A medicane, or Mediterranean cyclone with characteristics similar to
tropical cyclones, is simulated using a kilometre-scale
ocean–atmosphere coupled modelling platform. A first phase leads to
strong convective precipitation, with high potential vorticity
anomalies aloft due to an upper-level trough. Then, the deepening and
tropical transition of the cyclone result from a synergy of baroclinic
and diabatic processes. Heavy precipitation results from uplift of
conditionally unstable air masses due to low-level convergence at
sea. This convergence is enhanced by cold pools, generated either by
rain evaporation or by advection of continental air masses from northern
Africa. Back trajectories show that air–sea heat exchanges moisten the
low-level inflow towards the cyclone centre. However, the impact of
ocean–atmosphere coupling on the cyclone track, intensity and
life cycle is very weak. This is due to a sea-surface cooling 1 order
of magnitude weaker than for tropical cyclones, even in the area of
strong enthalpy fluxes. Surface currents have no impact. Analysing the
surface enthalpy fluxes shows that evaporation is controlled mainly by
the sea-surface temperature and wind. Humidity and temperature at the
first level play a role during the development phase only. In
contrast, the sensible heat transfer depends mainly on the temperature
at the first level throughout the medicane lifetime. This study shows that
the tropical transition, in this case, is dependent on processes
widespread in the Mediterranean Basin, like advection of continental
air, rain evaporation and formation of cold pools, and dry-air
intrusion.
Introduction
Medicanes are small-size Mediterranean cyclones presenting, during
their mature phase, characteristics similar to those of tropical
cyclones. This includes a cloudless and almost windless column at the
centre, spiral rainbands, and a large-scale cold anomaly surrounding
a smaller warm anomaly, extending at least up to the mid-troposphere
(∼400hPa; Picornell et al., 2014). However, they differ
from their tropical counterparts in many aspects. First, their
intensity is much weaker, with maximum wind speed reaching those of
tropical storms or a Category 1 hurricane on the Saffir–Simpson scale
for the most intense of them (Miglietta et al., 2013). Second, they
are much smaller, with a typical radius ranging from 50 to 200 km
(Picornell et al., 2014). Third, their mature phase lasts a few hours
to 1 to 2 d because the small size of the Mediterranean Basin leads
them to fall onto land rapidly and because the ocean heat capacity is
weak. Fourth, they develop and sustain over a sea-surface temperature
(SST) of typically 15 to 23 ∘C (Tous and Romero, 2013),
much colder than the 26 ∘C threshold of tropical
cyclones (Trenberth, 2005; although tropical cyclones formed by
a tropical transition can develop over colder water; McTaggart-Cowan
et al., 2015). Finally, at their early stage, vertical wind shear and
the horizontal temperature gradient are necessary for their development
(e.g. Flaounas et al., 2015).
In the last decade, several studies have investigated their characteristics
and conditions of formation from satellite observations (Claud
et al., 2010; Tous and Romero, 2013), climatological studies (Gaertner
et al., 2007; Cavicchia et al., 2014; Flaounas et al., 2015) or
case studies based on simulations (Davolio et al., 2009; Miglietta
et al., 2013, 2017; Miglietta and Rotunno, 2019). A feature common to
many medicanes is the presence of an elongated upper-level trough
(also know as a PV streamer) bringing cold air with high values of
potential vorticity (PV) from higher-latitude regions. Other local
effects favouring their development are lee cyclones forming south of
the Alps or north of the northern African reliefs (Tibaldi et al., 1990),
coastal reliefs favouring deep convection (Moscatello et al., 2008),
and relatively warm sea-surface waters able to feed the process of
latent heat release during their mature phase.
The medicane cases meeting all the previous criteria represent only
a small portion of the Mediterranean cyclones (e.g. 13 of 200 cases
of intense cyclones or roughly one per year in the study of Flaounas
et al., 2015). Due to this scarcity, clearly defining the properties
enabling the separation of medicanes from other Mediterranean cyclones is
still challenging. A study using dynamical criteria concluded that
medicanes are very similar to other intense cyclones, with a slightly
weaker upper-level and a stronger low-level PV anomaly (Flaounas
et al., 2015). Recent comparative studies (e.g. Akhtar et al., 2014;
Miglietta et al., 2017) showed a large diversity of duration,
extension (size and vertical extent) and characteristics (dominant
role of baroclinic vs. diabatic processes) within the medicane
category.
The role of the large-scale environment like the PV streamer and of
the associated upper-level jet in medicane formation has been the
subject of several studies (Reale and Atlas, 2001; Homar et al.,
2003;
Flaounas et al., 2015; Carrió et al., 2017). In a case study in
September 2006, it was shown for the first time that the crossing of
the upper-level jet by the cyclone resulted in its rapid deepening by
interaction between low- and upper-level PV anomalies (Chaboureau
et al., 2012). Recently, the ubiquitous presence of PV streamers and
their key role in the development of medicanes have been confirmed in
several cases (Miglietta et al., 2017). These studies concluded also
that, during their life cycle, medicanes can rely either on purely
diabatic processes or on a combination of baroclinic and diabatic
processes (Mazza et al., 2017; Fita and Flaounas, 2018; Miglietta and
Rotunno, 2019).
Conversely, the investigation of the contribution of surface processes
has motivated fewer studies. Some of them assessed the relative
importance of surface heat extraction vs. latent heat release and
upper-level PV anomaly throughout the cyclone lifetime by using
adjoint models or factor separation techniques (Reed et al., 2001;
Homar et al., 2003; Moscatello et al., 2008; Carrió et al.,
2017). They concluded that the presence of the upper-level trough
during the earlier stage of the cyclone and the latent heat release
during its developing and mature phases are necessary. In contrast,
the role of surface heat fluxes is more elusive. Like in tropical
cyclones, the latent heat fluxes always dominate the surface enthalpy
processes (the sensible heat flux represents 25 % to 30 % of the
turbulent heat fluxes prior to the tropical transition and 15 % to
20 % during the mature phase; Pytharoulis, 2018). Early studies
concluded that low-level instability controlled by surface heat fluxes
may be “an important factor of intensification” (Reed et al., 2001,
case of January 1982) and that the latent heat extraction from the sea
is a “key factor of feeding of the latent-heat release” (Homar
et al., 2003, case study of September 1996). Turning off the surface
turbulent fluxes during different phases of the cyclone was
in contrast to this view. Indeed, the role of surface enthalpy in feeding
the cyclonic circulation proved important during its earliest and
mature phases, whereas its role is marginal during the deepening
(Moscatello et al., 2008, case study of September 2006).
More recently, studies simulating several cyclones suggested that the
impact of the surface fluxes on the cyclone are probably
case-dependent (Tous and Romero, 2013; Miglietta and Rotunno,
2019). The latter work especially compared the medicanes of October 1996 (between the Balearic Islands and Sardinia) and December 2005
(north of Libya) to investigate the relative role of the WISHE-like
mechanism (WISHE – wind-induced surface heat exchange: Emanuel, 1986; Rotunno
and Emanuel, 1987) and baroclinic processes. In the case of October
1996, the cyclone warm core is formed by latent heat release fed at
the low level by sea-surface heat fluxes. Surface fluxes are above
1500 Wm-2 over large areas due to persistent orographic
winds bringing cold and dry air for several days prior to the cyclone
development that contribute to destabilising the surface layer. The
features characteristics of tropical cyclones are well marked: warm
core extending up to 400 hPa, symmetry, low-level convergence
and upper-level divergence, and strong contrast of equivalent
potential temperature θe (∼8∘C) between the surface and 900 hPa as
evidence of latent heating. Conversely, in the December 2005 case, the
cyclone develops within a large-scale baroclinic environment, with the
PV streamer slowly evolving into a cut-off low. The features similar to tropical cyclones are less evident: a weaker warm core due to warm-air seclusion and
weaker gradient of θe (∼3–4 ∘C) between the surface and 900 hPa. The
surface enthalpy fluxes play only a marginal role and peak around
1000 Wm-2 for a few hours. The authors concluded that
mechanisms of transition towards medicanes are diverse,
especially concerning the role of the air–sea heat exchanges.
