Introduction
Arctic mixed-phase clouds are long-lived, and widespread
single-layer stratocumulus (Sc) decks are common in the autumn, winter, and
spring. These clouds are maintained and driven by convection caused by strong
radiative cooling at the boundary layer (BL) inversion
e.g.. In numerical models,
mechanisms affecting the break-up of these Sc clouds – including glaciation
e.g. or break-up
into convective cumulus (as occurs in cold-air outbreaks, CAOs) – are
often too efficient, leading to radiative biases in the polar regions
.
Several studies
e.g.
have addressed the issue of premature glaciation of modelled mixed-phase Sc,
often concluding that the cause is an overactive ice phase and strong
influence of the Wegener–Bergeron–Findeisen (WBF) mechanism. The WBF
mechanism causes a constantly changing, unstable microphysical structure;
however, these clouds have been observed to persist for long periods of time,
and thus they have the opportunity to move geographically.
In a CAO, stable Arctic Sc decks are transported southwards from over the sea
ice to over the warm ocean. These clouds often display closed-cellular
structure at first, where narrow downdraught rings surround broad updraught
columns . Increased sensible heat
fluxes and BL depth promote the development of
precipitation through increased cloud turbulence .
Transitions between closed- and open-cellular convection have been the focus
of several studies, many of which consider warm, ice-free clouds
e.g..
Factors controlling this transition in CAOs are poorly understood, where the
mixed-phase state of the clouds adds further complexity.
In warm clouds, cleaner scenarios (with lower aerosol particle and cloud
droplet number concentrations) are susceptible to the formation of open cells
due to efficient precipitation development
.
However, drizzle formation has been found to be influenced more so by
larger-scale meteorology, such as moisture fluxes and temperature
fluctuations, than aerosol–cloud interactions .
Similarly in CAOs, thermodynamic interactions – namely diabatic processes
such as latent heat release from condensation and cloud-top radiative cooling
– have been shown to strongly influence the broadening of convective cells
. Such interactions are also thought
to have an important role in generating dynamical overturning in the
persistent mixed-phase Sc upstream in CAOs.
Regions of high surface pressure are often found upstream of CAOs in the
European Arctic . In the
high Arctic (≥ 80∘ N, over sea ice), such regions contribute
towards reduced cloud fractions
.
High-pressure systems are associated with large-scale subsidence and, in
turn, strong BL inversions . In warm
marine environments, such inversions have been shown to lead to a shallow BL
depth, increased cloudiness, and increased BL mixing
. Previous studies suggest that
large-scale subsidence may affect CAO cellular transitions
e.g. and can even reduce the lifetime
of liquid marine Sc modelled over a warming surface .
Subsidence associated with synoptic-scale meteorological features therefore
has the potential to influence the microphysical evolution of BL clouds;
however, the relationship between subsidence and mixed-phase cloud
microphysics has not yet been studied.
The role of microphysics–dynamics interactions in sustaining
microphysically unstable Arctic mixed-phase Sc is poorly understood;
therefore, it is imperative to assess such feedbacks to gain a holistic view
of their role in the Arctic system. By studying the cloud microphysical
response to external stressors, such as large-scale subsidence, we can better
evaluate the influence of environmental factors on the lifetime of
mixed-phase Sc in the Arctic. Here, we investigate the influence of
subsidence on a stable cloud, precipitating clouds, and a cloud forced by a
warming surface to demonstrate how subsidence can affect a variation of
microphysical scenarios common to the Arctic. By doing so, we will show which
microphysical feedbacks are affected by subsidence and test how the
combination of subsidence and a warming surface can affect BL development.
Methods
Model set-up
We use the UK Met Office Large Eddy Model LEM, to investigate the influence of large-scale
subsidence on mixed-phase marine Sc cloud microphysics. The set up is the
same as that used by , whose study gives further details
on the model itself. Momentum is conserved using the Piacsek–Williams
PW; centred difference scheme, whilst the total
variation diminishing (TVD) monotonicity-preserving scheme of
, known as ULTIMATE, is used for scalar advection
.
Cyclical boundary conditions and a damping layer (500 m below model lid)
were imposed. Vertical profiles of potential temperature (Θ), water
vapour mixing ratio (Qvap), and wind speed (U and V) were
implemented to initialise the model (Fig. ): these
profiles were extracted from previous LEM runs of Arctic mixed-phase Sc,
specifically from 10 h in the ocean case detailed by ,
where a primary ice parameterisation derived from observations from the
Aerosol-Cloud Coupling and Climate Interactions in the Arctic (ACCACIA)
campaign was implemented. These fields give a stable BL experiencing strong
(approximately 10–15 m s-1) N–S winds. A humidity inversion,
coinciding with the BL temperature inversion, is present in the initial
Qvap field (Fig. a): previous
studies e.g. have shown that
such inversions are often observed in the Arctic and may act as a source of
moisture to BL clouds below. Surface sensible and latent heat fluxes were
calculated by the model, using near-surface Θ and Qvap
values, to represent an oceanic surface. The microphysics scheme was used, providing
single-moment liquid (with a prescribed droplet number) and double-moment
ice, snow, graupel, and rain.
Profiles of potential temperature (Θ), water vapour mixing
ratio (Qvap), and wind speed (U, V) used to initialise the
LEM.
In large-eddy simulation (LES) models, large-scale subsidence (Wsub) is often imposed
as a tuning factor to maintain cloud-top height. In such models,
Wsub is usually calculated from an imposed large-scale
horizontal divergence. In practice, a constant divergence is assumed below
the BL temperature inversion – with zero divergence above – producing a
linear increase in Wsub with height below the inversion and a
constant vertical wind above it . Here,
we calculate Wsub using this method, increasing linearly with
altitude up to 1500 m. At altitudes > 1500 m,
Wsub=Wsub (1500 m) (representing zero divergence
aloft).
In the literature, the imposed horizontal divergence in LES studies often
ranges from 2.5 × 10-6 , through
3.75 × 10-6
, to
5 × 10-6 s-1 . In this study, three
different levels of imposed divergence – 0,
2.5 × 10-6, and 5 × 10-6 s-1 – are used
in four separate tests to investigate the role of large-scale subsidence in
both stable and precipitation-favouring microphysical scenarios.
The first three scenarios give an indication of how subsidence can affect the microphysics of Arctic
mixed-phase clouds that remain at approximately the same
latitude, whilst the fourth considers geographical movement.
