# Insights into the convective evolution of Mediterranean tropical-like cyclones

Stavros Dafis, Chantal Claud, Vassiliki Kotroni, Konstantinos Lagouvardos, Jean-François Rysman

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## To cite this version:

Stavros Dafis, Chantal Claud, Vassiliki Kotroni, Konstantinos Lagouvardos, Jean-François Rysman. Insights into the convective evolution of Mediterranean tropical-like cyclones. Quarterly Journal of the Royal Meteorological Society, 2020, 146 (733), pp.4147-4169. 10.1002/qj.3896. hal-03018731

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RESEARCH ARTICLE

# Insights into the convective evolution of Mediterranean tropical-like cyclones

Stavros Dafis<fnref n="1" />,<fnref n="2" />* |

Chantal Claud<fnref n="1" /> |

Vassiliki Kotroni<fnref n="2" /> |

Konstantinos

Lagouvardos<fnref n="2" /> | Jean-François Rysman<fnref n="1" />

**Correspondence**

Stavros Dafis, LMD/IPSL, CNRS UMR 8539, École Polytechnique, Université Paris Saclay, ENS, PSL Research University, Sorbonne Universités, UPMC Univ Paris 06, Palaiseau, France.

Email: sdafis@lmd.polytechnique.fr

**Funding information**

Direction générale de l'armement -
Ministère des Armées; National
Observatory of Athens

**Abstract**

This study aims at understanding how deep convection is organized and contributes to the intensification of nine Mediterranean tropical-like cyclones which developed between 2005 and 2018. Through a multi-satellite approach, a combination of infrared and microwave diagnostics provides insights into the temporal and spatial evolution of deep convection. ERA5 reanalysis complements the remote-sensing observations and is used to compute the vertical wind shear and vortex tilt to investigate their interactions with deep convection. Results show that vertical wind shear and topography have an important impact on the organization of deep convection and the symmetry of the cyclones. Only a fraction of these cyclones experienced intense convective activity close to their centres and we show that persistent deep convection in the upshear quadrants led to intensification periods. Convective activity solely in the downshear quadrants was not linked to intensification periods, while short-lived hurricane-like structures develop only during symmetric convective activity, leading to cyclone intensification in some of the cases. Finally, a classification of the Mediterranean tropical-like cyclones is proposed based on the evolution of deep convection and their intensification periods.

**KEYWORDS**

deep convection, Mediterranean, remote-sensing, subtropical cyclones, tropical-like cyclones, wind shear

# 1 | INTRODUCTION

The Mediterranean Sea is a well-known hot-spot for cyclogenesis with hundreds of cyclones of variable structure, lifetime and intensity forming every year (Petterssen, 1956; Trigo et al., 1999; Ulbrich et al., 2012; Flaounas et al., 2015; Lionello et al., 2016). Potential vorticity (PV) streamers, which intrude high-PV stratospheric air into the lower

atmosphere, and intense cyclogenesis have been proven as important precursors of strong Mediterranean cyclones (Raveh-Rubin and Flaounas, 2017) even though their size, intensity and lifetime are inferior to other extratropical cyclones (Čampa and Wernli, 2012). A small fraction of these cyclones exhibit characteristics similar to tropical cyclones (TCs), for example, a deep warm core, an axisymmetric structure with a windless centre (the “eye”) and

<footnote n="1">¹LMD/IPSL, CNRS UMR 8539, École Polytechnique, Université Paris Saclay, ENS, PSL Research University, Sorbonne Universités, Palaiseau, France</footnote>

<footnote n="2">²National Observatory of Athens, Institute for Environmental Research and Sustainable Development, Athens, Greece</footnote>
sustained wind speeds close to hurricane-force strength. Mediterranean Tropical-Like Cyclones (MTLCs) can pose a serious threat to populated coastal areas by producing all kinds of severe weather, but also resulting in heavy dust transport from Africa towards Europe (Fita and Flaounas, 2018) and leading to sea-surface changes which can last for several days or weeks. These changes include the rapid decrease of sea-surface temperature (Noyelle et al., 2019) or phytoplankton blooms with comparable magnitude to hurricane cases (Kotta and Kitsiou, 2019). Climatological studies suggest that in a warming climate, even though the number of occurrence of MTLCs will remain stable, their intensity may increase dramatically as well as their lifetime (Cavicchia and von Storch, 2012; Walsh et al., 2014; Romera et al., 2017; Romero and Emanuel, 2017; González-Alemán et al., 2019).

A long-term and still active debate about this group of Mediterranean tropical-like cyclones (MTLCs or “medicanes”) is based on the different mechanisms responsible for their development which have links to extratropical and tropical cyclone theory (Shapiro and Keyser, 1990; Emanuel, 2005; Miglietta and Rotunno, 2019). The contributions of baroclinic and diabatic processes are not well understood and despite several studies trying to quantify the contribution of convection in the intensification of MTLCs, no consensus has emerged. In particular, it is difficult to assess the relative importance of convection versus baroclinic instability because MTLCs develop first as typical extratropical cyclones in baroclinic environments and then experience tropical transition (TT) through tropospheric heating (Davis and Bosart, 2003). A key contributor to the large variability of structures seen in MTLCs is the influence of diabatic heating by convection. The fluxes of heat and moisture from the sea to the atmosphere can result in a large latent-heat release within developing MTLCs. However, it is also known that latent-heat release can interact with the baroclinic dynamics in a strongly nonlinear way (Kuo et al., 1991; Stoelinga, 1996). The generally accepted model for the formation of an MTLC is the development of a low-level cyclone as a response to an upper-level PV anomaly and a surface baroclinic zone, a process that is observed in the majority of Mediterranean cyclones. As a second stage, the low-level PV (LPV) anomaly generated by diabatic processes becomes important and interacts with the baroclinicity at low levels (Miglietta et al., 2017). Vertical motions are induced by the LPV anomaly embedded in baroclinic shear. This contributes to the further generation of LPV through latent-heat release in moist ascent, related to the intensification mechanism proposed by Montgomery and Farrell (1992). More recent numerical studies have addressed the importance of the diabatic production of latent- and sensible-heat release in

mid-troposphere through convection during warm seclu-
sions in the Mediterranean (Tous and Romero, 2013;
Mazza et al., 2017), similar to other cyclogenetic areas
(e.g. Posselt and Martin, 2004). Moreover, despite the pre-
sented conceptual framework for the formation of MTLCs,
additional factors dictate their genesis, such as the pres-
ence and intensity of deep convection (DC), the differential
surface friction and the uneven topography of the Mediter-
ranean which complicate further any attempt to categorize
the cyclones within strict boundaries.

