The sensitivity of the October 1996 Medicane in the western
Mediterranean basin to sea surface temperatures (SSTs) is investigated with a
regional climate model via ensemble sensitivity simulations. For 11 SST
states, ranging from -4 K below to +6 K above the observed SST field
(in 1 K steps), 24-member ensembles of the medicane are simulated. By using
a modified phase space diagram and a simple compositing method, it is shown
that the SST state has a minor influence on the tracks of the cyclones but a
strong influence on their intensities. Increased SSTs lead to greater
probabilities of tropical transitions, to stronger lower- and upper-level warm
cores and to lower pressure minima. The tropical transition occurs sooner
and lasts longer, which enables a greater number of transitioning cyclones to
survive landfall over Sardinia and re-intensify in the Tyrrhenian Sea. The
results demonstrate that SSTs influence the intensity of fluxes from the sea,
which leads to greater convective activity before the storms reach their
maturity. These results suggest that the processes at steady state for
medicanes are very similar to tropical cyclones.
Introduction
The Mediterranean basin is one of the most cyclogenetic regions in the world,
with a majority of its cyclones being baroclinic .
However, it has been shown since the 1960s, using remote sensing instruments,
that unusual cyclones with a visual similarity to tropical cyclones are also
sometimes observed . In contrast to asymmetric,
synoptic-scale extratropical cyclones, these cyclones are of a smaller scale,
axisymmetric, frontless and sometimes have a well-defined eye at their
center. These cyclones are now referred to as tropical-like Mediterranean
cyclones, or medicanes. According to the climatological study of
, over the last 60 years medicanes have occurred with a frequency of 1.57±1.30 events per year.
Medicanes are intense low-pressure systems that present similar
characteristics to tropical cyclones: an area with no cloud at the center,
spiral bands surrounded by deep convection, intense surface winds, a lower- and
upper-troposphere warm core, formation over the sea, and a rapid dissipation
after landfall . In recent decades, thanks to
high-resolution regional numerical weather prediction models and
observational data, detailed examinations of several medicane cases have been
carried out e.g.,.
The question of the influence of sea surface temperatures (SSTs) on the
development and the characteristics of medicanes has been tackled by several
studies. found a minor influence of small SST
anomalies on the medicane of 23 January 1982.
showed that the development scenario of the medicane of 12 September 1996 had
many similarities with the air–sea interaction instability mechanism,
especially with the latent heat fluxes acting as
a sustainer of convection. According to them, the medicane would have been
both weaker and had a delayed development if the SSTs had been colder.
showed the strong sensitivity of the same medicane
to SSTs using an axisymmetric cloud-resolving model in which other
environmental influences were not included.
studied the impact of systematic changing of SSTs in a simulation of the
26 September 2006 medicane. According to them, the cyclone was mainly
sensitive to uniform SST changes larger than 2 K and increasingly lost its
tropical features as the SSTs became colder.
investigated the influence of SSTs on the 7 November 2014 Medicane through
the imposition of climatological SSTs and uniform warm and cold SST
anomalies. A linear deepening and a longer lifetime of the medicane were
observed as the SST anomalies increased from -3 to +1 K.
The October 1996 Medicane was previously studied by
, using a 50-member ensemble of regional climate
model simulations. It was shown that standard extratropical dynamics were
responsible for the cyclogenesis and that the tropical transition of the
cyclone resulted from a warm seclusion process. Our present study aims to
assess the role of SSTs in the development and the intensity of this cyclone.
Ensembles are created for different SST states through dynamical downscaling
of reanalysis data and applying a uniform change to the observed SST field in
a range of -4 to +6 K. As such, we seek to assess the sensitivity of the
medicane to a range of SST changes extending well beyond observational
uncertainty and to instead consider SST changes in ranges more typically
associated with natural or externally forced variability. To identify any
potential threshold and/or nonlinear behavior in the system, we further
extend the SST states to encompass the range -4 to +6 K. To the best of
our knowledge, ours is the first study to use ensemble simulations combined
with uniform SST changes to evaluate the influence of SSTs on the formation
of a particular medicane.
Section provides an overview of the medicane case, while
Sect. describes the model setup and methodology. Results are
presented in Sect. , while the discussion and conclusions
are included in Sect. .