Details of the tests conducted are listed in Table . The
control simulations apply no large-scale subsidence, apply a prescribed droplet
number concentration (Ndrop) of 100 cm-3, and use the
(hereafter, D10) parameterisation for primary ice
nucleation. As in , an approximation of the D10
parameterisation is used, where we assume an aerosol particle number
concentration of 2.20 cm-3 (for implementation in the parameterisation)
throughout the domain.
Test 1 (Sect. ) considers the effect of imposing different
levels of subsidence on the microphysical properties of a stable mixed-phase
Sc layer. In Sect. and , parameters relating to
development of precipitation in the liquid or ice phase are varied to test
the microphysical response under different levels of large-scale subsidence.
For example, we expect to enhance rain formation by decreasing
Ndrop (test 2, Sect. ) and increase snow
formation by increasing Nice (test 3, Sect. ).
However, decreasing Nice should sustain the liquid phase
against the WBF mechanism, also likely affecting rain formation. Therefore,
test 3 has the potential to affect both phases in the modelled clouds.
Simulation list.
Test
Run
Horizontal divergence
Prescribed Ndrop
Nice
Surface forcing
number
label
[s-1]
[cm-3]
parameterisation
[Y/N]*
1
CNTRL
OFF
100
D10
N
1
LOSUB
2.5 × 10-6
100
D10
N
1
HISUB
5.0 × 10-6
100
D10
N
2
CNTRL_Ndrop50/150
OFF
50/150
D10
N
2
LOSUB_Ndrop50/150
2.5 × 10-6
50/150
D10
N
2
HISUB_Ndrop50/150
5.0 × 10-6
50/150
D10
N
3
CNTRL_D10x0.5/2
OFF
100
D10 × 0.5/2
N
3
LOSUB_D10x0.5/2
2.5 × 10-6
100
D10 × 0.5/2
N
3
HISUB_D10x0.5/2
5.0 × 10-6
100
D10 × 0.5/2
N
4
CNTRL_SURFWARM
OFF
100
D10
Y
4
LOSUB_SURFWARM
2.5 × 10-6
100
D10
Y
4
HISUB_SURFWARM
5.0 × 10-6
100
D10
Y
* See text for further details.
Test 4 investigates larger-scale BL interactions with a stable mixed-phase Sc
layer. In CAOs, clouds move southwards off the sea ice and thus are subjected
to a warming ocean surface. Model simulations in tests 1, 2, and 3 do not
include any surface forcing: surface temperatures are allowed to vary through
feedbacks with the BL above, yet they are not monotonically forced to become
warmer. Such a forcing is applied in test 4 to investigate the combined
influence of subsidence and a warming surface, simulating motion southwards.
Near-surface temperatures are kept constant at 263.48 K until 5 h to allow
adequate time for model spin-up, after which they are forced to warm
linearly, in hourly increments, to 265.66 K at approximately 11 h 20 min.
This warming profile was artificially constructed based on approximated
ERA-Interim ECMWF reanalysis; 2 m temperature variations
over the ocean in the Svalbard archipelago, close to the sea ice, during a
cold-air outbreak 23 March 2013; seeand Fig. S1 in the Supplement for
further details.
We employ a horizontal resolution of 120 m over a 16 km × 16 km
domain centred on 71∘ N in the European Arctic to allow appropriate
shortwave (SW) radiation calculations to be made by the model. Vertical resolution for
the majority of model simulations was 20 m up to 1500 m, decreasing to
50 m between 1500 and 3000 m (domain lid) to reduce computational cost.
A second domain structure was tested to check sensitivities to this set up:
the high-resolution region was extended to 2300 m (again, reducing to 50 m
above this height). Whilst our results are largely unaffected by the
introduction of more vertical levels (not shown; see
Fig. S2), this modified domain structure was
applied in Sect. (test 4) due to increasing cloud height.
Results
Test 1: stable stratocumulus
(a, b) Time series of the domain-averaged LWP and IWP from
simulations imposing different magnitudes of large-scale subsidence.
Black: control cases; blue: low Wsub (LOSUB);
red: high Wsub (HISUB). (c–k) Planar X–Y
views of (c, f, j) vertical velocity at 1000 m (W1000),
(d, g, j) LWP, and (e, h, k) IWP. Planar views shown at 11 h.
Firstly, the influence of large-scale subsidence on the evolution of a stable
mixed-phase marine Sc is examined. Prescribed droplet number concentrations
and parameterised primary ice nucleation were not altered.
In all cases, the modelled clouds display the typical representation of a
liquid-topped Arctic single-layer mixed-phase Sc, with heterogeneous ice
number concentrations spread throughout the cloud below (not shown,
Figs. S3–S5).
Domain-averaged liquid- and ice-water paths (LWPs, IWPs) are shown in
Fig. a and b, where the first 3 h of each
simulation is excluded due to model spin-up. A stable Sc is modelled in the
absence of Wsub (CNTRL,
Fig. a). Increasing Wsub (LOSUB: low Wsub;
HISUB: high Wsub) strengthens the temperature inversion, as shown in
Table , thus reducing entrainment into the cloud from
above the BL. Consequently, both the LWP and the IWP increase after
approximately 5 h. These traces become more variable with time when
subsidence is imposed, as is particularly visible in the IWP traces,
suggesting increased dynamic activity in the modelled clouds. Longwave (LW)
radiative cooling is instrumental in allowing this convection to develop (Fig. S6).
Key BL and cloud microphysical parameters affected by large-scale
subsidence in test 1. ΔΘil is calculated across the
BL inversion and is listed to illustrate the inversion strength. Peak mass
sublimation/evaporation and production rates are quoted at 9 h, comparable
with Fig. .
Run
Peak TKEa,b
ΔΘil
Peak LWPb
Peak IWPb
Min/Max δQsg/δt
Minc/Max δQrain/δt
label
[m2 s-2]
[K]
[g m-2]
[g m-2]
[g kg-1 h-1]
[g kg-1 h-1]
CNTRL
1.0
7.52
62.9
17.5
-0.059/0.010
-2.9 × 10-4/1.3 × 10-4
LOSUB
1.3
7.74
65.4
18.2
-0.119/0.025
-5.2 × 10-4/2.5 × 10-4
HISUB
1.7
7.84
75.6
22.8
-0.158/0.041
-8.1 × 10-4/2.9 × 10-4
a At cloud top. b Maximum values attained within 12 h simulation time.
c Minimum below cloud.
(a–c) Total turbulent kinetic energy (TKE, shading) and
relative humidity (RH, white contours) time series for differing levels of
subsidence. (d–i) Vertical profiles, at 9 h, of (d) solid precipitation (snow + graupel) mass tendency
(δQsg/δt), (e) rain mass tendency
(δQrain/δt), (f) ice–liquid potential
temperature (Θil, solid) and total water mixing ratio
(Qtot, bold dashed), (g) vertical velocity variance
(w′2), (h) vertical flux of water vapour
(w′Qvap′), and (i) buoyancy flux (w′Θ′).