Very few studies exist in the literature dedicated to
the convective evolution and the environments of MTLCs
from an observational point of view. Claud et al. (2010),
Miglietta et al. (2013) and Dafis et al. (2018) used a com-
bined approach with infrared and microwave diagnostics
to show that DC occurrence in MTLCs peaks several hours
before the maximum strength of the cyclones, showing a
longer time lag than in strong extratropical Mediterranean
cyclones (Galanaki et al., 2016) and more similar char-
acteristics with TCs. Other studies have tried to explain
the convective structure of these cyclones with numeri-
cal simulations (e.g. Lagouvardos et al., 1999; Pytharoulis
et al., 2000; Emanuel, 2005; Tous et al., 2012; Carrió
et al., 2017). Winstanley (1970) was probably the first to
investigate an MTLC as a deep Mediterranean cyclone just
north of Libya on 23 September 1969 which was respon-
sible for severe flash floods in Tunisia and Algeria, with
nearly 600 casualties and 250,000 people left homeless.
The convective and persistent nature of precipitation was
highlighted, as well as the presence of a quasi-symmetrical
cloud-free centre (an “eye”) visible in satellite images (see
their figure 7c) giving evidence for a warm-core cyclone
with an axisymmetric structure. The first reference to
warm-core cyclones in the Mediterranean was introduced
by Ernst and Matson (1983) while a few years later, Ras-
mussen and Zick (1987) studied a sub-synoptic warm-core
vortex and compared the environment and the cyclone
dynamics with polar lows. They used the first Meteosat
satellite data to observe DC around the cyclone and
argued that DC was most pronounced at the early stages
of the cyclone, before the formation of an “eye”. Claud
et al. (2010) studied the convective evolution and precipita-
tion of three MTLCs in the west and central Mediterranean
and showed that deep convective clouds and rainfall pre-
ceded the maximum intensity of the cyclones. Miglietta
et al. (2013) also came to similar results by investigat-
ing 14 MTLCs with a combined satellite-monitoring and
modelling approach. The evolution of DC and lightning
activity of the MTLC “ROLF” in 2011 was studied by
Dafis et al. (2018), who showed that the convective evo-
lution of the cyclone shares more similar characteris-
tics with TCs than intense extratropical Mediterranean
cyclones.
The rapid advances in remote sensing of the Earth from space in the past two decades have made it possible to observe cyclones worldwide in great detail and with an increasing spatial and temporal resolution (Tourville *et al.*, 2015). Even though the temporal availability of polar-orbiting satellites in the midlatitudes is limited to a few overpasses per day, they complement the geostationary satellites which provide rapid-scans of the atmosphere. The most commonly used approach to indicate the presence, the intensity and the fractional coverage of deep convective clouds is based on the use of infrared (IR) brightness temperature (BT) provided by geostationary satellites in high temporal and spatial resolution. Most authors (e.g. Chen and Houze, 1997; Yang and Slingo, 2001; Machado *et al.*, 2002; Wilcox, 2003; Tian *et al.*, 2004; Hong *et al.*, 2006; Wu and Ruan, 2016) define a threshold for IR10.8 µm BTs between 230 and 240 Kelvin under which it is assumed DC will be observed. One major drawback in adopting this method is the lack of discrimination between high-level clouds (e.g. cirrus, cirrostratus) and convective clouds, especially in their developing stage. Moreover, the analysis of microwave (MW) satellite imagery from polar-orbiting satellites which have the ability to detect and measure liquid and frozen hydrometeors, even in the lowest parts of the troposphere, has also been utilized by several studies to detect DC (Hong *et al.*, 2005; 2008; Claud *et al.*, 2010; Harnos and Nesbitt, 2011; Alvey *et al.*, 2015; Harnos and Nesbitt, 2016; Rysman *et al.*, 2016; 2017; Fischer *et al.*, 2018).

The current study uses a novel approach to investigate the DC evolution of nine MTLCs spanning between 2005 and 2018, through a multi-satellite approach with an objective of better understanding the contribution of convection to the intensification of these cyclones. Moreover, the European Centre for Medium-range Weather Forecasts (ECMWF) ERA5 reanalysis is utilized, combined with satellite retrievals, to investigate the influence of vertical wind shear (VWS) on convective and cyclone asymmetries, and to explore the steering mechanisms of DC during the different stages of their evolution. Section 2 contains a brief discussion of the nine MTLCs studied, the manual tracking method, as well as the satellite data used for detecting DC and the ERA5 data. In Section 3, we describe how DC is organized in MTLCs and what the role of VWS is in the structural response of the cyclones and the position of DC activity. The main findings and possible future work are discussed in Sections 4 and 5 respectively. Supporting information Appendix S1 provides a more detailed description of the manual tracking procedure and *in situ* observations during the MTLCs, with special focus on ERA5 performance in reproducing the cyclones' intensity.

## 2 | DATA AND METHODS

### 2.1 | Cases and tracks

Given the lack of a clear definition for the MTLCs and the lack of a general consensus about the number of cyclones that experience TT in the Mediterranean, let alone the absence of an analogous dataset to the Tropical Cyclone Best Track, the choice of the most representative MTLCs is not trivial. For the present study, nine previously identified MTLCs have been chosen between 2005 and 2018 among other cases in the literature (e.g. Miglietta *et al.*, 2013) with a variable size, intensity and duration, because for them the manual tracking of the cyclone centre could be performed with high confidence. In addition, the study period was chosen to start in 2005 when the second generation of Meteosat satellites was available, providing spatial and temporal homogeneity to the satellite data. More details about the manual tracking and how the trajectories were built are presented in Supporting information S1 in Appendix S1.

Table 1 presents the nine selected case-studies of MTLCs spanning between 2005 and 2018, with dates and duration indicating the periods for which a manual tracking of the cyclones was performed, whereas their total lifetime, mostly as extratropical cyclones at earlier stages, was longer (Di Muzio *et al.*, 2019). For the manual tracking of the cyclones, the High-Resolution Visible (HRV) and the IR channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) were used, available every 5 min through the Rapid Scanning Service (RSS) or every 15 min (RSS is available since 2008). The maximum cyclone intensity, for both the maximum wind speed and the minimum sea-level pressure (SLP) was derived either from *in situ* observations or ERA5 reanalysis data. The distance that cyclones covered during their lifetime and their mean propagation speed were estimated by the manual satellite-tracking. Additional information about the ERA5 performance, compared to the *in situ* observations used, can be found in Supporting information S2 in Appendix S1.

Figure 1 shows the cyclone-centre position according to the hourly ERA5 reanalysis based on SLP minimum location and the observed tracks. For most of the cases, the mean cyclone position error in ERA5 is less than 50 km, except for *Med2006* and *ROLF* when the model was not able to accurately reproduce the cyclone track. It is worth mentioning that the model was able to reproduce the erratic loops of the cyclones (e.g. *Med2005* and *QEN-DRESA* in Figure 1), a feature that was not simulated in previous reanalysis datasets (e.g. NCEP and ERA-Interim, see Pytharoulis *et al.* (2017)).
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<table><caption>**TABLE 1** An overview of the nine MTLCs used for this study, showing the duration of the manual tracking in hours, the maximum 10 m wind speed (m·s⁻¹) and SLP (hPa) either by *in situ* observations or derived by ERA5 (asterisked)</caption><thead><tr><th></th><th>Dates (duration hr)</th><th>Max 10 m wind (m·s⁻¹)</th><th>Min SLP (hPa)</th><th>Distance covered (km)</th><th>Mean propagation speed (m·s⁻¹)</th></tr></thead><tbody><tr><td>Med2005</td><td>15 December 2005 (44)</td><td>40</td><td>979</td><td>1850</td><td>11.5</td></tr><tr><td>Med2006</td><td>26 September 2006 (15)</td><td>40</td><td>986</td><td>350</td><td>10.4</td></tr><tr><td>Med2007</td><td>16 November 2007 (24)</td><td>20*</td><td>998</td><td>470</td><td>5.6</td></tr><tr><td>ROLF</td><td>06–09/11/2011 (60)</td><td>21</td><td>991</td><td>960</td><td>4.5</td></tr><tr><td>ILONA</td><td>22 January 2014 (26)</td><td>17</td><td>990</td><td>440</td><td>4.8</td></tr><tr><td>QENDRESA</td><td>07–08/11/2014 (26)</td><td>43</td><td>978</td><td>660</td><td>7.4</td></tr><tr><td>TRIXIE</td><td>31 October 2016 (60)</td><td>31</td><td>999</td><td>972</td><td>4.5</td></tr><tr><td>NUMA</td><td>19 November 2017 (54)</td><td>30</td><td>998</td><td>711</td><td>3.7</td></tr><tr><td>ZORBAS</td><td>29 September 2018 (48)</td><td>33</td><td>987</td><td>933</td><td>5.5</td></tr></tbody></table>

Note: The distance covered (km) by the cyclones and the mean propagation speed (m·s⁻¹) were calculated from the manual tracking.

## 2.2 | Detecting deep convection with SEVIRI and AMSU-B/MHS

In order to detect DC using SEVIRI, a similar method to Olander and Velden (2009) is used. This method relies on the channel differencing between the water vapour channel WV6.2 µm and the window channel IR10.8 µm (ΔBT) of SEVIRI pixels used at the nominal spatial resolution of about 3 km. Typically during clear-sky conditions, the IR10.8 channel has a peak spectral response close to or at the surface of the Earth, while the WV6.2 channel peaks at about 350 hPa, thus ΔBT is typically negative. In the presence of opaque and convective clouds, this spectral response can change significantly and even reverse. During intense DC, important amounts of WV can be transported in the upper troposphere or lower stratosphere where it is re-emitted at higher temperatures in the WV6.2 channel than in the window channel (Schmetz et al., 1997). Positive ΔBT (WV6.2 – IR10.8 > 0) values are attributed to convection penetrating the tropopause but not necessarily collocated with cloud overshoots (Setvak et al., 2007; Chung et al., 2008; Bedka et al., 2010), as WV can remain in the lowest stratosphere for several hours. Not all convective clouds do penetrate the tropopause, but all of them can contribute to the warming of the middle troposphere through condensational heating and release of latent heat. In order to detect the DC in IR data, pixels accounted as containing deep convective clouds must meet the criterion of ΔBT greater than or equal to –10 K. The –10 K ΔBT threshold was chosen to be representative of DC after additional analysis of collocating SEVIRI data with DC diagnostics calculated with passive microwave data.