Medicane case
In this paper we study Medicane Cornelia, which occurred in the western
Mediterranean between 7 and 10 October 1996. The cyclone is discussed in
detail in and , with
a synthesized description of the case in . Here we
provide an abridged overview of the case.
Inner simulation domain (0.0625∘ resolution) and medicane
in reanalysis. SSTs (shading), sea level pressure (hPa, blue contours) and
500 hPa wind vectors, representative of the steering flow, are shown for 7 October 1996 at 06:00 UTC. The cyclone's track is shown with a grey line,
marked at 6 h intervals from 6 October 1996 at 06:00 UTC. The plot is based on
ERA-Interim data.
Medicane Cornelia began its life as an extratropical cyclone with frontal
structures on 6 October 1996 near the Algerian coast. By 12:00 UTC on 7 October
it had tracked northwards, guided by the steering flow of a 500 hPa cutoff low, to
lie between the Balearic Islands and Sardinia. A clear eye-like structure was
present by this stage , and the central pressure had
deepened below 1000 hPa with SSTs close to
20 ∘C (Fig. ). From here Cornelia tracked
eastwards, crossing Sardinia on 8 October and weakening over land, before
re-intensifying as it tracked east into the Tyrrhenian Sea
. By 9 October the medicane was situated north
of Sicily, with the central vortex having become more intense and compact
. Cornelia then tracked southeastwards, crossing
Calabria on the night of 9 October, where intense winds were recorded, before
dissipating in the Ionian Sea during 10 October .
Data and methodologyExperimental setup
The numerical simulations are performed with the full-physics,
non-hydrostatic COSMO Climate Limited-Area Model (CCLM;
) version cosmo4.8-clm19. CCLM is the community
model of the German regional climate research community jointly developed further by the CLM community. The two-step downscaling configuration begins
with a 257×271 grid point, 0.165∘ resolution parent
domain, which is forced at the lateral boundaries by ERA-Interim reanalysis
. A 288×192 grid point,
0.0625∘ resolution domain (Fig. ) is then nested
within the 0.165∘ parent domain; the 0.165∘ domain covers
an area slightly smaller than the EURO-CORDEX domain
and is shown in . For both downscaling steps, the
model setup includes an extended microphysics scheme accounting for cloud
water and cloud ice for grid scale precipitation, based on
, the
radiation scheme, and the Tiedtke parameterization scheme for convection
. Heat fluxes from the ocean to the
atmosphere are parameterized using a stability-, roughness-length-dependent
surface flux formulation based on . Both domains
feature 40 vertical levels and a 6-hourly update of the boundary conditions.
One ensemble is performed, driven by the 0.7∘ resolution
ERA-Interim reanalysis .
Ensemble generation
According to previous studies , numerical
forecasts are highly sensitive to initial and boundary conditions. In
particular, the location of the lateral boundaries can have a strong impact
on circulation anomalies within the model domain
e.g.,. In this study, the
technique of domain shifting is employed to generate an ensemble
. This technique consists of two downscaling
steps with a series of simulations that have domains that are slightly shifted in
space. We use the same procedure as in .
The first downscaling step entails the following:
locating a central domain over Europe (same as in
),
shifting the central domain in terms of longitude and latitude in eight directions (north, south, east, west,
northeast, northwest, southeast and southwest) in three steps (0.25, 0.50 and
0.75∘),
running the model on each of the 24 domains using ERA-Interim as initial and boundary
conditions.
The second downscaling step entails the following:
using the 24 simulations of the first downscaling step as initial and boundary conditions for
the smaller, nested domain (Fig. ) with a finer resolution
over the western and central Mediterranean basin.
(a) Percentage of cyclones encountering a tropical
transition over the 24-member ensembles for different SST changes, using
classification criteria based on the cyclone phase space. (b) Mean
period of time during which transitioning cyclones are classified as
medicanes for different SST changes. Error bars represent standard deviation.
The black line is based on a linear regression.