As surface fluxes may strongly depend on the SST, a change of the
oceanic surface conditions may, in theory, impact the development of
a medicane. Several sensitivity studies investigated the impact of
a uniform SST change, for instance to anticipate the possible effect
of the warming of Mediterranean surface waters due to climate
change. Consistent tendencies were obtained in different case studies
(Homar et al., 2003, case of September 1996; Miglietta et al., 2011,
case of September 2006; Pytharoulis, 2018, case of November 2014;
Noyelle et al., 2019, case of October 1996). As expected, warmer
(colder) SSTs lead to more (less) intense cyclones
even though changes of SST by less than ±2∘C
result in no significant change in the track, duration or intensity of
the cyclone.
The impact of coupling atmospheric and oceanic models has been studied
mainly using regional climate models on seasonal to interannual timescales. Comparing coupled and non-coupled simulations showed an
impact of the coupling when the horizontal resolution of the model is
at least 0.08∘ (Akhtar et al., 2014). This resolution is also
necessary to reproduce, in a realistic way, the characteristic processes
of medicanes, including warm cores and strong winds at the low
level. Coupled simulations resulted in more intense surface heat
fluxes, in contrast to what is usually obtained in tropical cyclones
due to the strong cooling effect of the cyclone on the sea surface
(Schade and Emanuel, 1999; D'Asaro et al., 2007). This can be due to
the use of a 1-D ocean model and its limited ability to reproduce the
oceanic processes responsible for the cooling. The need of higher
resolutions to observe an impact of the coupling was confirmed by
Gaertner et al. (2017) and Flaounas et al. (2018). Both studies
compared several simulations at the seasonal or interannual scale,
both coupled and uncoupled and from several regional climate modelling
platforms. The lack of impact they obtained was attributed to the
relatively low horizontal resolution of the simulations, between 18
and 50 km. Finally, a case study based on higher-resolution
(5 km) simulations of the medicane of November 2011 showed no
strong impact of the surface coupling. The SST was 0.1 to
0.3 ∘C lower only, the sea-level pressure (SLP) minimum was 2 hPa
higher and the maximum surface wind was 5 ms-1 lower (Ricchi
et al., 2017). The impact of ocean–atmosphere coupling in
high-resolution (∼1–2 km), convection-resolving models
has, to the best of our knowledge, not been evaluated yet.
In the present study, we assess the feedback of the ocean surface on
the atmosphere in the case of the medicane of November 2014 (also
known as Qendresa) using a kilometre-scale ocean–atmosphere coupled
model. We investigate the role of the surface processes, especially
during the mature phase of the medicane, and we examine the role of
the different parameters (including SST) controlling these fluxes
throughout the life cycle of the cyclone.
A brief description of the medicane, of the modelling tools and of the
simulation strategy are given in Sect. 2. In Sect. 3, the results of
the reference simulation are used to describe the medicane
characteristics and life cycle and to present the impact of the
coupling. The roles of the surface conditions and mechanisms
controlling the air–sea fluxes during the different phases are
assessed in Sect. 4. These results are discussed in Sect. 5, and some
conclusions are given.
Case study and simulations
The case study is the Qendresa medicane that affected the region of
Sicily on 7 November 2014. It has been the subject of several studies
based on simulations. They investigated the role of SST anomalies or
the impact of a uniform SST change (Pytharoulis, 2018); the respective
role of upper-air instability, surface exchanges and latent heat
release (Carrió et al., 2017); or the predictability of the event,
depending on the initial conditions and horizontal resolution of the
model (Cioni et al., 2018). All those studies showed that the
predictability of this event and especially of its track is rather
low, even with high horizontal (1–2 km) and vertical (50 to
80 levels) grid resolutions of current operational numerical weather
prediction (NWP) centres. A recent study based on the ensemble
forecasts of the ECMWF (European Centre for Medium-Range Weather
Forecasts; Di Muzio et al., 2019) showed that the predictability of
occurrence (with respect to the operational analysis) is good with as early
as 7.5 d lead time, but the predictability of the position is weak,
especially between 4 and 1 d lead time (their Fig. 6). The
predicted central pressure is also consistently 10 to 14 hPa
higher than the analysed one, whatever the lead time considered.
The 7 November 2014 medicane
On 5 and 6 November 2014, a PV streamer extended from northern Europe
to northern Africa, bringing cold air (-23∘C) and
enhancing instability aloft. A general cyclonic circulation developed
over the Western Mediterranean basin, while the Eastern Mediterranean was
dominated by high pressures (Fig. 1a). At the low
level on 6 November, the cold and warm fronts associated with the
baroclinic disturbance were reinforced due to a northward advection of
warmer and moist air from northern Africa (Fig. 1b). The system moved
towards the Strait of Sicily and deepened during the night of 6 to
7 November. In the early hours of 7 November, the upper-level PV
trough and the low-level cyclone progressively aligned (Fig. 1c),
reinforcing the PV transfer from above and the low-level
instability. Strong convection developed, with heavy precipitation in
the Sicily area. The low-level system rapidly deepened in the morning
of 7 November, with a sudden drop of 8 hPa in 6 h, and
evolved into the quasi-circular structure of a tropical cyclone, with
spiral rainbands and a cloudless eye-like centre. The maximum
intensity was reached at around 12:00 UTC on 7 November to the north of
Lampedusa (see Fig. 3 for main place names). The system drifted
eastwards and slowly weakened during the afternoon of 7 November,
with a first landfall on Malta at around 17:00 UTC. It then moved
northeastwards to reach the Sicilian coasts in the evening. It
continued its decay during the following night close to the Sicilian
coasts and lost its circular shape and tropical-cyclone appearance
at around 12:00 UTC on 8 November.
Potential vorticity (PV) anomaly at 300 hPa (colour scale) and SLP
(isocontours every 4 hPa) at 12:00 UTC on 6 November (a) and 06:00 UTC on 7 November (c); temperature (colour scale, ∘C) and wind at 850 hPa
at 06:00 UTC on 6 November (b) from the ERA5 reanalysis.
Simulations
Three numerical simulations of the event were performed using the
state-of-the-art atmospheric model Meso-NH (Lac et al., 2018) and the
oceanic model NEMO (Madec and the NEMO Team, 2016).