The three humidity sounding channels around 183 GHz provided by the cross-scanning Microwave

Humidity Sounder (MHS) and the Advanced Microwave Sounding Unit (AMSU-B) on board National Oceanic and Atmospheric Administration (NOAA) and Meteorological Operational (MetOp) polar-orbiting satellites are sensitive to frozen hydrometeors and thus can detect DC. More specifically, the DC detection algorithm of Hong et al. (2005) was used to detect areas covered with deep convective clouds, which has been extensively used and validated in the Mediterranean (e.g. Funatsu et al., 2007; 2018; Rysman et al., 2016; 2017; Dafis et al., 2018). For the current study, we make use of three diagnostics for detecting convective clouds: the Deep Convection (DC), the Moderate Rainfall (MR) and the Convective Overshooting (COV) (Hong et al., 2005; Funatsu et al., 2007). Both DC and COV indicate deep convective clouds while MR corresponds to intense convective rainfall (Funatsu et al., 2007; Alhammoud et al., 2014). The DC detections are always included in the MR, and COV indicates areas with very strong DC activity with overshooting tops. From now on, in order to define areas covered by DC, the SEVIRI ΔBT values above –10 K will be referred to as “DCPIXELS”, and the MR - DC diagnostics calculated from MW sounder retrievals combined will be referred to as “MWDC”.

## 2.3 | Calculating vertical wind shear with ERA5

The VWS was calculated using the ERA5 gridded analyses ECMWF provided by the Copernicus Climate Data Store. The ERA5 dataset is available hourly on a 0.25° × 0.25° latitude–longitude grid and with 37 vertical pressure levels. The calculations to derive the vertical deep-layer shear (DLS) follow Hanley et al. (2001), and Corbosiero and Molinari (2002), for example, by computing the mean
<figure><img src="image_5.png" /><figcaption>**FIGURE 1** The nine observed cyclone tracks (black) plotted every 30 min (position with white dots) and the tracks based on the position of minimum SLP from ERA5 plotted every 1 hr (red). The main geographical features mentioned in the text are annotated. Hour is dd/mm_hhz (UTC) [Colour figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>

wind components on a cylindrical area-weighted average between 850 and 300 hPa every 1 hr over a radius of 200 km. However, given the smaller extent of the MTLCs, the radius of the cylinder was chosen to be much smaller than the aforementioned studies for the TCs, as well as the upper-level boundary for the computation of DLS which is lower (i.e. 300 hPa), in order to avoid pressure levels in the stratosphere above the Mediterranean during autumn and winter months. Moreover, the gridded analyses were not interpolated on the observed storm tracks given the small average position errors between the ERA5 and the observed storm-centre positions (Figure 1). For the current study, the terminology regarding shear will be as follows: the direction of the DLS vector will be referred to as downshear and the opposite direction as upshear. Moreover, in order to assess the impact of DLS on the cyclone structure, the vortex tilt was defined as the horizontal displacement between the local maxima of 950 and 500 hPa cyclonic circulations within 200 km of the cyclone centre every 1 hr. Even though ERA5 has higher spatial resolution than previous reanalysis datasets, it may not

be fully adequate to realistically simulate the structure and intensity of the MTLCs (Zhang *et al.*, 2020) and even numerical simulations with higher spatial resolution provide different results regarding the structure and intensity of MTLCs (e.g. Ragone *et al.*, 2018). Nevertheless, ERA5 is able to reproduce the cyclone trajectories better than previous reanalyses in terms of deviation from observed tracks, and simulates the formation of warm-core structures within the MTLCs studied. Additional analyses for the nine studied MTLCs were also performed to derive the vertical extent of the vortex core axis (not shown) to check the calculations of ERA5 vortex tilt.

## 3 | RESULTS

### 3.1 | An overview of deep convection activity in MTLCs

By collecting the DCPIXELS detected by SEVIRI every 30 min, we can estimate the occurrence of DC during
<figure><img src="image_6.png" /><figcaption>**FIGURE 2** Composite azimuthal distribution of aggregated DCPIXELS using the complete lifetime of each MTLC. The shade is the relative occurrence of DC for each individual case (note that the legend is not the same for each case). Top: (a) *Med2005*, (b) *Med2006* and (c) *Med2007*. Middle: (d) *ROLF*, (e) *ILONA* and (f) *QENDRESA*. Bottom: (g) *TRIXIE*, (h) *NUMA* and (i) *ZORBAS* [Colour figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>

the manual tracking of the cyclones. Figure 2a-i show the counts of DCPIXELS within 200 km radius from the MTLCs' centres detected during the whole periods of manual tracking as if we follow the cyclones from above (bird's-eye view). In addition, Figure 3a-i provide an overview of the temporal evolution of DC occurrence by aggregating the DCPIXELS around the cyclones. These two graphs summarize the DC activity and allow a comparison for the spatial distribution and temporal evolution of DC.

Starting with *Med2005*, DC was present in all four quadrants, but mostly concentrated in the north part of the cyclone during the first 5 hr of manual tracking, from 13 December 2005, 2100 UTC (Figures 2a and 3a). An

important weakening of DC was noticeable in the following 12 hr, especially close to the cyclone centre (Figure 3a). This period was characterized by a strong deepening and intensification of the cyclone according to ERA5 and to the study of Fita and Flaounas (2018). The remaining 28 hr until the end of cyclone life, the cyclone was moving fast eastwards and DC was concentrated within the first 100 km, at the north-northeastern parts (Figure 2a), having two peaks around 1700 UTC 14 December and 0700 UTC 15 December 2005 (Figure 3a). In the morning of 15 December 2005, brief periods of semicircular patterns of DC around the centre resulted in a cloud-free area with a radius of 20 km from the centre. After 15 December 2005, 1500 UTC, DC was not present within 100 km from the
<figure><img src="image_7.png" /><figcaption>**FIGURE 3** Composite distribution of aggregated DCPIXEL normalized by the distance from the cyclone centre every 30 min and time series of SLP minima by ERA5 every 1 hr (black line). The shade is the relative occurrence of DC for each individual case (note that the legend is not the same for each case). Top: (a) *Med2005*, (b) *Med2006* and (c) *Med2007*. Middle: (d) *ROLF*, (e) *ILONA* and (f) *QENDRESA*. Bottom: (g) *TRIXIE*, (h) *NUMA* and (i) *ZORBAS* [Colour figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>

cyclone centre and only shallow clouds were detected by the IR channels of SEVIRI (BTs higher than 245 K) until 1800 UTC east of 27°E (Figure 1a).

The *Med2006* case had a much shorter lifetime and smaller size than *Med2005*, but the greater impact in terms of damage onshore (Moscatello *et al.*, 2008a; Davolio *et al.*, 2009). The manual tracking of the cyclone using SEVIRI was possible after 26 September 2006, 0600 UTC, when it was embedded in a cold front producing a strong line of convection (Chaboureau *et al.*, 2012). Figure 3b shows that when the cyclone was in the Gulf of Taranto between 0600 UTC and 0900 UTC (Figure 1b), that is, between 0600 and 0900 UTC 26 September 2006 (Figure 3b), DC was concentrated close to the centre. When the MTLC moved onshore between 0900 UTC and

1000 UTC, DC gradually weakened, especially close to the cyclone centre. When the cyclone left the coasts of Salento Peninsula and entered the Adriatic Sea after 1000 UTC, DC was almost absent within the first 50 km from the centre (e.g. 1700 UTC in Figure 3b). DC remained active between 50 km and 200 km from the centre, with a peak of occurrence in the west side of the cyclone (Figure 2b) between 1400 and 1600 UTC (Figure 3b) but the eastern side was free of DC within 50–150 km radius (Figure 2b) as a dry slot from east-southeast was evident in the WV6.2 channel of SEVIRI (not shown). In the HRV channel, an eye-like structure was visible between 1200 and 1800 UTC but no DC was detected, as the cloud-top IR10.8 BTs were warmer than 250 K. Eventually, the cyclone reached the mainland of Italy again at 1800 UTC and gradually dissipated.
On 15 November 2007, an Alpine lee cyclogenesis occurred in the Gulf of Genoa, and the surface cyclone (Med2007) experienced TT while moving south towards Sardinia, according to McTaggart-Cowan et al. (2010). The tracking of the cyclone in our study, started on 15 November 2007, 1600 UTC at 42.2°N, 7.35°E, about 150 km northwest from Corsica (Figure 1c). During the first 4 hr until 2000 UTC, DC was important in the northern and western parts of the cyclone, even close to the centre (Figures 2c and 3c), but in the following 7 hr until 0300 UTC, DC was not detected within the first 50 km from the cyclone centre (Figure 3c). In fact, DC was only pulsating far away from the centre and only in the northern parts, close to the coasts of France. The first 50 km from the cyclone centre remained DC-free until the early morning on 16 November 2007, when a new round of convective activity with isolated storm cells began after 0600 UTC (Figure 3c) when the cyclone was approaching Sardinia (Figure 1c). The cyclone centre remained offshore but within 20 km of the west coasts of Sardinia until 1400 UTC, with small and scattered convective clouds being found in all quadrants. The cyclone lost its structure moving onshore after 1500 UTC and the manual tracking was not possible after 1600 UTC 16 November 2007.

