Influence of condensation and latent heat release upon
barotropic and baroclinic instabilities of vortices in a
rotating shallow water f-plane model
Masoud Rostami, Vladimir Zeitlin
To cite this version:
Masoud Rostami, Vladimir Zeitlin. Influence of condensation and latent heat release upon
barotropic and baroclinic instabilities of vortices in a rotating shallow water f-plane model.
Geophysical and Astrophysical Fluid Dynamics, Taylor & Francis, 2017, 111 (1), pp.1-31.
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This is the Authors‟ Original Manuscript (AOM); that is, the manuscript in its
original form; a „preprint‟. The Version of Record (VOR) of this manuscript has
been published and is available in the: “Geophysical & Astrophysical Fluid
Dynamics”.
Published online: 4 Jan 2017
http://dx.doi.org/10.1080/03091929.2016.1269897
DOI: 10.1080/09500693.2015.1022623
November 18, 2016
Geophysical and Astrophysical Fluid Dynamics
oneandtwolayer˙revision4
This is the Authors’ Original Manuscript (AOM); that is, the manuscript in its original form;
a ‘preprint. The Version of Record (VOR) of this manuscript has been published and is
available in the: “Geophysical & Astrophysical Fluid Dynamics”.
Published online: 4 Jan 2017
http://dx.doi.org/10.1080/03091929.2016.1269897
Geophysical and Astrophysical Fluid Dynamics
Vol. 00, No. 00, 00 Month 0000, 1–29
DOI: 10.1080/09500693.2015.1022623
Influence of condensation and latent heat release upon barotropic and
baroclinic instabilities of vortices in rotating shallow water f -plane model
†
MASOUD ROSTAMI† and VLADIMIR ZEITLIN †
Laboratoire de Météorologie Dynamique/Université Pierre et Marie Curie (UPMC)/ Ecole Normale
Supérieure (ENS)/CNRS, Paris, France
(Received 00 Month 20xx; final version received 00 Month 20xx)
Analysis of the influence of condensation and related latent heat release upon developing barotropic and
baroclinic instabilities of large-scale low Rossby-number shielded vortices on the f - plane is performed within
the moist-convective rotating shallow water model, in its barotropic (one-layer) and baroclinic (two-layer)
versions. Numerical simulations with a high-resolution well-balanced finite-volume code, using a relaxation
parameterisation for condensation, are made. Evolution of the instability in four different environments, with
humidity (i) behaving as passive scalar, (ii) subject to condensation beyond a saturation threshold, (iii) subject to condensation and evaporation, with two different parameterisations of the latter, are inter-compared.
The simulations are initialised with unstable modes determined from the detailed linear stability analysis
in the “dry” version of the model. In a configuration corresponding to low-level mid-latitude atmospheric
vortices, it is shown that the known scenario of evolution of barotropically unstable vortices, consisting in
formation of a pair of dipoles (“dipolar breakdown”) is substantially modified by condensation and related
moist convection, especially in the presence of surface evaporation. No enhancement of the instability due
to precipitation was detected in this case. Cyclone-anticyclone asymmetry with respect to sensitivity to
the moist effects is evidenced. It is shown that inertia-gravity wave emission during the vortex evolution
is enhanced by the moist effects. In the baroclinic configuration corresponding to idealised cut-off lows in
the atmosphere, it is shown that the azimuthal structure of the leading unstable mode is sensitive to the
details of stratification. Scenarios of evolution are completely different for different azimuthal structures, one
leading to dipolar breaking, and another to tripole formation. The effects of moisture considerably enhance
the perturbations in the lower layer, especially in the tripole formation scenario.
Keywords: Moist-convective Rotating Shallow Water, Vortex Dynamics, Barotropic Instability,
Baroclinic Instability
1.
Introduction
The purpose of the present paper is to understand how the effects of moist convection and
condensation affect instabilities and evolution of large-scale atmospheric vortices. Our main
interest is in the impact of condensation and related latent heat release upon dynamics, so we
will not have to recourse to the full-scale thermodynamics of the moist air and will be using
a simplified model where only the most rough features of the moist convection are taken into
account. Dynamically, large-scale low Rossby-number vortices, which we will be considering
in the f -plane approximation, are well-described within the quasi-geostrophic (QG) models,
where the effects of moist convection may be included in a simple way, on the basis of conservation of the moist potential vorticity (Lapeyre and Held 2004). Yet, by construction, QG
models miss an important dynamical ingredient, inertia-gravity waves (IGW). (Another element which the QG model misses is sharp density/potential temperature fronts, although
those are out of the scope of the present paper). Vortex instabilities are known to produce
IGW emission, and its quantification is important in the general context of understanding the
sources of IGW in the atmosphere. That is why we choose to work with the so-called moistconvective rotating shallow water model (mcRSW) which incorporates the moist convection
Corresponding author. Email: zeitlin@lmd.ens.fr Address: LMD-ENS, 24 Rue Lhomond, 75005 Paris, France
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and condensation in a simple, albeit self-consistent, way. As usual, the QG equations may
be recovered in the model in the limit of small Rossby numbers. The model in its barotropic
and baroclinic versions, respectively, was proposed in (Bouchut et al. 2009, Lambaerts et al.
2011a) and was inspired by the pioneering work by Gill (1982). The work of Ooyama (1969)
was probably the first where such kind of model, in axisymmetric version, was applied for
studying dynamics of atmospheric vortices - tropical cyclones. This approach was later pursued by Zehnder (2001). A similar model, with special attention to the parameterisation of
the boundary layer processes, was used by Schecter (2009) for understanding tropical cyclogeneses. Recently, the barotropic version of the model was applied to modelling the development
of instabilities of tropical cyclones (Lahaye and Zeitlin 2016).
Unlike the latter papers dealing with intense vortices with high Rossby numbers, we will be
using the model for studying instabilities of large-scale small Rossby number barotropic and
baroclinic vortices and their nonlinear dynamical saturation (it should be emphasized that the
term “saturation” is used below to describe both the saturation of the moist air in the thermodynamical sense, and also dynamical saturation of the instability in the sense that growth
predicted by linear analysis ceases and gives rise to reorganisation of the flow). To quantify
dynamical influence of moisture, we will be comparing the behavior of vortices in “dry” and
“moist-precipitating” configurations of the model, with the moisture being a passive tracer in
the former (which is thus, in fact, moist (M), but not precipitating) and having a condensation sink (MP) which creates a moist-convective vertical flux in the latter. (We should recall
that, in the framework of mcRSW, condensation and precipitation are synonymous.) Adding
evaporation source gives a third, moist-precipitating-evaporating (MPE) configuration, which
will be also studied. Our strategy will be the same as that of (Lambaerts et al. 2011b, 2012), in
studying dynamical influence of moisture upon instabilities of barotropic and baroclinic jets.
A notable difference with these papers, though, is that in the present study we also include
the effects of surface evaporation, which will be shown to be important. However, we will be
not dwelling into details of the boundary-layer processes, and will be limiting ourselves by the
simplest possible parameterisations of fluxes across the lower boundary of the model.
