water content measurements exceeding 0.01 g m-3 from the
CDP. It is notable that droplet concentrations (Fig. 10) are much higher in
the second spring case than in the first spring case (max median values
∼ 60 and ∼ 400 cm-3 for spring cases 1 and 2,
respectively) and this is attributed to differences in aerosol
concentrations. Ndrop values are similar in the two summer cases (max median
values 100–150 cm-3) and lie between the two spring cases. The
different aerosol loadings in spring cases 1 and 2 may have led to the riming
indirect effect playing a role in controlling the ice phase. Case 2 had
higher aerosol loadings and increased CCN availability, with smaller droplet
sizes (Fig. 10). In this case IWC values were also much lower than in the
case 1 and it is possible that reduced riming efficiency of the smaller
droplets contributed to reduced ice mass growth through riming.
Percentile plots (50th, 25th, 75th percentiles, whiskers to
10 and 90 %) as a function of altitude for LWC from CDP (green), and
median droplet number concentration (purple), median droplet diameter (grey)
and median temperature (red). Data are averaged over 100 m deep layers.
(a)–(d) are for spring case 1, spring case 2, summer case 1 and summer
case 2, respectively.
Box and whisker plots with 50th, 25th, 75th percentiles,
whiskers to 10 and 90 % and outliers between 95 and 100 % as a function
of altitude for ice number concentrations (black) and median temperature
(red) (a–d and altitude averages as in Fig. 10). The box in
yellow provides an indication of the full extent of cloud layers
investigated. (a)–(d) are for spring case 1, spring case 2, summer
case 1 and summer case 2, respectively.
Box and whisker plots with 50th, 25th, 75th percentiles,
whiskers to 10 and 90 % and outliers between 95 and 100 % as a function
of altitude for ice mass (black) and median ice crystal diameter with
outliers between 95 and 100 % (blue) ((a)–(d) and altitude averages
as in Fig. 10). The box in yellow provides an indication of the full
extent of cloud layers investigated. (a)–(d) are for spring case 1,
spring case 2, summer case 1 and summer case 2, respectively.
During the spring cases the mixed-phase cloud layers were found to be
approximately adiabatic and exhibited generally uniform increases in LWC and
droplet diameter (Fig. 10) to liquid cloud tops that were observed to
precipitate ice. At and above cloud top, well-defined temperature inversions
were present and dew points revealed a marked dry layer just above cloud
top. It was observed that cloud penetrated into the inversion layer, rather
than being capped below it. On average the cloud top was seen to extend
∼ 30 m into the inversion layer over which range the mean
temperature increase was ∼ 1.6∘ C.
The ice phase is very likely to have been initiated through primary
heterogeneous ice nucleation in the temperature range spanned by these
clouds (approximately -10 to -20 ∘C).
Generally, low concentrations of ice crystals were
observed (max median value 0.61 L-1) (Table 2) but with peaks up to
∼ 5–10 L-1 in both spring cases (Fig. 11). Cloud top
regions consisted of small liquid droplets (median diameter
∼ 15 and 25 µm for spring cases 1 and 2, respectively) (Fig. 10a–b),
together with small irregular ice crystals (Figs. 3a, 5a). In both of
these cases, ice crystal diameter increased to maximum values of 530
and 660 µm, respectively (Fig. 12a, b). The variability in ice crystal
diameter (Fig. 12a, b) shows periods where maximum ice crystal diameters
increased to ∼ 2 mm. These crystals were often comprised of a
mixture of large rimed irregular particles (Figs. 3, 5) and dendritic snow
crystals. Median IWC values in the spring cases reached ∼ 0.01 g m-3
(Fig. 12a, b), with peak values during case 1 of up to
∼ 0.3 g m-3 compared with 0.1 g m-3 in case 2. The
highest median LWCs (Fig. 10) were observed at cloud top during spring
cases, peaking at 0.3 and 0.5 g m-3 during cases 1 and 2, respectively.
While these clouds were seen to be fairly uniform, time series data (Figs. 2, 4) show some of the variability in the microphysics that was observed
during the science flight.