The cyclone "ROLF" was the longest-lasting and probably the most intense case of MTLC until 2011 according to Dafis et al. (2018). Tracking of the cyclone started on 6 November 2011, 1800 UTC when it was over Mallorca (Figure 1d), when DC was very active close to the cyclone centre, as well as further away, covering the largest part of the Balearic Sea. DC continued to be active until the peak of occurrence on 7 November 2011 between 1300 UTC and 1700 UTC (Figure 3d). Figure 2d shows that DC was mostly detected close to the cyclone centre, in almost all quadrants, with storm initiation close to the centre and cyclonic outward expansion of convective clouds (i.e. between 0600 and 2300 UTC 7 November 2011 in Figure 3d). After the maximum intensity of the cyclone on 8 November 2011, 0300 UTC according to ERA5, DC remained very active mostly in the southern and eastern parts. In the morning of 8 November 2011 (Figure 3d), a large mesoscale convective system (MCS) developed in the eastern parts of the cyclone and it was wrapped cyclonically into the circulation, lasting for nearly 12 hr. This MCS is responsible for the high number of DCPIXELS in Figure 2d in the northern flank of the cyclone. After 1800 UTC 8 November 2011, DC gradually disappeared from the satellite detections and until 9 November 2011, 0600 UTC, only a cyclonic circulation of shallow clouds was evident in the satellite imagery.

The MTLC case of "ILONA" is described thoroughly in Cioni *et al.* (2016). In the present study, the manual tracking of the cyclone was not possible during its whole

lifetime given the absence of a well-defined cyclone centre. The manual tracking started on 21 January 2014, 1000 UTC when the cyclone was over the Adriatic Sea, and its centre was at 43.7°N, 14.5°E (Figure 1e) where a TT took place according to Cioni *et al.* (2016). The size of this MTLC was exceptionally small compared to the rest of the studied cyclones, with DC being detected only within 100 km from the centre and being mostly active within the first 25 km (Figures 2f and 3f) with a constant cyclone weakening according to ERA5. The cyclone remained offshore, east of the coasts of Italy, until its complete dissipation on 22 January, 1200 UTC when it was not possible to be tracked any more with the satellite imagery.

On 7 November 2014, an MTLC that developed in the Strait of Sicily was very well covered by surface stations and a radar system (Cioni *et al.*, 2018; Pytharoulis, 2018). The MTLC "QENDRESA", named by the Free University of Berlin, reached the highest intensity in terms of maximum wind speed (43 m·s⁻¹) and lowest measured SLP (978 hPa) among the rest of the MTLCs (Table 1). The manual tracking started on 7 November 2014, 0800 UTC when the cyclone was over the island of Pantelleria (Figure 1f) and the pre-existing DC was propagating outward, far away from the centre. In the following 8 hr until the cyclone reached Malta, DC was not detected within the first 25 km and barely detected between 25 and 50 km from the cyclone centre, and it was short-lived and scattered further away (i.e. until 1600 UTC 7 November 2014 in Figure 3f). While the cyclone was crossing Malta at 1600 UTC, DC was initiated and wrapped around the cyclone and was most active close to the cyclone centre (Figure 2f). Almost all the detected DCPIXELS were found within the first 100 km from the cyclone centre until the dissipation of the cyclone east of the coasts of Sicily on 8 November 2014 (Figure 1f).

The MTLC "TRIXIE" was one of the longest-lasting cases, with the manual tracking lasting 60 hr between 29 October 2016, 0000 UTC and 31 October, 1200 UTC (Figure 1g). TRIXIE was about 180 km southeast of Sicily at 36.0°N, 16.5°E on 29 October 2016, 0000 UTC when a closed cyclonic circulation was visible in the satellite imagery. Several rounds of DC activity were detected in the first 30 hr of the tracking, with storms starting to develop close to the centre and expanding outwards cyclonically (i.e. between 0000 UTC 29 October and 0600 UTC 30 October 2016 in Figure 3g). The most intense DC activity started after 1200 UTC 30 October 2016 (Figure 3g) and lasted for about 21 hr until 31 October 2016, 0900 UTC. DCPIXELS were mostly detected in the western parts of the cyclone and covered a large part of the cyclone periphery (Figure 2g), especially between 2100 UTC 30 October and 0300 UTC 31 October 2016 when a small cloud-free "eye-like" structure was developed in the cyclone centre
and a short intensification period was evident in ERA5
analysis (Figure 3g).

The cyclone that developed in the south Ionian Sea on 16 November 2017 and experienced TT the following day on 17 November 2017 (Marra et al., 2019) was named “NUMA” by the Free University of Berlin. The tracking of the cyclone started on 17 November 2017, 0000 UTC when the cyclone centre was about 150 km east from the coasts of Calabria region and south from Salento Peninsula (Figure 1h). In general, ERA5 underestimated the intensity of the cyclone, showing higher SLP values than *in situ* observations (see Supporting information S2 in Appendix S1). During the first 8 hr of the manual tracking, the first 50 km from the centre were free of DC and almost totally cloud-free. The cyclone remained almost stationary in the north Ionian Sea for more than 20 hr (Figure 1h) and DC was mostly active within 100–150 km from the cyclone centre (Figure 3h). Moreover, DC had a marked preference for the northeastern quadrant of the cyclone, evident by a high count of DCPIXELS (Figure 2h). When NUMA started moving towards Greece on 18 November 2017, 1200 UTC about 9 hr after reaching the maximum intensity according to ERA5, a burst of DC activity was detected in the east-northeast part, as shown by the peak of DC activity close to the centre in Figure 3h after 1600 UTC. The final stage of the cyclone was characterized by an intense MCS north from the centre when it was crossing the Gulf of Patras between 0100 and 0400 UTC 19 November 2017 (Figure 1h). Interestingly, the DC activity of NUMA followed the diurnal solar circle, with a peak of DC activity a few hours after the local sunset and a minimum of DCPIXELS count around noon, on both 17 and 18 November 2017.

The last case of our study is the MTLC “ZORBAS” that
developed between 28 and 30 September 2018. The man-
ual tracking of the cyclone started on 28 September 2018,
0000 UTC when the cyclone was in the south Ionian Sea, at
34.2°N, 18.6°E (Figure 1i). DC activity was almost always
close to the centre, except for a short period between 0900
and 1200 UTC 28 September 2018 (Figure 3i). Later on the
same day, a convective cell that was first detected at 1400
UTC evolved into a large MCS that lasted for almost 10 hr,
until 0000 UTC 29 September 2018. This storm initiated
close to the centre (Figure 3i) and was wrapped around the
cyclone, with the maximum DCPIXELS occurrence found
in the southwest quadrant (Figure 2i). While ZORBAS was
approaching Greece in the early morning of 29 September
2018, a large MCS developed in the northwest quadrant
and remained active until the cyclone reached the coasts of
Greece at 1200 UTC. ERA5 was not able to realistically cap-
ture the cyclone intensification during the high DC activity
in the early morning of 29 September 2018 (see Figure 3i
and Supporting information S2 in Appendix S1).