It should be stressed that condensation and related moist convection are essentially nonlinear phenomena, and hence the techniques of linear stability analysis are inapplicable in the
moist-precipitating case. So, as in the case of jets (Lambaerts et al. 2011b, 2012), we will be
performing linear stability analysis of “dry” vortices, and then using the obtained unstable
modes to initialise numerical simulations of both ”dry” and moist-precipitating (and evaporating) evolution of the instability. The well-balanced high-resolution finite-volume numerical
scheme adapted for mcRSW in (Bouchut et al. 2009, Lambaerts et al. 2011a), will be used in
these simulations. The model resolves well the IGW, including front (shock) formation, the
precipitation fronts, and maintains balanced states. It also allows for self-consistent inclusion
of topography, which is however out of the scope of the present paper.
By construction the one-layer version of the model is a limit of the two-layer one with
infinitely deep upper layer, see below. So, physically, vortices in the one-layer model represent
idealised low-level atmospheric vortices, while the baroclinic vortices that we treat in the twolayer model are upper-level vortices, of the type of cut-off lows frequently encountered in the
atmosphere at mid-latitudes.
The paper is organised as follows. The model, both in one- and two-layer versions, and
the vortex configurations to be studied are introduced in section 2. Linear stability analysis
framework and results are presented in section 3. Section 4 contains results on nonlinear
evolution of the barotropic and baroclinic vortex instabilities in “dry”, moist-precipitating
and moist-precipitating and evaporating cases, and their inter-comparison. Conclusions and
discussion are presented in section 5.
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2.
3
The model and the background flow
In this section we present the model we are working with. It is a rotating shallow water model
where convective fluxes due to the latent heat release are added at the interface between the
lower, humid, and the upper, dry layer, as well as surface evaporation at the lower boundary.
Although multi-layer generalisation of the model is possible, cf. the references in sect. 1 above,
we will be using the two- layer version, and its one-layer reduction. The model retains the
most rough features of the moist convection, yet in a self-consistent way, and allows to follow
both vortex and inertia-gravity wave components of the flow.
2.1.
Moist-convective rotating shallow water model
2.1.1. Equations of motion
The equations of the two-layer mcRSW, as introduced in (Lambaerts et al. 2011a) are:
D1 v 1
+ f ẑ × v 1 = −g∇H (h1 + h2 ),
Dt
v1 − v2
D2 v 2
+ f ẑ × v 2 = −g∇H (h1 + sh2 ) +
βP1 ,
h2
Dt
∂t h1 + ∇.(h1 v 1 ) = −βP1 ,
∂t h2 + ∇.(h2 v 2 ) = +βP1 ,
∂t Q1 + ∇.(Q1 v 1 ) = −P1 + E.
(1)
Here v i is the horizontal velocity field in layer i = 1, 2 (counted from the bottom) and
Di /Dt is the corresponding horizontal material derivative. f is the Coriolis parameter, which
will be supposed to be constant, ẑ is the unit vector in z-direction, hi are thicknesses of
the layers, θi is the normalised potential temperature in each layer, s = (θ2 /θ1 ) > 1 is the
stratification parameter. Let us recall that this model is obtained from the primitive equations,
with pseudo-height as vertical coordinate, by vertical averaging between the material surfaces
zi−1 , zi , with zi − zi−1 = hi and adding additional convective flux due to the latent heat
release through z1 . This convective flux is then linked to the water-vapour condensation P1
in the lower humid layer through the moist enthalpy conservation, and gives a sink (source)
in the mass conservation equation in the lower (upper) layer. The coefficient β is determined
by the background stratification in the parent primitive-equations model, see Lambaerts et
al. (2011a). Due to the convective mass exchange the same flux leads to appearance of the
Rayleigh drag in the upper-layer momentum equation. At the same time, condensation gives
a sink in the bulk moisture content Q1 in the lower layer. If surface evaporation E is present,
it provides a source of moisture in the lower layer. Finally, condensation and moisture content
are related by a simple relaxation relation:
Q1 − Qs
H(Q1 − Qs ),
(2)
τ
where H(.) is the Heaviside (step) function, and Qs is a saturation value. This scheme is of the
type used in general circulation models (Betts and Miller 1986). In what follows the simplest
parameterisation with a constant Qs is used. Note that the condensed water is dropped off
the dynamics, and we do not consider the inverse phase transition liquid water - water vapor
in this simplified model. (Hence the evaporation E, if any, is the surface one in the model,
and in this sense there is no difference between condensation and precipitation, and they will
P1 =
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be used as synonyms in what follows). Radiation cooling will be omitted as well, cf. Ooyama
(1969).
It is useful to consider the limit τ → 0 in (2), because the relaxation time τ is small (several
hours) in the atmosphere, and will be small (several time-steps) in the numerical simulations
presented below. As shown in (Gill 1982, Bouchut et al. 2009), in this (wet) limit
P = −Qs ∇·v,
(3)
and precipitation is directly proportional to the wind convergence. There exist several simple
parameterisations for surface evaporation, for example, proportional to the deviation of the
local value of humidity from the saturation: E = E1 = γ(Qs − Q)H(Qs − Q) , or proportional
to the wind velocity: E = E2 = δ|v |, where coefficients γ and δ are adjustable parameters.
Both were used in the literature, e.g. (Neelin et al. 1987, Goswami and Goswami 1991), the first
more adapted for situations with weak winds, and the second - to strongly under-saturated
boundary layer. The two may be combined, cf. e.g. (Ooyama 1969), (Kondo et al. 1990):
E = E3 = κ|v |(Qs − Q)H(Qs − Q). We will be testing all three of them below.
In the limit of very deep upper layer h2 → ∞ we obtain a simplified one-layer version of
the model :
∂t v 1 + (v 1 ·∇)v 1 + f ẑ × v 1 = −g∇h1 ,
∂t h1 + ∇· (v 1 h1 ) = −βP1 ,
(4)
∂t Q1 + ∇·(Q1 v 1 ) = −P1 + E,
see Lambaerts et al. (2011a) for a detailed demonstration.
2.1.2. Conservation laws
Conservation laws of the standard RSW model change in the presence of precipitation and
related convection. Although mass and bulk humidity are not conserved in the lower layer,
their combination m1 = h1 −βQ, corresponding in this simplified model to the moist enthalpy,
is locally conserved in the absence of surface evaporation:
∂t m1 + ∇·(m1 v 1 ) = 0.
(5)
This shows the consistency of the model, in spite of its simplicity. Potential vorticity (PV)
equations in each layer in the presence of precipitation and without evaporation, E = 0,
become:
(∂t + v 1 ·∇)
ζ1 + f
ζ1 + f
=
βP1 ,
h1
h21
(6)
(∂t + v 2 ·∇)
ζ2 + f
ζ2 + f
ẑ
v1 − v2
=−
βP
+
·
∇
×
βP
,
1
1
h2
h2
h2
h22
(7)
where ζi = ẑ·(∇ × v i ) = ∂x vi − ∂y ui (i = 1, 2) is relative vorticity, and qi = (ζi + f )/hi , i = 1, 2
is PV layerwise. Hence, PV in each layer is not a Lagrangian invariant in precipitating regions.