This results in one set of 24 simulations for the reference (observed) SSTs
from ERA-Interim. It is important to emphasize that all choices of domain
boundaries are equally valid and that the central “unshifted” domain is
not the “correct” domain. Any simulated differences between the ensemble
members are thus a consequence of the inherent uncertainty resulting from
forcing the regional model with imperfect boundary conditions (i.e.,
reanalysis) and the chaotic nature in which the system responds to
differences in the lateral boundary conditions. As such, the potential
subsequent formation of a medicane should always be considered in a
probabilistic rather than a deterministic manner. Simulated characteristics
of the medicane (e.g., its track) must thus also be interpreted in a
statistical sense, and the ensemble mean characteristics may not correspond
exactly to the observed characteristics, which are themselves just one of
many potential realizations.
As in , the initialization time of the first step
simulations is 00:00 UTC on 1 October 1996, while the inner domains are
initialized at 00:00 UTC on 4 October 1996. A 72 h lag was previously found to
be a satisfactory compromise between introducing sufficient spread in the
ensemble and the ability to capture the event in the simulations
.
SST changes
To assess the sensitivity of the October 1996 Medicane to SSTs, we perturb
the SST forcing in the 0.0625∘ domain by adding SST anomalies in a
range of -4 to +6 K, in 1 K increments, to the observed SST field. In
addition to the ensemble using observed SSTs, this creates 10 extra 24-member
ensembles relating to our chosen case, each with their own unique SST forcing. SSTs were
modified uniformly across the entire 0.0625∘ domain.
Cyclone phase space
We base our analyses on the three-dimensional diagnostics proposed by
, which were first applied to the study of medicanes by
, and subsequently by others
, to analyze medicane
tropical transition. The three following parameters are computed in a radius
of 150 km from the cyclone's center (as successfully used by
) and are used to define the cyclone phase space.
The thermal symmetry in the lower troposphere (B) is the difference in mean
600–900 hPa thickness between the left and right semicircles with respect to
the cyclone's trajectory.
The lower-tropospheric thermal wind (-VTL) is the vertical derivative of
the cyclone's geopotential height perturbation between 900 and 600 hPa.
The upper-tropospheric thermal wind (-VTU) is the vertical derivative of
the cyclone's geopotential height perturbation between 600 and 400 hPa.
The exact definitions that we use for these parameters represent a modified
version of the diagnostics proposed by , which take
into account the limited vertical extent and the smaller spatial scale of
medicanes compared to tropical cyclones
.
Our exploration radius is thus reduced from 500 to 150 km and the upper
bound of -VTU is reduced from 300 to 400 hPa. The
resulting phase space diagrams can be very erratic on an hourly timescale.
Therefore, a 3 h running mean is applied to the computed parameters to give
the final phase space diagram. Following , in order to
classify a cyclone as a medicane, the following objective criteria must apply
simultaneously at least one time step: B<10 m,
-VTL>0 and -VTU>0.
Cyclone tracking
The simulated cyclones are tracked based on the mean sea level pressure
(MSLP). As hourly data were used, this proved to be sufficient to correctly
follow the cyclone track. The tracking algorithm works as follows.
Initially, the location of the minimum pressure is identified within the area of the
western Mediterranean basin at 00:00 UTC on 8 October; at that point in time
the cyclone is fully developed with a core pressure below 1013 hPa, is
located over Sardinia and is found in every simulation.
The positions of the MSLP minima in the adjacent time steps (backward and forward in time)
are determined using a nearest-neighbor algorithm, applied within a circle
with a radius of 0.9∘ from the previous MSLP minimum.
The algorithm stops if the cyclone's minimum pressure exceeds 1013 hPa or has made landfall
on the French or Spanish coastline (Corsica, Sardinia, Sicily and continental Italy are not considered as
landfall).
Every track is verified manually with respect to its consistency with the MSLP
fields.
Track densities based on all cyclones for an SST change
of (a)-3 K, (b)0 K (original
SSTs), (c)+3 K and (d)+6 K.
This algorithm gives coherent trajectories for cyclones both with and
without a tropical transition. The algorithm ensures that only one cyclone
track is identified in each ensemble member. Continental Italy is not
considered as landfall in order to follow the medicanes even when they make
landfall; this is done in order to specifically calculate the evolution of the phase
space parameters after landfall. In practice, medicanes dissipate rapidly
after landfall.