(g–i) w′2, w′Qvap′, and w′Θ′ are total
quantities (sub-grid + advected). w′2 is used as an indicator for
circulation strength, whilst the total (advected plus sub-grid) water vapour
and buoyancy fluxes illustrate the mean dynamical motions in the BL. A
combined measure of sub-grid and advected fluxes are shown as these are of
similar orders of magnitude and both make a non-negligible contribution to
the flux budget (not shown, Fig. S7). In
particular, the sub-grid w′Qvap′ fluxes are dominant in cloud
and near the surface, due to the stability of these layers. Area in grey
represents CNTRL cloudy regions.
Planar X–Y views of the vertical velocity at 1000 m (W1000), LWP, and
IWP fields at 11 h (Fig. c–k) further
illustrate the effect subsidence has on the spatial structure of the clouds.
With increasing Wsub, numerous regions of high LWP/IWP develop,
with heightened heterogeneity across the domain. Domain-wide variability in
W1000 also increases with Wsub. Broad updraught regions
surrounded by narrow downdraught rings become apparent. Localised regions of
high LWP and IWP can be associated with strong updraughts at 1000 m, and
lower IWPs mirror the shape of the downdraught rings around the updraught
regions. This locality becomes clearer with increasing Wsub
(Fig. i, k).
Figure shows a time series of turbulent kinetic energy (TKE) in panels a–c and
vertical profiles of key properties in panels d–i. Increasing
Wsub increases the snow and graupel mass tendencies below cloud
(Fig. d). Strong snow sublimation is simulated at
cloud top in all cases, with steady snow production in and below cloud.
Regions of enhanced δQsg/δt coincide with strong
rain evaporation (Fig. e); all of the rain
produced evaporates below cloud, and no rain mass reaches the surface.
Precipitation as snow does reach the surface; however, the spatial
distribution becomes more heterogeneous with increased Wsub
(not shown, Figs. S3–S5). Observational studies of
Arctic mixed-phase marine Sc and North Atlantic CAOs
have previously reported precipitation as
snow below cloud with little rain measured, indicating that our
idealised study is in broad agreement with measurements in this region.
A downward flux of heat and moisture into cloud top is modelled in all cases,
caused by the temperature and humidity inversions
(Fig. h, i): with increased levels of
Wsub, w′Θ′ increases more so in the sub-cloud layer,
whilst w′Qvap′ increases throughout the BL. Sub-cloud
enhancement of w′Θ′ coincides with the top of regions of enhanced
snow and graupel mass growth (Fig. d). Modelled
ice–liquid potential temperatures Θil,
following in the LO- and HISUB cases
are colder than the CNTRL throughout the BL
(Fig. f). All cases display a stable BL structure
in the lower 1200 m of the BL and an unstable structure within cloud. A
minor inversion is modelled at approximately 500 m in the CNTRL case which
is co-located with a total water mixing ratio (Qtot) inversion
and a moist surface layer (Fig. a).
TKE increases throughout the BL with increasing subsidence
(Fig. b, c) and peaks at cloud top in all cases,
likely influenced by the high evaporation and sublimations rates of rain and
snow at the BL-capping temperature inversion. In all simulations, TKE
typically increases with altitude through the BL. When subsidence is imposed,
these TKE profiles tend towards a coupled, well-mixed BL through the top-down
and bottom-up propagation of TKE. This coupling is particularly clear in the
HISUB case (Fig. c); however, the cloud-top peak
in TKE remains dominant throughout every case. Increasing Wsub
produces a more coupled, dynamic BL due to a heightened LWP, efficient LW
radiative cooling, and increased rain evaporation and snow growth below
cloud.
Test 2: droplet number concentration
The influence of large-scale subsidence on the formation of rain in a
mixed-phase marine Sc is now considered. Prescribed droplet number
concentrations were varied to a lower (Ndrop= 50 cm-3)
and higher (Ndrop= 150 cm-3) threshold to affect rain
formation: the modelled liquid mass is distributed amongst this
concentration, such that a lower (higher) concentration will yield larger
(smaller) cloud drops. Therefore, we expect the lower concentration of cloud
droplets to allow for more efficient rain formation.
conducted a similar sensitivity study when
studying Sc-to-cumulus transitions with an LES model and found that
decreasing droplet number concentrations, and enhancing precipitation,
significantly affected the transition efficiency.
Domain-averaged LWP (a) and IWP (b) time series
for simulations with different Ndrop whilst varying the imposed
Wsub. Black: control cases; blue: low
Wsub; red: high Wsub. (c–e) buoyancy flux (w′Θ′), (f–h) water vapour flux
(w′Qvap′), (i–k) vertical velocity variance
(w′2). Vertical profiles shown at 9 h.
From Fig. a, the Ndrop50 scenarios produce a
slightly greater LWP and IWP after 8 h than Ndrop100 or Ndrop150. Increasing
Ndrop has little effect on the LWP or IWP; the results of the
Ndrop100 and Ndrop150 cases are remarkably similar. Additionally, changing
Ndrop has little effect on the depth of the cloud layer
modelled in the CNTRL cases (shown by shading in
Fig. c–k). In general, varying
Wsub affects the modelled LWP, IWP, and dynamical fluxes more
than the microphysical changes (varying Ndrop).
A: change in δQsg/δt (g kg-1 h-1) (shading) between subsidence cases and the
corresponding CNTRL simulation for test 2. Red corresponds to increased
production, whilst blue shows increased sublimation relative to the associated
CNTRL. Nsg (L-1) is shown as contours. B: as
panel A, instead the change in δQrain/δt (g kg-1 h-1) is shown with Nrain (L-1) as
contours. (a–c) LOSUB, (d–f) HISUB.
Figure shows the mass production and
sublimation/evaporation rates of snow/graupel and rain relative to the CNTRL
in panels A and B respectively. Absolute domain-averaged number
concentrations from each subsidence simulation are overlaid as contours.
Varying Ndrop has only a minor effect on the time evolution of
the snow and graupel number concentration (Nsg). Snow mass
production rates (relative to the CNTRL) increase towards cloud base and
below cloud with increasing Wsub, whilst snow sublimation rates
at cloud top also increase. Non-zero snow concentrations reach the surface in
all simulations (Fig. A).