In the absence of evaporation, the conservation of the moist enthalpy in the lower layer allows
to derive a new Lagrangian invariant, the moist PV:
(∂t + v 1 ·∇)
ζ1 + f
= 0.
m1
(8)
It should be noted that surface evaporation renders the system forced, and destroys the
conservation of moist enthalpy and moist potential vorticity. Care should be taken in numerical
simulations with evaporation, as moist enthalpy should remain everywhere
positive to ensure
R
thermodynamic stability. The dry energy of the system is E = dxdy(e1 + e2 ), where the
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energy densities of the layers are:
(
2
5
2
e1 = h1 v21 + g h21 ,
2
2
e2 = h2 v22 + gh1 h2 + sg h22 .
Supposing that there are no energy exchanges through the boundaries, we get:
Z
(v 1 − v 2 )2
.
∂t E = − dxdy βP gh2 (1 − s) +
2
(9)
The first term in this equation corresponds to production of potential energy (for stable
stratifications) due to upward convection fluxes; the second term corresponds to destruction
of kinetic energy due to the Rayleigh drag.
The horizontal momentum of individual layers is not conserved due to convective mass
exchanges, but the total momentum of the two-layer system is conserved, cf (Lambaerts et al.
2011a).
2.2.
Vortex configurations
We start with a simpler case of one-layer model, which will also serve for benchmarking.
Anticipating the use of axisymmetric solutions, we write down the “dry” (P1 = 0) version of
(4) in polar coordinates (r, θ) in terms of radial and azimuthal components of the velocity
v = ur̂ + v θ̂, where hats denote unit vectors in corresponding directions:
Du v 2
−
− fv = −g∂r h,
Dt
r
Dv uv
(10)
+
+ fu = −g∂θ h,
r
Dt
∂t h + 1 ∂r (hru) + 1 ∂θ (hv) = 0.
r
r
Here D/Dt is the horizontal material derivative in polar coordinates (we omit the subscript
1 from now on). As is clear from these equations, and well-known, any axisymmetric flow
(vortex) with azimuthal velocity v = V (r) and thickness h = H(r) in cyclo-geostrophic
equilibrium (gradient wind balance in the language of meteorology)
V
+ f V = g∂r H
(11)
r
is an exact solution of (10). In what follows we are interested in isolated vortices, i.e. those satisfying (11) and having zero circulation at infinity. It √
is simpler to work with non-dimensional
√
variables and we will be using the following scaling: gH0 for velocity, Rd = gH0 /f for r,
and 1/f for time, where H0 is the non-perturbed thickness of the layer. Star notation will
be adopted for non-dimensional variables. We choose to work with so-called α-Gaussian vortices with the following non-dimensional distribution of azimuthal velocity (non-dimensional
variables are denoted by an asterisk):
α
V ∗ (r∗ ) = ±r∗ 2 exp(
−r∗ α + 1
),
2
α ≥ 1.
(12)
Here the positive sign corresponds to cyclones and the negative one to anticyclones. The
corresponding profile of H(r∗ ) is given by the primitive of the l.h.s. of (11) calculated with
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M. ROSTAMI & V. ZEITLIN
(12):
1
1√
1
r∗ α 1
1
1
H (r ) = 1 − (±)
2e2 α Γ( + )G(
, + ), where
α
α 2
2 α 2
∗
∗
1
G(x, a) =
Γ(a)
Z
a
e−t ta−1 dt.
x
(13)
The α-Gaussian vortices have two parameters: α and , which control the steepness of the
azimuthal velocity profile and the amplitude of the velocity, respectively. This class of vortices
was used in recent studies of vortex instabilities (Kloosterziel et al. 2007, Lahaye and Zeitlin
2015). It is slightly different from another profile, also used in the literature (Carton et al. 1989,
Baey and Carton 2002), but the two coincide at α = 2. Such profiles provide a simple analytical
form of a shielded (i.e. with zero circulation at infinity, and hence finite energy) vortex. Radial
distribution of the relative vorticity in the vortex is given by (1/r∗ )d(r∗ (V ∗ (r∗ )))/dr∗ , therefore
cyclonic vortices have a core of positive relative vorticity inside a ring of negative relative
vorticity, and vice verse for anticyclonic vortices. So we deal with vortices that possess a sign
reversal in the radial vorticity profile, which should produce a barotropic instability, according
to well-known criteria. We focus below on vortices with small Rossby numbers, i.e. with peak
azimuthal velocities of small amplitude. If we recall the interpretation of the one-layer model
as a two-layer model with infinitely deep upper layer, the above configuration corresponds
to a vortex in the lower layer with motionless upper layer. An opposite situation of a vortex
with the same profile in the upper layer and motionless lower layer can be considered in the
two-layer version of the model. Such upper-layer vortices, so called cut-off lows, e.g. (Gimeno
et al. 2007), are frequently produced in the atmosphere in mid-latitudes by meandering uppertropospheric jets. Writing the “dry” two-layer system in polar coordinates is straightforward,
and the two-layer analog of (11) is
V
r1 + f V1 = g∂r (H1 + H2 ) ,
(14)
V2
+
f
V
=
g∂
(H
+
sH
)
.
2
r
1
2
r
It is clear that taking the profile (12) for V2 , supposing H1 +sH2 = const, and taking H1 +sH2
in the form of (13), allows to find unambiguously H1 and H2 for an upper-layer vortex.
3.
Linear stability analysis
In this section we formulate the linear stability problem, sketch the method of its solution,
and present results of the linear stability analysis of the alpha -Gaussian vortices in one- and
two-layer versions of the model.
3.1.