During the summer cases, the cloud layers spanned a higher temperature range
(-10 ∘C < T < 0 ∘C) and
well-defined temperature inversions at cloud top were less evident. There
was a much greater tendency towards there being multiple cloud layers that
were shallower and less well coupled. During summer case 2 a significant
temperature inversion was observed (Fig. 10d) in the cloud base region,
which suggested a decoupling of the boundary layer and the cloud system
above. Liquid cloud top regions with few (generally < 1 L-1)
ice crystals, formed through heterogeneous ice nucleation at these
temperatures, were observed in both cases (Fig. 11c, d). LWCs in summer case
1 were lower than the spring cases (median values < ∼ 0.1 g m-3)
but similar in shape to the uniform profiles seen in the
spring cases. The second summer case had higher median LWCs (up to 0.35 g m-3)
and showed much more variability with a number of increases and
decreases in median LWC values with altitude (Fig. 10d).
Median cloud top ice concentrations in summer case 1 were similar to the
spring cases (∼ 0.2 L-1) (Fig. 11d); however, maximum
median values lower down in the cloud reached 3.35 L-1 (Table 2), about
a factor of 14 higher than in the spring cases. Peaks in ice number
concentrations around the -5 ∘C level reached between 30 and 40 L-1.
During the summer, the clouds spanned the temperature range from -3 to
-8 ∘C, where a well-known mechanism of secondary ice production
operates through splintering during riming, the Hallett–Mossop process. The observations in this case of liquid water together with ice
particles at temperatures around -5 ∘C are consistent with
this process being active and enhancing ice number concentrations (Figs. 7, 9).
Time series (Figs. 6, 8) showed more variation than in the spring
cases. Distinct liquid cloud tops were still evident, but at lower altitudes
significant variations in LWCs, droplet number concentrations and ice number
concentrations were seen together with gap regions where little or no cloud
was present. On a number of occasions predominantly liquid conditions were
swiftly replaced by regions of high concentrations of columnar ice crystals.
Some of these transitions took place over ∼ 1 s or
horizontal distance of the order 60 m. These rapid fluctuations were
attributed to the contributions from the H–M process. The process of
glaciation through secondary enhancement of ice number concentrations is
likely to have caused some of this increased variability in cloud properties
too, with liquid droplets quickly being removed through depletion of liquid
water by the ice phase. The cloud layers during summer case 2 spanned a
higher temperature range than summer case 1. Cloud tops were around -4 ∘C,
and median ice number concentrations reached maximum values
of 2.5 L-1, about an order of magnitude higher than in the spring
cases. Time series (Fig. 8) and percentile plots (Fig. 11d) showed peaks in
ice number concentrations of up to ∼ 25 L-1 and in these
regions probe imagery revealed distinctive columnar ice crystals likely to
have grown from splinters, produced via H–M, into habits typical of growth at
these temperatures around -4 ∘C. In addition, the formation
of high ice concentrations may have led to the dissipation of some liquid
cloud regions below cloud top due to consumption of the liquid phase by ice
crystals growing by vapour diffusion (i.e. ice crystal growth via the
Wegener–Bergeron–Findeisen (WBF) process (Bergeron, 1935). This is consistent with
the observed summer clouds being more broken than the clouds observed during
spring. However, as discussed in the introduction, it is also recognised
that cloud–radiation interactions may lead to the separation of cloud layers
during the Arctic summer.
Comparison of the observed Nice with the D10 parameterisation of primary
ice nuclei numbers revealed that during the spring case 1 maximum median
Nice was lower than the primary IN concentrations predicted by D10, but
similar in spring case 2. Peaks in Nice were much higher than the
D10 IN predictions, by an amount depending on the aerosol measurement period
used as input to D10 (Table 2). Our observations show deviations in the ice
concentrations of as much as an order of magnitude compared with the D10 IN
prediction. The variation in ice number concentrations observed in the
spring cases could be explained by the variability in observed IN values
presented in the DeMott et al. (2010) paper.
In the summer cases the enhancement of Nice through the H–M process
made a realistic comparison difficult. Despite this difficulty, the first
summer case had cloud top temperatures that were just outside the H–M
temperature zone (-10 ∘C) and the median Nice in this
region was ∼ 0.2 L-1, which is within a factor of 2 of
the values predicted by D10 (Table 2). At lower altitudes the increase in cloud
temperatures allowed rime splintering to enhance concentrations to above
what would be expected via primary heterogeneous ice nucleation. In the
second summer case cloud top temperatures were higher (-4 ∘C),
and enhancement of the ice crystal number concentrations through SIP
prevented observations of any first ice by primary nucleation being made.
Ice crystal number concentrations were thus enhanced to values above what
was predicted by D10 throughout the depth of the cloud.