Figure B shows a contrasting trend for rain
production/evaporation. Decreasing Ndrop strongly affects
Nrain as expected; for example, Nrain increases
by approximately 9 L-1 between the HISUB_Ndrop100 and
HISUB_Ndrop50 cases. For the LOSUB comparison, Nrain
increases by approximately 6 L-1 in cloud. Increasing
Wsub enhances the Nrain produced by decreasing
Ndrop in the modelled cloud. δQsg/δt
at cloud base, relative to the CNTRLs, does not change significantly when
changing Ndrop, even with strengthened rain mass evaporation in
this region; however, the below-cloud enhancement of
δQsg/δt by increasing Wsub is
apparent in each case.
Increasing Ndrop has a smaller effect on Nrain
than decreasing it, as expected by the thermodynamic indirect effect; with
more droplets available, droplet size decreases due to less competition for
water vapour. Nrain decreases in Ndrop150 with respect to the
Ndrop100 or Ndrop50 cases, and the in-cloud mass production and below-cloud
evaporation rates are smaller. Despite this, increasing Wsub
still marginally increases the mass production/evaporation rates with respect
to the CNTRL_Ndrop150 case.
From these simulations, we suggest that the level of imposed large-scale
subsidence can significantly affect the liquid phase in clean mixed-phase Sc,
as Wsub positively forces the rain mass production/evaporation
rates modelled in these precipitation-favouring microphysical scenarios.
Test 3: ice number concentration
The influence of Wsub on a mixed-phase marine Sc when changing
ice number concentrations is now considered. Heterogeneous primary ice
formation is represented using the D10 parameterisation with aerosol number
concentrations calculated during the study by . Previous
studies
have shown that the lifetime of springtime single-layer mixed-phase clouds at
high latitudes is strongly dependent on Nice. Here, a lower
(Nice= D10 × 0.5) and higher (Nice= D10 × 2) threshold are implemented to change the number concentration of
modelled ice, and snow, particles.
As Fig. but with changing ice number
concentrations.
Figure illustrates the domain-averaged LWP and IWP for
test 3. The CNTRL cloud layer – as shown by the shaded area in
Fig. c–k – becomes shallower with
increasing Nice. When no subsidence is imposed (CNTRL,
black/grey lines Fig. a), decreasing
Nice increases the LWP as expected through the influence of the
WBF mechanism, whereas increasing Nice has the opposite effect.
However, in CNTRL_D10x2, both the LWP and IWP increase sharply
after 9 h (Fig. a, b). This LWP peak occurs
earlier with increasing Wsub (as shown by the blue and brown
traces in Fig. a). This trend can also be seen in the IWP traces. The cause of
this increase is not clear; however, it may be due to localised cloud
convection caused by the high Nice, which has been previously
modelled by .
Trios can be easily identified in Fig. a,
where decreasing Nice affects the LWP more so than altering
Wsub. Although the key factor influencing the LWP is
Nice, Wsub acts to produce LWPs which are stable,
or even increase, with time. In contrast, the CNTRL simulations typically
produce a decreasing trend (with the exception of the D10 × 2 scenario).
Wsub affects the modelled fluxes
(Fig. c–k) more so than altering
Nice; however, the exception to this trend is the high
Nice (D10 × 2) simulations, as subsidence does not
stimulate this scenario as clearly as the other microphysical scenarios
shown. Despite this, there are some notable differences in the flux profiles:
for example, the extremes in the w′Θ′ profiles are more exaggerated in
the LO- and HISUB cases than the CNTRL when a lower Nice is
modelled (Fig. c–e). These comparisons
suggest that Wsub can have a strong dynamical effect on
liquid-dominated mixed-phase clouds, but its influence on those with more ice
is limited.
As Fig. , but instead the ice number
concentration is varied (test 3).
From Fig. A, Nsg increases
with increasing Nice and decreases only slightly between the
LO- and HISUB cases. Additionally, snow mass sublimation rates at cloud top
and production rates below cloud increase with increased Wsub. The
increase in LWP and IWP in CNTRL_D10x2 at 9–10 h (Fig. 6a) affects our comparison,
as increased snow mass is modelled at this time; therefore, the LO- and
HISUB_D10x2 simulations produce less snow mass than the baseline.
Efficient rain mass production takes place with a lower Nice,
as shown in Fig. B, due to the greater
liquid mass being distributed over a fixed Ndrop.
δQrain/δt increases with Wsub in
the D10 × 0.5 case. In-cloud mass production and below-cloud rain
evaporation rates increase in LO- and HISUB_D10x0.5 relative to
CNTRL_D10x0.5, as do the snow growth rates below cloud
(Fig. B). With less ice available, cloud-top radiative
cooling becomes more efficient due to a heightened liquid fraction
(Fig. a), increased rain formation
(Fig. Bd), efficient snow growth
(Fig. Ad), and vigorous turbulence
(Fig. i). Consequently, cloud-top height
increases in D10 × 0.5, whilst this ascent is suppressed in D10 × 2.
This ascent adds complexity into the interpretation of
Fig. Aa, Ad, Ba, and Bd as we are comparing
clouds which are ascending at different rates. Strong cloud-top
evaporation/sublimation of rain/snow is modelled above 1500 m with the
ascending CNTRL cloud, whilst the LO- and HISUB cases have no activity at
these altitudes; therefore the anomaly between the Wsub and
CNTRL simulations appears positive at these heights.
LWP and below-cloud rain evaporation are enhanced in CNTRL_D10x0.5 with
comparison to CNTRL_D10 and CNTRL_D10x2; however, w′2 is not
strongly affected (Fig. i–k).
Figure shows δQsg/δt and
δQrain/δt at 9 h to illustrate differences between
the D10 × 0.5, D10, and D10 × 2 CNTRL cases.
δQsg/δt is similar in the D10 and D10x0.5
simulations, whilst the LWP and rain evaporation/production processes are
positively forced by decreasing Nice. In the turbulent
subsidence cases, δQsg/δt does increase below cloud
with increasing Wsub (Fig. A).
This is the only key difference between decreasing Nice and
increasing Wsub; therefore, increased latent heating through
snow growth at cloud base – alongside heightened below-cloud rain
evaporation and efficient cloud-top radiative cooling via a high LWP – is
required to generate the heightened TKE (as illustrated here by w′2) in
these scenarios. Convection is suitably induced in LO- and HISUB_D10x0.5
as the modelled snow growth rates are greater
(Fig. S8). Whilst the same Nice
is modelled in each of these scenarios, the subsidence cases produce a much
colder BL than CNTRL_D10x0.5; therefore, the environmental conditions in
LO- and HISUB_D10x0.5 facilitate snow growth below cloud, whilst the
control produces comparatively inefficient growth conditions.