Linear stability of vortices in the one-layer model
3.1.1. Formulation of the linear stability problem
To analyse the linear stability of vortex solutions we apply the standard linearisation procedure by considering a small perturbation of the axisymmetric background flow: The linearised
non-dimensional equations read:
V∗
2V ∗ ∗
∗
∗ +
∗ )u − (1 +
(∂
∂
)v = −∂r∗ η ∗ ,
t
θ
r∗
r∗
∗
V
V∗
1
(∂r∗ V ∗ + 1 + ∗ )u∗ + (∂t∗ + ∗ ∂θ∗ )v ∗ = − ∗ ∂θ∗ η ∗ ,
(15)
r
r
r
∗
V
1
1
(∂t∗ + ∗ ∂θ∗ )η ∗ + H ∗ ∂r∗ + ( ∗ ∂r∗ r∗ H ∗ ) u∗ + ∗ H ∗ ∂θ∗ v ∗ = 0,
r
r
r
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instabilities of vortices in the mcrsw model
7
where we denote the perturbations of u and v by the same letters, and the perturbation of h
by η. We are looking for the normal-mode solutions with harmonic dependence on time and
polar angle
(u∗ , v ∗ , η ∗ )(r∗ , θ∗ , t∗ ) = Re[(iũ, ṽ, η̃)(r∗ )ei(lθ
∗
−ωt∗ )
],
(16)
where l and ω are the azimuthal wavenumber and the frequency, respectively. Substitution of
(16) in (15) yields the eigen-problem:
2V ∗
lV ∗
(1 + ∗ ) −Dr∗
r∗
r
ũ
ũ
ũ
∗
∗
V
lV
l
∗)
ṽ
ṽ ,
M1 × ṽ =
×
=
ω
(17)
∗
(1
+
+
D
V
r
r∗
r∗∗
r∗∗
η̃
η̃
η̃
lV
1
lH
H ∗ Dr∗ + ∗ Dr∗ (r∗ H ∗ )
∗
r
r
r∗
where Dr∗ denotes the differentiation operator with respect to r∗ . Complex eigenfrequencies
ω = ωr + iωI with positive imaginary part (ωI > 0), correspond to instabilities with linear
growth rate σ = ωI . Below we perform a numerical linear stability analysis of the problem
(17) with the help of the pseudo-spectral collocation method (Trefethen 2000). The system is
discretised over an N -point grid and Dr∗ becomes the Chebyshev differentiation operator. To
avoid the Runge phenomenon, Chebyshev collocation points are used, with a stretching in the
radial direction allowing to densify the collocation points in the most dynamically interesting
region near the center of the vortex, as in (Lahaye and Zeitlin 2015) where the method of
Boyd (1987) was adapted to the stability problem of circular vortices. In order to make the
standard parameters, Rossby and Burger numbers, to appear, an alternative scaling can be
used, based on the typical horizontal scale of the background flow L(r = Lr∗ ). In this case,
the matrix in l.h.s. of (17) becomes:
2V ∗
Bu
lV ∗
(1 + Ro ∗ ) −
Dr∗
Ro ∗
Ro
∗r
∗ r
lV
Bu
l
V
∗
,
M 1 = (1 + Ro ∗ + Ro.Dr∗ V )
(18)
Ro ∗
∗
r
r
Ro
r
∗
∗
1
lH
lV
Ro[H ∗ Dr∗ + ∗ Dr∗ (r∗ H ∗ )]
Ro ∗
Ro ∗
r
r
r
where Ro = U/f L, Bu = gH/f 2 L2 = (Rd /L)2 .
3.1.2. Results of the linear stability analysis
We describe in this subsection the results of the linear stability analysis of cyclonic and
anticyclonic α-Gaussian vortices obtained by pseudo-spectral collocation method, which was
briefly sketched above. We present in Fig. 1 a typical output of the numerical linear stability
analysis. The structure of unstable modes together with the background vortex profile of a
cyclone are displayed. Results for an anti-cyclone with the same parameters are similar (not
shown).
We have analysed the linear stability of cyclonic and anticyclonic vortices for the values
of steepness parameter α varying from 2 to 6, and the amplitude parameter varying from
0.05 to 1, with a general result that the growth rate of the unstable modes monotonically
increases with α and , as follows from Fig. 2, right panel. The azimuthal wavenumber of the
most unstable mode increases with α, cf. Fig. 2, left and middle panels. There is a switch in
the azimuthal structure of the most unstable mode when steepness increases. These results
qualitatively agree with those of Baey and Carton (2002) which were obtained with a similar,
but not the same, vortex profile. It is worth noting that our results show that for the same
values of parameters, the growth rates of the most unstable modes are higher for cyclonic than
for anticyclonic vortices, which shows cyclone-anticyclone asymmetry already at this level.
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M. ROSTAMI & V. ZEITLIN
Figure 1. Upper row: left - radial structure (u, v, η)(r) of the most unstable mode (vertical line: position of the critical
level); right - corresponding pressure and velocity fields on the x − y plane. Lower row: left - azimuthal velocity profile
and vorticity of the background barotropic cyclone with α = 4, = 0.1061; right - Chebyshev grid points (resolution
N = 550), and thickness of the vortex H(r). Stability analysis is performed within the “dry” model.
Figure 2. Dependence of the “dry” linear growth rates of different azimuthal modes on steepness for anticyclonic (left
panel) and cyclonic (middle panel) vortices with = 0.1414, and dependence of the growth rate of the mode l = 2 upon
steepness and amplitude parameters α and (right panel)
3.2.
Linear stability of vortices in the two-layer model
3.2.1. Formulation of the linear stability problem
The linearisation procedure around a vortex solution H1∗ , H2∗ , V1∗ and V2∗ in layer-wise
cyclo-geostrophic equilibrium (14) in the two-layer case follows the same lines as in the onelayer case above. The eigen-frequencies and corresponding eigen-modes are found from the
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Figure 3. Structure of the most unstable mode of an upper-layer cyclone with α = 4, , H2 /H1 = 0.6, l = 2, = 0.08 and
s = 1.37. Upper row: left (right) - pressure and velocity fields in the x − y plane in the upper (lower) layer Lower row:
left - H1 and H2 of the background vortex, right - radial structure of the unstable mode, dashed (solid) lines: imaginary
(real) part. Stability analysis is performed within the “dry” model.
non-dimensional eigen-problem:
2V ∗
lV1∗
(1 + ∗1 ) −Dr∗
0
0
−Dr∗
∗
6
r
r
∗
∗
6
lV
V
l
l
1
1
6
∗
3
2
0
0
6 (1 + ∗ + Dr∗ V1 )
ũ1
r
r∗∗
r∗∗
r∗
6
6 ṽ1 7 6 ∗
lH1
lV1
1
∗ ∗
7 6
6
∗
∗
0
0
0
6 η̃1 7 6 H1 Dr + r∗ Dr (r H1 )
∗
r
r∗
M2 × 6
7=6
lV2∗
2V2∗
6 ũ2 7 6
0
0
−Dr∗
(1 + ∗ ) −sDr∗
4 ṽ 5 6
∗
2
6
r
∗r
6
V
lV2∗
l
l
η̃2
2
∗)
6
∗
0
0
(1
+
+
D
V
s ∗
r
2
6
r∗
r∗
r∗∗
r∗
4
lH2
lV2
1
0
0
0 H2∗ Dr∗ + ∗ Dr∗ (r∗ H2∗ )
r
r∗
r∗
2
3
7
7
7 2
2
3
3
7
ũ1
ũ1
7
6 ṽ1 7
7 6 ṽ1 7
6
7
7
7 6
6 η̃ 7
7 6 η̃1 7
7 × 6 ũ 7 = ω 6 ũ1 7 ,
6 27
7 6 27
7 4 ṽ 5
4 ṽ 5
2
2
7
7
η̃2
η̃
2
7
7
5
(19)
where M 2 is the 6 × 6 operator matrix which can be rewritten in terms of Rossby and Burger
numbers with the help of the scaling r = Lr∗ similar to (18) (not shown).
3.2.2. Results of the linear stability analysis
As was already explained, we are interested in upper-layer cyclones. The most unstable
mode of an α-Gaussian upper-layer cyclone is presented in Figure 3. As in the one-layer case,
we analysed the dependence of the growth rate on the parameters of the background vortex
which is presented in Figs. 4 and 5. An important conclusion following from this analysis is
that there is a swap between l = 2 and l = 3 in azimuthal structure of the most unstable
mode with changing steepness of the vortex profile and/or thickness ratio, for strong enough
stratifications.
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Figure 4. Dependence of the “dry” growth rates of different azimuthal modes on steepness for upper-layer cyclone with
= 0.1, H2 /H1 = 0.6, and s = 1.37.
Figure 5. Variation of the “dry” growth rate of the most unstable mode of the upper-layer cyclone with H2 /H1 and
α = 4 for weak (s = 1.1, left panel) and strong (s = 1.37, right panel) stratification.