The microphysical structure of the spring and summer stratocumulus layers
was found to be consistent with previous observations of Arctic clouds. We
observed generally low droplet number concentrations that were enhanced
during incursions of higher aerosol loadings, similar to findings by
Verlinde et al. (2007). During spring cases, LWCs and liquid droplet size
increased uniformly to cloud top, however during summer months the vertical
structure of cloud layers was more variable (e.g. Hobbs and Rangno, 1998).
During spring cases in particular, liquid cloud tops at distinct temperature
inversions continually precipitated low concentrations of ice into the cloud
below, which has been observed previously in the Arctic. Rogers et al. (2001)
made airborne measurements of IN in thin, low-level Arctic clouds in
the same temperature range as our spring cases. They found evidence for a
few IN in these clouds with concentrations of ice that were similar to the
observations presented here.
During the Arctic summer, Hobbs and Rangno (1998) observed generally higher
ice concentrations with columnar and needle ice crystals in concentrations
of “tens per litre” where stratocumulus cloud top temperatures were between
-4 and -9∘ C. Rangno and Hobbs (2001) found that high
ice particle concentrations were common during late spring and summer in the
Arctic. Despite the presence of some columnar ice, many of the crystals were
irregular in shape, and it was suggested that shattering of freezing drops
> 50 µm or the fragmentation of fragile ice may have
contributed to the high concentrations. Although we have not performed habit
classification analysis on our data set the images suggest that the ice phase
in summer cases was dominated by columnar ice, with evidence of a small
number of irregular ice particles. Previous laboratory studies found that
larger droplets were necessary to initiate rime splintering (Mossop, 1980)
and Hobbs and Rangno confirm that in the cases they studied a threshold
droplet size of 28 µm was required, below which secondary ice
production did not take place. In the limited summer cases we had in the
appropriate temperature range, secondary ice production took place in the
presence of concentrations of liquid droplets over this threshold size.
Table reproduced from Grosvenor et al. (2012) reporting
observations of ice number concentrations, aerosol concentrations
> 0.5 µm and primary IN predictions using the D10
parameterisation.
The summer cases we observed contained median values of Nice that were
4–6 times greater than we observed in the spring cases. In both summer cases
where the H–M process was active droplet sizes were similar, and we did not
find any evidence for a thermodynamic indirect effect leading to differences
in the efficiency of secondary ice production in summer cases. Changes in
aerosol concentrations and composition have been suggested as a possible
factor in explaining previous observations of the glaciation of Arctic
clouds at different temperatures (Curry et al., 1996). During spring case 2
higher concentrations of aerosol were observed when compared to spring case
1. Droplet number concentrations were also much higher in spring case 2,
generally 300–400 cm-3 in comparison to spring case 1 where
concentrations were generally ∼ 50–100 cm-3. Despite
this, no significant difference was observed in the ice number
concentrations. However, it should be noted that despite the higher total
concentrations, the population of aerosol > 0.5 µm was not
significantly enriched in spring case 2 compared to the spring case 1. D10
has a dependency only on this portion of the aerosol size distribution, which may explain the similar primary ice number concentrations for both spring
case studies. Although we did not make any direct measurements of IN, in both
Arctic spring cases and Antarctic cases primary heterogeneous ice nucleation
was identified as the dominant source of ice. It is very likely that the
higher concentrations of ice in the Arctic cases when compared to the
Antarctic were therefore due to increasing IN availability, which is
consistent with the glaciation indirect effect.
Grosvenor et al. (2012) studied stratocumulus clouds in the Antarctic over
the Larsen C Ice Shelf. These observations contained periods where
temperatures were comparable to those in the spring cases studied here. The
lower layers of Antarctic cloud were also reported to contain higher
concentrations of ice produced via the H–M process, similar to the summer
cases that we have discussed. A summary of some of the measurements reported
from the Antarctic in Grosvenor et al. (2012) can be found in Table 3.
Measurements of cloud regions outside the H–M temperature zone revealed very
low ice number concentrations, with maximum values about 2 orders of
magnitude lower than those observed in the spring cases reported here.