Microphysical tendencies comparison of CNTRL_D10,
CNTRL_D10x0.5, and CNTRL_D10x2. Vertical profiles, at 9 h, of solid
precipitation (snow + graupel) mass tendency
(δQsg/δt) and rain mass tendency
(δQrain/δt) are shown. Area in grey represents
CNTRL_D10 cloudy regions.
w′2 is greatest with the LO- and HISUB_D10x0.5 simulations
(Fig. i) due to dynamical stimulation by the
heightened rain mass evaporation and snow mass production at cloud base
(Fig. B). The clouds are more dynamic with
increasing Wsub, and it is the liquid-dominated (D10x0.5)
clouds which are more vulnerable to this dynamic stimulation. Clouds with
greater Nice suppress the liquid phase; therefore,
Nice has a key role in mediating the strength of turbulent
overturning generated in the mixed-phase clouds.
Test 4: surface warming
As described in Sect. , our previous tests consider
scenarios that would elicit a microphysical response whilst keeping the
surface boundary conditions approximately constant. Tests 1–3 are idealised
and are not representative of the environmental forcings encountered when
these clouds move southwards: observations show a sharp near-surface air
temperature gradient in CAO flows transitioning southwards from the cold sea
ice to the warm ocean. To address this, we further consider the combined
dynamical impact of large-scale subsidence and a warming surface on both the
BL and cloud microphysical structure. Whilst our domain size is not
appropriate to resolve the explicit transition from closed- to open-cellular
convection far downstream in a CAO, we will show how large-scale subsidence
influences the microphysical stability of a stable mixed-phase marine Sc over
a warming surface, upstream from this strong cellular convection.
As Fig. but with the addition of a warming
surface (test 4). Planar views (c–k) are shown at 10 h to capture
the bulk cloud structure coinciding with the CNTRL_SURFWARM peak in LWP
and IWP shown in panels (a) and (b).
More convection is modelled with time under the destabilising conditions of a
warming surface (Fig. ). Domain-averaged LWPs and IWPs
are similar in the subsidence cases, increasing almost monotonically with
time (Fig. a, b). Slightly greater LWPs are
modelled in HISUB_SURFWARM than in the LOSUB counterpart. Subsidence acts
to produce greater LWPs and IWPs than the CNTRL up to approximately 10 h, at
which point CNTRL_SURFWARM undergoes a significant convective
transformation marked by a sharp increase in both LWP and IWP. Planar views
of Fig. c–e show that, at this time, the
CNTRL_ SURFWARM cloud contains numerous regions of very high LWP
(> 200 g m-2) and IWP (> 50 g m-2) co-located with strong
updraughts at 1000 m.
As Fig. but with the addition of a warming surface
(test 4). Note the different colour scale in panels (a)–(c) and
extended x range over which data are shown in all panels except (f),
with comparison to Fig. . Vertical profiles (panels
d–i) are shown at 10 h.
Cloud top and surface sources of TKE couple in all cases
(Fig. a–c). The CNTRL case couples rapidly at
approximately 10 h (Fig. a), coincident with the
peak in LWP and IWP shown in Fig. a, b.
Within approximately 1.5 h, the two TKE sources decouple again. Cloud top
and surface sources of TKE dominate the LO- and HISUB_SURFWARM profiles
separately from approximately 7 h onwards. LOSUB_SURFWARM displays a
similar coupling at 10 h to CNTRL_SURFWARM, yet it remains coupled
afterwards and undergoes a second TKE burst between 11 and 12 h. TKE
evolution in HISUB_SURFWARM is more gradual than the CNTRL and LOSUB
cases: the top-down and bottom-up propagation of TKE steadily increases with
time to couple the separated cloud and surface sources.
Cloud-top height increases in CNTRL_SURFWARM
(Fig. a), whilst this ascent is strongly
suppressed in HISUB_SURFWARM (Fig. c) and
marginally suppressed in LOSUB_SURFWARM
(Fig. b). Negative w′Θ′ fluxes at cloud
top again suggest entrainment of warm air into the cloud layer from above the
BL in each case; however, this flux is stronger in CNTRL_SURFWARM than in
the subsidence cases, indicating that greater entrainment rates are
accompanying the cloud-top ascent.
Key BL and cloud microphysical parameters affected by large-scale
subsidence in test 4. Mass tendencies are quoted at 10 h, comparable with
Fig. .
Run
Peak TKEa,b
ΔΘil
Peak LWPb
Peak IWPb
Min/Max δQsg/δt
Minc/Max δQrain/δt
label
[m2 s-2]
[K]
[g m-2]
[g m-2]
[g kg-1 h-1]
[g kg-1 h-1]
CNTRL
2.8
7.63
147.7
32.7
-0.266/0.083
-4.8 × 10-4/1.8 × 10-3
LOSUB
3.9
8.06
119.8
39.6
-0.234/0.051
-1.3 × 10-3/4.5 × 10-4
HISUB
2.3
8.37
118.3
32.7
-0.284/0.071
-1.3 × 10-3/6.6 × 10-4
a At cloud top. b Maximum values
attained within 12 h simulation time. c Minimum below cloud.
Significantly larger values of w′Qvap′ and w′Θ′ are
modelled below cloud in the CNTRL_SURFWARM simulation
(0.052 g kg-1 m s-1 and 0.045 K m s-1, respectively)
than in the subsidence cases, coinciding with the rapid BL coupling shown in
Fig. a. Convective activity increases at this
time, with w′2 increasing up to 0.90 m2 s-2 in cloud
alongside a peak (cloud top) TKE of 2.8 m 2 s -2
(Table ). Additionally, rain mass production is enhanced
in CNTRL_SURFWARM; however, below-cloud rain evaporation is still weaker
than in the LO- and HISUB_SURFWARM simulations. Rain evaporative cooling
below cloud in LO- and HISUB_SURFWARM acts to decouple the surface and
in-cloud heat sources from each other (Fig. i).
As a result, the w′Θ′ profiles swing through significant extremes
below cloud: from 0.021, through -0.011, to
0.028 K m s-1 in the HISUB_SURFWARM case. Furthermore, the warming
surface produces an unstable Θil profile at the surface in
each simulation (Fig. f).
Z–X slices for the CNTRL_SURFWARM case at 10 h.