Atmospheric model
The non-hydrostatic French research model Meso-NH version 5.3.0 is
used here with a fourth-order centred advection scheme for the
momentum components and the piecewise parabolic method advection
scheme from Colella and Woodward (1984) for the other variables,
associated with a leapfrog time scheme. A C grid in the Arakawa
convention (Mesinger and Arakawa, 1976) is used for both horizontal
and vertical discretisations, with a conformal projection system of
horizontal coordinates. A fourth-order diffusion scheme is applied to
the fluctuations of the wind variables, which are defined as the
departures from the large-scale values. The turbulence scheme (Cuxart
et al., 2000) is based on a 1.5-order closure coming from the system
of second-order equations for the turbulent moments derived from
Redelsperger and Sommeria (1986) in a one-dimensional simplified form
assuming that the horizontal gradients and turbulent fluxes are much
smaller than their vertical counterparts. The mixing length is
parameterised according to Bougeault and Lacarrere (1989), who related
it to the distance that a parcel with a given turbulent kinetic energy
at level z can travel downwards or upwards before being stopped by
buoyancy effects. Near the surface, these mixing lengths are modified
according to Redelsperger et al. (2001) to match both the
Monin–Obukhov similarity laws and the free-stream model
constants. The radiative transfer is computed by solving long-wave and
short-wave radiative transfer models separately using the ECMWF
operational radiation code (Morcrette, 1991). The surface fluxes are
computed within the SURFEX module (Surface Externalisée; Masson
et al., 2013) using, over sea, the iterative bulk parameterisation ECUME
(Belamari et al., 2005; Belamari and Pirani, 2007) linking the surface
turbulent fluxes to the meteorological gradients through the
appropriate transfer coefficients. The Meso-NH model shares its
physical representation of parameters, including the surface flux
parameterisation, with the French operational model AROME (Seity
et al., 2011) used for the Météo-France NWP with a current
horizontal grid spacing of 1.3 km. In this configuration,
deep convection is explicitly represented, while shallow convection is
parameterised using the eddy diffusivity Kain–Fritsch scheme (Pergaud
et al., 2009).
In the present study, a first atmosphere-only simulation with a grid
spacing of 4 km has been performed on a larger domain of
3200km×2300km (D1; see Fig. 2). This
simulation started at 18:00 UTC on 6 November and lasted
42 h until 12:00 UTC on 8 November. Its initial and
boundary conditions come from the ECMWF operational analyses Cy40R1
(horizontal resolution close to 16 km, 137 vertical levels)
every 6 h.
Map of the large-scale domain D1, with the domain D2 indicated by
the solid-line frame and the area of interest (AI) indicated by the
dashed-line frame.
As described in the following, this 4 km simulation provides
initial and boundary conditions for simulations on a smaller domain of
900km×1280km (D2; Fig. 2). This domain
extension was chosen as a trade-off between computing time and an
extension large enough to represent the physical processes involved in
the cyclone life cycle, including the influence of the coasts. All
simulations on the inner domain D2 share a time step of 3 s
and their grid (with horizontal grid resolution of 1.33 km and
55 stretched terrain-following levels). Atmospheric and surface
parameter fields are issued every 30 min.
Oceanic model
The ocean model used is NEMO (version 3_6) (Madec and the NEMO
Team, 2016), with physical parameterisations as follows. The total
variance dissipation scheme is used for tracer advection in order to
conserve energy and enstrophy (Barnier et al., 2006). The vertical
diffusion follows the standard turbulent kinetic-energy formulation of
NEMO (Blanke and Delecluse, 1993). In the case of unstable conditions,
a higher diffusivity coefficient of 10 m2s-1 is
applied (Lazar et al., 1999). The sea-surface height is a prognostic
variable solved thanks to the filtered free-surface scheme of Roullet
and Madec (2000). A no-slip lateral boundary condition is applied, and
the bottom friction is parameterised by a quadratic function with
a coefficient depending on the 2-D mean tidal energy (Lyard et al.,
2006; Beuvier et al., 2012). The diffusion is applied along
iso-neutral surfaces for the tracers using a Laplacian operator with
the horizontal eddy diffusivity value νh of
30 m2s-1. For the dynamics, a bi-Laplacian operator is
used with the horizontal viscosity coefficient ηh of
-1×109m4s-1.
The configuration used here is sub-regional and eddy-resolving, with
a 1/36∘ horizontal resolution over an ORCA grid from 2.2 to
2.6 km resolution named SICIL36 (ORCA is a tripolar grid with
variable resolution; Madec and Imbard, 1996), which was extracted from
the MED36 configuration domain (Arsouze et al., 2013) and shares the
same physical parameterisations with its “sister” configuration
WMED36 (Lebeaupin Brossier et al., 2014; Rainaud et al., 2017). It
uses 50 stretched z levels in the vertical, with level thickness
ranging from 1 m near the surface to 400 m at the sea
bottom (i.e. around 4000 m depth) and a partial step
representation of the bottom topography (Barnier et al., 2006). It has
four open boundaries corresponding to those of the D2 domain shown in
Fig. 2, and its time step is set to 300 s. The initial and
open boundary conditions come from the global 1/12∘ resolution
PSY2V4R4 daily analyses from Mercator Océan International
(Lellouche et al., 2013).
Configuration of simulations
The 3-hourly outputs of the large-scale simulation on D1 are used
as boundary and initial conditions for three different simulations on the
smaller domain D2, based on the previously described atmospheric and
oceanic configurations. These three simulations start at
00:00 UTC on 7 November and last 36 h, until
12:00 UTC on 8 November. The first atmosphere-only simulation
called NOCPL uses a fixed SST forcing, while the CPL and NOCUR
simulations are two-way coupled between Meso-NH and NEMO-SICIL36. In
CPL, the SURFEX–OASIS coupling interface (Voldoire et al., 2017)
enables exchanging the SST and two-dimensional surface currents from
NEMO to Meso-NH and the two components of the momentum flux, the solar
and non-solar heat fluxes and the freshwater flux from Meso-NH to NEMO
every 15 min. The NOCUR run is similar, except that the surface
currents are not transmitted from NEMO to Meso-NH.
Comparison of the simulated tracks (triangles) of the non-coupled
run (NOCPL; red), coupled run with SST only (NOCUR; cyan) and fully coupled
run (CPL; blue) with the best track (black closed circles) based on
observations as in Cioni et al. (2018). The position is shown every hour,
with time labels every 3 h, starting at 09:00 UTC on 7 November until 12:00 UTC on 8 November. In colours is initial sea surface temperature (SST;
∘C) at 01:00 UTC on 7 November.
In order to ensure that the impact of the coupling in the NOCUR and
CPL configurations originates from the time evolution of the SST
rather than from a change in the initial SST field, the SST field used
as a surface forcing in NOCPL is produced by the CPL run, 1 h
after the beginning of the simulation (i.e. after the initial
adjustment of the oceanic model). This field (Fig. 3) is kept constant
throughout the simulation.
Validation
Figure 3 compares the tracks of Qendresa obtained in the three
different simulations with the best track based on observations
(brightness temperature from radiance in the 10.8 µm channel
measured by the SEVIRI instrument aboard the MSG – Meteosat Second Generation – satellite; see Cioni
et al., 2018). All the simulated tracks are shifted northwards with
respect to the observations since the beginning of the
simulations. The mean distance between the simulated and observed
tracks is close to 85 km, with no significant difference
between the simulations. Cioni et al. (2018) showed that using
horizontal resolutions finer than 2.5 km is mandatory to
accurately represent the fine-scale structure of this cyclone and its
time evolution. Sensitivity studies showed that better resolution
results in simulated track closer to observations. The best agreement
is obtained with a nested configuration and an inner domain at
300 m resolution. In the present study, several sensitivity
tests were performed on the smaller domain to improve the simulated
track: (i) the starting time of the simulation was changed between
12:00 UTC on 6 November and 00:00 UTC on 7 November
with an increment of 3 h; (ii) the number of vertical levels in
Meso-NH was increased to 100, with stretching to ensure a better
sampling in the atmospheric boundary layer; and (iii) the atmospheric
simulation was performed without nesting, initial and boundary
conditions from ECMWF, and a horizontal resolution of 2 km. Note
that our inner domain D2 is close in its extension to the domain used
by Cioni et al. (2018). None of these tests (eight in total) significantly
improved the track, the northward shifting of the cyclone occurring in
every case in the early hours of 7 November.
