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Dynamical Effects of Aerosol Perturbations on Simulated Idealized Squall Lines
ZACHARY J. LEBO* AND HUGH MORRISON
Mesoscale and Microscale Meteorology Division, National Center for Atmospheric Research,1 Boulder, Colorado
(Manuscript received 12 May 2013, in final form 5 October 2013)
ABSTRACT
The dynamical effects of increased aerosol loading on the strength and structure of numerically simulated
squall lines are explored. Results are explained in the context of Rotunno–Klemp–Weisman (RKW) theory.
Changes in aerosol loading lead to changes in raindrop size and number that ultimately affect the strength of
the cold pool via changes in evaporation. Thus, the balance between cold pool and low-level wind shear–
induced vorticities can be changed by an aerosol perturbation. Simulations covering a wide range of low-level
wind shears are performed to study the sensitivity to aerosols in different environments and provide more
general conclusions. Simulations with relatively weak low-level environmental wind shear (0.0024 s21) have
a relatively strong cold pool circulation compared to the environmental shear. An increase in aerosol loading
leads to a weakening of the cold pool and, hence, a more optimal balance between the cold pool– and environmental shear–induced circulations according to RKW theory. Consequently, there is an increase in the
convective mass flux of nearly 20% in polluted conditions relative to pristine. This strengthening coincides
with more upright convective updrafts and a significant increase (nearly 20%) in cumulative precipitation. An
increase in aerosol loading in a strong wind shear environment (0.0064 s21) leads to less optimal storms and
a suppression of the convective mass flux and precipitation. This occurs because the cold pool circulation is
weak relative to the environmental shear when the shear is strong, and further weakening of the cold pool with
high aerosol loading leads to an even less optimal storm structure (i.e., convective updrafts begin to tilt
downshear).
1. Introduction
Recently, the sensitivity of deep convective clouds to
anthropogenic aerosol perturbations has received considerable attention in the literature (e.g., Khain et al.
2004; Khain and Pokrovsky 2004; Khain et al. 2005;
Wang 2005; Koren et al. 2005; Grabowski 2006; Seifert
and Beheng 2006; Teller and Levin 2006; Van den
Heever et al. 2006; Fan et al. 2007; Tao et al. 2007; Van
den Heever and Cotton 2007; Khain et al. 2008; Lee et al.
2008b,a; Rosenfeld et al. 2008; Fan et al. 2009; Khain and
Lynn 2009; Koren et al. 2010; Noppel et al. 2010; Ekman
et al. 2011; Lee 2011; Lebo and Seinfeld 2011; Grabowski
* Current affiliation: Cooperative Institute for Research in Environmental Sciences, National Oceanic and Atmospheric Administration, Boulder, Colorado.
1
The National Center for Atmospheric Research is sponsored
by the National Science Foundation.
Corresponding author address: Zachary J. Lebo, National Center
for Atmospheric Research, P.O. Box 3000, Boulder, CO 80307.
E-mail: [email protected]
DOI: 10.1175/MWR-D-13-00156.1
Ó 2014 American Meteorological Society
and Morrison 2011; Seifert et al. 2012; Morrison 2012;
Tao et al. 2012; Lebo et al. 2012; Storer and van den
Heever 2013). Because aerosols are fundamentally linked
to the formation of cloud droplets and ice crystals in our
atmosphere, it should come as no surprise that changes
in the ambient concentration of these particles may
lead to changes in cloud properties. However, because
of the complexity of these systems (i.e., mixed-phase
microphysics, dynamical feedbacks, radiative feedbacks, etc.), understanding how an increase in ambient
aerosol number concentration affects macroscale features is highly challenging. Our understanding of the
effects of increased aerosol loading on the warm region
of these clouds is rooted in the work of Gunn and
Phillips (1957) and Squires (1958) whereby it was shown
that increases in aerosol number suppress collision–
coalescence and thus mitigate the formation of precipitation. Yet, more recent studies have suggested that even
in warm clouds the effects of aerosols can be quite complex due to feedbacks between microphysics and dynamics (e.g., Ackerman et al. 2004; Lu and Seinfeld
2005; Wood 2007; Bretherton et al. 2007; Chen et al. 2011).
Moreover, the complexities of the extensive mixed-phase
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region in deep convective clouds result in numerous
other changes that may ultimately lead to a net increase
or decrease in precipitation.
Several studies have suggested that deep convection is
intensified in polluted compared to pristine environments (e.g., Tao et al. 2007; Fan et al. 2009; Rosenfeld
et al. 2008; Lebo and Seinfeld 2011; Lebo et al. 2012),
while others indicated little to no sensitivity (e.g., Khain
and Lynn 2009; Morrison 2012). Convective invigoration in these studies has often been explained through
increased latent heating in polluted conditions (e.g., Van
den Heever et al. 2006; Rosenfeld et al. 2008; Khain and
Lynn 2009; Lebo and Seinfeld 2011; Lebo et al. 2012).
Mechanistically, this is caused by a reduction of droplet
collision–coalescence, leading to lofting of liquid water
above the freezing level that in turns drives enhanced
freezing and ice processes (e.g., Rosenfeld et al. 2008).
More recently, Lebo et al. (2012) described the enhancement of latent heating in polluted relative to
pristine conditions because of larger condensation rates
directly associated with higher droplet concentrations
and smaller mean droplet size. Other studies have related the intensification or weakening of convection to
changes in cold pools and low-level convergence (e.g.,
Tao et al. 2007; Lee et al. 2008b; Seigel et al. 2013).
Significant disagreement among modeling studies of
aerosol effects on deep convection likely reflects in part
the underlying complexity of these systems, with numerous interacting microphysical and dynamical processes leading to complementary or competing effects
(Morrison 2012).
The overall sensitivity of the strength of deep convection to aerosols is also likely related to the environmental conditions and dynamical characteristics of the
system being analyzed. For example, Tao et al. (2007)
examined tropical convection using a two-dimensional
(2D) cloud resolving model (CRM) with bin microphysics and showed that precipitation is enhanced in
moist environments and suppressed in drier environments; the authors related these changes to differences in
rain evaporation rates and cold pool strength. However,
Lebo and Seinfeld (2011) found no such sensitivity to
relative humidity for supercells using a three-dimensional
(3D) CRM with bin microphysics. Fan et al. (2009) demonstrated using a 2D CRM with bin microphysics that
in environments with weak environmental vertical wind
shear, an increase in aerosol loading acts to enhance
convection while in strong-shear environments, the same
increase in aerosol loading has little effect or even suppresses convection. More generally, environmental shear
exerts a dominant control on storm type, with increasing
shear favoring single-cell, multicell, and supercell storms
(see, e.g., Markowski and Richardson 2010).
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Of particular interest is the sensitivity of mesoscale
convective systems (MCSs), specifically squall lines, to
aerosol loading. Squall lines are a type of linear MCS
that commonly occurs in the tropics and midlatitudes.
They are responsible for producing heavy precipitation,
large hail, damaging straight-line winds, and occasional
tornadoes. A key aspect of squall-line organization
and maintenance is the inherent balance between the
cold pool strength and environmental wind shear (e.g.,
Thorpe et al. 1982; Nicholls et al. 1988; Weisman et al.
1988; Rotunno et al. 1988; Fovel and Ogura 1989; Szeto
and Cho 1994; Robe and Emanuel 2001; Weisman and
Rotunno 2004; James et al. 2005; Bryan et al. 2006;
Takemi 2007). Rotunno et al. [1988, hereafter referred
to as Rotunno–Klemp–Weisman (RKW) theory] discuss in detail how the optimal state of a squall line exists
in an environment where the contribution of vorticity
from the cold pool balances the contribution of vorticity
from the low-level environmental shear. If the shear is
too weak, the line will tilt in the upshear direction. On
the other hand, if the cold pool is too weak, the squall
line tilts in the downshear direction. This is important
because upshear and downshear tilting can lead to
weakening of updrafts from enhanced entrainment of
dry environmental air and adverse perturbation pressure gradient forces (Markowski and Richardson 2010;
Parker 2010). Changes in cold pool strength via changes
in microphysical processes ought to lead to changes in
the low-level dynamics and hence the strength and organization of squall lines (Fig. 1).