Aerosol concentrations from a CAS probe (similar to the one deployed in this
study) reported generally lower concentrations of aerosol particles
Dp > 0.5 µm. The D10 IN predictions in the
Antarctic were reported to compare better with maximum, rather than mean ice
values. A similar result was found in this study where predicted primary IN
values were greater than observed median values. However, when comparing
with peak ice concentration values the scheme significantly underpredicted
these. Grosvenor et al. (2012) discussed the possibility that due to the
D10 parameterisation being based on mean IN concentrations from many samples,
the finding that IN predictions compared well with the maximum values rather
than mean values may suggest the scheme was over predicting IN
concentrations generally in the Antarctic (for these particular cases at
least). In the H–M layer in the Antarctic over Larsen C, ice crystal number
concentrations were found to be higher than those observed in colder
temperature regimes (not spanning the H–M temperature range), in keeping
with the findings from the Arctic presented this paper. However the
concentrations produced by the H–M process in the Antarctic were generally
only a few per litre, approximately an order of magnitude lower than those
observed during the summer cases in the Arctic.
Conclusions
Detailed microphysics measurements made in Arctic stratocumulus cloud layers
during the early spring and summer have been presented.
Two spring and two summer cases were presented. The cloud layers during summer
cases spanned a warmer temperature range (∼ 0 ∘C ≥T > -10 ∘C)
than in spring (generally ∼-10 ∘C ≥T > -20 ∘C).
Spring case 2 had significantly higher aerosol concentrations (∼ 300–400 cm-3)
compared to the first spring case (∼ 50–100 cm-3). Despite this difference, ice number
concentrations were found to be similar in both spring cases, suggesting the source of the increased
aerosol concentrations was not providing additional IN that were efficient over the temperature
range of -10 ∘C > T > -20 ∘C.
In the spring cases, cloud layers appeared more uniform with steady increases in
LWC and cloud droplet size to cloud top, where low concentrations (< 1 L-1)
of ice were frequently observed to precipitate through the depth of the cloud layer. The small
irregular particles observed at cloud top grew to a median diameter ∼ 500 µm in
both cases with peaks in diameter > 1000 µm as the crystals descended
through the cloud. 2D-S imagery revealed the dominant growth habit to be dendritic in nature.
The summer cases consisted of multiple cloud layers that were observed to be more variable than
in the spring. However, liquid cloud top regions were still evident and ice was again observed to precipitate into the cloud layers below.
The maximum median ice number concentrations observed within cloud layers during the
summer cases were approximately a factor of 5 (or more) higher than in the spring cases. This enhancement
in the ice number concentrations is attributed to the contribution of secondary ice production through the H–M process.
This finding suggests that low level summer stratocumulus clouds situated in the H–M temperature
zone in the Arctic may contain significantly higher ice number concentrations than in spring clouds
due to the temperature range of the former spanning the active H–M temperature zone.
Predicted values from the DeMott et al. (2010) scheme of primary ice nuclei, using aerosol
measurements obtained during the science flights as input, tended to overpredict IN concentrations
compared to the observed maximum median ice crystal number concentrations during the spring, but underpredict
IN when compared to peak ice crystal concentrations. This variation can be attributed to uncertainties
in the application of the DeMott scheme. During the summer cases, due to contributions from secondary
ice production, the scheme predicted significantly lower values of ice particles than those observed.
We found some support for the riming indirect effect when comparing our spring cases. In spring
case 2 higher aerosol loadings and smaller droplets were observed and ice water contents were lower
than in spring case 1 (where aerosol concentrations were much lower). It is possible the smaller
droplets in case 2 reduced the riming efficiency leading to lower ice mass values.
Grosvenor et al. (2012) observed lower concentrations of aerosol > 0.5 µm
in the Antarctic when compared to similar measurements made in the Arctic. They found that IN
predictions using D10 agreed better with their observed peak ice concentration values rather
than their maximum mean values. They measured approximately an order of magnitude lower primary
ice concentrations in summer Antarctic clouds than in our spring Arctic cases, but did observe
enhancement through SIP in warmer cloud layers where concentrations increased to a few per litre.
These were still about an order of magnitude less than the enhanced concentrations observed in the
Arctic summer cases presented here, but were similar to the peak values observed in spring cases
over the Arctic (where no SIP was observed).
The Supplement related to this article is available online at doi:10.5194/acp-15-3719-2015-supplement.
Acknowledgements
This project was supported by the Natural Environment Research Council under
grant NE/1028296/1. Airborne data were obtained using the BAe-146-301
Atmospheric Research Aircraft [ARA] flown by Directflight Ltd and managed by
the Facility for Airborne Atmospheric Measurements (FAAM), which is a joint
entity of the Natural Environment Research Council (NERC) and the Met
Office.
Edited by: E. Weingartner
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