Time series of the maximum of the 10 m wind speed and of the 10 m
wind averaged over a 100 km radius around the cyclone centre (a) and minimum
sea-level pressure (b) as obtained in the different simulations on 7 November and 8 November until 12:00 UTC. The thin red line in (a) indicates
the 18 ms-1 wind speed threshold. The background shading (here and in
the following time-series plots) indicates the development (light blue),
mature (orange) and decay (grey) phases. The observations of SLP in Linosa
(black plain circles) are shown for comparison in (b); the observations of
wind speed from Malta, Lampedusa and Pantelleria are shown in (a) – see
text.
The deepening and maximum intensity of the simulated cyclone are
nevertheless close to the observed ones, even if a direct (i.e.
co-localised) comparison is not possible due to the northward shift of
its track. A strong deepening of almost 15 hPa is obtained in
the first 12 h of the CPL simulation (Fig. 4b), with a minimum
value at 12:30 UTC on 7 November close to the minimum
observed at Linosa station. This station is the closest point to the
best track at the time of the observed maximum intensity of the
storm. The surface wind speed peaks at the same time (Fig. 4a), and
its time evolution agrees well with METAR observations at the stations
of Lampedusa, Pantelleria or Malta. Also, the time evolution of the
wind speed averaged over a 50 km radius around the cyclone
centre is in good agreement with the control simulation of Cioni
et al. (2018). Despite the northward shift of its track, the medicane
simulated by Meso-NH is very realistic and can be used to explore the
processes at play, especially concerning the role of the sea surface
thanks to the CPL simulation.
Medicane life cycle and coupling impact
This part presents first the successive phases of the event based on
an analysis of upper-level and mid-troposphere processes. Then, we
assess the impact of accounting for the short-term evolution of the
SST in the atmospheric surface processes.
Chronology of the simulated event
We use the methodology of Fita and Flaounas (2018) based on
upper-level and low-level dynamics, asymmetry, and thermal wind to
characterise the phases of the medicane. Figure 5 shows the
300 hPa PV anomaly, SLP, surface wind and equivalent potential
temperature θe at 850 hPa from the NOCPL
simulation. Phase space diagrams are commonly used to describe in
a synthetic way the symmetric characteristics of the cyclone as well
as the thermal characteristics and extent of its core. The present
version in Fig. 6 showing the evolution of Qendresa from
01:00 UTC on 7 November to 12:00 UTC on 8 November is
derived from the original work of Hart (2003) using the adaptation of
Picornell et al. (2014) for smaller-scale cyclones. The radius used
for computing the low-troposphere thickness asymmetry B and the
low-troposphere and upper-troposphere thermal winds (-VTL
and -VTU, respectively) were fitted to the radius of
maximum wind at 850 hPa and is close to 100 km, and
the low troposphere and upper troposphere are defined here as the
925–700 and 700–400 hPa levels, respectively. The radius
value of 100 km is in agreement with several other studies
focusing on medicanes and avoids a smooth-out of the warm-core
structure (Chaboureau et al., 2012; Miglietta et al., 2011; Cavicchia et al.,
2014; Picornell et al., 2014) but may lead to an
underestimation of the cyclone extension. Indeed, the radius of
maximum wind is ill defined or larger during the first stage of the
cyclone, but it is steady and close to 90 km during the major
part of its lifetime. As a result, the diagram obtained is likely less
representative of the cyclone structure during its first hours but
fits well after 10:00 UTC.
Potential vorticity at 300 hPa (colour scale) and SLP (isocontours
every 4 hPa; the 1000 hPa isobar is in bold) (a, c, e, g) and equivalent
potential temperature (∘C; colour scale) and wind at 850 hPa,
SLP, and 6 PVU at 300 hPa isocontours (red) (b, d, f, h) from the NOCPL
simulation.
Phase diagram of the NOCPL-simulated cyclone from 01:00 UTC on 7 November to 12:00 UTC on 8 November, with low-tropospheric thickness
asymmetry inside the cyclone (B) with respect to low-tropospheric thermal
wind (-VLT) (a) and upper-tropospheric thermal wind (-VUT) with
respect to low-tropospheric thermal wind (b). The development phase is in
blue, the mature phase in red and the decay phase in black.
At 06:00 UTC on 7 November, the PV streamer has moved
northwards from Libya and is located to the south of the SLP minimum
(Fig. 5a). A south–north cold front is visible in the 850 hPaθe, east of the cyclone centre, and the medicane
centre is located under the left exit of the upper-level jet
(Fig. 5b). The minimum SLP starts to decrease until reaching 985 hPa
at around 11:00 UTC, corresponding to a strong deepening rate of
1.4 hPah-1 for 10 h. This phase also marks the increase
in the maximum wind at the low level and in the wind speed averaged over
a 100 km radius around the cyclone centre (Fig. 4). It is
referred to as “development phase” in the following. The heaviest
rainfall occurs here (Fig. 7), with 10 h accumulated rain above
200 mm locally and instantaneous values above
50 mmh-1 east of Sicily and at sea between Pantelleria
and Malta. As in Fita and Flaounas (2018), the maximum thermal wind is
obtained during this phase (Fig. 6).
Histogram of the mean rain rate distribution (in number
of grid points) for the development (blue) and mature (red) phases in the
NOCPL simulation. The enclosed figure zooms in on the highest rates.
Then, the upper-level jet moves further over the Ionian Sea and
Sicily. The SLP minimum is aligned with the 300 hPa PV anomaly
at 11:00 UTC on 7 November (Fig. 5c). This marks the beginning
of the “mature phase”, with a maximum intensity at around
12:00 UTC (Fig. 4). The medicane presents the circular shape
typical of tropical cyclones with spiral rainbands, and a warm,
symmetric core (Fig. 5d) extended up to 400 hPa (Fig. 6). The
upper-level PV anomaly stays wrapped around the SLP until
17:00 UTC, and both structures drift eastwards to the south of Italy
(Fig. 5e). The medicane slowly decreases in intensity (Fig. 4) until
it makes landfall in the southeast of Sicily at 18:00 UTC. The
cold front drifts eastwards away of the cyclone centre, evolving into
an occluded front wrapped around the SLP minimum (Fig. 5f). This
mature phase, although the most intense of the cyclone, produces more
scattered rainfall than the development phase (Fig. 7).
The cyclone then moves northeastwards towards the Ionian Sea and
continuously weakens until 12:00 UTC on 8 November (“decay
phase” hereafter). The SLP minimum steadily increases (Fig. 4); at this point, the
upper-level PV anomaly has evolved into a cut-off and is still aligned
with the cyclone centre (Fig. 5g), and the 850 hPa warm core has
extended ∼250km around the cyclone centre (Fig. 5h).