This method gives reasonable tracks during most of the cyclone's lifetime,
which allows the computation of the phase space parameters. In the early
phase of the cyclone the tracks can be slightly erratic. However, this does
not affect the results because this period is before the earliest stage of
the cyclone's life used for composite analysis (20 h before the time of
maximum warm-core strength; see Sect. ). The phase
space parameter B could significantly change with a more sophisticated
tracking algorithm because it is sensitive to the exact location of the
track position. While our method of distinguishing a medicane from a
non-medicane requires that all criteria mentioned in Sect.
are fulfilled simultaneously, for the systems considered in this study the
evaluation of -VTU alone would have led to the same
systems being identified.
Track density plots are obtained by counting, for each grid point, the number
of tracks that cross a 50 km radius circle around the respective grid point
for all members of a given SST ensemble, and dividing by the total number of
tracks (see , for a similar method applied to
Northern Hemisphere winter storms).
Cyclone compositing
In order to extract the mean signal from fields that show large variability,
we use a simple arithmetic-averaging technique called cyclone compositing.
This technique has been frequently applied to both extratropical and tropical
cyclones
e.g.,.
Following , we align the temporal evolution of the
simulated cyclones to a common reference time: for each track we identify the
time step when -VTU is at its maximum, B<10 m and
-VTL>0. This instant is meant to reflect the stage of
maximum warm-core strength and is hence referred to as the maximum warm-core
time (MWCT). Such an instant is found for all cyclones analyzed in this
study, even non-transitioning ones. As we focus on transitioning cyclones,
for studying mechanisms it proves most instructive to base our analyses on
composites of the 10 most powerful transitioning cyclones for each SST, i.e.,
those that have the greatest -VTU at MWCT (except
when ΔSST=-4∘C because for this SST state only 7 cyclones
transition). Results are insensitive to whether we take the mean or median of
the composited cyclones.
Track densities based on all cyclones classified as medicanes for an
SST change of (a)-3 K, (b)0 K (original
SSTs), (c)+3 K and (d)+6 K.
ResultsProbability of transition and track density
With the specified criteria based on the phase space parameters, it can be
determined if a cyclone undergoes a tropical transition, i.e., if it can be
regarded as a medicane. This is done for each of the 24 ensemble members of
each of the 11 SST states. It is found that increasing SST leads to an
increasing number of medicanes (Fig. a). While at
ΔSST=-4 K only 30 % of the ensemble members generate a
transitioning cyclone, at +5 and +6 K all members produce a medicane.
Note that even with observed SSTs, i.e., ΔSST=0 K, medicane transition probability is less than 85 %. This points
towards the probabilistic nature of medicane formation: the observed medicane
was one of many potential realizations for the observed SST state; small
changes in the observed initial conditions could have developed to inhibit
the real-world formation of Medicane Cornelia as well. The largest increase in
medicane development rate is found between -4 and -3 K (from 7 to
16 medicanes). It could be speculated that this sudden increase is related to
a specific SST threshold, similar to the empirical threshold of
26.5∘C, which is found for the development of tropical cyclones
. However, here the SSTs are much lower (around
20 ∘C).
From each ensemble, those cyclones that are classified as a medicane are
selected. For this subset, the mean and standard deviation of the period of
time during which the cyclone was classified as a medicane are calculated. The
length of this period increases almost linearly with increasing SSTs
(Fig. b). For an SST change of -4 K, the period
of time is very short, with values of around 5 h. In contrast, the period of
time lasts longer at higher SSTs. For example, at ΔSST=+6 K the cyclones are classified as medicanes for about 104 h on average.
Not only the mean but also the standard deviation between the time periods
in the different ensemble members increases with increasing SSTs.
Figure presents track densities of cyclones for an
SST change of -3, 0, +3 and +6 K. The figure must be viewed taking
into account that cyclones begin to form between Sardinia and the Balearic
Islands, then move through Sardinia and finally go southeast of the
Tyrrhenian Sea. All track density plots are very similar when SSTs change and
it only seems to be a greater dispersion of tracks when we increase SSTs,
especially east of Sardinia and south of continental Italy. Therefore, one
can conclude that the SST state has little influence on the track of the
medicane, with the large-scale steering flow instead playing the dominant
role.