(a) Total ice mass mixing ratio (Qisg, shading) and liquid water
mass mixing ratio (Qliq, contours). (b) Total ice number
concentration (ice + snow + graupel, Nisg, shading) and rain number concentration
(Nrain, contours). (c) Vertical velocity (W, shading) and
relative humidity (RH, contours). Identified detached below-cloud cumuli are highlighted
by red ellipses, and cumuli merged with the Sc are indicated by white ellipses.
Z–X slices of several microphysical variables from CNTRL_SURFWARM are
shown in Fig. to illustrate the cloud
structure at 10 h. In the bottom panel, below-cloud cumuli form which either
couple to the Sc layer (white ellipses) or remain separate (red ellipses).
Cumuli are identified by adjacent updraught/downdraught regions with
100 % relative humidity (or close to 100 %). These cumuli structures are clearly
visible in the Qliq contour field (top panel,
Fig. ). Cumuli can be seen from 8 h
onwards and become more frequent with time. At this time, two
spatially close cumuli form at approximately -7000 and -3500 m, marking
the boundaries of a detraining layer of moisture above cloud top.
Additionally, a similar, completely detached moist layer can be seen above
cloud top coinciding with the 6000 m cumulus.
Z–X slices for the HISUB_SURFWARM case at 12 h. Panels are
arranged similarly to Fig. .
HISUB_SURFWARM has much larger updraught and downdraught regions than
CNTRL_SURFWARM: from approximately 11 h onwards, these often extend to
almost the full height of the BL
(Fig. ). No distinct sub-cloud
cumuli can be identified in HISUB_SURFWARM, whereas these are common in
CNTRL_SURFWARM (Fig. ): the addition
of subsidence acts to suppress their formation and allow a more homogeneous
Sc layer to be maintained in a BL undergoing top-down and bottom-up coupling
of TKE. The coupling process is more gradual in HISUB_SURFWARM than the
CNTRL or LOSUB counterparts, suggesting that subsidence plays a role in
whether or not this rapid TKE coupling and cloud-top ascent can take place.
Discussion
Effect of subsidence on bulk cloud properties
Imposing large-scale subsidence in simulations of marine Arctic mixed-phase
Sc increases the LWP and IWP of the modelled clouds through increased
convective activity throughout the domain (Fig. ).
Wsub does not affect the cloud depth
(Figs. , ); only
Nice notably affects the modelled cloud depth
(Fig. ). Dynamical stimulation by subsidence – which
would sustain a mixed-phase Sc for longer against the WBF mechanism – may
therefore have been previously missed in observations and modelling studies.
Increasing Wsub has a greater effect on the liquid phase than
the ice phase
(Figs. , , );
however, increasing subsidence causes the development of heterogeneity in the
LWP and IWP fields, leading to instabilities in the modelled clouds. In
particular, the radiative properties of the clouds would be affected by the
heterogeneous spread in LWP, where regions of high LWP would be more
reflective to incoming SW radiation and
more efficiently cooled via longwave radiative cooling.
Localised regions of high IWP are typically co-located with updraughts in our
simulations, likely due to the method of parameterising ice nucleation in our
model. Namely, additional nucleation mechanisms (e.g. contact, immersion) are
not represented to give us a predictable source of ice number concentrations
similar to. These mechanisms would likely influence
our results if they were explicitly resolved in our model; for example, we
would expect contact nucleation in downdraughts, through interaction with
interstitial aerosol particles.
Subsidence strongly influences the LWP; however, increasing
Wsub marginally increases the domain-averaged IWP
(Fig. b).
Figure b shows that the peak IWP attained
by CNTRL_D10x2 is also achieved in the HISUB_D10 case, suggesting that
increasing Wsub can have a similar effect on the bulk ice
properties of the cloud as increasing Nice. However, a much
larger LWP is also modelled when subsidence is imposed, creating a
microphysical structure that may be more robust against the WBF mechanism.
This may allow mixed-phase conditions to be sustained for longer against a
higher Nice – a problem that is often faced when modelling
Arctic mixed-phase Sc
.
Effect of subsidence on microphysics and precipitation
In the chosen microphysical scenarios that may affect precipitation
development in mixed-phase marine Sc, Wsub enhances rain
evaporation at cloud top and base. Increased subsidence leads to larger rain
mass production rates and a greater Nrain within cloud, and
this effect is particularly clear when lowering either Ndrop
(Ndrop50, Fig. ) or Nice
(D10 × 0.5, Fig. ). In these cases, the increase
in Nrain due to subsidence is less than can be attributed to
the microphysical changes; for example, an increase of approximately
6 L-1 is modelled in the Ndrop50 scenario due to increasing
Wsub, whilst an increase of approximately 9 L-1 is
achieved by lowering Ndrop from 100 to 50 cm-3
(Fig. B).
From tests 2 and 3, Wsub amplifies the modelled turbulence in
scenarios allowing for efficient rain formation (e.g. Ndrop50,
Fig i). Wsub also acts to
promote more turbulence (Fig. k) and rain
formation (Fig. B) in a microphysical
scenario that produces little rain in its absence (Ndrop150). Conversely,
increasing Nice in test 3 does not have the same effect, and
Wsub does little to promote turbulence in this scenario. Whilst
the ice categories do little to stimulate convection, they are responsible
for suppressing rain formation; for example, a higher Nice (and
thus, Nsg) suppresses the strong rain production/evaporation
processes modelled at a lower Nice
(Fig. B). With weakened rain formation and
evaporation, less vigorous overturning is modelled in D10 × 2 than D10
or D10 × 0.5. Whilst the liquid phase drives the development of
dynamical overturning, the ice phase has a strong influence – through the
WBF mechanism – on whether this convective activity can actually develop.
Similarly, total ice number concentrations (ice + snow + graupel,
Nisg, Fig. b) are
largely unaffected by a warming surface (with comparison to
Fig. S3b); however, both
Qliq and Nrain increase. Precipitation formation
is enhanced in downdraught regions
(Figs. , ).
Weaker below-cloud rain evaporation occurs in CNTRL_SURFWARM
(Fig. e), and the upward propagation of heat and
moisture from the surface causes distinct cumuli to form below cloud and join
with cloud base. These cumuli dynamically stimulate the cloud from below
(Fig. ) and have a similar effect on the
cloud as the introduction of subsidence in tests 1–3; for example, the
warming surface allows a greater Nrain to form in cloud
(Fig. ). In fact, Nrain in
CNTRL_SURFWARM is much more comparable with the corresponding
domain-averaged values of the LO- and HISUB_Ndrop50 simulations in test 2
(Fig. B) – the efficient-liquid-precipitation cases – than any of the previous control simulations.