The parameterization of rain microphysics in particular has been noted as an important factor in the
strength and maintenance of squall lines given the impact of rain evaporation on cold pool characteristics
(e.g., Ferrier et al. 1995; Morrison et al. 2009; Bryan and
Morrison 2012; van Weverburg et al. 2012). For example, Morrison et al. (2012) found that the strength and
speed of a squall line was sensitive to the raindrop breakup
parameterization implemented in a bulk microphysics
model. Given that the ambient aerosol number concentration leads to substantial changes in droplet number and thus collection processes, it is postulated that
increased anthropogenic aerosol loading could have
similar effects on squall-line dynamics by impacting cold
pool evolution. Since aerosols can affect cold pool
characteristics because of their impact on cloud microphysics, RKW theory provides a potentially useful
conceptual framework by which to analyze aerosol effects on squall lines. These effects are schematically
summarized in Fig. 1. Figure 1 serves two purposes: 1) it
provides a conceptual framework of a typical squall line
and 2) it suggests pathways for aerosols to affect squallline dynamics. The proposed effects are confirmed and
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FIG. 1. Schematic of aerosol effects on squall lines for relatively (top) weak and (bottom) strong low-level wind
shear in the context of RKW theory (Rotunno et al. 1988). (from left to right) Increasing aerosol loading and (from
top to bottom) increasing low-level shear are depicted. Symbols are defined in the legend for convenience. The
strength of the induced circulations/vorticity is shown by the thickness of the circular arrow. The relative sizes of the
cloud droplets (blue circles) and raindrops (red circles) are portrayed via increased or decreased sizes of the representative circles. Note that the tilt of the convective clouds is exaggerated for illustrative purposes.
described in detail in sections 4 and 5. Briefly, however,
the key idea is that aerosols ultimately affect the raindrop size distribution which in turn alters the bulk rain
evaporation rate and cold pool intensity. These effects
alter the balance of the cold pool–induced circulations
with the low-level environmental shear to produce an
intensification (weakening) of the squall line in relatively weak (strong) wind shear environments.
Before proceeding, it is important to keep in mind the
potential shortcomings of RKW theory as discussed in
Stensrud et al. (2005) and Bryan et al. (2006). In particular, Stensrud et al. (2005) noted that observed longlived, severe squall lines were often far from the optimal
state. They also pointed out that some measures of
system strength (e.g., total and maximum vertical velocity) in the simulations of Rotunno et al. (1988) and
Weisman and Rotunno (2004), which served as a basis
for RKW theory, did not peak near the optimal state.
Other issues include the role of mid- to upper-level
shear (e.g., Fovell and Ogura 1995; Parker and Johnson
2004) as well as the applicability of RKW theory to broader
environments because the simulations of Rotunno et al.
(1988) and Weisman and Rotunno (2004) used only a
single thermodynamic sounding. Moreover, several studies have simulated long-lived squall lines in suboptimal
states (e.g., Fovel and Ogura 1988, 1989; Lafore and
Moncrieff 1989; Rotunno et al. 1990; Coniglio and
Stensrud 2001; Weisman and Rotunno 2004), despite the
original applicability of RKW theory in Rotunno et al.
(1988) to explain the longevity of squall lines. Nonetheless, simulations from more recent squall-line studies
have generally supported RKW theory (Bryan et al.
2006; Morrison et al. 2012). However, Morrison et al.
(2012) found that while structure and intensity of convective updrafts were consistent with RKW theory, surface precipitation peaked in suboptimal conditions. A
thorough and systematic study that addresses all of these
potential issues is beyond the scope of the present work.
While the sensitivity of aerosol effects on deep
convective systems to environmental shear has been
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previously described (e.g., Lee et al. 2008b; Fan et al.
2009), these studies did not provide a dynamical explanation for this sensitivity. Thus, the broad motivation for our study is to provide a dynamical context
for investigating aerosol effects on squall lines, especially in terms of sensitivity to environmental
shear. The specific goals of this study are to
1) quantify the enhancement or suppression of convection and precipitation in a squall line due to increased
aerosol number concentration;
2) provide a conceptual framework for the dynamical
effects of increased aerosol loading on squall lines by
exploring sensitivity of these effects to environmental wind shear in the context of RKW theory.
To address these points, we focus our attention on the
changes in cold pool strength produced by increasing
the aerosol number concentration and how it relates to
the environmental shear. Before presenting the simulated results, section 2 provides background information
on the microphysics model, domain setup, and chosen
squall-line case; section 3 introduces key aspects of RKW
theory necessary for analyzing the model simulations
performed here. Two particular cases, one representing
a weak shear scenario and the other a strong shear scenario are discussed both conceptually and quantitatively
in section 4. Section 5 is reserved for the analysis of both
changes in precipitation and convective strength within
the aerosol number concentration–low-level environmental shear parameter space. Last, we present the
important conclusions from this work in section 6.
2. Methods
a. Dynamical framework
The bulk microphysics model of Morrison et al. (2009)
[as adapted by Lebo et al. (2012), see below for more
details] is coupled to the Weather Research and Forecasting Model (WRF), version 3.3.1 (Skamarock et al.
2008), for use as a 3D ‘‘cloud resolving’’ model. The
model is compressible and nonhydrostatic. The model
domain is defined to be 124 km 3 714 km in the meridional and zonal directions, respectively. The domain is
extended to 20 km in the vertical. Horizontal grid spacing
is 1 km. There are 80 levels in the vertical; the vertical grid
spacing is about 0.25 km. To maintain dynamical stability,
the time step is set at 2.5 s for all simulations with a duration of 8 h. Rayleigh dampening is applied to the uppermost 5 km of the domain. The boundaries are set to be
open in the zonal direction and periodic in the meridional
direction. Since the simulations are specifically designed
to be idealized, we neglect the effects of radiation,
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surface fluxes, and Coriolis acceleration in the present
study. Advection of scalars is calculated using a fifthand third-order monotonic advection scheme in the
horizontal and vertical, respectively.
b. Microphysics model
The simulation of aerosol impacts on clouds of any
type relies on several key components contained within
the cloud microphysics model. Here, the assumption
that all points within a model domain are at saturation if
condensed water is present (the saturation adjustment
assumption) is relaxed so that the supersaturation is
predicted prognostically (analogous to the method used
in more detailed bin microphysics models). Without the
prediction of supersaturation, it was shown in Lebo et al.
(2012) that the bulk model did not qualitatively agree on
the sign of the change in the convective mass flux and
precipitation compared to bin model simulations for an
increase in aerosol loading. However, the inclusion of
a prognostic supersaturation algorithm in a bulk microphysics scheme (Morrison et al. 2009) provided good
quantitative agreement with detailed bin model simulations for the changes in convective mass flux with
aerosol loading in a supercell. Given this, and that highresolution bin microphysics simulations over a large
domain and longer time scales are computationally
prohibitive (especially if one wants to perform numerous simulations for various environmental parameters),
we restrict the simulations here to include bulk microphysics, namely the scheme of Morrison et al. (2009)
as modified in Lebo et al. (2012) to include prognostic
supersaturation.
The bulk microphysics scheme is also modified to
explicitly represent aerosol activation and regeneration
[see Lebo and Seinfeld (2011) for more details]. Briefly,
the aerosol model represents the ambient aerosol distribution via 36 mass-doubling bins with a smallest
aerosol diameter of 0.01 mm. Activation is predicted by
applying K€
ohler theory to the unactivated aerosol
population. To determine the size of the newly activated
droplets over the course of a single time step, we apply
the assumption of Kogan (1991) as used by Khain et al.
(2000) and Xue et al. (2010) in which the newly formed
droplet size is simply a factor k larger than the dry
aerosol diameter. Bulk mass and number mixing ratio
tendencies due to activation are then added to the bulk
tendencies from other cloud processes.