However, Fig. shows the track densities
obtained with the same method, but tracks are taken into account only
when cyclones are classified as medicanes. The two local maxima of density
east and west of Sardinia illustrate that the simulations exhibit two
distinct classes of medicane formation: those for which MWCT occurs before
crossing Sardinia and weaken after the crossing and those for which
MWCT occurs after crossing Sardinia, mostly near the Italian peninsula, and
continue to deepen after the crossing. It is observed that between 60 %
and 85 % of the medicanes are of the second type, depending on the SST
change. However, there is no systematic dependency between the observed
percentage and ΔSST. While some medicanes of the first type that lose
their medicane status while crossing Sardinia go on to re-transition in the
Tyrrhenian Sea, others fail to regain medicane status. In addition to this,
many medicanes of the second type first achieve medicane status in the
Tyrrhenian Sea, as suggested by the two local maxima.
Figure also shows that, apart from
increasing the period of time when cyclones are transitioning, the track is
always similar: the first transition is before Sardinia, then crossing Sardinia
and finally moving southeast to Calabria through the Tyrrhenian Sea. Even if the
variability increases with higher SSTs, it seems that tracks are not
SST-dependent.
Intensity of the cyclones
As a first step, the intensities of the cyclones are analyzed in terms of the
minimum core pressure. For this purpose, the composite (see
Sect. ) sea level pressure minimum (i.e., the mean of
the 10 pressure minima from the tracks of the 10 cyclones that have the
greatest -VTU at MWCT) is calculated for each ΔSST. The composite mean of the minimum MSLP decreases from
1004 hPa at -4 K to 981 hPa at +6 K, while the standard deviation,
i.e., the variability, between the individual ensemble members strongly
increases at higher SSTs (Fig. ). A regression equation
specification error test showed that the null
hypothesis that the relationship between ΔSST and minimum
MSLP is linear can be rejected at a significance level of 0.01. That means
that there is a nonlinear relationship between SSTs and the minimum pressure of the medicanes. SSTs seem to act as an amplifying factor of an
already existing minimum pressure caused by a higher tropospheric feature.
Dependence of composite minimum pressure on SST change. The error
bars represent standard deviation.
As the SSTs are not uniformly distributed in the Mediterranean Sea, one may
ask whether the differences between the different realizations of the cyclone
are caused by differences in the local SSTs along the specific cyclone tracks
of the individual ensemble members. To assess the role of local SSTs along
the cyclone tracks, we calculate the mean SSTs in a radius of 150 km around
the cyclone center and take the average of those values from MWCT -20 h
until MWCT for each track. These average SST values are presented together
with the minimum pressure for all ensemble members of all SST states
(including non-transitioning cyclones) in Fig. . For
each SST state, the local SSTs encountered by all cyclones before MWCT vary
in the range of 1 K around a mean value. In each ensemble the local SSTs along
the cyclone track are thus roughly similar. The minimum pressure, however,
can still vary considerably. For example, at +6 K the simulated values of
minimum pressure range from 954 to 1002 hPa. In addition to this, we also
find that there are certain ensemble members, i.e., those with particular
domain shifts that enter the 10-member composites more often than others
across the range of SST states. Taken together, these findings indicate that
while there is a clear tendency towards more intense medicanes at higher
SSTs, higher SSTs are not the sole criterion for an intense medicane. A
mesoscale environment supportive of rapid intensification and tropical
transition is also crucial, and local SSTs are not sufficient to fully
account for the variability of the cyclones' minimum pressure.
Dependence of minimum pressure on mean SST in a radius of 150 km,
as encountered by the cyclone from -20 h before MWCT until MWCT.
Colors represent global SST change. Note that this plot is based on all
cyclones and is not a composite average.
Figure shows the temporal evolution of the composite
minimum of sea level pressure for all ΔSST from -20 h
before to +10 h after MWCT. The curves are almost equally spaced at
-20 h, but they diverge as MWCT is approaching and reach a minimum at
MWCT for almost all SST states. It is evident that at higher SSTs medicane
transition and deepening begins earlier, the deepening rate is larger and
the medicanes retain their tropical-like structure longer compared to at
lower SSTs (Figs. , in the Appendix).