3.2 | Vertical wind shear influences

The next step in order to understand the distribution of DC
in the selected MTLCs is to identify environmental factors
dictating the cyclone evolution. VWS has been proven to
be an important factor for the development, intensification
and dissipation of TCs (Corbosiero and Molinari, 2002;
Zeng et al., 2010; Li et al., 2016). Strong VWS may inhibit
the genesis or intensification of a TC as the vertical axis of
the vortex is tilted which can lead to a decreased and less
symmetric convective activity and eventually dissipation
of the cyclone (DeMaria, 1996; Frank and Ritchie, 2001).
Even though studies of the impact of VWS on cyclones may
explain particular processes and mechanisms associated
with the evolution of the TCs, only a few studies focused on
the Mediterranean have taken VWS into account (e.g. Tous
and Romero, 2013; Cavicchia et al., 2014). To our knowl-
edge, no detailed analysis about the VWS and the vortex
tilt, that influence the evolution of convection in MTLCs,
exists in the literature.

In order to study the influence of VWS on DC in
the selected MTLCs, a shear-relative framework was
employed, rotating the DCPIXELS around the storm
centres according to the DLS vector provided by ERA5
every 1 hr so that the DLS vector was pointing due north.
Figure 4 shows the counts of DCPIXELS within a 200 km
radius from the MTLCs’ centres rotated relative to the
DLS vector direction. Compared to Figure 2, DCPIXELS
are concentrated mostly in the downshear left quadrant
in agreement with similar studies on TCs (e.g. Cor-
bosiero and Molinari, 2002; 2003; Stevenson et al., 2014;
Li et al., 2016). The influence of DLS is mostly evident
for the MTLCs *Med2005*, *ROLF* and *TRIXIE*, while for
*Med2007*, *NUMA* and *ZORBAS* comparable DC activity
is found in the upshear left quadrants. The downshear
and upshear left preference near the core of the cyclones
suggest that the strong helical nature of updraughts, due
to very small orbital periods, plays a role in shifting the
maximum convective activity counter-clockwise from
updraught initiation downshear.

In addition, the intensity of DLS seems to play an
important role in organizing DC, especially when it
exceeds 10 m·s⁻¹. This effect is shown in Figure 5 for
MTLCs *ROLF*, *TRIXIE*, *NUMA* and *ZORBAS* which expe-
rienced more than 10 m·s⁻¹ DLS for several hours during
their lifetime and their maximum intensity was estimated
after a prolonged period of strong DC. The biggest impact
of strong DLS on DC in the vicinity of the cyclone cen-
tre compared to the analysis for all values of DLS speed in
Figure 4 was found on *NUMA* and *ZORBAS* (cf. Figure 4
with Figure 5), where DC was mostly found in the down-
shear left quadrant in a strongly sheared environment. The
peak of DC in the upshear quadrants for these four MTLCs
<figure><img src="image_8.png" /><figcaption>**FIGURE 4** Composite azimuthal distribution of aggregated DCPIXELS rotated with respect to the DLS vector. The shade is the relative occurrence of DC for each case (note that the legend is not the same for each case). Top: (a) *Med2005*, (b) *Med2006* and (c) *Med2007*. Middle: (d) *ROLF*, (e) *ILONA* and (f) *QENDRESA*. Bottom: (g) *TRIXIE*, (h) *NUMA* and (i) *ZORBAS*. The red arrow shows the direction of the DLS vector pointing due north [Colour figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>

coincided with the activity of the long-lasting MCSs close to the cyclone centre discussed in Section 3.1 and Supporting information S2 in Appendix S1. In order to show the impact of strong DLS on the position of DC, we kept the DCPIXELS only for the periods with DLS stronger than 10 m·s⁻¹ in Figure 5. The mean values of DLS for constructing Figure 5 were 13.5, 12.4, 11.9 and 10.9 m·s⁻¹ for *ROLF*, *TRIXIE*, *NUMA* and *ZORBAS*, with maximum DLS values 25.5, 15.0, 15.9 and 14.3 m·s⁻¹ respectively.

To investigate these patterns further, the DC detections within the last 6 hr before the time of maximum cyclone intensity were rotated with respect to the DLS vector, regardless of the DLS speed (Figure 6). During the intensification period of the long-lasting MTLCs (except

for *Med2005*), persistent DC activity was detected in the upshear quadrants of the cyclones and it was concentrated close to the centre. In the upshear parts of a cyclone, especially during strong DLS, subsidence and dry air intrusions are expected to inhibit DC (Reasor *et al.*, 2004; Riemer *et al.*, 2010; Tang and Emanuel, 2010). Most probably this is the reason why during strong DLS with values higher than 15 m·s⁻¹ and up to 28 m·s⁻¹ in *Med2005*, DC was barely detected in the upshear quadrants (not shown). Studies on TCs have shown that the presence of DC in the upshear quadrants within 100 km from the cyclone centre is associated with intensification periods due to the high efficiency of symmetric convection in converting diabatic heating to kinetic energy (Nolan *et al.*, 2007;
<figure><img src="image_9.png" /></figure>

**FIGURE 5** As in Figure 4 but for DLS values greater than 10 m·s⁻¹. The shade is the relative occurrence of DC for each case (not normalized) of (a) ROLF, (b) TRIXIE, (c) NUMA and (d) ZORBAS. The red arrow shows the direction of the DLS vector pointing due north [Colour figure can be viewed at wileyonlinelibrary.com]

<figure><img src="image_10.png" /></figure>

**FIGURE 6** As in Figure 4 but for the 6 hr period before the maximum intensity of the cyclones and for all DLS speed values. The shade is the relative occurrence of DC for each case of (a) ROLF, (b) TRIXIE, (c) NUMA and (d) ZORBAS. The red arrow shows the direction of the DLS vector pointing due north [Colour figure can be viewed at wileyonlinelibrary.com]
Harnos and Nesbitt, 2011; 2016; Fischer et al., 2018). Similar results are presented for these MTLCs, during weak to moderate DLS. The DLS during these periods was stronger than 8 m·s⁻¹ with mean DLS values of 12.9 m·s⁻¹ for ROLF, 10.6 m·s⁻¹ for TRIXIE, 10.0 m·s⁻¹ for NUMA and 10.6 m·s⁻¹ for ZORBAS, and maximum values of 13.2, 11.7, 10.7 and 11.1 m·s⁻¹ respectively (Figure 6). These values are within the VWS speed values discussed in Cavicchia et al. (2014) and Tous and Romero (2013) for older case-studies on MTLCs.

## 3.3 | Influences of deep convection and wind shear on the cyclone structure and intensity

In order to show how the cyclone structure changes due to the presence of VWS and DC, and understand the spatial and temporal differences in DC evolution and intensity changes among the selected MTLCs, the vortex tilt is computed and discussed in detail. Observations show that *Med2005*, *Med2007* and *QENDRESA* share a few common characteristics in terms of DC and VWS evolution, especially at the incipient stage of their tropical-like characteristics, while during *ROLF*, *TRIXIE*, *NUMA* and *ZORBAS* the DC activity had different evolution. According to the distance from the cyclone centre, associative relationships between DC activity, vortex tilt and cyclone intensification are presented, and finally the MTLCs are grouped in three categories. Figure 7 shows the first proposed group of MTLCs consisted of the cases *Med2005*, *Med2007* and *QENDRESA* for which the maximum intensity of the cyclones was found at the early stages of their development and during very weak DC activity, mostly away from the cyclone centre. Moreover, the VWS was weakening during this period of deepening, despite the absence of DC.

The maximum intensity of *Med2005* was estimated in the early morning of 14 December 2005 (Figure 3a) when there were no detections of DCPIXELS close to the core of the cyclone (<50 km) (Figures 7a and 8a and Supporting information S2 in Appendix S1). After reaching the minimum SLP (Figure 3a), the cyclone experienced strong DLS after 1500 UTC 14 December 2005 and DC started to develop close to the centre with a short period of limited DC in the early morning of 15 December (Figure 8a). The vortex tilt was limited, less than 70 km and most of the time less than 50 km, despite more than 20 m·s⁻¹ DLS (Figures 7b,c and 8a). DCPIXELS were mostly initiated and detected downshear left, with rare detections upshear left (e.g. Figure 7b), where the azimuthal location of DC was shifted towards the vortex tilt vector (Figure 7b,c). Whether the actual role of the vortex tilt is to organise DC upshear or if the upshear vortex tilt is a response to

vorticity generation associated with DC cannot be currently answered with the data used in this study. A possible explanation about the cyclonic rotation of the vortex tilt left of the shear vector between 0900 and 1300 UTC 15 December (Figure 8a) is the cyclonic rotation of the mid-level vortex as a response to the strong DLS, in order to reduce the vortex tilt (Jones, 1995; Reasor et al., 2004). Similarly to Fita and Flaounas (2018), ERA5 SLP was constantly increasing on 14 and 15 December (Figure 3a) leading to cyclone filling and dissipation. Miglietta and Rotunno (2019) argue that *Med2005* may not have experienced a typical TT and the deep warm-core formation was mainly a result of baroclinic processes, such as a warm seclusion. The observations of DC evolution also suggest that during the period of maximum cyclone intensity, the absence of DC complicates the explanation of the mid/upper-level warming of the cyclone found in ERA5 and in Fita and Flaounas (2018).