Xue et al. (2010) demonstrated the importance of
aerosol regeneration on cloud properties in orographic
clouds. Here, aerosol regeneration refers to the process
by which a cloud droplet completely evaporates within
a time step and thus reproduces an aerosol particle. Following Mitra et al. (1992), it is assumed that the evaporation
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of a single cloud droplet results in the regeneration of
a single aerosol particle. The regenerated aerosols are
assumed to be distributed identical to the initial aerosol
distribution. This assumption implies that the effect of
collection processes is small on the evolution of the
aerosol distribution. More sophisticated methods for
incorporating the effects of cloud processes on aerosols
are currently being developed (e.g., Lebo and Morrison
2013). However, exploration of such effects is beyond
the scope of the present study.
c. Model setup
Convection is triggered in the model by applying
forcing directly to the vertical velocity w field over the
first hour of the simulations (Ziegler et al. 2010). The
forcing is applied within a half cylinder with radii of
10 km in the x direction and 2.5 km in the z direction;
a maximum acceleration of 0.5 m s21 is located at the
center of the half cylinder. (Note that the w forcing is
uniform in the line-parallel dimension.) The w forcing
decays radially from the center assuming a cosine
function of the radius. Random thermal perturbations
(amplitude 0.1 K) to the initial sounding are applied
within a region 40 km wide in the x direction centered
around the region of w forcing and 4 km deep to initiate
3D motion. This is unlike previous works in which
convection is initiated via the application of a warm or
cold bubble in the lower troposphere. We choose to
initiate convection in this manner so as to allow the lowlevel dynamics to spin up unimpeded by initial warm or
cold bubbles that could potentially lead to changes in the
quasi-steady-state cold pool. To allow the squall line to
spin up, we restrict most of the analysis to the final 4 h of
the simulations (i.e., between 4 and 8 h, unless stated
otherwise). Since all simulations are spun up for 4 h and
use the same forcing parameters, the effects of this assumption on the overall results should be minimal.
The CRM is initialized with the sounding (Fig. 2) from
the observationally based squall-line case study of the
Eighth International Cloud Modeling Workshop held in
July 2012 in Warsaw, Poland (Muhlbauer et al. 2013).
The initial sounding comprises the 0000 UTC 20 June
2007 soundings from Lamont, Oklahoma (LMN), below
700 hPa and from Norman, Oklahoma (OUN), above
700 hPa to represent the prestorm environment. The
sounding is smoothed using a 1–2–1 smoother with 20
iterations. The chosen sounding has a convective available potential energy (CAPE) of about 6800 J kg21
based on the most energetic parcel. The observed Du
from wind-profiler data in Purcell, Oklahoma, was between 12 and 14 m s21 over a depth of 5 km. Details of
the observed squall line from this case are given by
Morrison et al. (2012).
FIG. 2. Skew T–logp diagram of the sounding used to initialize
the CRM. Temperature (black) and dewpoint temperature (blue)
are shown. The parcel following a moist adiabat lifted from the
lifted condensation level (LCL) is also displayed (red). Wind barbs
are depicted for the Du 5 12 m s21 case showing the depth of the
shear layer.
Since the focus of this work is on the sensitivity of
squall lines to aerosol perturbations in environments
with different vertical wind shears, the wind profile
(Fig. 2) is only relevant for the scenario in which the
change in the line-normal (or zonal in this case) wind
between the surface and the top of the shear layer (Du) is
12 m s21. For this study, we specify a relatively deep
shear layer of 5 km. Note that the mean wind is subtracted from the profile (hence, above the shear layer,
the line-normal wind is 0 m s21), but this has little impact
on the simulated results because the model is nearly
Gallilean invariant (since surface friction is neglected
and the lower boundary is free slip). The line-normal
wind decreases linearly with height from the surface
the top of the shear layer. For the purposes of this
experiment, we perform simulations for Du 5 8, 12,
16, 20, 24, 28, and 32 m s21 (corresponding to values
of shear equivalent to 0.0016, 0.0024, 0.0032, 0.0040,
0.0048, 0.0056, and 0.0064 s 21, respectively). Simulations with even higher wind shear were performed;
however, these systems were found to be unstable
and the squall line was either short lived or did not
form at all.
The simulated squall lines analyzed below have
a realistic squall-line structure, similar to the observations from this case (see Morrison et al. 2012).
Morrison et al. (2012) present a detailed comparison of
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WRF simulations using the Morrison et al. (2009) microphysics scheme with observations for this case using
a similar model setup. In particular, the model is able to
reproduce the overall observed reflectivity field with
a well-defined convective core and trailing stratiform
region. Further comparison of the simulations with observations is beyond the scope of this study; a more detailed comparison of several model simulations with
observations for this case is being performed as part of
the World Meteorological Organization (WMO) Cloud
Modeling Workshop (Muhlbauer et al. 2013).
To test the sensitivity of squall lines to aerosol perturbations, simulations are performed with initial aerosol number concentrations of 100, 200, 500, 1000, and
2000 cm23, encompassing relatively clean maritimeinfluenced air to rather polluted urban-influenced air.
Aerosols are assumed to be soluble ammonium bisulfate. The sensitivity to aerosol composition is beyond
the scope of the present study. The aerosols are assumed
to be lognormally distributed with a standard deviation
and geometric mean diameter of 1.8 and 0.08 mm, respectively. Most of the analysis below revolves around
a comparison of cases in which Na 5 100 or 1000 cm23
(clean and polluted scenarios, respectively). The parameter space is further explored in section 5.
d. Sensitivity simulations
We performed an additional set of simulations in
which saturation adjustment was employed for calculations of cloud water condensation and evaporation.
These simulations help to isolate effects of increased
latent heating aloft from changes in the cold pool by
neglecting the dependence of the droplet condensation
rate (and the associated latent heating) on the mean
cloud droplet size, thereby limiting the mechanism of
increased latent heating in polluted conditions. Previous work has shown that the response of the convective mass flux to aerosol perturbations using the
Morrison et al. (2009) bulk microphysics scheme with
saturation adjustment is either negligible or slightly
negative for supercells (e.g., Lebo et al. 2012; Morrison
2012). Thus, if the primary effect of aerosol perturbations on squall lines is to affect the low-level dynamics,
the simulations using saturation adjustment ought to
exhibit enhanced convection as well. On the other
hand, if the primary effect of an increase in aerosol
loading is to alter the latent heating rates aloft and
feedback on the dynamics of the system, the sensitivity
simulations with saturation adjustment ought to show
little sensitivity to aerosol number concentration.
These simulations are performed only for the relative
weak and strong wind shear environments (i.e., Du 5
12 and 32 m s21).
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A final set of sensitivity simulations were performed
using soundings with less CAPE (down to 2000 J kg21
based on the most energetic parcel) to confirm that the
results presented below can be generalized for squall lines
(not shown). The sensitivity soundings were formed by
systematically decreasing the water vapor mixing ratio in
the lowest 5 km to achieve a reduction in CAPE.
e. Statistical significance
Statistical significance is determined by using all
points N in the domain and in time (i.e., N 5 nx 3 ny 3
nz 3 nt, where nx, ny, nz, and nt correspond to the number
of points in the x, y, and z directions, and output times,
respectively). Student’s t tests are performed on the
means of two samples of size N corresponding to a clean
and polluted scenario to rule out the null hypothesis
(in other words, we are confident that the two means are
not identical).
3. Cold pool–shear interaction
It is important to first discuss the dynamical context by
which squall lines form and persist to carefully analyze
the effects of aerosol perturbations on their strength and
structure. To do so, we revisit the hallmark work of
Rotunno et al. (1988) in which a theory (RKW theory)
for long-lived squall lines was formulated. RKW theory
suggests the importance of the balance between the
contribution of vorticity from the cold pool and the
contribution of vorticity from the environmental shear
to squall-line structure and maintenance. To look at this
relationship in more detail, the cold pool intensity c2 is
defined as
c2 5 22
ðH
0
2BL dz,
(1)
where H is the top of the cold pool and BL corresponds
to the buoyancy at some point L behind the gust front.
Equation (1) is derived for an idealized hydrostatic
density current (c is the density current propagation
speed) and thus in more realistic 3D nonhydrostatic
simulations, determining the exact location of L is quite
challenging. Following RKW theory and Markowski
and Richardson (2010), L should correspond to the
point behind the gust front in which the zonal flow relative to the gust front is stationary. Moreover, the
pressure within the cold pool at L should be nearly hydrostatic. For the purpose of this present work, we
choose L to be a fixed location 30 km behind the gust
front and zonally average over a 20-km band around L
as well as average in the meridional (line parallel) direction to get a characteristic value of c for the squall
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FIG. 3. Profiles of (a) mean convective updraft mass flux and (b) domain-averaged and temporally averaged
(between 4 and 7 h) convective updraft fraction for clean (Na 5 100 cm23, solid) and polluted (Na 5 1000 cm23,
dashed) conditions with low wind shear (i.e., Du 5 12 m s21).
line. We find (as will be shown later) that the results are
qualitatively insensitive to the chosen L as long as L is
not within 10–15 km of the gust front where large nonhydrostatic effects occur.