These findings indicate that subsidence has the potential to positively force
the liquid phase in Arctic mixed-phase marine Sc whilst having little effect
on the ice phase. presented observations of cloud
microphysics over the transition from sea ice to ocean and found that the ice
phase changed little under the dynamical evolution of the BL, whilst the
liquid water content increased four-fold. Therefore, mixed-phase clouds with
low number concentrations of primary ice, such as those commonly observed in
the springtime Arctic, may be vulnerable to dynamical changes induced by
subsiding air from above or a warming surface from below.
Effect of subsidence on the BL and dynamics
In tests 1–3, convective activity increases with Wsub through
increased BL TKE and below-cloud w′2. Solar heating acts to marginally
offset the formation of defined closed-cellular structure; however, the
cloud-driven convection is strongly dependent on cloud-top LW radiative
cooling (see Fig. S6). Additionally, rain mass
formation rates, number concentrations, and the domain-averaged LWP increase
with increasing Wsub. This finding mirrors the conclusions of
, where the authors found that increasing the
resolved TKE and/or temperature positively influences the liquid phase in an
ice-saturated environment, as these conditions contribute towards sustaining
water saturation.
In the absence of surface warming, all modelled BLs display a stable
Θil profile. This stability is likely influenced by the
stable conditions used to initialise the model, and one must note that only a
single set of initial conditions were used in this study. A moist layer is
maintained close to the surface in the CNTRL simulation
(Fig. a), below the sub-cloud mixed layer,
whereas this moisture source is eroded in the subsidence cases. Additionally,
the CNTRL case presents a minor BL Θil inversion, and a
stronger Qtot inversion, at approximately 500 m. The
combination of these inversions and the moist surface layer suggests that the
CNTRL simulation is, in fact, more strongly decoupled from the surface than
the subsidence cases at the time step shown (9 h, Fig. ).
However, the subsidence cases display a similar strongly decoupled profile in
TKE to the CNTRL at earlier times (e.g. 5 h, Fig. ). TKE
increases with time in the BL when subsidence is imposed, and it promotes
top-down mixing of TKE through the sub-cloud layer towards the surface by the
end of the simulations, tending towards a coupled profile. However, cloud-top
TKE still dominates the BL profiles in the LO- and HISUB cases
(Fig. b, c), suggesting that mixing throughout
the BL is still not homogeneous and the clouds remain approximately decoupled
from the surface by the termination time of the simulations. This decoupling
allows radiative cooling at cloud top and evaporative cooling/latent heating
below cloud to drive convective activity in the cloud layers, irrespective of
surface sources.
With a larger LWP, stronger cloud-top radiative cooling is expected,
promoting a greater cloud-top height .
Subsidence acts to restrict cloud-top ascent by reinforcing the BL
temperature inversion (Table ), thus lowering the
entrainment rate of air from above. Cloud LWP increases in the absence of
notable entrainment, allowing for stronger cloud-top LW radiative cooling and
subsequent precipitation development within cloud. BL temperatures are
therefore cooler with imposed subsidence than without
(Fig. i), due to the combined effect of reduced
entrainment, strong cloud-top radiative cooling, and enhanced evaporative
cooling below cloud.
A lack of subsidence combined with a warming surface acts to push cloud top
significantly higher, and increase the LWP, through the formation of the
below-cloud cumuli (namely in CNTRL and LOSUB_SURFWARM,
Fig. d). Higher levels of Wsub
act to stabilise the Sc layer and suppress cumuli formation from the warming
surface (as is seen in the CNTRL_SURFWARM case). TKE production is
positively influenced in the CNTRL and LOSUB_SURFWARM cases, with strongly
separated cloud and surface sources, and peak values approximately 3
times greater than modelled in test 1 (Tables
and ). Cloud-top TKE splits in two in both CNTRL and
LOSUB_SURFWARM (Fig. a, b); however, it is
unlikely that this is a domain artefact as the vertical resolution is
consistent through this altitude range. It is possible that the PW advection
scheme is introducing spurious oscillations into the advected quantities,
caused by the the sharp gradient at the cloud boundary due to the formation
of these dynamic cumuli as discussed by. Peak TKE is
only marginally stronger in HISUB_SURFWARM than in test 1
(Tables and ), suggesting that higher
Wsub offsets the efficient in-cloud TKE production which occurs
when the system is additionally forced by a warming surface. By suppressing
the formation of below-cloud cumuli, subsidence acts to produce a stable, yet
dynamic, Sc layer, whilst strong convection and spatial heterogeneity are
simulated with low or no subsidence. With more heterogeneity, there is an
increased likelihood for instability in the cloud layer, which will likely
influence the fate of the cloud downstream.
Role of domain resolution
Whilst CAOs are discussed to motivate our study, we must stress that our
chosen domain configuration is not optimal for the explicit study of
Sc-to-cumulus transitions downstream in a CAO. Large high-resolution domains
are required to accurately resolve the small-scale microphysical processes
within these phenomena ; however, our domain size
and resolution are restricted by computational expense.
demonstrated that our spatial resolution may allow
entrainment rates to be overpredicted by approximately 50 %
. Whilst the authors concluded that the resolution
imposed here can still provide a useful insight into BL evolution,
accurately resolved turbulence requires higher spatial resolution.
found that a higher-resolution set-up produced
enhanced BL convection and a deeper BL depth. Furthermore,
found that the simulated vertical mixing of
vapour and Θ fields improved, and the modelled LWP increased, in their
open-cellular convection simulations by increasing spatial resolution.
Influence of domain resolution on changing imposed large-scale
subsidence. Only the CNTRL and HISUB cases are considered. LWP (a) and IWP (b) time series for simulations with 120 m resolution
(default configuration) and 60 m resolution (high-resolution configuration).
Black: CNTRL, default; grey: CNTRL, high resolution;
red: HISUB, default; and pink: HISUB, high resolution.
(c–h) Vertical profiles (at 9 h) of (c) solid
precipitation (snow + graupel) mass tendency
(δQsg/δt), (d) rain mass tendency
(δQrain/δt), (e) ice–liquid potential
temperature (Θil, solid) and total water mixing ratio
(Qtot, dashed), (f) buoyancy flux (w′Θ′),
(g) vertical flux of water vapour (w′Qvap′), and
(h) total turbulent kinetic energy (TKE). Fluxes shown are total
quantities (sub-grid + advected). Area in grey represents
CNTRL_Δx120m cloudy regions.