Similarly to *Med2005*, the minimum SLP of MTLC *Med2007* was estimated at early stages on 15 November 2007 during very weak and scattered DC activity (Figures 3c, 8c and 7d). DLS decreased about 10 m·s⁻¹ during DC activity before the maximum intensity of the cyclone (see Supporting information S2 in Appendix S1), before 2000 UTC 15 November and the vortex tilt was rather strong, up to 100 km downshear right. After 0400 UTC 16 November, DCPIXELS detections started to increase close to the cyclone centre but DC was scattered and short-lived (e.g. Figure 7e), in contrast to the outer MCSs developing within 100–200 km from the centre (e.g. Figure 7e,f). The vortex tilt decreased below 50 km during DC activity and progressively turned from the upshear right to the downshear right quadrant (Figure 8c) as the cyclone was approaching the coasts of Sardinia. Figure 4c shows that the DLS vector seems to divide the DC-active left quadrants from the less DCPIXELS-covered right ones, indicating updraught motions on the left and downward motions to the right of the wind shear vector. This apparent DC organization may have a connection to a strongly baroclinic environment, as does the constant DLS vector pointing northeast (Figure 8c), but further analysis is needed to verify this claim.

*QENDRESA* is the last MTLC of this group, for which DC and SLP evolution followed a similar pattern to *Med2005* and *Med2007*, but the cyclone intensity was much stronger. The minimum SLP was estimated on 7 November 2014, 1700 UTC by ERA5 (Figure 3f) and in accordance with Cioni *et al.* (2018) and Carrió *et al.* (2017) (see also Supporting information S2 in Appendix S1). In the previous 9 hr the DC activity close to the centre was very weak (Figures 3f and 8f) and high BTs (>250 K) were detected by SEVIRI (Figure 7g), while DLS was weakening with values below 10 m·s⁻¹ (Figure 8f). Pytharoulis (2018)
<figure><img src="image_11.png" /><figcaption>**FIGURE 7** Infrared brightness temperature (BT) from channel IR10.8 (K) (grey) and DCPIXELS (K) (blue and red) derived from SEVIRI Meteosat satellites. Overlapped dots: Diagnostics from microwave sounders for deep convection (MWDC) (green), convective overshooting (COV) (white asterisks) and the scanning footprint (orange) within 15 min from SEVIRI scans. The red circles enclose disks within 200 km from the centre of the cyclone, plotted every 50 km and the coastline is shown with an orange solid line. The arrows show the magnitude and direction of DLS (red) and the vortex tilt (green – proportional to radius). Top: During *Med2005* (a) on 14 December 2005 at 1100 UTC, (b) at 2000 UTC (AMSU-B NOAA-17), and (c) on 15 December 2005 at 0900 UTC. Middle: During *Med2007* (d) on 15 November 2007 at 2230 UTC, (e) on 16 November 2007 at 0500 UTC, and (f) at 1230 UTC. Bottom: During *QENDRESA* (g) on 7 November 2014 at 1200 UTC, (h) at 1700 UTC, and (i) on 8 November 2014 at 0400 UTC (MHS NOAA-18) [Colour figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>

attributed the weakening of DLS to DC activity, but we show that there was a continuous weakening even when only shallow convection was detected (i.e. BTs warmer than 245 K) (Figures 7g and 8f). Just before 1600 UTC, the cyclone reached Malta when DC initiation was detected close to the centre (Figures 1f and 7h). This sudden DC initiation over Malta may be attributed to surface friction and the low-level mass convergence (Wakimoto and Black, 1994), while no significant change to the DLS intensity took place to tilt the cyclone (Figure 8f). The vortex tilt remained at less than 50 km during the lifetime of the cyclone and for this reason, its direction fluctuated constantly (Figure 8f), mostly found to the right of the DLS vector pointing south-southeast during the DC activity.

The sharp changes of vortex tilt are more frequent during weak tilting and vertical alignment of the vortices where the mid-level vortex does not change much in position but shifts in direction. The weak vortex tilt cannot directly be connected with the organization of DC in the southern parts of the cyclone during the night of 7 November 2014 and the morning on 8 November 2014 (Figures 7h-i and 8f). It is worth mentioning that in the early morning of 8 November 2014, COV detections by MHS (Figure 7i) indicated the presence of very deep updraughts between 50 and 100 km from the cyclone centre and DLS reached a minimum after a prolonged period with DC activity (Figure 8f) while the cyclone was weakening fast. Previous studies have shown that shallow convection is detected
<figure><img src="image_12.png" /><figcaption>**FIGURE 8** Time-series for (a) *Med2005*, (b) *Med2006*, (c) *Med2007*, (d) *ROLF*, (e) *ILONA*, (f) *QENDRESA*, (g) *TRIXIE*, (h) *NUMA* and (i) *ZORBAS*, of area-weighted average DLS magnitude (m·s⁻¹) calculated by ERA5 analysis within 200 km radius (red line), DLS direction (red arrows), counts of DCPIXELS (blue bars) within 50 km radius from cyclone centre, and the vortex tilt (km) (green shading) and direction (green arrows) calculated by ERA5 analysis every 1 hr. The black line indicates the time of maximum cyclone intensity. See the text for more details. Hour is dd-mm-yy_hhz (UTC) [Colour figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>

during the tropical-like phase of MTLCs (Claud *et al.*, 2010; Miglietta *et al.*, 2013; Cioni *et al.*, 2016; Marra *et al.*, 2019).

A second group of MTLCs can be formed with cyclones which lasted more than 1 diurnal cycle and experienced significant DC activity prior to their maximum intensity: *ROLF*, *TRIXIE*, *NUMA* and *ZORBAS*. These MTLCs were also discussed in Section 3.2 as DC was more symmetric

compared to the rest of the cases, and covered a larger part of the cyclones' periphery. In addition, the long-lasting and intense DC activity may have played an important role in their intensification later than their genesis time, a clear distinction from the first group.

*ROLF* was one of the longest-lasting MTLCs until 2011 and the synoptic conditions that led to its formation can
be found in previous studies by Miglietta et al. (2013) and Dafis et al. (2018). The cyclone followed a northeast direction starting from the Balearic Islands on 6 November 2011, following the direction of DLS (Figure 8d). DLS was weaker than $10 \text{ m} \cdot \text{s}^{-1}$ until 2200 UTC 7 November and the vortex tilt was mostly found upshear (Figures 8d and 9b) and more than 200 DCPIXELS per hour were detected in all quadrants within 50 km radius from the centre (Figure 8d). With the gradual increase of DLS on 8 November, the vortex tilt was reduced and turned downshear left as DCPIXELS, MWDC and COV were constantly generated downshear left and right (e.g. Figure 9c), and DCPIXELS were moving fast counter-clockwise to the upshear left quadrant. While persistent MCSs were found upshear before the maximum intensity of ROLF at 0300 UTC 8 November (Figure 3d and Supporting information S2 in Appendix S1), the downshear convection was followed by cyclone weakening, despite the more vertical alignment of the cyclone and the comparable number of DCPIXELS (Figure 8d).