RKW theory suggests that a key factor in determining
the structure and strength of a squall line is the ratio
c/Du. For c/Du 1 (or what will be referred to as
a suboptimal shear environment), the squall line tends
to lean back over the cold pool (upshear). The other
extreme is the case in which c/Du 1 (or what will be
referred to as a suboptimal squall line). In this scenario,
the line tilts downshear. The optimal state occurs when
c/Du ’ 1. As c/Du approaches unity, the line tends to be
more upright and thus entrainment of the environmental air and adverse pressure perturbation effects are reduced, aiding to increase updraft velocities within the
convective region.
The structure of a squall line in terms of environmental shear and c is the focus of RKW theory. Here,
we look at the sensitivity of squall-line structure and
strength to changes in aerosol number concentration.
Thus, we vary Du directly while varying c indirectly
through aerosol perturbations. For example, if c/Du 1
and an increase in aerosol loading leads to a significant decrease in c, the squall line is more optimal in the
polluted environment for a given Du and, hence, convective updrafts should be more upright and stronger
according to RKW theory. Performing this comparison for the range of environmental shear profiles described above allows us to analyze the sensitivity of
a squall line to aerosol perturbations in the context of
RKW theory.
4. Results
For brevity, we initially restrict the analysis to a weak
shear case and a strong shear case, characterized by
Du 5 12 and 32 m s21, respectively. By doing so, we can
specifically address aerosol sensitivity in these distinctly
different environments before exploring the entire parameter space in detail. Moreover, much of the analysis
is restricted to comparing simply the 100 and 1000 cm23
cases for clarity, hereafter referred to as clean and polluted conditions, respectively.
a. Weak shear environment
In Fig. 3 we show profiles of spatially averaged and
temporally averaged (4–7 h) convective updraft mass
flux and convective updraft fraction. Here, we define the
mean convective updraft mass flux as a function of
height [MF(z)] to be the product of the vertical velocity
w and the air density r for all locations in which w $
2 m s21, divided by the total area of the domain. Qualitatively, the results presented here are not sensitive to
the chosen threshold value for w. Here we see both
a consistent increase in the convective mass flux and
a decrease in the convective updraft fraction (defined as
the fraction of the domain at a given vertical level containing updrafts of at least 2 m s21) for an increase in
aerosol loading. As described in the introduction, invigoration of deep convection has often been explained
in previous studies via the suppression of collision–
coalescence and enhancement of mixed- and cold-phase
processes and hence latent heating aloft in polluted
compared to pristine conditions (e.g., Khain et al. 2004;
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FIG. 4. Cross sections of line-averaged updraft velocity (color contours) and 20.05 J kg21 buoyancy contour (solid
line). Also shown is the location of the maximum of the line-averaged updraft velocity and the corresponding width at
that level. The x direction has been normalized to the mean location of the gust front. The cross sections are computed by averaging over the last 4 h of the simulations. Cross sections are shown for (a),(b) Du 5 12 m s21 and (c),(d)
Du 5 32 m s21. Aerosol loading is depicted for (a),(c) 100 cm23 and (b),(d) 1000 cm23. The vertical dashed line
denotes the position of the surface gust front.
Rosenfeld et al. 2008; Lebo and Seinfeld 2011), or because of increased latent heating due to larger condensation rates associated with smaller mean droplet size
(Lebo et al. 2012). As described later in this section, the
latter mechanism contributes to the invigoration of
convection in polluted conditions in the simulations
here. However, compared to some previous studies of
aerosol impacts on deep convection (e.g., Van den
Heever et al. 2006; Lebo and Seinfeld 2011; Lebo et al.
2012; Morrison 2012), the increase in convective updraft
mass flux shown here is much larger, upward of 20% at
some levels. This suggests an additional mechanism
leading to enhanced convection beyond just the direct
change in latent heating following the mechanisms described above. This additional enhancement is caused by
changes in cold pool strength with increased aerosol
loading and interaction of the cold pool with environmental shear. In particular, the decrease in the convective updraft fraction with increased aerosol loading is
suggestive of a narrower (at least in the horizontal
plane) updraft. Morrison et al. (2012) showed a similar
response to changes in the parameterization of drop
breakup and related this finding to more upright updrafts consistent with RKW theory. All else being equal, if
the convective updraft core is cylindrical, then as updrafts
become more upright the horizontal width (at a given
vertical level) approaches the radial width of the convective core. Thus, smaller horizontal widths suggest
more upright updrafts. This is confirmed in Figs. 4a,b
where the occurrence of more upright (and stronger)
updrafts is seen with increased aerosol loading via a shift
forward in the maximum of the vertically averaged convective mass flux. The shift forward is approximately
2 km. The shift is most noticeable in the midlevel maximum updraft velocity and the connection between the
low-level and mid- to upper-level updrafts that is present
in the polluted scenario (Fig. 4b, dark blue shading) and
not present in the clean case (Fig. 4a).
To understand why the convective mass flux increases
and the convective updraft fraction decreases, we turn to
profiles of the condensed mass concentrations (Fig. 5a).
Here we see that with increased aerosol loading (solid to
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999
FIG. 5. Profiles of (a) bulk condensed mass concentrations and (b) relative change in mean hydrometeor volumetric
radius averaged spatially and temporally (between 4 and 7 h) for clean (Na 5 100 cm23, solid) and polluted (Na 5
1000 cm23, dashed) conditions with weak wind shear (i.e., Du 5 12 m s21). The five hydrometeor classes, namely,
cloud (green), rain (red), ice (black), snow (blue), and graupel (orange), are shown. Note that in (a), the cloud water
mass concentration is multiplied by a factor of 3 to better represent the differences between the two aerosol scenarios.
dashed) there is an enhancement of supercooled liquid
water (green) and a subsequent increase in ice mass
concentration aloft (black). However, Fig. 5b suggests
that despite these increase in mass concentrations there
are smaller cloud droplets and ice crystals on average
(mean volume radius, due to the large increase in number
concentration). There is very little change in the snow
mass concentration and snow size (blue) but a rather
substantial change in graupel (orange). Here we see that
the graupel mass concentration decreases but the mean
size increases (about 20% throughout most of the column). As these larger graupel particles fall, they melt
and this results in larger mean raindrop size as well
(red). Furthermore, since the addition of aerosol particles acts to mitigate the collision–coalescence process,
the formation of numerous small raindrops via warm
processes (i.e., autoconversion and accretion) is hindered. This reduces the number concentration of raindrops and helps promote the growth of larger raindrops
via cold-rain mechanisms (riming and subsequent melting
in particular). Thus, even though the mass evaporation
rate of a single drop is proportional to its radius (in other
words, a larger raindrop will evaporate mass faster than
a smaller counterpart), there are far fewer raindrops on
average in polluted compared to pristine conditions and
they fall faster leading to shorter residence time and
a smaller mass concentration (although this is somewhat
compensated by ventilation effects). These results (fewer
larger raindrops in polluted conditions versus many
smaller raindrops in more pristine air) suggests that the
bulk rain evaporation rate ought to be reduced as
a result of increasing the aerosol number concentration.
The changes observed in the model results are shown
schematically in Fig. 1 (top) where the sizes of the particles are depicted by changes in the corresponding
symbol size.
Figure 6b indeed demonstrates that the increase in
raindrop mean size in conjunction with a decrease in
bulk mass concentration in polluted compared to pristine conditions leads to a substantial decrease in the rain
evaporation rate within the cold pool. All else being
equal, this leads to less negative buoyancy (Fig. 6a).
Figure 6c shows that the reduction in negative buoyancy
occurs throughout most of the cold pool (at least for
points more than 20 km behind the surface gust front,
defined to be the line-averaged mean position of the
location in the x direction in which the wind direction
changes sign). Moreover, Fig. 6d shows that the cold
pool is slightly shallower in the polluted case (for points
more than 10 km behind the gust front).