In the following, the impact of the ocean–atmosphere coupling on the
cyclone intensity is assessed by comparing the results of the CPL,
NOCUR and NOCPL simulations. The time period for this comparison is
7 November only, as the medicane lost a large part of its
intensity in the evening of 7 November.
SST evolution
Taking into account the effect of the SST change only (NOCUR) results
in a slightly slower and weaker deepening by 1.5 hPa and
a maximum wind speed that is 3 ms-1 higher (Fig. 4). Including
the effect of the surface currents on the atmospheric boundary layer
gives a slightly more intense cyclone (1.5 hPa less and
8 ms-1 stronger maximum wind). Figure 3 shows no
significant difference in the tracks between the NOCPL, NOCUR and CPL
simulations, except when the cyclone centre loops east of Sicily at
the end of the day. The median values of the SST difference between
CPL and NOCPL over the whole domain and the values of the 5 %, 25 %, 75 %
and 95 % quantiles are shown in Fig. 8. The median surface cooling
is very weak (0.1 ∘C at the end of the development
phase, ∼0.2∘C at the beginning of the decay
phase). Its evolution during the decay phase is also weak, with values
of 0.25 ∘C at 23:00 UTC, on 7 November. The
maximum cooling is 0.6 ∘C. To focus on the effects of
this surface cooling on the surface processes feeding the cyclone, we
used a conditional sampling technique to isolate the areas with
enthalpy flux above 600 Wm-2 (this corresponds to the
mean value of the 80 % quantile of the enthalpy flux on the day of
7 November). The enthalpy flux is defined here as the sum of the
latent heat flux LE and the sensible heat flux H. In this
area (EF600 hereafter), the SST difference and its time evolution are
slightly larger, with a median difference of -0.2∘C
at the beginning of the mature phase and -0.4∘C at
the end of 7 November. In NOCUR, the SST difference in EF600 is
slightly larger than in CPL, but the difference is not significant. The
SST cooling in this area of less than 0.4 ∘C (median
value) is much weaker than typical cooling values observed under
tropical cyclones, which commonly reach 3 to 4 ∘C
(e.g. Black and Dickey, 2008). In addition, the spatial extent of the
cooling does not form a wake as in tropical cyclones (not shown).
Time series of the median differences between the SST in
the CPL and NOCPL simulations, in the whole domain (red) and in the EF600
area (blue; see text for definition), on 7 November. The boxes indicate
the 25 % and 75 % quantiles and the whiskers the 5 % and 95 % quantiles.
The SST differences in the EF600 area between the NOCUR and NOCPL
simulations are also shown (cyan). Some of the boxes have been slightly
shifted horizontally for clarity.
The conclusion of this part is that surface cooling is 1 order of
magnitude smaller than what is obtained under tropical cyclone, with
no significant impact of the surface currents. However, quantifying the
surface cooling in other medicanes could lead to contrasting
results. For instance, a surface cooling of 2 ∘C was
obtained in an ocean–atmosphere–waves coupled simulation of a strong
storm in the Gulf of Lion (Renault et al., 2012). Investigating the
reasons of such a discrepancy are beyond the scope of the present
work. The stronger cooling could be due to the storm track staying at
the same place in the Gulf of Lion for a long time. The difference can
also come from a different oceanic preconditioning (their case
occurred in May), with stronger stratification or a shallower mixed
layer that amplifies cooling due to the mixing and entrainment process.
Impact on turbulent surface exchanges
A comparison of the time evolution of the turbulent fluxes in the
NOCPL and CPL simulations shows very weak differences even in the
EF600 area (Fig. 9a). At the end of the run, the mean difference of
the enthalpy flux is 25 Wm-2, with a standard deviation
of 13 Wm-2. This is weak compared to the values of the
turbulent fluxes on this area, between 500 and 800 Wm-2
for LE and 100 and 250 Wm-2 for H. Expressed
in percentage of the fluxes, the relative difference is ∼2 % at
the beginning of the mature phase and 5 % at 21:00 UTC on
7 November. The difference of H is 7±4Wm-2
(relative difference between 4 % and 10 %). Thus, coupling has a very
weak impact on the turbulent heat fluxes even in the EF600
area. Again, the effect of the surface currents (CPL vs. NOCUR in
Fig. 9b) is not significant.
Time series of the mean values and standard deviations (error
bars) of the total turbulent heat flux (blue), latent heat flux (cyan) and sensible
heat flux (red) in the CPL (open circles) and NOCPL (triangles) simulations (a) and of the mean difference between CPL and NOCPL turbulent fluxes (open
circles; same colour code) and between NOCUR and NOCPL turbulent fluxes, in
percentage relative to the NOCPL values (b) in the EF600 area.
In the following, except if otherwise specified, the results of the
NOCPL simulation are used to investigate the medicane behaviour,
focusing on the area of interest (AI in Fig. 2).
Role of surface fluxes and mechanisms
This section investigates which surface parameters control the surface
heat fluxes during the different phases of the medicane, among the
SST, surface wind, temperature and humidity.
Representation of surface fluxes and methods
In numerical atmospheric models, the turbulent heat fluxes are
classically computed as a function of surface parameters using bulk
formulae:
1H=ρcpChΔUΔθ,2LE=ρLvCeΔUΔq.
Here, ρ is the air density, cp the air thermal capacity
and Lv the vaporisation heat constant. The gradient
ΔU corresponds to the wind speed at the first level with
respect to the sea surface, Δθ is the difference
between the SST and the potential temperature at the first level
θ, and Δq is the difference between the specific
humidity at saturation, with temperature equal to SST and the
specific humidity at the first level. The transfer coefficients
Ch and Ce are defined as
Ch1/2=Chn1/21-Chn1/2κψTz/L,
and
Ce1/2=Cen1/21-Cen1/2κψqz/L,
with κ being the von Karman's constant, ψT and ψq
empirical functions describing the stability dependence,
Chn and Cen the neutral transfer
coefficient for heat and moisture, and L the Obukhov length (which
depends, in turn, on the virtual potential temperature at the first
level and on the friction velocity u∗). In the ECUME
parameterisation used in this study, the neutral transfer
coefficients Chn and Cen are defined as
polynomial functions of the 10 m equivalent neutral wind
speed (defined as in Geernaert and Katsaros, 1986). They also
depend on the wind speed at 10 m and on the Obukhov length
through the stability functions. The Obukhov length is expressed as
in Liu et al. (1979):
L=-Tv2u∗2κgTv∗,
with Tv being the virtual temperature at the first level,
depending on the temperature and specific humidity, and Tv∗ the scale parameter for virtual temperature, depending on the
temperature and humidity at the first level. As a consequence, the
transfer coefficients depend as the fluxes on the wind speed, on
the temperature and specific humidity at the first level, and on
the SST. In the following, we do not distinguish between the
temperature and potential temperature at the first level.
Time series of the median values of latent (blue) and sensible
heat fluxes (red; a) and of SST (b) in the EF600 area (see text) in the
NOCPL run on 7 November. The boxes corresponds to the 25 % and 75 %
quantiles and the whiskers to the 5 % and 95 % quantiles.