To test the influence of resolution on our findings, we increase the
horizontal resolution to 60 m (Δx) and the vertical resolution to
10 m, whilst maintaining the domain height. This set-up therefore decreases
the spatial extent of the domain by half in both X and Y. Vertical resolution
was 10 m up to 2000 m, decreasing to 20 m above this height. By increasing
our model resolution, we aim to provide a more accurate representation of the
modelled entrainment rates. Due to computational expense, only two test cases
are considered: the CNTRL and HISUB simulations from test 1
(Sect. ).
Little difference between the domain-averaged LWP and IWP can be identified
between the CNTRL cases (black/grey,
Fig. a, b). In the HISUB example,
increasing the model resolution amplifies the irregularities in both the LWP
and IWP traces. In particular, the IWP is significantly more variable with
time than in the default set-up.
In general, increasing the resolution does not alter the trends identified
previously – for example, the positive below-cloud moisture fluxes, higher
below-cloud rain mass evaporation and snow mass growth rates, and increased
TKE with increasing Wsub. In fact, it should be noted that the
below-cloud rain mass evaporation rates are enhanced with comparison to the
coarse-resolution HISUB case, suggesting that the evaporation rates shown in
Sect. , , and may be
underestimated. The Qtot profiles illustrate clear decoupling
in the CNTRLs, with a weaker inversion in the HISUB cases. Additionally, both
Δx60 simulations produce a greater TKE peak towards the surface, in
addition to the peak simulated at cloud top, due to the dominating influence
of the sub-grid contribution to the TKE towards the surface
(Fig. h).
Whilst we can test the influence of increased resolution on our findings,
increasing our domain size would be too computationally expensive for our
set-up. Larger domains are often used to allow mesoscale interactions between
developing open convective cells to be resolved.
suggest that a domain of 100 × 100 km,
with 50–100 m spatial resolution, is required to truly encapsulate any
mesoscale interactions between developing convective cells in CAOs. We cannot
speculate what mesoscale interactions may occur between the different
scenarios presented here; however, one must note that such interactions have
been previously simulated to occur over the transition between closed and
open convective cells in CAOs; thus these effects should be investigated in
further work.
Conclusions
Large-scale subsidence is often imposed in LES models as a tuning factor to
maintain cloud-top height; however, the influence of this parameter on
mixed-phase cloud microphysics has not been previously investigated. Here, we
have shown how large-scale subsidence affects the microphysical structure of
Arctic mixed-phase marine Sc using the UK Met Office Large Eddy Model
. By subjecting four idealised
scenarios – a stable Sc, varied droplet (Ndrop) or ice
(Nice) number concentrations, and a warming surface – to
different levels of subsidence, we have identified a clear relationship
between subsidence and convection development, with potential implications
for mixed-phase BL clouds forming in the ocean-exposed Arctic regions.
Key features identified in this study are as follows:
With no surface forcing (tests 1–3), increasing the imposed large-scale subsidence (Wsub)
reinforces the BL temperature inversion and thus reduces entrainment from the free troposphere. With less air
from aloft mixing into the clouds, a greater LWP (and often, IWP) develops, allowing for efficient precipitation
development, cloud-top radiative cooling, and downdraught production. All of the rain produced evaporates below
cloud. The combination of strong cloud-top radiative cooling, below-cloud rain evaporative cooling, and latent
heating from snow growth at cloud base generates more TKE within the BL. These three requirements combine to
form a feedback loop consisting of LWP, below-cloud rain evaporation/snow growth, and TKE development, positively forced by the magnitude of Wsub.
In microphysical scenarios which promote efficient rain production (low Ndrop or low
Nice), Wsub enhances rain mass production and evaporation rates, TKE at cloud
top and at the surface, and turbulent activity throughout the BL. Modelled Nrain increases
with Wsub, whilst Nsg marginally decreases. Modelled rain evaporates efficiently,
coinciding with regions of snow growth. These microphysical processes stimulate the cloud dynamically by
introducing perturbations in moisture and temperature below cloud. Only precipitation as snow reaches the
surface, mirroring observations of mixed-phase marine Sc in the Arctic and in CAOs.
Altering the ice phase feeds back onto the liquid phase through the influence of the WBF mechanism
(test 3, Fig. ). Nice has a key role in mediating the strength of
turbulent overturning induced in these mixed-phase clouds by suppressing the liquid phase. However,
Nice is also a crucial component at the opposite end of the scale: there needs to be enough
ice present to produce enough latent heating via depositional growth to force convection from cloud base.
With more dynamical motion, the liquid phase may be sustained more effectively against the WBF mechanism.
This is a crucial result for the understanding of mixed-phase Sc in the Arctic – particularly in the
Arctic spring – where high-pressure, stable conditions are common across the region. These clouds have been
observed to persist for long periods of time, and subsidence caused by large-scale meteorology could be acting
to sustain these clouds microphysically against dissipation or glaciation.
The feedbacks identified from test 1–3 are not so clearly related when a warming surface is
additionally imposed: significantly larger values of w′Qvap′ and w′Θ′ are modelled
with no Wsub, coinciding with the rapid BL coupling shown in Fig. a.
In-cloud rain production rates produced in CNTRL_SURFWARM are also much greater than without surface forcing
in test 1. A warming surface, with a lack of subsidence, acts to dynamically stimulate the modelled cloud from
below, similar to how subsidence stimulates it from above. Below-cloud cumuli form in CNTRL_SURFWARM, and
to a lesser extent in LOSUB_SURFWARM, which act to push cloud top higher, generate high LWPs, and cause
significant spatial heterogeneity in the cloud layer. This cumuli formation is suppressed when under high
levels of subsidence (HISUB_SURFWARM); the combination of these two forcings counteract one another to
produce a stable, yet dynamic, Sc layer.
This study presents a clear relationship between large-scale subsidence and
the development of convection in liquid-dominated mixed-phase clouds common
to the Arctic. We propose that the influence of large-scale subsidence in
both Arctic mixed-phase marine Sc and CAOs should be considered in further
work, using models of different spatial scales. In particular, it would be
beneficial to study the development of CAO flows – with a high-resolution,
large domain – under a transitional profile of subsidence, i.e. flowing from
a high-pressure region. Our results suggest that a high Wsub
will amplify turbulent activity and rain production/evaporation in any stable
mixed-phase Sc modelled, and a weakening of subsidence alongside a warming
surface will likely promote cloud-top ascent, below-cloud cumuli formation,
and strong spatial heterogeneities throughout the cloud layer. Therefore,
further investigating the role of subsidence in CAO flows will be beneficial
to our ability to accurately model and understand the break-up of these cloud
decks. More generally, comprehending the physical impact of subsidence on
marine mixed-phase cloud microphysics at higher latitudes will allow us to
better predict how clouds in the Arctic region may change in the depleted-sea-ice future.