Figures 6c,d show that the region chosen to determine
the value of c [namely, point L in Eq. (1)] does not
qualitatively affect the change in c for an increase in
aerosol loading as long it is not within 10–20 km of the
gust front. Picking a location close to the gust front
would have a large effect on the results, but doing so
would be inconsistent with the derivation of c from
density current theory as explained in section 3. We
compute c over the region between 20 and 40 km behind the gust front, namely, where the cold pool top
is relatively flat (Fig. 6d). Increasing aerosol loading
leads to a consistent decrease in c/Du and thus a more
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MONTHLY WEATHER REVIEW
VOLUME 142
FIG. 6. Profiles of (a) mean buoyancy and (b) rain evaporation rate averaged spatially and temporally for clean
(Na 5 100 cm23, solid) and polluted (Na 5 1000 cm23, dashed) conditions; (c) mean lowest level buoyancy and
(d) mean cold pool depth within 100 km of the gust front; (e) time series of line-averaged c/Du and the (f) mean
change in gust front position. Note than in (f), the change is from polluted minus clean. All graphs are for simulations
with weak wind shear (i.e., Du 5 12 m s21). Temporal averaging for profiles covers the range from 4 to 7 h, except in
(b), where the averaging is extended to 1–7 h to capture the development phase of the cold pool.
optimal state according to RKW theory for the weak
wind shear case (Fig. 6e). This decrease in c/Du is quite
large, ranging from 10% to 20% and thus providing
a mechanism for the statistically significant invigoration
(p 5 7.025 3 1028) seen in Fig. 3a (in addition to increased latent heating caused by changes in condensation rate described below). The polluted, stronger squall
line also ought to move slower (since c is smaller)
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1001
FIG. 7. Profiles of horizontally and temporally averaged (for 4 # t # 8 h) latent heating rates for simulations
performed with (a) explicit supersaturation treatment and (b) saturation adjustment. Shown are data for the clean
(Na 5 100 cm23, solid) and polluted (Na 5 1000 cm23, dashed) scenarios for those simulations with weak wind shear
(i.e., Du 5 12 m s21). The net heating (black) is shown and the heating rates are separated into warming (red) and
cooling (blue) for clarity.
compared to the clean, weaker squall line. Figure 6f
confirms this hypothesis by showing the mean change of
the gust front position as a function of time. Here,
a negative value means that the gust front in the polluted
scenario trails the gust front in the clean case. The
negative slope from 5.5 h and onward shows that the
polluted squall line moves slower by about 2 km h21
over that time frame.
Evidence for the invigoration effects of increased
aerosol loading via both latent heating increases and
a more optimal balance between the cold pool intensity
and low-level environmental wind shear is provided
in Figs. 7 and 8. As described in section 2c, additional
simulations were performed using a version of the
bulk microphysics scheme with saturation adjustment.
Previous work has shown that the response of the
convective mass flux to aerosol perturbations using the
Morrison et al. (2009) bulk microphysics scheme with
saturation adjustment is either negligible or slightly
negative for supercell storms (e.g., Lebo et al. 2012;
FIG. 8. (a) Time series of line-averaged c/Du (as in Fig. 6e) and (b) relative change (polluted minus clean) in mean
convective updraft mass flux for Du 5 12 m s21, except for simulations performed with saturation adjustment. Data
are averaged between 4 and 7 h.
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MONTHLY WEATHER REVIEW
VOLUME 142
FIG. 9. As in Fig. 3, but for simulations with high wind shear (i.e., Du 5 32 m s21).
Morrison 2012). Thus, by using saturation adjustment,
the effect of aerosol perturbations on latent heating
through modification of mean droplet size and hence
condensation rate is neglected and, thus, we can focus on
the low-level cold pool effects. Figures 7a,b corroborate
the results of Lebo et al. (2012). Simulations using the
baseline model configuration with explicit condensation/
evaporation show a substantial increase in mean latent
heating in polluted compared to pristine conditions, but
the simulations using saturation adjustment show little
difference. Although differences in mean latent heating
between polluted and pristine conditions are small in
simulations with saturation adjustment, there is still a
small increase in the convective mass flux (for z . 7 km),
consistent with changes in cold pool intensity leading
to a more optimal squall line according to RKW theory
(Fig. 8). Specifically, the decrease in c/Du shown in
Fig. 6e is also present in simulations performed with
saturation adjustment (i.e., negligible latent heating
effects) shown in Fig. 8a. Thus, it is clear that the effects
of an increase in aerosol number concentration on
both latent heating (because of increased condensation from smaller mean droplet size) and cold pools is
to enhance convection for relatively weak wind shear
conditions.
b. Strong shear environment
As the low-level wind shear increases, the ratio of c to
Du decreases for constant c. If the wind shear is high
enough, c/Du can become less than 1 and, hence, less
optimal. For the weak wind shear simulations described
previously, c was found to lie between 25 and 33 m s21.
Thus, we choose the high-shear case to be one in which
Du 5 32 m s21 so that c/Du is less than unity during most
of the simulation. Note that changes in c do occur between the simulations. However, the change in c due to
a change in low-level wind shear is much smaller than
the change in Du.
Comparing Figs. 3 and 9, we see that as Du increases,
there is a reduction in the invigoration of the convective
mass flux with an increase in aerosol loading. In the high
shear scenario, there is a small decrease in the convective mass flux between 2 and 5 km, with little change
seen elsewhere. Furthermore, Fig. 9b shows an increase
in the convective updraft fraction for an increase in
aerosol number. This is opposite of the response for the
weak wind shear environment described above. Because
c/Du is less than 1 for the clean case, this means that the
line should tilt more forward (see Figs. 4c,d; cf. the weak
low-level wind shear scenario) under more polluted
conditions. Evidence of this is again seen in Figs. 4c,d,
which shows a slight forward shift of the updraft cores.
According to RKW theory, this ought to result in a reduction in the strength of the line, but Fig. 9a suggests
otherwise. This contradictory finding is a direct result of
the increase in droplet condensation and hence latent
heating due to enhanced aerosol number concentration
discussed earlier that acts to compensate the weakening caused by the forward titling of the squall line (as
demonstrated with the sensitivity simulations using
saturation adjustment). As was also shown previously
in the weak wind shear scenario, the low-level updrafts tend to be more connected with the mid- to upperlevel updrafts in the polluted case (dark red contours in
Fig. 4c,d).
In Fig. 10 we see that the evaporation rate in the cold
pool decreases slightly with increased aerosol loading,
primarily below 2.5 km. The average buoyancy in the
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LEBO AND MORRISON
1003
FIG. 10. As in Fig. 6, but for simulations with strong wind shear (i.e., Du 5 32 m s21).
cold pool is somewhat less negative. Figures 10c,d show
that the buoyancy is slightly less negative for all points
behind the gust front while the cold pool depth is more
or less unchanged up to 50 km behind the gust front.
These small changes combine to decrease c/Du by ,10%
on average (Fig. 10e). Since c/Du , 1 for the clean
case, the reduction in c means that the system is tilted
somewhat more downshear and the effects of aerosol
loading on the cold pool act to weaken convection.
Again, however, one has to consider all aerosol effects
on the dynamics and since the buoyancy aloft increases
due to enhanced latent heating (Fig. 11), the overall
effect is only a slight (although statistically significant,
p 5 1.006 3 1027) suppression in the vertically integrated convective mass flux (Fig. 9a). These changes are
portrayed schematically in Fig. 1 (bottom).
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MONTHLY WEATHER REVIEW
FIG. 11. As in Fig. 7, but for the strong wind shear scenario (i.e.,
Du 5 32 m s21). Note that only data for the simulations performed
with explicit supersaturation treatment are shown since a squall
line did not form for the polluted case when using the saturation
adjustment scheme.
5. General results within the aerosol number
concentration–environmental wind shear
parameter space
While the previous section provides evidence for
the enhancement of convection in weak wind shear
environments and negligible impact or a weakening of
convection in strong shear environments, it is important
to understand how the aerosol sensitivity varies over
a range of low-level environmental wind shears. Moreover, it is important to also understand how these
VOLUME 142
changes in dynamics lead to changes in precipitation. In
Fig. 12 we show the relative change in convective mass
flux and precipitation as a function of environmental
wind shear (here again defined as the difference in the
line-normal wind between the surface and the top of the
shear layer at 5 km). The relative changes are shown
for an increase in aerosol number from 100 cm23 to
the corresponding values on the y axis. We find that as
the low-level wind shear decreases, squall lines are more
susceptible to aerosol effects (via both enhanced convection and increased precipitation). In these cases, the
line tends to tilt back over the cold pool and thus any
weakening in the cold pool will bring the updraft core
closer to the gust front and thus enhance convection
consistent with RKW theory (see Fig. 4). We see that in
the lowest shear scenario, the convective mass flux increases by at least 10% and the precipitation increases
by nearly 20% for some aerosol loadings. Both of these
changes are found to be statistical significant at the 0.05
significance level using a standard Student’s t test for the
two simulations.