4.
Nonlinear evolution of barotropic and baroclinic instabilities of vortices: comparison
of “dry”, moist-precipitating, and moist-precipitating and evaporating simulations
In this section we present the results of comparison of nonlinear evolution of the barotropic
and baroclinic instabilities of vortices which were analysed at the linear level in section 3. We
perform fully nonlinear numerical simulations in one- and two-layer mcRSW models with the
help of the finite-volume well-balanced RSW code with a relaxation scheme for precipitation,
as in (Lambaerts et al. 2011b, 2012). The simulations which are presented below are initialised,
for both cyclonic and anticyclonic vortices, by the α-Gaussian profiles of H(r) and V (r).
The most unstable mode, which was obtained by the linear stability analysis of section 3,
was superimposed, with a small amplitude ≈ 0.01, on the background vortex at the initial
moment. A change of parameter β can be absorbed in rescaling of Q and τ , so it was kept
equal to unity in the simulations. τ was taken to be as short as possible, several time-steps,
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11
first, to be consistent with physical reality, and second, in order to be able to confront the
results with qualitative analysis available in the immediate relaxation limit. Q was chosen to
be sufficiently close to Qs , in order to assure non-negligible condensation. We will compare
nonlinear evolutions of l = 2 and l = 3 instabilities and see that they are significantly different.
The following numerical experiments were performed:
• One-layer barotropic model : evolution of 1) anicyclonic and 2) cyclonic vortex with
superimposed most unstable modes in dry (M), moist-precipitating (MP) and moistprecipitating with surface evaporation (MPE) configurations. All three surface evaporation schemes E1, E2, and E3 were tested. The MPE III results are not systematically
presented as with the above choice of initial (uniform) distribution of moisture they are
similar to MPE II results.
• Two-layer baroclinic model : evolution of an upper-layer cyclone with superposed unstable
modes with 1) dipolar and 2) tripolar azimuthal structure in all configurations mentioned
above.
Pressure, velocity and PV fields obtained in these experiments were used for diagnostics
of vortices, and divergence field was used to diagnose inertia-gravity waves. Humidity field
Q and precipitation field P were used to diagnose evolution of moisture and condensation.
The growth rates of the instability were analyzed with the help of dry energy norm of the
perturbations.
4.1.
Evolution of the barotropic instability: dipolar splitting
In this section we present results of numerical simulations of the evolution of the vortex instability in the barotropic one-layer model where the leading instability has azimuthal wavenumber l = 2. Various diagnostics of the influence of moist effects upon developing instability are
displayed.
4.1.1. Vortex evolution as seen in the PV and humidity field
The inter-comparison of the development of the barotropic instability in “dry” (M), with
moisture behaving as passive scalar, moist-precipitating (MP), and most precipitating and
evaporating (MPE I, MPE II), with the surface evaporation parameterisations E1 and E2
discussed in section 2, environments are presented in Figs. 6 and 7, for anticyclonic and
cyclonic vortices, respectively. The dry PV anomaly (PVA) q − f /H0 is used for diagnostics.
We also made experiments with the mixed parameterisation of evaporation E3 which give
similar to E2 results (not shown). We will come back to this point later.
To analyse the results, let us first concentrate on the “dry” evolution of the instability
(first row in Figs. 6, 7). For both anticyclone and cyclone it consists in appearance of satellite
vortices of the sign opposite to the main vortex at the periphery of this latter. As time
goes on, the core of the initial vortex becomes elliptic and two satellite vortices intensify.
The satellite vortices exert shear and strain on the core, and finally split it in two. The two
vortices originating from the core pair with satellites and produce two vortex dipoles running
in opposite directions. This is a barotropic dipolar breaking described in the literature (Baey
and Carton 2002).
Let us now see how precipitation and evaporation modify the “dry” evolution scenario. The
initial moisture in all simulations was distributed uniformly and unsaturated, albeit close to
saturation: Q0 = 0.89, and Qs = 0.9. When Q > Qs , as follows from (2) the precipitation
switches on. As shown in section 2.1, precipitation and evaporation affect the PV. A useful insight on the evolution of vorticity in the presence of precipitation can be obtained by
considering (4) in QG approximation. Following (Lambaerts et al. 2011b) we get:
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Figure 6. Evolution of PVA of the anticyclonic vortex with α = 4, = 0.1061, l = 2, γ = 0.01, δ = 0.001 during the
saturation of the barotropic instability in four different environments: M, MP, MPE I, and MPE II, respectively from
top to bottom.
(∂t + v g ·∇)(∇2 ψ − ψ) = βP1 ,
(∂t + v g ·∇)(Q̃ − Qs ∇2 ψ) = −P1 ,
(20)
where Q̃ is the moisture deficit with respect to the saturation, v g is the geostrophic velocity,
and ψ is the geostrophic stream function of the flow v g = ẑ ∧ ψ. In the immediate relaxation
limit (τ → 0), we can assume that Q̃ ≈ 0 and get:
Qs (∂t + v g ·∇)ζg = P1 ,
∇2 ψ
(21)
where ζg =
is the quasi-geostrophic vorticity. It is clear from this formula that cyclonic
motions in the precipitation regions become intensified. This is exactly what is observed in the
second rows of Figs. 6, 7. As a consequence, the resulting dipoles become asymmetric, with a
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13
Figure 7. Same as in Fig. 6 but for the cyclonic vortex.
dominant cyclonic part. Correspondingly, their trajectories change and become meandering,
as compared to the quasi-rectilinear ones in the dry case (not shown). These phenomena
are pronounced even more in the presence of evaporation. For both parameterisations of
evaporation, the cyclonic partner of each dipole pair is enhanced and occupies a larger area,
while the anticyclonic partner is inhibited and shrinks, as compared with the case without
evaporation. A net enhancement of the cyclonic component of the dipoles is confirmed by
Fig. 8 where we show the corresponding evolution of maximum and minimum pressure. As
follows from Fig. 8, in all precipitating environments the pressure maximum is weakened and
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Evolution of the maximum pressure
Evolution of the minimum pressure
1.035
Pressure
1.025
M,
MP,
MPE I, (γ = 0.01)
MPE II,(δ = 0.001)
0.93
0.92
Pressure
1.03
0.94
1.02
1.015
0.9
0.89
1.005
0.88
50
Evolution of
0.87
0
100
150
200
[ f−1]
theTime
maximum
pressure
100
150
200
1
M,
MP,
MPE I, (γ = 0.01)
MPE II,(δ = 0.001)
1.1
1.06
1.04
M,
MP,
MPE I, (γ = 0.01)
MPE II,(δ = 0.001)
0.99
Pressure
1.08
1.02
0
50
Time
[ f−1]
Evolution of the
minimum
pressure
1.12
Pressure
0.91
1.01
1
0
M,
MP,
MPE I, (γ = 0.01)
MPE II,(δ = 0.001)
0.98
0.97
0.96
50
100
Time [ f−1]
150
200
0.95
0
50
100
Time [ f−1]
150
200
Figure 8. Evolution of the maximum (left) and minimum (right) pressure in different environments of the cyclonic (top),
and the anticyclonic (bottom) vortices, both with α = 4, l = 2, = 0.1016.