The time evolution of the median values and 5 %, 25 %, 75 % and 95 %
quantiles of the latent and sensible heat fluxes is given in
Fig. 10a for 7 November, in the EF600 area, and the time
evolution of the median values and quantiles of the SST in
Fig. 10b. The latent heat flux is always much higher than the
sensible heat flux, as this is generally the case at sea when the
SST is above 15 ∘C (e.g. Reale and Atlas,
2001). The sensible heat flux represents here 22 % of the
enthalpy flux during the development phase and 12 % to 15 % during
the decay phase. Both fluxes have asymmetric distributions, with
upper tails (95 %) longer than lower tails (5 %). This is
partly due to the conditional sampling (LE+H>600Wm-2) used here, as low fluxes are cut off. The
median value of H is maximum at the end of the development phase
(180 Wm-2 at 08:00 UTC), while its 95 %
quantile is maximum at the beginning of the development phase
(332 Wm-2 at 04:00 UTC). During the mature
phase, both the median and 95 % quantile values of H decrease
continuously. Conversely, the median value of LE is
maximum (635 Wm-2) at 09:00 UTC during
the development phase, and it stays approximately constant until
15:00 UTC. The 95 % quantile is maximum
(845 Wm-2) at the end of the development
phase. LE starts to decrease later and more slowly than
H (at around 15:00 UTC, as the system has started to weaken). The median
values of LE in this EF600 sampling are constant or
slightly increasing until the evening (20:00 UTC), whereas
the minimum values (5 % quantile) increase continuously until
the end of the day. Again, this is probably partly due to the
sampling used here.
The distributions of the SST are asymmetric throughout the event,
with lower tails much longer than upper tails (Fig. 10b). The SST
maximum (close to 24 ∘C) is almost constant with
time. The lower and median values vary due to the conditional
sampling EF600 and the motion of the cyclone away from the warm SST
area.
To investigate the mutual dependencies and co-variabilities of the
fluxes and parameters listed above, we used the rank correlation of
Spearman, which corresponds to the linear correlation between the
rank of the two variables in their respective sampling (Myers
et al., 2010). This metric enables relating the variables of interest monotonically rather
than linearly and is more appropriate in
the case of non-linear relationships.
The co-variabilities are analysed in the whole domain first, to
determine the main contribution to the fluxes globally, then in the
EF600 area to isolate surface processes controlling the growth and
maturity of the medicane. The values are given in Tables 1 to 3 for
the EF600 area and for three time periods of the development, mature
and decay phases, respectively, i.e. 09:00, 13:00 and
18:00 UTC on 7 November.
Spearman's rank correlations between the enthalpy flux,
latent and sensible heat flux, and related parameters (10 m wind speed
U10, potential temperature at 10 mθ, SST and humidity at 10 mq) at 09:00 UTC on 7 November, from the CPL simulation, in the EF600 area.
At the low level, this phase corresponds to a low-pressure system
resulting from the evolution of the instability generated by the
lee cyclone of the northern African relief, with strong baroclinic
structures. During the first hours, the areas of heavy
precipitation are co-localised with frontal structures. A warm
sector is visible east of the domain, with a cold front extending
southeast from the south of Italy and a very strong low-level
convergence between the southeasterly flow in the warm sector and
the south-to-southwesterly flow in the cold sector (see Fig. 5b).
Map of equivalent potential temperature (warm colours) and
virtual potential temperature below 19 ∘C (blue shades) at first
level; horizontal convergence rate above 1×10-3ms-2 at 100 m
(yellow contours), 10 m wind (arrows) and SLP (black contours) at 08:30 UTC
on 7 November (a); and vertical cross section of equivalent potential
temperature and virtual potential temperature (colour scale), tangential
wind (black vectors; the vertical component is amplified by a factor 20),
and potential vorticity anomaly (white contour at 5 PVU) along a west–east
transect (b) (dashed line in a). Grey stars indicate the position of the
SLP minimum.
Time series of Spearman's rank-order correlation rs between
the latent heat flux LE and 10 m wind speed (green), potential temperature at
10 m (red), SST (blue), and specific humidity at 2 m (cyan) in the whole
domain (a) and in the EF600 area (b) in the CPL simulation.
Maps of the turbulent heat fluxes LE(a), H(d), 10 m wind
U10(b), 10 m potential temperature (c), SST (e) and specific humidity
at 2 m(f) at 09:00 UTC on 7 November in the CPL simulation.
At 08:30 UTC on 7 November (Fig. 11), strong convergence
lines develop close to the cyclonic centre, between Sicily and
Tunisia. The low-level virtual potential temperature
θv superimposed onto the equivalent potential
temperature θe is used here as a marker of cold
pools (with an upper limit of 19 ∘C for
θv – Ducrocq et al., 2008; Bresson et al.,
2012). Some of these cold pools result from evaporation under
convective precipitation, while those located at sea along the
northern African coast originate from dry and cold air advected from
inland. The discrimination between these two kinds of cold pools
was done using a simulation without the latent heat transfer due to
rain evaporation (not shown here). The cold and moist air spreads
to the surface, following density currents, and is advected
northeastwards by the low-level flow. To the west and south of the
domain, cold pools were formed at night by radiative processes over
land and were advected over sea with a vertical extent of ∼1000m (see the westernmost part of the W–E transect;
Fig. 11b).
The upwind edge of the cold pools is the place of strong horizontal
convergence at the low level, leading to uplift and deep convection of
air masses with high θe. During the development
phase, the cold pools move northwards with the southerly flow,
towards the centre of the cyclone. Then, they contribute to triggering
convection in the northwesterly low-level flow with high
θe (Fig. 11b). The warm surface anomaly
propagates close to the cyclone centre (now located under the
300 hPa PV anomaly) up to 3000 m and generates
a low- to mid-troposphere PV anomaly. At the same time, a dry-air
intrusion from the upper levels brings air masses with low
θe and relative humidity below 20 % to
3000 m, resulting in an upper-to-mid-troposphere PV anomaly
(Fig. 15a and c).
To identify the surface parameters controlling evaporation at sea,
the time evolution of the Spearman's rank correlations between
LE, U10, θ, the SST and q is given in
Fig. 12 and Tables 1 to 3.
During this phase, in the whole domain, the parameters governing
LE are the SST and the wind (positively correlated), the
specific humidity (negatively) and the potential temperature
(negatively). Potential temperature and humidity are also strongly
positively correlated (rs=0.55 over the whole
domain) because cold and dry air is advected from the Tunisian
and Libyan continental surface by the southerly low-level flow
(Fig. 13b, c and f; at 09:00 UTC). This air mass
progressively charges itself in heat and moisture in the area of
strongest enthalpy fluxes at sea to the north of Libya (Fig. 13a). The
EF600 area, with strong fluxes and cold and dry air, corresponds also
to warm SSTs (Fig. 13e). Here, LE is mainly controlled by
the wind and by the SST, θ has no effect (weak or negative
correlations; Fig. 12b, Table 1) and q has a weak effect.
LE is always much higher than H (Fig. 10a), resulting in
the “strong flux area” EF600 being controlled by LE
rather than H. LE is also more homogeneous than H in
EF600. However, H can be strong locally (Fig. 13d). During this
development phase, H is controlled mainly by θ at the first
level (Fig. 14), partly indirectly through the stratification and
transfer coefficient (not shown). In the EF600 area also, H is
mainly governed by θ (rs=-0.70 at
09:00 UTC), the SST influence is always weak and the wind
plays a secondary role. The enhanced control by the potential
temperature is partly due to the continental air masses advected
from northern Africa and partly to the presence of the cold pools
under the areas of deep convection and strong wind.
Same as Fig. 12 but between the sensible heat flux H and 10 m
wind speed (green), potential temperature at 10 m (red), and SST (blue).