TRIXIE resulted in severe weather events in southern Greece on 31 October 2016. According to ERA5, the SLP during TRIXIE was fluctuating between 1,010 and 1,014 hPa on 29 and 30 October 2016 (Figure 3g). A strongly tilted structure is evident during the same period (Figure 8g) with the vortex tilt downshear and pulsating storms close to the cyclone centre (Figure 9d). The vortex tilt was gradually decreasing between 2100 UTC 29 October and 1200 UTC 30 October but also the DC activity and DLS were weakening (Figures 3g and 8d). After 1200 UTC 30 October a sudden shift of DLS direction coincided with a burst of DC close to the centre, producing very strong updraughts as indicated by the detections of COV in Figure 9e. Even though a direct causality cannot be addressed here, the upshear-shift of the vortex tilt and the increased DC activity at the same time must be closely related, such that the simultaneous decreasing vortex tilt could be attributed to vorticity generation by diabatic heating. The persistent DC activity close to the centre was followed by a strong cyclone deepening during the night of 30 October and early morning of 31 October according to ERA5 (Figure 3g) and *in situ* observations (see Supporting information S2 in Appendix S1). Similarly to ROLF, MCSs had a clear preference for the upshear left quadrants before the maximum intensity of the cyclone at 0300 UTC 31 October (Figures 3g and 9f).

NUMA had two distinct periods of strong DC activity close to the centre. The first one between 1200 UTC 17 November and 0600 UTC 18 November 2017 was directly associated with an MCS in the upshear left quadrant which was detected by numerous DCPIXELS (Figure 9h) and COV for more than 12 hr when DLS was weaker or slightly stronger than $10 \text{ m} \cdot \text{s}^{-1}$ and the vortex tilt was less than

50 km (Figure 8h). Also during this period, the maximum intensity of the cyclone was estimated by ERA5 as for Marra et al. (2019). The DC activity was clearly closer to the centre compared to the first 12 hr of the tracking, even though MWDC and COV were detected in the outer parts of the cyclone periphery (e.g. Figure 9g). During the incipient decrease of DC activity between 0600 and 1500 UTC 18 November the cyclone started weakening and the vortex tilt reached a minimum. The DLS speed was steady during this period and changed direction from northeast to southeast (Figure 8h). The second round of strong DC activity after 1500 UTC was detected during an increasing vortex tilt downshear as the cyclone was approaching west Greece (Figures 8h and 9i). The DCPIXELS were first detected downshear and then were cyclonically wrapped around the centre until the landfall of the cyclone in Greece where severe weather events were reported (see Supporting information S2 in Appendix S1).

During the first 12 hr of ZORBAS' manual tracking, DC was pulsating and organized in two distinct bands (e.g. Figure 9j) when the vortex tilt was less than 50 km (Figure 8i). After 1400 UTC 28 September 2018, an MCS in the upshear left quadrant was constantly detected upshear by numerous DCPIXELS and MWDC for more than 10 hr. After 0000 UTC 29 September, an increasing vortex tilt upshear was calculated as the DLS was slightly increasing, and DC activity started to increase close to the centre (Figure 8i). As the cyclone was approaching Greece on 29 September, ERA5 showed a constant filling of the cyclone but *in situ* observations indicated a deepening (see Supporting information S2 in Appendix S1 for more details) as the DC was wrapped cyclonically around the centre in all quadrants (Figures 3i, 8i and 9l). The maximum intensity of the cyclone was estimated around 1000 UTC before it made landfall in south Greece, when DC activity showed a maximum in the downshear and upshear left quadrants (Figures 8i and 9l).

The third proposed group consists of the short-lasting MTLCs Med2006 and ILONA. Their size was much smaller than the rest of the cyclones discussed in this study (Figure 2b,e) and DC activity was weak or not detected for several hours during their lifetime (Figures 3b,e and 8b,e). During Med2006, many DCPIXELS were detected downshear during very strong DLS exceeding $15-20 \text{ m} \cdot \text{s}^{-1}$ (Figure 8b) but surprisingly, the estimated vortex tilt was weak. On the contrary during ILONA, DLS was weaker than $10 \text{ m} \cdot \text{s}^{-1}$ and the vortex tilt was found downshear and upshear right, tilted more than 100 km (Figure 8e) during DC activity close to the centre. Both cyclones were embedded within larger cyclonic systems (Chaboureau et al., 2012; Cioni et al., 2016) and the short-lasting DC activity downshear close to the centre of Med2006 (Figure 2b) and the upshear right quadrants of ILONA
<figure><img src="image_13.png" /><figcaption>**FIGURE 9** As in Figure 7 but for *ROLF* (a) on 7 November 2011 at 0230 UTC (NOAA-18 MHS) and (b) at 2030 UTC (MetOp-A MHS), (c) on 8 November 2011 at 1330 UTC (NOAA-18 MHS); for *TRIXIE* (d) on 29 October 2016 at 0900 UTC (MetOp-A MHS), (e) on 30 October at 1930 UTC (MetOp-A MHS), (f) on 31 October 2016 at 0100 UTC; for *NUMA* (g) on 17 November 2017 at 0300 UTC (NOAA-19 MHS) and (h) at 2230 UTC, (i) on 18 November 2017 at 2200 UTC; and for *ZORBAS* (j) on 28 September 2018 at 0830 UTC (NOAA-18 MHS), (k) on 29 September 2018 at 0100 UTC, and (l) at 0930 UTC [Colour figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>

(Figure 2e) were not associated with cyclone intensification periods (Figures 3e and 8e).

4 | DISCUSSION

The complexity of the developing MTLCs precludes the
clear presence of a dominant simple mechanism for

growth; however, we tried to investigate the evolution of
DC during their lifetime and extract some new and useful
information. *In situ* data are still too sparse to observe the
formation process and resolve the interior cyclone struc-
ture. Two very recent studies by Fita and Flaounas (2018)
and Miglietta and Rotunno (2019) have raised the ques-
tion to what extent the MTLCs are self-sustained vor-
tices and if they should be categorized according to their
<figure><img src="image_14.png" /><figcaption>**FIGURE 10** Decision tree classifier for MTLCs according to DC evolution [Colour figure can be viewed at wileyonlinelibrary.com]</figcaption></figure>

precursors, stages of evolution and contribution of diabatic processes. The first paper suggests that due to the hybrid structure of the MTLCs and the process of TT, these cyclones should be treated as subtropical cyclones which can form in other oceans of the globe between 20°N and 40°N (Evans and Guishard, 2009; González-Alemán et al., 2015; Bentley et al., 2016; 2017) or 20°–40°S (Evans and Braun, 2012; Dowdy et al., 2019). The latter paper suggests the categorization of MTLCs into three groups, based on (a) the presence of baroclinic instability and a dominant warm-seclusion process, (b) intensity of air–sea interactions and diabatic heating, and (c) the interaction of the cyclone with upper-level PV anomalies. In the present study, our observations seem to confirm that such a categorization of the MTLCs is possible. We divided the nine case-studies into groups with respect to their convective evolution and their intensification periods (Figure 10). Results show that the first group of MTLCs, *Med2005*, *Med2007* and *QENDRESA*, experienced their maximum intensity after a prolonged period of a weak DC activity close to their centres. For these cases we show that the DLS decreased during the absence of DC and the cyclone maximum intensity was observed before the organization of DC close to the centre. In addition, the spatial extent of organized DC close to the centre is much smaller than for the cases of *ROLF*, *TRIXIE*, *NUMA* and *ZORBAS*. The location of heat sources in a barotropic vortex strongly affects the strength and the structure of the cyclone. This is well analysed by numerous previous studies which also deal with the transformation of an extratropical vortex into a TC, either by naming it “diabatic intensification” (Montgomery and Farrell, 1992) or TT (Davis and Bosart, 2004). This first group of MTLCs seems to have intensified into a baroclinic environment where DC possibly had a secondary role to their TT, while DC developed later close to the centre due to either environmental shear or interactions with topography. Topography is likely an important factor for their development and further intensification, either due to influences of mid/upper-level disturbances such as the PV-banner southwest of the Alps for the *Med2007* case (McTaggart-Cowan et al., 2010), the

interaction with the dry environment and Saharan dust for the case of *Med2005* (Fita and Flaounas, 2018), or the direct landfall of *QENDRESA* in Malta and Sicily (see Supporting information S2 in Appendix S1).