As the shear increases to between 15 and 25 m s21, the
simulations shift to a different regime in which the change
in the convective mass flux with increased aerosol loading
may be slightly positive or slightly negative (Fig. 12a).
For a given shear over this range of shear values, Fig. 12b
shows an increase in precipitation by 3%–5%. The reason
for these opposing effects on precipitation and convective
mass flux is that aloft, enhanced buoyancy due to increased latent heating in the polluted environment leads
to a slight increase in the strength of convection and an
increase in the total condensed mass concentration. This
is offset by a weakening caused by the decreased cold
pool strength (since, in the clean environment, the
system is already nearly optimal and so weakening of
the cold pool produces a suboptimal environment).
FIG. 12. The relative change in (a) temporal (for 4 # t # 8 h) and domain-averaged convective updraft mass flux
and (b) cumulative precipitation as a function of low-level line-normal wind shear (x axis) for an increase in Na
(y axis). Changes are shown relative to Na 5 100 cm23, which represents a clean environment. Warm (cool) colors
correspond to increases (decreases) with increased aerosol loading.
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LEBO AND MORRISON
Thus, as a whole, the change in the convective mass flux
is small, but the enhancement in mixed-phase and cold
microphysical processes aloft leads to small increases in
precipitation.
As the shear approaches the upper bound of the parameter space explored here, the convective mass flux
decreases somewhat for large changes in aerosol loading
(again, a balance between an increase aloft and decrease
at low-levels—see Fig. 9a), but the precipitation strongly
decreases with increased aerosol loading (Fig. 12).
Changes in the convective mass flux for the highest wind
shear scenario are similar to that for the middle regime
discussed above, but the change in precipitation has the
opposite sign. This is explained by examining Fig. 13.
Here we have plotted normalized rain rates, total condensed mass concentration, and relative humidity as
a function of line-normal distance from the leading edge
of the gust front (thin dashed line). These figures illustrate two important points. First, as the environmental
shear increases (black to blue to red), the maximum rain
rate and maximum total condensed mass concentration
shift closer to the gust front. Quantitatively this difference from Du 5 12 to 32 m s21 is about 28 and 11 km for
the rain rate and total condensed mass concentration,
respectively. Moreover, these results are consistent with
changes in tilting of the convective updrafts with increased aerosol loading discussed previously, especially
for the weak wind shear scenario (i.e., Du 5 12 m s21)
due to the shift forward (downshear) in the maximum
rain rate of between 4 and 5 km for polluted compared
to pristine conditions (Fig. 13a). Second, Fig. 13a shows
that as the shear increases from 24 to 32 m s21, the rainrate maximum shifts toward the gust front by about
10 km, but the leading edge of the precipitation does not
move as far downshear. However, Fig. 13b demonstrates
that more condensed water mass exists downshear of the
gust front as the shear increases (in fact, the shift forward in the maximum is about the same as the shift
forward in the leading edge of the precipitation). This is
important because the background environment is quite
dry relative to the region within 50 km behind the gust
front (Fig. 13c). In other words, more precipitation falls
at or ahead of the gust front in the strongest shear case
and subsequently evaporates before reaching the surface. This explains the large decrease in precipitation
with increased aerosol loading for the strongest shear
case. This is also consistent with the small increase of
1%–2% in the relative humidity ahead of the gust front
with increasing low-level shear (i.e., the environment is
moistened as a result of the downshear shift of falling
precipitation and its subsequent evaporation; Fig. 13).
Figure 12 suggests that the response of squall lines to
an aerosol perturbation may not be monotonic. Specific
1005
FIG. 13. Normalized line-normal (a) rain rate, (b) total hydrometeor mass concentration, and (c) relative humidity for Du 5 12
(black), 24 (blue), and 32 m s21 (red). Shown are line- and temporally averaged (for 4 # t # 8 h) values for simulations run with
Na 5 100 (solid) and 1000 cm23 (dashed). The vertical dashed line
corresponds to the leading edge of the gust front.
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MONTHLY WEATHER REVIEW
evidence of the nonmonotonicity in the aerosol-induced
response of deep convection lies in the weak wind shear
scenarios where we find that the increase in the convective mass flux and precipitation is less when the aerosols
are increased to 2000 cm23 as compared with 1000 cm23.
However, these differences are quite small and at this
point, only speculative arguments can be made about
the causes given the lack of a large enough sample of
simulations demonstrating the nonmonotonicity and
that the change in precipitation and convective mass
flux predicted from 1000 and 2000 cm23 are not statistically significant.
6. Conclusions
The sensitivity of numerically simulated squall lines to
aerosol perturbations is investigated across a wide range
of background environmental shear profiles in the context of RKW theory. A two-moment bulk microphysics
scheme (Morrison et al. 2009) with explicit treatment of
supersaturation (Lebo et al. 2012) and coupled to a
binned aerosol scheme (Lebo and Seinfeld 2011) was
used in WRF for this study. Recent work concerning
aerosol effects on deep convection has provided a mix of
results (see section 1). Here we presented evidence that
the effects of aerosol perturbations on deep convection
are a distinct function of the environment and dynamical
characteristics of the system being investigated. Thus,
results presented herein are applicable to squall lines
only and not necessarily other types of deep convection
(e.g., while the convective cores of squall lines are
strongly influenced by cold pool–induced circulations
in the context of low-level environmental shear, other
systems like supercells are likely to exhibit different
sensitivities owing to their different dominant dynamical
driving mechanisms).
The key conclusions of this study are as follows:
1) Weak shear—In relatively weak low-level shear environments, an increase in aerosol number concentration led to an increase in convective mass flux
(strengthening), corroborating the work of Fan et al.
(2009). This was caused by a weakening of the cold
pool in polluted conditions since the rain mass concentration was smaller and the raindrops were larger
and thus less readily evaporated. In the context of
RKW theory, this weakening of the cold pool reduced
the ratio of c/Du toward a more optimal value consistent with stronger, more upright convective updrafts.
Increased latent heating resulting from greater condensation because of the reduced mean cloud droplet
size in polluted conditions also contributed to invigoration of the squall line.
VOLUME 142
2) Strong shear—In relatively strong low-level shear
environments, an increase in aerosol loading led to
fairly small changes in the convective mass flux
although there was a small suppression at the highest
shear values. In the context of RKW theory this is
explained by a decrease of c/Du from a more optimal
state in pristine conditions (c/Du ; 1) to a less
optimal state (c/Du , 1) because of the reduced cold
pool strength in polluted conditions. This led to
greater forward (downshear) tilting of convective
updrafts with increased aerosol loading and hence
weakening of the updrafts. However, this weakening
via cold pool–shear interactions was compensated by
invigoration due to greater condensation and latent
heating in polluted conditions. In the highest shear
conditions and for relative large aerosol perturbations, the cold pool effects outweighed the increase in
latent heating so that there was an overall suppression
of the convective mass flux in polluted compared to
pristine conditions. For smaller aerosol perturbations
and in somewhat less strongly sheared conditions,
these two effects compensated and the overall impact
of aerosols on the convective mass flux was very small.
While the convective mass flux was found to be enhanced in weak shear and slightly suppressed in strong
shear, the effect on precipitation is more complicated.
For the weakest wind shear, it was shown that an increase in aerosol loading led to an increase in the convective mass flux because of both increased latent
heating and more upright updrafts that enhanced the
formation of more precipitation (condensed mass aloft
increased with increasing aerosol number concentration). As the low-level wind shear was increased, the
simulated squall line entered a middle regime whereby
aerosols had limited effects on the convective mass flux
but precipitation increased with an increase in aerosol
number. The increase in precipitation resulted from an
increase in latent heating due to greater condensation
that ultimately led to an increase in condensed mass in
polluted conditions. For the highest wind shear scenario,
a third regime was evident in which increased aerosol
loading led to a small decrease in the convective mass
flux but a substantial decrease in precipitation. This was
due to updrafts that tilted more downshear, producing
precipitating hydrometeors that fell ahead of the gust
front and readily evaporated.