Composite time series of minimum pressure from -20 h before until
+10 h after MWCT for each SST change.
It is observed that the phase space parameters -VTU
and -VTL at MWCT increase linearly with increasing
SSTs (Fig. ). It is obvious that medicanes get
stronger when SSTs increase, as the thermal winds between 600 and 900 hPa and
400 and 600 hPa at MWCT increase in almost the same proportion.
Figure presents the temporal evolution of the composite
of those two parameters from -20 h before to +10 h after MWCT for each
ΔSST. There is a roughly parallel evolution for each ΔSST for the parameter -VTU with similar
rates of increase. This contrasts with the evolution of minimum pressure, which
showed different rates for different ΔSST
(Fig. ). The evolution for the parameter
-VTL is more erratic but, at least for positive SST
changes, the observation is similar. Regressing the hourly magnitudes of
-VTU and -VTL against each
other in the period MWCT -20 h to MWCT separately for each SST state
composite reveals greater differences in the magnitudes of
-VTU and -VTU at colder SST
states. This suggests the development of a deeper medicane warm core with
higher thermal coherence in the warmer SST composites, likely generated by
enhanced upper-level latent heat release from more intense convective
updrafts at higher SSTs (Fig. ).
Dependence of composite of (a)-VTU
and (b)-VTL at MWCT on SST change. The
error bars represent standard deviation.
Composite time series of (a)-VTU
and (b)-VTL from -20 h before to
+10 h after MWCT for each SST change.
The 10 h mean of composite vertical wind speed at 500 hPa for an SST
change of (a)-3 K, (b)0 K (original
SSTs), (c)+3 K and (d)+6 K (colors), as well as composite
mean sea level pressure (contours) between MWCT -20 h and MWCT -10 h
(left column) and between MWCT -10 h and MWCT (right column). The
values on the x and y axis indicate the distance from the center of the
medicane in kilometers.
The influence of the fluxes from the sea
Similar to tropical cyclones, the main source of potential energy of
medicanes is the thermodynamic disequilibrium between the atmosphere and the
underlying sea surface. Therefore, it is generally accepted that there is a
direct relationship between SST and cyclone intensity
. The prescribed SST changes directly affect
the sensible and latent heat fluxes from the ocean into the atmospheric
boundary layer. To analyze the heat fluxes under different SST
conditions, the composite structure of the latent heat fluxes from the sea
are computed 20 and 10 h before MWCT, and at MWCT. The horizontal structure
of the medicane is remarkably well defined for ΔSST=+3 and
+6 K, with strong gradients of pressure near the center of the cyclone,
very low heat fluxes in the eye region and the strongest heat fluxes of more
than 400 W m2 in a radius between 50 and 100 km around the center
(Fig. ). This structure is consistent with the air–sea
interaction proposed by for tropical cyclones. It is
worth noting that the horizontal structure of the fluxes is not perfectly
symmetrical, which is caused by the surrounding islands and continental land
area. In particular, there are systematically weaker fluxes northeast of the
composite medicane. This effect is the imprint of continental Italy, which is
characterized by considerably lower latent heat fluxes than the ocean areas.
Composite latent heat fluxes from the sea for an SST change
of (a)-3 K, (b)0 K (original
SSTs), (c)+3 K and (d)+6 K (colors), as well as composite
mean sea level pressure (contours) at MWCT -20 h (left column),
MWCT -10 h (center column) and MWCT (right column). The values on the
x and y axis indicate the distance from the center of the medicane in
kilometers.
For ΔSST=-3 K there is no well-defined spatial structure in
the composite heat fluxes and the heat fluxes are very low with values below
150 W m2 (Fig. a). Nevertheless, the
cyclones of this composite are classified as a medicane based on the phase
space parameters. Therefore, the fluxes from the sea might play a minor role
in the formation of those medicanes.
In composites of vertical cross sections around the cyclone centers, the
vertical wind speeds were analyzed (not shown). It was found that the largest
vertical wind speeds occur in the middle troposphere around 500 hPa.