The second group consists of long-lasting MTLCs which have experienced an occlusion at their early stage with or without significant DC contribution, but their intensification is observed later, after intense DC activity close to their centre (Figure 10). This group can be compared with the weak Atlantic baroclinically induced TCs discussed in the studies of Davis and Bosart (2003; 2004), which usually reach intensities below Category 2 in the Saffir–Simpson Hurricane Wind Scale. During most of their lifetime, DC is scattered and numerical studies on barotropic cyclones with asymmetrically distributed DC have shown a limited positive but mostly negative effect on the intensification of TCs (e.g. Nolan and Grasso, 2003). But MTLCs develop in the midlatitudes between 30° and 45°N where the conversion of heat energy released by DC close to the cyclone centre can lead to a net kinetic energy increase with a much higher efficiency rate than in the Tropics (Nolan et al., 2007, their figure 21). Moreover, values of VWS higher than $10 \text{ m} \cdot \text{s}^{-1}$ do not seem to inhibit their TT and intensification as previous studies have suggested, but even promote the development of DC close to the centre either downshear or towards the direction of the vortex tilt, similar to studies on TCs (e.g. Corbosiero and Molinari, 2002; Stevenson et al., 2014).

Studies on extratropical cyclones in the Atlantic have shown that TT becomes unlikely when the VWS magnitude exceeds $10 \text{ m} \cdot \text{s}^{-1}$ (DeMaria et al., 2001), while Gallina and Velden (2002) have found that VWS inhibits further intensification of the Atlantic TCs if it exceeds $7–8 \text{ m} \cdot \text{s}^{-1}$. The negative impact of VWS in the formation or intensification of TCs has also been studied through the ventilation theory which explains how dry and cool air from the upper/mid-troposphere decreases the equivalent potential temperature near the core of the cyclones (Tang and Emanuel, 2010). The loss of latent heat in the upper levels of the core can result in an increase of sea-level pressure, and thus a dissipation (Gray, 1968;
Frank and Ritchie, 2001). On the contrary, Bracken and Bosart (2000) after studying Atlantic tropical cyclogenesis found that weak VWS is necessary for developing depressions to further intensify and become TCs, as it promotes synoptic-scale ascent. In the current study, not only do the MTLCs survive in a strongly sheared environment, but the cyclones of this group can also intensify. In addition, observations of long-lasting DC that was wrapped in the upshear quadrants of the cyclones leading to axisymmetric diabatic heating of the warm core during moderate DLS and a tilted vortex could suggest a mechanism similar to the vortex resiliency explained in Reasor *et al.* (2004). The symmetric DC close to the core of the TCs has been connected to rapid intensification periods (e.g. Fischer *et al.*, 2018). Interestingly, we have not observed a significant effect of DC activity on the decrease of DLS compared to studies in the Tropics and subtropics. Only the extratropical precursor of *TRIXIE* was quite similar to Hurricane *Michael* in 2000 (Davis and Bosart, 2003), which was at first an intense extra-tropical cyclone when the weakening of DLS occurred within the precursor baroclinic environment with the synergy of DC activity and baroclinic processes. For Hurricane *Michael*, the decrease of DLS was due to both a nonconservative redistribution of PV along the vorticity vector and to the diabatically induced upper-tropospheric outflow during DC activity. An impressive anticyclonic upper-level outflow was evident in *TRIXIE*, but the complex interaction of *TRIXIE* with Mediterranean topography and the upper-tropospheric configuration complicate the interpretation of the DLS evolution. Numerical simulations should be conducted to support this observation and explore the influence of upper-tropospheric troughs and PV anomalies on the MTLCs' evolution similar to Fischer *et al.* (2017).

In the third suggested group of MTLCs (Figure 10), a small fraction of cyclones can be included, mostly due to the rare circumstances that need to take place at the same time. Strong or weak surface baroclinity and upper-level PV anomalies can create subsynoptic vortices, embedded into a larger cyclonic feature, but DC seems to play a secondary role in their intensification, perhaps because of the limited lifetime or due to other environmental factors, such as strong ventilation by VWS. Such an example is the case of *Med2006*, when a subsynoptic vortex embedded into a larger cyclone intensified after the interaction with an upper-level PV streamer (Chaboureau *et al.*, 2012; Miglietta *et al.*, 2017; Miglietta and Rotunno, 2019). Interestingly, Moscatello *et al.* (2008b) highlighted the importance of sensible- and latent-heat fluxes during DC before the maximum intensity of *Med2006*, while Chaboureau *et al.* (2012) suggested a more important contribution to the intensification of the cyclone by the interaction with the jet stream aloft. In this category, we may also include

the small subsynoptic cyclones with a shallow warm core that form after an occlusion and exhibit tropical-like characteristics for a short period of time. *ILONA* was also embedded into a much larger low-pressure system, under a maximum of upper-level PV anomaly, and its evolution was closely tied to the precursor upper-level disturbance (Cioni *et al.*, 2016). Our study shows that DC was shallow with no MWDC/COV detections and confined to a small fraction of the cyclone periphery. Additional observational and numerical studies are needed to investigate the actual contribution of DC to their evolution.

## 5 | SUMMARY AND FUTURE WORK

In this study, infrared and microwave satellite diagnostics were used to study the evolution of DC in MTLCs which developed between 2005 and 2018. ERA5 reanalysis data complemented the analysis in order to explain the multiple effects of DLS on the organization of DC and the symmetry of the cyclones. Despite the sparse *in situ* observations and uncertainties in numerical reanalysis, we believe that the presented results elucidate the effects of DC on the structure and evolution of the MTLCs. As a last step to this contribution, a classification of MTLCs was proposed according to the DC contribution to their development and intensification.

The main findings can be summarised as follows:

1. Long-lasting and organized DC activity close to the centre of the MTLCs precedes the cyclone maximum intensity of *ROLF*, *TRIXIE*, *NUMA* and *ZORBAS*. For these cases, persistent DC is detected in the upshear quadrants during the cyclone intensification periods.

2. DC activity located solely downshear was not linked to intensification periods and was more frequent during moderate and strong DLS.

3. DLS affects cyclone structure and organization of DC in most of the MTLCs. Upshear DC activity was detected often during an upshear vortex tilt.

4. Decreasing DLS was observed during very weak and sporadic DC activity during *Med2005*, *Med2007* and *QENDRESA* which are amalgamated into a group based on a hypothesis that DC did not play a dominant role in their intensification.

Due to the much drier environment of the Mediterranean basin compared to the Tropics, additional studies are needed to explain the interactions between the downdraughts of storms, the ventilation of low-entropy air in the low/mid-levels but also the response of MTLCs' structure to different depths of DLS (e.g. Finocchio *et al.*, 2016). The
<figure><img src="image_15.png" /></figure>

weakening of DLS during intense DC activity (Davis and Bosart, 2004) was not observed in this study, and since the VWS is directly related to mid/upper-tropospheric trough pathways, an additional study could incorporate methods to explain MTLCs and trough interactions (e.g. Fischer et al., 2017). Moreover, very few studies have explored the mechanisms leading to the “cyclone-eyes” formation in MTLCs, either from subsidence linked to DC activity (Moscatello et al., 2008b) or from dry air advection (Fita and Flaounas, 2018). Additional observational and numerical studies are needed to research and provide a complete understanding of the inner core of MTLCs. Previous studies have shown that DC is weaker or shallower during and after the maximum intensity of some MTLCs (e.g. Claud et al., 2010; Miglietta et al., 2013; Cioni et al., 2016; Marra et al., 2019) but this statement was not confirmed for the majority of the selected MTLCs presented in this study. In addition, the DC during NUMA followed the diurnal solar cycle, probably due to the radiative cooling of the cloud tops, a process that increases instability in the troposphere (Wu and Ruan, 2016), but additional analysis has to be conducted to investigate this feature. Finally, a numerical study of the DC contribution to the MTLCs' evolution following this observational study should be carried out, with a special focus on the growth rates of the cyclones depending on the proposed classification.

ACKNOWLEDGEMENTS

This study was sponsored by the Direction générale
de l'armement - Ministère des Armées (DGA) and a
National Observatory of Athens internal grant. Meteosat
data were retrieved from the Earth Observational Portal
of EUMETSAT. MHS and AMSU-B data were obtained
through the French Mixed Service Unit project ICARE/
Climserv/Aeris. The manual cyclone-track data for the
MTLCs and all the scripts used for this study can be pro-
vided upon request. We would like to thank the three
anonymous reviewers for their careful corrections and
constructive suggestions during the review process.

ORCID

Stavros Dafis https://orcid.org/0000-0002-1513-1930

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**How to cite this article:** Dafis S, Claud C, Kotroni V, Lagouvardos K, Rysman J-F. Insights into the convective evolution of Mediterranean tropical-like cyclones. *Q J R Meteorol Soc.* 2020;146:4147–4169. https://doi.org/10.1002/qj.3896