These results provide a context by which aerosol
perturbations can dynamically alter a midlatitude squall
line. While results were presented in detail for a single
thermodynamic profile in this study, an additional suite
of simulations (not shown) with lower CAPE (down
to 2000 J kg21) were performed to corroborate and
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LEBO AND MORRISON
generalize the results across a wide range of conditions
typically observed in midlatitude squall-line environments. An important aspect of this work is that the terms
‘‘weak wind shear’’ and ‘‘strong wind shear’’ are relative
to the cold pool intensity and thus depend on the environmental sounding. Therefore, simulations with reduced CAPE tend to have less precipitation, weaker
cold pools, and an optimal state that occurs at relatively
weaker wind shear according to RKW theory. The robustness of the results lies in the overarching effect of an
increase in aerosol loading that leads to a suppression in
cold pool intensity across the low-level shear parameter
space explored. Changing the thermodynamic state of
the system will in fact alter the optimal point in the lowlevel wind shear–cold pool intensity parameter space
according to RKW theory, but has limited impact on the
overall aerosol effects. That said, the exploration of
aerosol effects in drastically different thermodynamic
environments (i.e., the tropics) is important, but is beyond the scope of the present study and should be addressed in future work.
Acknowledgments. The case presented here stems
from a squall-line case study that was part of the Eighth
International Cloud Modeling Workshop held in Warsaw, Poland. Funding for this work was provided by the
Advanced Study Program at the National Center for
Atmospheric Research. Additional support was provided by U.S. DOE ASR DE-SC0008648 and the NSF
Science and Technology Center for Multiscale Modeling of Atmospheric Processes (CMMAP), managed by
Colorado State University under Cooperative Agreement ATM-0425247. The authors also thank in particular George Bryan for his assistance with setting up the
squall-line case and Morris Weisman for valuable suggestions to improve the study.
REFERENCES
Ackerman, A. S., M. P. Kirkpatrick, D. E. Stevens, and O. B. Toon,
2004: The impact of humidity above stratiform clouds on indirect aerosol climate forcing. Nature, 432, 1014–1017.
Bretherton, C. S., P. N. Blossey, and J. Uchida, 2007: Cloud droplet
sedimentation, entrainment efficiency, and subtropical stratocumulus albedo. Geophys. Res. Lett., 34, L03813, doi:10.1029/
2006GL027648.
Bryan, G. H., and H. Morrison, 2012: Sensitivity of a simulated
squall line to horizontal resolution and parameterization of
microphysics. Mon. Wea. Rev., 140, 202–225.
——, J. C. Knievel, and M. D. Parker, 2006: A multimodel assessment of RKW theory’s relevance to squall-line characteristics. Mon. Wea. Rev., 134, 2772–2792.
Chen, Y.-C., L. Xue, Z. J. Lebo, H. Wang, R. M. Rasmussen, and
J. H. Seinfeld, 2011: A comprehensive numerical study of
aerosol–cloud interactions in marine stratocumulus. Atmos.
Chem. Phys., 11, 9749–9769, doi:10.5194/acp-11-9749-2011.
1007
Coniglio, M. C., and D. J. Stensrud, 2001: Simulation of a progressive derecho using composite initial conditions. Mon.
Wea. Rev., 129, 1593–1616.
Ekman, A. M. L., A. Engstrom, and A. Soderberg, 2011: Impact of
two-way aerosol–cloud interaction and changes in aerosol size
distribution on simulated aerosol-induced deep convective
cloud sensitivity. J. Atmos. Sci., 68, 685–697.
Fan, J., R. Zhang, G. Li, and W.-K. Tao, 2007: Effects of aerosols
and relative humidity on cumulus clouds. J. Geophys. Res.,
112, D14204, doi:10.1029/2006JD008136.
——, and Coauthors, 2009: Dominant role by vertical wind shear in
regulating aerosol effects on deep convective clouds. J. Geophys. Res., 114, D22206, doi:10.1029/2009JD012352.
Ferrier, B. S., W. Tao, and J. Simpson, 1995: A double-moment
multiple-phase four-class bulk ice scheme. Part II: Simulations
of convective storms in different large-scale environments and
comparisons with other bulk parameterizations. J. Atmos. Sci.,
52, 1001–1033.
Fovell, R. G., and Y. Ogura, 1988: Numerical simulations of a midlatitude squall line in two dimensions. J. Atmos. Sci., 45, 3846–
3879.
——, and ——, 1989: Effect of vertical wind shear on numerically
simulated multi cell storm structure. J. Atmos. Sci., 46, 3144–
3176.
——, and ——, 1995: The temporal behavior of numerically simulated multicell-type storms. Part I: Modes of behavior.
J. Atmos. Sci., 52, 2073–2095.
Grabowski, W. W., 2006: Indirect impact of atmospheric aerosol in
idealized simulations of convective-radiative quasi equilibrium. J. Climate, 19, 4664–4682.
——, and H. Morrison, 2011: Indirect impact of atmospheric
aerosol in idealized simulations of convective-radiative quasi
equilibrium. Part II: Double-moment microphysics. J. Climate, 24, 1897–1912.
Gunn, R., and B. B. Phillips, 1957: An experimental investigation
of the effect of air pollution on the initiation of rain. J. Meteor.,
14, 272–280.
James, R. P., J. M. Fritsch, and P. M. Markowski, 2005: Environmental distinctions between cellular and slabular convective
lines. Mon. Wea. Rev., 133, 2669–2691.
Khain, A., and A. Pokrovsky, 2004: Simulation of effects of atmospheric aerosols on deep turbulent convective clouds using
a spectral microphysics mixed-phase cumulus cloud model.
Part II: Sensitivity study. J. Atmos. Sci., 61, 2983–3001.
——, and B. Lynn, 2009: Simulation of a supercell storm in clean
and dirty atmosphere using weather research and forecasting
model with spectral bin microphysics. J. Geophys. Res., 114,
D19209, doi:10.1029/2009JD011827.
——, M. Ovtchinnikov, M. Pinsky, A. Pokrovsky, and H. Krugliak,
2000: Notes on the state-of-the-art numerical modeling of
cloud microphysics. Atmos. Res., 55, 159–224.
——, A. Pokrovsky, M. Pinsky, A. Seifert, and V. Phillips, 2004:
Simulation of effects of atmospheric aerosols on deep turbulent convective clouds using a spectral microphysics mixedphase cumulus cloud model. Part I: Model description and
possible applications. J. Atmos. Sci., 61, 2963–2982.
——, D. Rosenfeld, and A. Pokrovsky, 2005: Aerosol impact on the
dynamics and microphysics of deep convective clouds. Quart.
J. Roy. Meteor. Soc., 131, 2639–2663, doi:10.1256/qj.04.62.
——, N. BenMoshe, and A. Pokrovsky, 2008: Factors determining the impact of aerosols on surface precipitation from
clouds: An attempt at classification. J. Atmos. Sci., 65, 1721–
1748.
1008
MONTHLY WEATHER REVIEW
Kogan, Y. L., 1991: The simulation of a convective cloud in a 3D
model with explicit microphysics. Part I: Model description
and sensitivity experiments. J. Atmos. Sci., 48, 1160–1189.
Koren, I., Y. J. Kaufman, D. Rosenfeld, L. A. Remer, and
Y. Rudich, 2005: Aerosol invigoration and restructuring of
Atlantic convective clouds. Geophys. Res. Lett., 32, L14828,
doi:10.1029/2005GL023187.
——, L. A. Remer, O. Altaratz, J. V. Martins, and A. Davidi, 2010:
Aerosol-induced changes of convective cloud anvils produce climate warming. Atmos. Chem. Phys., 10, 5001–5010, doi:10.5194/
acp-10-5001-2010.
Lafore, J., and M. W. Moncrieff, 1989: A numerical investigation of
the organization and interaction of the convective and stratiform regions of tropical squall lines. J. Atmos. Sci., 46, 521–
544.
Lebo, Z. J., and J. H. Seinfeld, 2011: Theoretical basis for
convective invigoration due to increased aerosol concentration. Atmos. Chem. Phys., 11, 5407–5429, doi:10.5194/
acp-11-5407-2011.
——, and H. Morrison, 2013: A novel scheme for parameterizing
aerosol processing in warm clouds. J. Atmos. Sci., 70, 3576–3598
——, ——, and J. H. Seinfeld, 2012: Are simulated aerosol-induced
effects on deep convective clouds strongly dependent on saturation adjustment? Atmos. Chem. Phys., 12, 9941–9964,
doi:10.5194/acp-12-9941-2012.
Lee, S. S., 2011: Dependence of aerosol-precipitation interactions
on humidity in a multiple-cloud system. Atmos. Chem. Phys.,
11, 2179–2196, doi:10.5194/acp-11-2179-2011.