Figure 9. Evolution of PVA of anticyclonic vortex with α = 4, = 0.1016 in the MPE II environment. The surface
evaporation coefficient δ = 0.01 is ten times larger than in the bottom row of Fig. 6.
the pressure minimum deepened, as compared to the “dry” case, in full accordance with the
PVA evolution.
It must be emphasised that the values of parameters γ and δ have significant influence on
the PVA evolution. Fig. 9 shows that enhancement of cyclonic vorticity is so strong at large
values of evaporation coefficient (δ = 0.01) that only a part of it enters the secondary dipole,
which becomes very compact, while another part is shed forming a vorticity strip subject to
secondary shear instabilities.
Comparison of evolution of humidity during the evolution of the instability of an anticyclonic
vortex in “dry” and moist-precipitating environments is presented in Fig. 10. The areas of
enhanced humidity, exceeding the saturation level, in the non-precipitating (M) simulation
indicate locations of precipitation zones in the precipitating environment.
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15
Figure 10. Evolution of the bulk humidity Q in M (upper row) and MP (lower row) environments for the anticyclonic
vortex with α = 4, = 0.1061.
4.1.2. Quantifying evolution of the instability: growth rate and precipitation
As was already said in section 2, condensation is an essentially nonlinear phenomenon, and
thus the moist instability cannot be studied by the standard means of the linear stability
analysis. To get an estimate of the growth rate of the moist instability we follow (Lambaerts
et al. 2011b) and measure it in the simulations by using the dry energy norm:
2
Z Z
η2
1d
S (t)
u2 + v 2
2
+g
, σ(t) =
log 2
.
(22)
S (t) =
H0 (x, y)
2
2
2 dt
S (t0 )
Linearisation of the “dry” system (4) about the state of rest leads to
Z Z
Z Z
dS 2 (t)
= −gH0 (x, y)
∇·(ηv )dxdy − gβ
ηP dxdy.
dt
(23)
The influence of precipitation is given by the second term in the r.h.s. of this equations, which
shows that s2 (t) is sensitive to the sign of the pressure perturbation in the precipitating region,
cf. (Gill 1982, Lapeyre and Held 2004, Lambaerts et al. 2011b).
Fig. 11 represents the variation of the growth rate in time for both anticyclonic and cyclonic
vortices, as follows from the simulations of Figs. 6, 7 in different environments. The prediction
for the “dry” growth rate obtained in section 3 is also shown for comparison. As follows from
the Figure, at the very beginning σ differs from the growth rate given by the linear stability
analysis. The reasons for such behaviour are (1) discretization errors (2) the fact that the
amplitude of the perturbation is small, yet finite, and thus the vortex with the superimposed
perturbation is (slightly) unbalanced and undergoes geostrophic adjustment (Zeitlin 2008) (see
also section 4.1.3 below). It takes several inertial periods to reach the geostrophic balance.
After this initial adjustment, the growth rate for about 15f −1 stays close to the linear one.
(The difference between the theoretical and measured growth rates diminishes with increasing
resolution and computational cost - not shown). Then the instability starts to dynamically
saturate and the growth rate diminishes. At the onset of the precipitation σ experiences a
short transient increase in precipitating environments, which is much more pronounced for
the cyclone, and then steadily decreases. This decrease is substantially faster in precipitating
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Figure 11. Variation of the growth rate of the barotropic instability of cyclonic (left) and anticyclonic (right) vortices,
both with α = 4, = 0.1061, l = 2, γ = 0.01 and δ = 0.001.
environments, as compared with the “dry” one. Such reduction of the growth rate can be
explained by the positive thickness anomaly in the precipitating region, cf. (23), which will
be confirmed in the next subsection. It should be emphasised that observed behaviour differs
compared to what was observed in the simulations of nonlinear evolution of the barotropic
instability of a jet in (Lambaerts et al. 2011b), where a persistent increase of the growth rate
of the instability was detected at the onset of precipitation. This means that the influence of
condensation and related latent heat release upon the growth rate of the barotropic instability
is not universal and depends on fine details of the flow - see also below.
In order to better understand the correspondence between the predictions of the linear stability
theory of section 3 and the results of numerical simulations, we decomposed the pressure and
velocity anomalies with respect to the unperturbed vortex in Fourier series in azimuthal
wavenumber l and traced the evolution of several Fourier-modes of the pressure field, as given
by numerical simulations in the dry environment initialised with the l = 2 perturbation. The
results are displayed in Fig. 12 and are similar for the Fourier-modes of the velocity field (not
shown). At initial stages l = 2 mode is dominant and follows well the prediction of the linear
theory. At the same time the mode l = 4, and then other even modes, start to grow from
their initially negligible, but non-zero due to discretisation errors, values. This growth is due
to nonlinear interaction of the original l = 2 perturbation, with itself, which projects onto the
2l = 4 mode, but also with other modes, which leads to eventual dynamical saturation of the
instability for both cyclonic and anticyclonic vortices. By symmetry reasons the amplitudes
of the modes with odd l remain very small. We were routinely making such benchmarks in all
simulations and will not present them anymore.
Let us now quantify the precipitation during the evolution of the instability. We recall that
in the immediate relaxation limit precipitation and wind divergence are directly linked, cf. (3).
We checked that this is, indeed, the case (not shown). The evolution of the total amount of
precipitation in the simulations of Figs. 6, 7 is presented in Fig. 13. As follows from the Figure,
the evolution of precipitation is bell-shaped before the splitting of the initial vortex into two
dipoles, and has a secondary peak due to precipitation inside the secondary dipoles. This peak
is due to the fact that an increase of convergence, and hence the precipitation, is observed
inside the anticyclonic partners of the secondary dipoles. This observation is confirmed by
Fig. 14, where the evolution of the PVA and precipitation, as given by the simulation of
Fig. 6, are superimposed. It is worth noting that precipitation patterns in all simulations are
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3
3
l=2, M
l=3, M
l=4, M
l=5, M
l=6, M
Linear σ
2
1
1
0
FT
FT
l=2, M
l=3, M
l=4, M
l=5, M
l=6, M
Linear σ
2
0
−1
−1
−2
−2
−3
−3
−4
−4
−5
0
17
50
100
Time [ f ]
−5
0
150
−1
50
100
Time [ f−1]
150
Figure 12. Logarithms of the normalised amplitudes of the first 6 Fourier modes of pressure as functions of time during
the “dry” evolution of the barotropic instability of the cyclonic (left) and anticyclonic (right) vortices. α = 4, l = 2,
γ = 0.01
Figure 13. Total precipitation of the cyclonic (left panel) and anticyclonic (right panel) vortex, both with α = 4, =
0.1061, in different environments.
close and do not depend much on the parameterisation of surface evaporation. The MPE
II and MPE III patterns are practically identical. As is clear from Fig. 7, the intensity of
the anticyclonic components of the secondary dipoles in the case of primary cyclone is much
weaker than for the primary anticyclone, which explains the difference in precipitation patterns
between the two. We finally present in Fig. 15 the evolution of the pressure anomaly η with
respect to initial vortex profile, with superposed precipitation, which corresponds to the (MP)
simulation of Fig. 6. As follows from the figure, precipitation is correlated with positive values
of η which explains is destructive influence upon the growth rate, cf. (23).