Vertical cross sections of equivalent potential
temperature θe (∘C; colour scale) and relative
humidity (%; isolines) (a, b), DPV (intensity) (c, d), and WPV
(intensity) (e, f) on a west–east transect across the cyclone centre, at
13:00 (a, c, e) and 18:00 UTC(b, d, f) on 7 November, in the CPL
simulation. The black contours in (c) to (f) correspond to intensities 1 and
3 (as defined in Miglietta et al., 2017).
Mature phase
At 13:00 on 7 November, the PV anomalies at 700 and 300 hPa
are aligned (Fig. 15c, e). A zonal cross section on the SLP minimum
shows that a low-level PV anomaly above 5 PVU formed
around the cyclone centre, extending from the surface up to the
300 hPa anomaly (Fig. 15). The warm core extends up to
850 hPa (Fig. 15a). Its upward development is limited by
colder air (low θe) brought from aloft. There is
low-level convergence (up to 800 hPa) towards the cyclone
centre, and deep convection close to the centre, but no or very weak
divergence at the mid-troposphere to upper troposphere. The cyclonic circulation
was reinforced with horizontal wind speed above 8 ms-1
at every level more than 10 km away from the cyclone
centre.
During this phase and the previous one, over the whole domain as in
the EF600 area, evaporation is controlled equivalently by the SST
and the wind speed, with a decreasing influence of the humidity
(Fig. 12, Table 2). The EF600 area extends further north, closer to
the cyclone centre, away from the area of cold and dry low-level
air. This cold-air inflow starts to warm and moisten under the
combined impact of the diurnal warming of the continental surfaces
(not shown) and of the strong enthalpy fluxes offshore (Fig. 16a, c
and f). The sensible heat flux is still controlled by the
temperature, with an increasing influence of the wind (Table 2).
Same as Fig. 13 but at 13:00 UTC on 7 November.
Decay phase
In the afternoon of 7 November, the cyclone first moves towards
colder SSTs in the east of the Strait of Sicily (Fig. 3). Then, it
crosses Sicily and reaches the Ionian Sea with even colder SSTs
at around 20:00 UTC before slowly decaying and losing its
tropical characteristics. Back trajectories are used to check
whether warm- and moist-air extraction from the sea surface
contributes to high θe values obtained around
the cyclone centre. They are based on the method of Schär and
Wernli (1993), adapted by Gheusi and Stein (2005). The chosen
trajectories originate from three different places and arrive at
the same place, at three vertical levels surrounding the level
closest to 1500 m, at 23:00 UTC on 7 November
(Fig. 17). Their equivalent potential temperature ranges from 31 to
38 ∘C at their first appearance in the domain and
is close to 45 ∘C on average at their final
point. Of these trajectories, θe increases
almost continuously, with a strong jump during their transit at the low
level (below 500 m) above the sea in the EF600 area (white
contour in Fig. 17). A separate analysis of the two different
stages in the trajectories was performed. Stage 1 corresponds
to the period when the particles remain in the low-level flow
(between 200 and 1200 m a.s.l.) south and east of Sicily
and stage 2 to their convective ascent from ∼300 to
1500 m. During stage 1, the potential temperature of the
particles decreases by 1 ∘C on average, while the
mixing ratio increases by 2.8 gkg-1. This shows that
the increase in θe is due to strong surface
evaporation. During stage 2, the mixed ratio of the particles
decreases by 2 gkg-1, and their potential temperature
increases by 4.1 ∘C. This indicates condensation
and latent heating and demonstrates the strong role of the sea
surface in increasing the moisture and heat of the low-level flow
before its approach on the cyclone centre and of diabatic
processes in reinforcing its warm core.
Map of the back trajectories of air parcels arriving
south of the cyclone centre at 23:00 UTC on 7 November, 1500 m a.s.l., at three different levels (circles, squares and diamonds). The first
point of the trajectories corresponds to the start of the D2 domain
simulation (00:00 UTC on 7 November). The colour scale indicates the
equivalent potential temperature (∘C), and the size of the symbol
is inversely proportional to altitude between 0 and 1000 m and constant
above 1000 m. Also shown are the values of the final equivalent potential
temperature and of the initial equivalent potential temperatures, the wind
field at 900 hPa (black vectors), and the surface enthalpy flux (grey
shades) with a threshold at 600 Wm-2 (white contour) at 15:30 UTC, when
the particles arrive at sea to the south of Sicily.
During the decay phase and in the whole domain the influence of the
humidity on LE is weak (Fig. 12a). EF600 is still located
on warm SSTs south of the domain (Fig. 18a, e) and corresponds
also to the strongest winds on the right-hand side of the cyclone
(Fig. 18b). Within this area, there is almost no influence of the
temperature or humidity on LE (Table 3). The influence of
the wind speed is decreasing; the role of the SST is strong until
21:00 UTC. After that, the cyclone reaches the northern
Ionian Sea with much colder SSTs, and the effect of the wind speed
becomes dominant at the very end (Fig. 12b). The sensible heat flux
is governed by the wind (see the strong N–S gradient in Fig. 18b)
rather than by the low-level temperature, except in the northern
part of EF600 (where the wind speed is also the highest).
Same as Fig. 13 but at 18:00 UTC on 7 November.
In summary, at the scale of the domain, both strong winds (in the
cold sector during the development phase, then close to the cyclone
centre and on its right side) and warm SSTs (in the south of the
domain) are necessary for strong latent heat fluxes. Within the area
of strong fluxes (also strong winds and warm SSTs), the evaporation
is mainly controlled by the wind (development and mature phases)
instead of by the SST (decay phase). In contrast, the sensible heat flux
depends mainly on the potential temperature in the surface
layer. Colder air masses lead to strong sensible heat flux rather
than strong wind or warmer SSTs. During the two first phases, cold
air is either advected from northern Africa or created by evaporation
under convective precipitation (cold pools). During the decay
phase, strong latent heat transfer over high SSTs warms the
near-surface atmospheric layer and lowers the sensible heat
transfer.
Discussion and conclusion
The comparison of the simulations with and without ocean coupling
shows no significant impact of the evolution of the SST on the
track, intensity or life cycle of the medicane. The weak SST
cooling, notably during the first 24 h of the simulation,
is likely responsible for that. In the strong flux area, where the
enthalpy flux feeding the cyclone in heat and moisture maintains
the convection and the latent heat release, the median value of the
SST cooling is between 0.2 and 0.4 ∘C. The effect
on H is -7 Wm-2 during the mature phase and
-12 Wm-2 at 23:00 UTC on 7 November
(less than 10 %). On LE, it is -19 and
-37 Wm-2 for the same two time periods (less than
5 %). Coupling with the surface currents has no significant
impact on the simulation.
Nevertheless, in this specific case, the SST exerts a strong
control on the latent heat flux that dominates the surface heat
transfer throughout the event. During the development phase, there
is also a strong influence of peculiarities of the central
Mediterranean: the transition between deep convection and heavy
precipitation associated with baroclinic processes and the cyclone
taking place downwind of the dry and cold low-level flow from northern
Africa. These air masses with low θv encounter
moist and warm air at sea and enhance the deep convection, together
with the cold pools formed by rain evaporation and
downdrafts. These cold pools of various origins displace the deep
convection at sea. Uplift of warm air masses increases the
low-level PV and reinforces the vortex, which is moved
northeastwards, closer to the PV anomaly aloft.