Figure shows the 10 h mean of the vertical wind
speeds at the 500 hPa level of the composite medicane and its evolution
before MWCT. Maximum vertical wind speeds occur around 50 km away from the
center of the cyclone, similar to the strongest heat fluxes. This reflects
the development of deep convection in the entire troposphere, i.e., the
deepening process that leads to the intensification of the medicane. As in
the case of the heat fluxes, the intensity of the vertical wind speeds
increases with increasing SSTs.
As one would expect, fluxes from the sea are higher when SSTs increase,
leading to greater vertical wind speeds and hence more intense deep
convection throughout the troposphere. This in turn leads to a more intense
deepening of the medicane and stronger sea level pressure gradients, thus
more intense medicanes. This chain of processes is coherent with the
classical model of for the steady state of tropical
cyclones.
Discussion and conclusions
In this study the sensitivity of a simulated medicane in the western
Mediterranean to SSTs was analyzed in an ensemble of full-physics,
non-hydrostatic regional model simulations with COSMO-CLM. In the first
downscaling step, 24-member ensembles were created by systematic shifts of
the model domain. In the second downscaling step with a horizontal resolution
of 0.0625∘, SSTs were changed uniformly by adding SST anomalies (in
a range of -4 to +6 K in 1 K increments) to the observed SST field,
creating eleven 24-member ensembles.
The cyclones were analyzed and classified according to a modified cyclone
phase space following . For each SST change, out of
the transitioning cyclones, the 10 cyclones featuring the strongest
upper-level warm cores were composited (except when ΔSST=-4 K because there are only 7 transitioning cyclones; see
Sect. ).
It was shown that the number of transitioning cyclones increases with
increasing SSTs. A particularly strong increase was found between ΔSST=-4 and -3 K, which corresponds to average SST values of
around 16 ∘C within the area of medicane development. These
results support the idea that a threshold exists for tropical-like cyclones
in the Mediterranean Sea, similar to tropical cyclones
. suggested that, as the
presence of medicanes is associated with cold-air intrusions, they can form
even when the SSTs are below the threshold of 26.5 ∘C for tropical
cyclones. Similarly, the duration of the transition increased almost linearly
with SSTs. The cyclone tracks showed small random variations in the different
ensemble members. However, the tracks of the cyclones, with or without
tropical transition, showed no systematic dependency on SSTs compared to the
control situation (ΔSST=0 K). This suggests that the track
characteristics depend on the large-scale dynamics of the upper-level
low, which determines the environmental steering conditions relevant for the
movement of the medicane.
Once the mesoscale environment is conducive to tropical transition and the
formation of a strong medicane, medicane intensity depends strongly on SSTs,
as found in our composites. The composite medicane's minimum pressure
decreases when SSTs increase, following a nonlinear relationship, in
contrast to the intensity of its lower- and upper-troposphere warm core, which
follow the linear evolution of the duration of the medicane. The process of
transitioning is roughly similar when SSTs change, except that the cyclones
transition earlier and are less affected by orography when crossing Sardinia.
As SSTs increase, the sensible and latent heat fluxes from the sea into the
atmosphere increase. The vertical wind speeds in a region of 50 km around
the eye of the medicane also increase, which can be explained by an
intensification of deep convection processes caused by the increased heat
fluxes. This deep convection leads to deeper sea level pressure minima,
stronger pressure gradients and upper-level warm cores, which occur at the
same time just before the medicanes make landfall and begin to dissipate.
found in a similar study of uniform SST
changes that the sensible and latent heat fluxes from the sea surface during
the transit of the cyclone across the Mediterranean Sea have the effect of
modifying the boundary layer and are thus efficient mechanisms for convective
destabilization. They concluded that warmer (colder) SSTs produce stronger
(weaker) sea surface fluxes, favoring an earlier (delayed) removal of
convective inhibition and enhancing (reducing) the development of convection
and the intensification of the cyclone. The results of our study, using
ensemble simulations, are in strong agreement with these conclusions. They
also concluded that the critical SST anomaly for which the atmospheric circulation displays the characteristics of the actually observed medicane is about ΔSST=-3 K. Even though we did not
compare our results to the observed phenomenon and the situation they studied
is located further south than ours, therefore showing higher SSTs of 1 to
2 ∘C, we also find that a critical value for the appearance of
medicanes is around ΔSST=-3 K.
found an almost linear deepening of the
medicane and an increasing lifetime as the SST anomalies increased from -3
to +1 K. A nonlinearity was, however, found as even warmer SST anomalies
were applied: a weaker medicane was simulated and this was mainly attributed
to the lack of a well-defined upper-air warm core. A nonlinearity was also
found at warmer SSTs in our study but only for minimum pressure and in the
direction of deepening and not weakening.