4.1.3. Inertia-gravity wave (IGW) emission
As was already said in the Introduction, the question of IGW emission during the evolution
of the instability, and of the influence of moist processes upon it, is of importance. We have
analysed the IGW emission for cyclonic and anticyclonic vortices in all four environments. As
a diagnostic of the IGW activity W we calculated the modulus of wind divergence integrated
over an annulus of non-dimensional width 0.5 situated sufficiently far from the vortex core,
at the non-dimensional distance 5.5 from the center:
Z r=6
Z 2π
W =
rdr
dθ |∇ · v| .
(24)
r=5.5
0
The time-evolution of thus defined IGW activity is presented in Fig. 16 for both anticyclonic
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4
Time = 60
Time = 90
Time = 120
Time = 150
MP
2
0
P = 0.0001
PVA= −0.3
PVA= −0.1
PVA= +0.1
−2
−4
4
Time = 60
Time = 90
Time = 120
Time = 150
MPE I
2
0
P = 0.0001
PVA= −0.3
PVA= −0.1
PVA= +0.1
−2
−4
4
Time = 60
Time = 90
Time = 120
Time = 150
MPE II
2
0
P = 0.0001
PVA= −0.3
PVA= −0.1
PVA= +0.1
−2
−4
4
Time = 60
Time = 90
Time = 120
Time = 150
MPE III
2
0
−2
−4
P = 0.0001
pva= −0.3
pva= −0.1
pva= +0.1
Figure 14. Joint evolution of PVA (thin contours) and precipitation (inside the thick contours), as follows from MP,
MPE I, MPE II, and MPE III (κ = 0.05) simulations of Fig 6, respectively from top to bottom.
Figure 15. Joint evolution of pressure anomaly η (colors) and precipitation (contours) in the MP environment for the
anticyclonic vortex with α = 4, = 0.1061.
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Figure 16. Evolution of the wave activity W of the cyclonic (top) and anticyclonic (bottom) vortices with = 0.1061, α =
4, l = 2 during the evolution of the barotropic instability in four different environments.
and cyclonic vortices. The IGW emission starts in both cases early, together with the elongation of the vortex core. A notable increase in the wave activity takes place when the core
vortex, accompanied by its two satellite vortices, splits into two dipoles at t ≈ 200. Another
remarkable increase in the wave activity happens at the beginning of the precipitation around
t = 50. The IGW emission has substantially stronger peaks in MP, MPE I and MPE II environments, as compared to the “dry” one M. The wave field corresponding to the events of
strongest IGW emissions: (1) at the onset of precipitation, (2) after formation and separation
of two dipoles is represented in the upper panel of Fig. 17. The fact that it is not only the
reorganisation of the flow, but also moist effects which are at the origin of the increase in IGW
activity, follows from inter-comparison of MP and MPE curves in Fig. 16, showing that with
an increase of precipitation due to evaporation the IGW activity increases. Fig. 17 also shows
a cyclone-anticyclone asymmetry in what concerns the wave emission, which is much more
pronounced for the cyclone, starting from t ≈ 100f −1 . A strong maximum in wave activity
produced by the cyclone in the MPE II environment corresponds to the high-amplitude wavepacket presented in the lower panel of Fig. 17. Yet, this large-amplitude IGW is not convection
- coupled, except for locations where the wave is passing through the second vortex dipole, as
follows from the distribution of precipitation which is not coupled to the wave.
4.2.
Evolution of the baroclinic instability: dipolar splitting
For the analysis of the evolution of the baroclinic instability, we will be following the same
lines as for the barotropic instability, except that we will be considering only a cyclonic vortex
in the upper layer, as in Sec. 3.2 above.
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Figure 17. Inertia-gravity wave emission as seen in the divergence field: Upper row - anticyclonic vortex with l = 2, =
0.1061, α = 4 in MP environment at (1) the beginning of precipitation about t = 45f −1 and (2) the separation of
two dipoles about t = 207f −1 ; Lower row - cyclonic vortex with l = 2, = 0.1061, α = 4 in MPE II environment at
t ≈ 175f −1 . Precipitation zones are delimited by thick contours.
4.2.1. Vortex evolution as seen in the PV and humidity field
We present in Figs. 18, 19 the evolution of the PVA, respectively in upper and lower layers,
during the evolution of the baroclinic instability of the upper-layer cyclone. In the upper layer,
the evolution is very similar to that of we have seen in the barotropic case. In the lower layer,
the initial negative (due to the absence of low-layer velocity of the background vortex and a
bump in thickness, cf. Fig. 3) PVA is stretched and positive values gradually appear forming
secondary dipoles. Enhancement of positive PVA in all precipitating cases is spectacular. It
leads to effective barotropisation of secondary dipoles.
4.2.2. Quantifying development of the instability: growth rate, precipitation, and IGW
emission
As in the barotropic case, we calculate the growth rate based on the dry energy norm,
which displays a similar behavior: following the linear stability analysis prediction for a dozen
of inertial periods, and then decaying, with a transient increase at the stage of formation of
lower-layer dipoles.
The precipitation peak in MP and MPE I environments corresponds to the process of splitting
of the initial vortex into two dipoles. The continuing increase in precipitation in MPE II
environment is related to a large value of evaporation coefficient and an increase of velocity
in intensifying lower-layer dipoles. It should be emphasised that overall precipitation remains
very small, as compared with the lower-layer vortex case of section 4.1.2. However, the position
of precipitation areas with respect to the vortex is different, and their spread in the MPE II
case is wider, as follows from Fig. 20.
The evolution of activity of baroclinic waves, calculated with the help of divergence of the
baroclinic velocity field v1 − v2 in the same way as in one-layer case, is presented in Fig. 21.
Apart from the initial peak which is related to the stretching of the core vortex, like in the
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Figure 18. Evolution of PVA in the upper layer during the evolution of the l = 2 instability of the upper-layer cyclone
with α = 4, = 0.08, s = 1.37, H0 = 3, H2 /H1 = 0.6, δ = 0.05, γ = 0.05.
barotropic case, no secondary enhancement of the IGW activity is observed. This is due to the
weak divergence field in the lower layer during the whole simulation, and weak precipitation.
4.3.
Nonlinear evolution of the baroclinic instability: tripole formation
Let us now sketch what happens if the mode l = 3 is the most unstable one. Following the
same lines as in the previous case of the most unstable mode with l = 2, we performed
numerical simulations of developing instability in different environments. We again checked
that the flow evolution follows the linear stability analysis at initial stages (not shown). We
show the results for pressure evolution in the lower, most interesting, layer in Fig. 22.
Comparison of the evolution of the moisture content in “dry” and moist-precipitating sim-
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Figure 19. Same as in Fig. 18, but for the lower layer.
ulations is presented in Fig. 23. The upper row of this Figure clearly indicates precipitation
zones appearing in precipitating environment in the middle row, which is confirmed by the
bottom row, where joint evolution of PVA and precipitation in the lower layer is displayed. As
follows from this Figure, the precipitation pattern is totally different compared to the dipolar
breakdown case, with formation of characteristic rain bands. We observe considerable quantitative differences of tripolar evolution scenario, as compared to dipolar breakdown, in the
behaviour of the growth rate and the wave activity. Evolution of the growth rate, calculated,
as usual, with the help of the dry energy norm is presented in Fig. 24.