Vertical profiles of PV (a) and DPV and WPV (b)
averaged within a 100 km radius circle around the cyclone centre at 09:00
(red), 13:00 (green) and 18:00 UTC (blue) on 7 November in the CPL
simulation.
Better knowing the intensity and the role of air–sea exchanges and
the related mechanisms could permit sorting medicanes, as proposed
by Miglietta and Rotunno (2019). Is the present case
governed by WISHE-like mechanisms or rather by diabatic and
baroclinic processes throughout its lifetime (second category in
Miglietta and Rotunno, 2019)? Strong air–sea exchanges at the
surface and latent heat release act to build the warm-core
anomaly, as seen in Sects. 4.3 and 4.4. The surface enthalpy fluxes
take intermediate values, with a maximum above 1500 Wm-2
for a few hours in areas with warm SST and strong winds downwind of
the dry low-level flow from northern Africa. Thermal features
characteristic of tropical cyclones are present, like low-level
cold-air advection from the south to the east and warm-air
advection from the south to the north (Reale and Atlas, 2001). The
gradient of θe between the surface and
900 hPa is around 6–7 ∘C. The wrapping of
the PV streamer around the cyclone centre evolves into an
upper-level cut-off at the end of the decay phase. Conversely,
some typical features are not present: even if there is weak
low-level convergence around the cyclone centre, no divergence is
seen at the upper level. The maximum latent heat flux within the EF600
area is more controlled by the SST than by the wind speed
(Figs. 12b and 13a, b and e). No minimum of potential temperature
or potential vorticity develops at 300 hPa close to the
cyclone centre during the mature phase, as a marker of the PV
anomaly erosion by the convective activity, and the upper-level PV
anomaly never completely detaches from the large-scale structure.
Figure 19 shows the vertical profiles of wet PV and dry PV (WPV and
DPV; defined as in Miglietta et al., 2017) averaged on the
100 km radius circle around the cyclone centre. WPV is
produced diabatically by latent heat release (their Eq. 4), and DPV
is generated by intrusion of stratospheric air into the upper
troposphere (their Eq. 3). The vertical profiles of PV, DPV and WPV
show a minimum WPV between 700 and 400 hPa during the
decay phase and a clear difference between DPV and WPV at the low
level (Fig. 19b). The DPV is weak up to the mid-troposphere and
increases sharply above 400 hPa. The WPV anomaly at the low
level develops up to 700 hPa during the development phase,
but its vertical extent reduces to 800 hPa during the
mature phase (13:00 UTC – see also Fig. 15e). This is due
to a dry-air intrusion during the mature and decay phases, which is
limited downwards by the warm core (Fig. 15a). At the beginning of
the decay phase, at 18:00 UTC, the latent heating within
the cyclone core increases the low-level WPV and erodes the dry and
cold (θe) air masses up to 650 hPa. The
warm-core and WPV anomaly extend upwards (Fig. 15b, f), and the DPV
anomaly is pushed up to 700 hPa (Fig. 15c, d).
This suggests that the medicane of November 2014 as simulated in
this study presents characteristics close to an extratropical
cyclone or medicane of the second category as in Miglietta and
Rotunno (2019). Its development phase is triggered by a PV streamer
bringing instability at the upper level and baroclinic processes
followed by strong convection at sea. This convection is enhanced
and maintained by cold pools due to rain evaporation at the low level
or by advection of dry and cold air from northern Africa. The
conjunction of advection of continental air masses with evaporation
under storms has not been identified as leading to tropical
transition of Mediterranean cyclones so far, even though it is
probably rather ubiquitous. Indeed both phenomena are rather
widespread in the Mediterranean. Surface fluxes are strong and
contribute to enhancing the convection potential until the mature
phase of the cyclone. Evaporation is mainly controlled by the SST
and by the wind speed during the whole event, while the temperature
difference between the SST and the cold air advected from northern
Africa during the development and mature phase play a strong role
during its development. The vertical development of the warm core
is limited by a dry-air intrusion that does not reach the lowest
levels of the troposphere. Dry-air intrusions have been recognised
as common processes in Mediterranean cyclones by Flaounas
et al. (2015), but their role in the cyclone life cycle was not
clearly assessed. Here, we suggest that they can act to limit
the extent of the convection at the beginning of the mature
phase. The convective activity is stronger during the development
than during the mature phase of the cyclone, resulting in heavy
rainfall 12 to 6 h before the maximum wind speed,
consistent with previous studies based on observations (Miglietta
et al., 2013; Dafis et al., 2018). Finally, these results are
consistent with those of Carrió et al. (2017), which show, by
using a factor separation technique, that while the role of the
upper-level PV anomaly is crucial in preconditioning the event, its
rapid deepening is due to the synergy of latent heat release and
upper-level dynamics.
Coupling the atmospheric model with a 3-D high-resolution oceanic
model shows that, in the present case, the surface cooling is too
weak to impact the atmospheric destabilisation processes at the low
level. Nevertheless, the effect of the medicane on the oceanic
surface layer is probably significant. To better understand the sea
surface evolution and the role of coupling, the ocean mixed layer
response to the medicane and the mechanisms involved will be
investigated in more detail in future work.
Code availability
The source codes are available online (WaveWatchIII at https://polar.ncep.noaa.gov/waves/wavewatch/, NOAA, 2020; OASIS at https://portal.enes.org/oasis, CERFACS, 2020; Meso-NH at http://mesonh.aero.obs-mip.fr/mesonh54, LA and CNRM, 2020, and SURFEX at http://www.umr-cnrm.fr/surfex/, CNRM, 2020).
The availability of additional data is indicated in the Sect. “Acknowledgements”.
Author contributions
MNB and CLB designed the simulations. MNB
performed the simulations. Both authors interpreted the results and wrote
the paper.
Competing interests
The authors declare that they have no conflict
of interest.
Special issue statement
This article is part of the special issue “Hydrological cycle in the Mediterranean (ACP/AMT/GMD/HESS/NHESS/OS inter-journal SI)”. It is not associated with a conference.
Acknowledgements
This work is a contribution to the HyMeX programme (Hydrological cycle in the
Mediterranean eXperiment – http://www.hymex.org, last access: 8 June 2020) through INSU-MISTRALS
support. The authors acknowledge the Pôle de Calcul et de Données
Marines for the DATARMOR facilities (storage, data access, computational
resources). The authors acknowledge the MISTRALS/HyMeX database teams
(ESPRI/IPSL and SEDOO/OMP) for their help in accessing the surface
weather station data. The PSY2V4R4 daily analyses were made available by the
Copernicus Marine Environment Monitoring Service
(http://marine.copernicus.eu, last access: 8 June 2020). The ERA5 reanalysis at hourly timescales
(10.24381/cds.bd0915c6) is produced by the European Centre for
Medium-Range Weather Forecasts (ECMWF) and made available by the Copernicus
Climate Change Service (https://cds.climate.copernicus.eu, last access: 8 June 2020). METAR
observations of SLP and wind were retrieved through the Weather Underground
portal at https://www.wunderground.com (last access: 8 June 2020). The authors thank Jean-Luc Redelsperger
(LOPS) for valuable discussions. We also thank Emmanouil Flaounas and two anonymous
reviewers, whose comments helped to greatly improve this paper.
Review statement
This paper was edited by Christian Barthlott and reviewed by Emmanouil Flaounas and two anonymous referees.
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