It is clear that our approach using prescribed SST changes can not fully
simulate the impact of SSTs on the development of a medicane, since feedback
processes from the medicane to the ocean are not taken into account. In
particular, our modeling strategy reflects Atmospheric Model Intercomparison Project (AMIP)-style studies, in which the complexity
of ocean–atmosphere interactions is removed from the modeling process by
prescribing SSTs as a lower boundary condition . This allows a clear but rather idealized attribution of
the observed effects to the applied SST changes. It should be noted that the
inflow into the computational domain is not changed, thus producing a large
difference between SSTs and air temperatures close to the lateral boundaries.
Furthermore, strong gradients are also induced between SSTs and land
temperatures. However, the temperatures over land, and coastal areas in particular, were proven to adapt rapidly to the SST changes before the
formation of the cyclone. studied the impact of
the modeling approach (with or without ocean–atmosphere coupling) on
simulated medicanes and found the medicane tracks and intensities to exhibit
little sensitivity. , meanwhile, studied the
robustness of COSMO-CLM coupled with a one-dimensional ocean model (1-D
NEMO-MED12). They showed that at high resolution, the coupled model is able
to not only simulate most medicane events but also improve the track length,
core temperature and wind speed of simulated medicanes compared to the
atmosphere-only simulations, suggesting that the coupled model is more
proficient for systematic and detailed studies of historical medicane events.
It would be valuable to assess the role of SSTs with such a coupled model.
With climate change, in the last decades of the 21st century (2070–2099)
the SSTs of the Mediterranean Sea are projected to increase by 1.73 to
2.97 K relative to 1961–1990 . Similarly to
, the results of this study suggest that if
the upper-air conditions of the atmosphere remain unchanged, stronger and
longer-lasting medicanes than today will appear more frequently in the
Mediterranean basin. However, the development of medicanes is influenced by
additional factors like the presence of baroclinic instability or a cold
cutoff low in the upper atmospheric layers. It is likely that climate change
will also affect these factors. and
both showed that the intensity of
medicanes is projected to increase, while their frequency will decrease.
Ensemble sensitivity studies, such as those presented here, are thus a
valuable tool for offering insights into how the life cycles of medicanes may
differ in a warmer climate.
Code and data availability
Information about the availability of the
COSMO-CLM source code can be found at https://www.clm-community.eu (last access: 14 April 2019). The
simulation data generated as part of this work have been archived at the DKRZ
World Data Center for Climate (https://www.dkrz.de/up/systems/wdcc, last access: 14 April 2019), are
publicly available under an open-access license
(http://cera-www.dkrz.de/WDCC/ui/Compact.jsp?acronym=DKRZ_LTA_961_ds00005, last access: 14 April 2019)
and citable as . Researchers interested in scientific
collaboration and/or data usage are asked to contact the authors.
Number of medicanes in each composite (one composite per SST state,
y axis) that have medicane status at a given time relative to MWCT. Note
that each composite contains 10 members, except for the -4 K anomaly SST
composite, which contains only 7 members as only 7 members underwent
transition.
Author contributions
RN performed the analysis and simulations and wrote the
manuscript. EM and NB contributed to the analysis. All authors contributed to
the writing of the manuscript and discussed the analysis and results.
Competing interests
The authors declare that they have no conflict of
interest.
Acknowledgements
The computational resources were made available by the German Climate
Computing Center (DKRZ). The authors would like to acknowledge the European
Union for funding this research through an Erasmus+ scholarship. Robin
Noyelle would like to thank Ingo Kirchner, Stefan Pfahl and Edoardo Mazza for
their fruitful comments.
Review statement
This paper was edited by Vassiliki Kotroni and reviewed by
two anonymous referees.
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