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Figure 20. Superposition of the precipitation and PVA in the lower layer during dipolar splitting of upper-layer cyclone.
Thick lines delimit precipitation regions. α = 4, = 0.08, s = 1.37, H0 = 3, H2 /H1 = 0.6, δ = 0.05, γ = 0.05.
Figure 21. Evolution of the wave activity of baroclinic IGW (α = 4, = 0.08, s = 1.37, H0 = 3, H2 /H1 = 0.6, δ =
0.05, γ = 0.05) during the evolution of the baroclinic instability of a vortex with l = 2 most unstable mode.
It shows an enhancement of the growth rate, which becomes higher than the “dry” one due
to precipitation. At the same time the dynamical saturation (decrease of the growth rate) is
faster in the moist-precipitating environment than in the “dry” one. Such behaviour was not
observed in the dipolar splitting scenarios, both barotropic and baroclinic, cf. Fig. 11. On the
contrary, it is very similar to what was observed in (Lambaerts et al. 2012) in the case of
baroclinic instability of the upper-layer jet.
The wave activity is measured in the same way as in barotropic and baroclinic dipolar
breakdown cases, and is presented in Fig. 25. It is persistent and is much stronger than in the
dipolar breakdown case at later stages of the evolution. The wave-field at the peak of wave
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Figure 22. Evolution of pressure anomaly in the “dry” simulation of the development of the baroclinic instability with
most unstable mode l = 3 in the lower layer.
Figure 23. Evolution of moisture in M (top) and MP (middle) environments and joint evolution of PVA and precipitation
in the MP simulation (bottom) of a vortex with l = 3 most unstable mode.
activity of Fig. 25 correspond to a packet of baroclinic IGW propagating out of the vortex
(nt shown).
5.
Summary, conclusions, and discussion
We performed a comparative analysis of development of barotropic and baroclinic instabilities of large-scale small Rossby-number anticyclonic and cyclonic shielded α-Gaussian vortices
evolving in initially uniform humidity field with moisture being (i) passively advected (M), (ii)
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Figure 24. Evolution of the growth rate of the perturbation during the tripolar evolution scenario in M and MP
environments.
Figure 25. Wave activity during the evolution of the baroclnic instability in tripole formation scenario in M and MP
environments.
Figure 26. Wave field corresponding to the peak of the wave activity of Fig. 25 .
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subject to precipitation beyond a saturation threshold (MP), with corresponding convective
flux, (iii) subject to precipitation and evaporation, with two different evaporation parameterisations. At a preliminary stage we accomplished a detailed linear stability analysis of the
vortex solutions, which provided unstable modes used for initialisations of direct numerical
simulations of the dynamical saturation of the instabilities.
Our general conclusion is that condensation and latent heat release, especially in conjunction with evaporation, considerably modify the evolution of the instabilities. The enhancement
of cyclonic component of the flow is universal, although particular modifications, including
decrease or increase of the growth rate and of the wave activity, are not universal and are
sensitive to the details of the flow configuration. Scenario of evolution of the instability is
sensitive to the details of the background vortex flow, in particular its stratification in the
two-layer case, with instabilities of different azimuthal structure having close growth rates
and evolving and precipitating differently. Strong differences are observed in the evolution of
unstable modes with azimuthal numbers l = 2 and l = 3, including sensitivity to the effects
of moisture. Thus, characteristic “rain bands” were found during the evolution of the tripolar
instability of the upper-layer vortex. Therefore, scenario of evolution of the atmospheric vortices, and in particular precipitation patterns, are highly sensitive to the azimuthal structure
of the most unstable mode, and the latter is sensitive to fine details of the vortex profile.
This is important to bear in mind in the general context of predictability of atmospheric
flows. It is worth emphasising in this context the influence of the upper-level dynamics of
the atmosphere upon precipitation in the lower layer which we observed. Although it leads to
qualitative changes, like e.g. structure and trajectories of secondary dipoles in dipolar splitting
scenario, the influence of moist effects upon low Rossby number vortices is less spectacular
than for the high Rossby number ones (Lahaye and Zeitlin 2015), where they lead to overall
intensification of the vortex and emission of convectively coupled waves. Still, precipitation
events enhance the emission of inertia-gravity waves, which is a fact of general importance.
Yet, comparing the results of our highly idealised simulations with observations would be a
too-far stretch.
To summarize the main results,
• In the barotropic case the linear stability analysis confirmed results of previous studies
with similar, albeit different, vortex profiles. Differences in growth rates of unstable
modes of the same azimuthal structure for cyclonic and anticyclonic vortices with the
same parameters, and thus cyclone-anticyclone asymmetry, were found. The azimuthal
structure of the most unstable mode changes when vortex parameters change. Nonlinear
simulations of the evolution of the instability showed that a known “dipolar splitting”
scenario, which we confirmed in the “dry” (M) environment, is modified by moist effects.
Both the structure and the direction of propagation of the resulting dipoles are changed
by the moist convection, especially in the presence of evaporation. If evaporation is
strong enough, the resulting dipoles can be completely reorganised. A strong cycloneanticyclone asymmetry in the response to the condensation and related convection, with
anticyclonic vortex evolution being affected much stronger. At the same time, IGW
emission, especially in moist-precipitating and evaporating environment, is substantially
stronger for the cyclonic vortex. We also detected an overall destructive influence of
precipitation and related convection upon the growth rate of the instability, apart from
a short transient increase of the growth rate, which differs from the results of Lambaerts
et al. (2011b, 2012). A substantial increase of the IGW activity was detected at the onset
of splitting of the initial vortex in two dipoles, in both dry and moist environments, and
also at the secondary dipoles’ separation stage. The condensation was shown to be at
the origin of the latter increase.
• In the baroclinic case the analysis was concentrated on the idealised upper-level cyclonic
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vortices of cut-off low type. Full linear stability analysis revealed sensitivity of the growth
rates and of azimuthal structure of the most unstable modes to the vortex parameters,
and in particular to the stratification and thickness ratio parameters. Nonlinear simulations with the most unstable mode of the same azimuthal structure l = 2 as in the
barotropic case gave a similar scenario of evolution, with strong enhancement of cyclonic
vorticity in the lower humid layer. On the contrary, the gravity wave activity was not enhanced by precipitation events due to the overall low values of velocity in the lower layer.
Nonlinear simulations with the most unstable mode with l = 3 revealed a totally different saturation scenario with secondary tripole formation, specific precipitation patterns
(“rain bands”) and enhanced inertia-gravity wave activity. Contrary to both barotropic
and baroclinic dipolar splitting scenarios of evolution, the growth rate of the perturbation is considerably enhanced by precipitation in this case, exceeding the “dry” linear
stability value.
Acknowledgements: We are grateful to N. Lahaye for help with numerical simulations
and discussions. We also thank anonymous Referees for careful reading of the manuscript and
useful suggestions.
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