——, L. J. Donner, V. T. J. Phillips, and Y. Ming, 2008a: The dependence of aerosol effects on clouds and precipitation on
cloud-system organization, shear and stability. J. Geophys.
Res., 113, D16202, doi:10.1029/2007JD009224.
——, ——, ——, and ——, 2008b: Examination of aerosol effects
on precipitation in deep convective clouds during the 1997
ARM summer experiment. Quart. J. Roy. Meteor. Soc., 134,
1201–1220, doi:10.1002/qj.287.
Lu, M.-L., and J. H. Seinfeld, 2005: Study of the aerosol indirect
effect by large-eddy simulation of marine stratocumulus.
J. Atmos. Sci., 62, 3909–3932.
Markowski, P., and Y. Richardson, 2010: Mesoscale Meteorology in
Midlatitudes. Wiley-Blackwell, 407 pp.
Mitra, S. K., J. Brinkmann, and H. T. Pruppacher, 1992: A wind
tunnel study on the drop-to-particle conversion. J. Aerosol
Sci., 23, 245–256.
Morrison, H., 2012: On the robustness of aerosol effects on an
idealized supercell storm simulated with a cloud systemresolving model. Atmos. Chem. Phys., 12, 7689–7705, doi:10.5194/
acp-12-7689-2012.
——, G. Thompson, and V. Tatarskii, 2009: Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and
two-moment schemes. Mon. Wea. Rev., 137, 991–1007.
——, S. A. Tessendorf, J. Ikeda, and G. Thompson, 2012: Sensitivity of a simulated midlatitude squall line to parameterization of raindrop breakup. Mon. Wea. Rev., 140, 2437–2460.
Muhlbauer, A., and Coauthors, 2013: Reexamination of the stateof-the-art of cloud modeling shows real improvements. Bull.
Amer. Meteor. Soc., 94, ES45–ES48.
Nicholls, M. E., R. H. Johnson, and W. R. Cotton, 1988: The sensitivity of two-dimensional simulations of tropical squall lines
to environmental profiles. J. Atmos. Sci., 45, 3625–3649.
Noppel, H., U. Blahak, A. Seifert, and K. D. Beheng, 2010: Simulations of a hailstorm and the impact of CCN using an
VOLUME 142
advanced two-moment cloud microphysics scheme. Atmos.
Res., 96, 286–301.
Parker, M. D., 2010: Relationship between system slope and
updraft intensity in squall lines. Mon. Wea. Rev., 138, 3672–
3578.
——, and R. H. Johnson, 2004: Structures and dynamics of quasi2D mesoscale convective systems. J. Atmos. Sci., 61, 545–
567.
Robe, F. R., and K. A. Emanuel, 2001: The effect of vertical wind
shear on radiative-convection equilibrium states. J. Atmos.
Sci., 58, 1427–1445.
Rosenfeld, D., U. Lohmann, G. B. Raga, C. D. O’Dowd,
M. Kulmala, S. Fuzzi, A. Reissell, and M. O. Andreae, 2008:
Flood or drought: How do aerosols affect precipitation?
Science, 321, 1309–1313.
Rotunno, R., J. B. Klemp, and M. L. Weisman, 1988: A theory for
strong, long-lived squall lines. J. Atmos. Sci., 45, 463–485.
——, ——, and ——, 1990: Comments on ‘‘A numerical investigation of the organization and interaction of the convective
and stratiform regions of tropical squall lines.’’ J. Atmos. Sci.,
47, 1031–1033.
Seifert, A., and K. D. Beheng, 2006: A two-moment cloud microphysics parameterization for mixed-phase clouds. Part 2:
Maritime vs. continental deep convective storms. Meteor.
Atmos. Phys., 92, 45–66.
——, C. K€
ohler, and K. D. Beheng, 2012: Aerosol-cloudprecipitation effects over Germany as simulated by a
convective-scale numerical weather prediction model. Atmos.
Chem. Phys., 12, 709–725, doi:10.5194/acp-12-709-2012.
Seigel, R. B., S. C. van den Heever, and S. M. Saleeby, 2013:
Mineral dust indirect effects and cloud radiative feedbacks of
a simulated idealized nocturnal squall line. Atmos. Chem.
Phys., 13, 4467–4485, doi:10.5194/acp-13-4467-2013.
Skamarock, W. C., and Coauthors, 2008: A description of the advanced research WRF version 3. NCAR Tech. Note NCAR/
TN–4751STR, National Center for Atmospheric Research,
Boulder, CO, 125 pp.
Squires, P., 1958: The microstructure and colloidal stability of
warm clouds: Part I— The relation between structure and
stability. Tellus, 10, 256–261.
Stensrud, D. J., M. C. Coniglio, R. P. Davies-Jones, and J. S. Evans,
2005: Comments on ‘‘‘A theory for strong long-lived squall
lines’ revisited.’’ J. Atmos. Sci., 62, 2989–2996.
Storer, R. L., and S. C. van den Heever, 2013: Microphysical processes evident in aerosol forcing of tropical deep convective
clouds. J. Atmos. Sci., 70, 430–446.
Szeto, J. M., and H. Cho, 1994: A numerical investigation of squall
lines. Part II: The mechanics of evolution. J. Atmos. Sci., 51,
425–433.
Takemi, T., 2007: A sensitivity of squall-line intensity to environmental static stability under various shear and moisture conditions. Atmos. Res., 84, 374–389.
Tao, W.-K., X. Li, A. Khain, T. Matsui, S. Lang, and J. Simpson,
2007: Role of atmospheric aerosol concentration on deep
convective precipitation: Cloud-resolving model simulations.
J. Geophys. Res., 112, D24S18, doi:10.1029/2007JD008728.
——, J. Chen, Z. Li, C. Wang, and C. Zhang, 2012: Impact of
aerosols on convective clouds and precipitation. Rev. Geophys., 50, RG2001, doi:10.1029/2011RG000369.
Teller, A., and Z. Levin, 2006: The effects of aerosols on precipitation and dimensions of subtropical clouds: A sensitivity
study using a numerical cloud model. Atmos. Chem. Phys., 6,
67–80.
MARCH 2014
LEBO AND MORRISON
Thorpe, A. J., M. J. Miller, and M. W. Moncrieff, 1982: Twodimensional convection in non-constant shear: A model of midlatitude squall lines. Quart. J. Roy. Meteor. Soc., 108, 739–762.
Van den Heever, S. C., and W. R. Cotton, 2007: Urban aerosol
impacts on downwind convective storms. J. Appl. Meteor.
Climatol., 46, 828–850.
——, G. G. Carri, W. R. Cotton, P. J. DeMott, and A. J. Prenni,
2006: Impacts of nucleating aerosol on Florida storms. Part I:
Mesoscale simulations. J. Atmos. Sci., 63, 1752–1775.
van Weverburg, K., A. M. Vogelmann, H. Morrison, and J. A.
Milbrandt, 2012: Sensitivity of idealized squall-line simulations to the level of complexity used in two-moment bulk
microphysics schemes. Mon. Wea. Rev., 140, 1883–1907.
Wang, C., 2005: A modeling study of the response of tropical deep
convection to the increase of cloud condensation nuclei concentration: 1. Dynamics and microphysics. J. Geophys. Res.,
110, D21211, doi:10.1029/2004JD005720.
1009
Weisman, M. L., and R. Rotunno, 2004: ‘‘A theory for strong longlived squall lines’’ revisited. J. Atmos. Sci., 61, 361–382.
——, J. B. Klemp, and R. Rotunno, 1988: Structure and evolution
of numerically simulated squall lines. J. Atmos. Sci., 45, 1990–
2013.
Wood, R., 2007: Cancellation of aerosol indirect effects in marine
stratocumulus through cloud thinning. J. Atmos. Sci., 64, 2657–
2669.
Xue, L., A. Teller, R. Rasmussen, I. Geresdi, and Z. Pan, 2010:
Effects of aerosol solubility and regeneration on warmphase orographic clouds and precipitation simulated by
a detailed bin microphysics scheme. J. Atmos. Sci., 67, 3336–
3354.
Ziegler, C. L., E. R. Mansell, J. M. Straka, D. R. MacGorman, and
D. W. Burgess, 2010: The impact of spatial variations of lowlevel stability on the life cycle of a simulated supercell storm.
Mon. Wea. Rev., 138, 1738–1766.

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