# Numerical investigation of the role of Saharan dust on the anomalous electrical structure of a thunderstorm over Corsica

Christelle Barthe, Pierre Tulet, Sybille de Sevin, Inès Vongpaseut, Sylvain Coquillat

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## To cite this version:

Christelle Barthe, Pierre Tulet, Sybille de Sevin, Inès Vongpaseut, Sylvain Coquillat. Numerical investigation of the role of Saharan dust on the anomalous electrical structure of a thunderstorm over Corsica. Atmospheric Research, 2025, 319, pp.107988. 10.1016/j.atmosres.2025.107988. hal-04984081

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Submitted on 21 Mar 2025

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# Numerical investigation of the role of Saharan dust on the anomalous electrical structure of a thunderstorm over Corsica

Christelle Barthe*, Pierre Tulet, Sybille de Sevin, Inès Vongpaseut, Sylvain Coquillat

LAERO, Université de Toulouse, CNRS, UT3, IRD, 14 Avenue Edouard Belin, Toulouse 31400, France

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## ARTICLE INFO

**Keywords:**

Cloud electrification
Dust aerosols
Anomalous charge structure
Cloud modeling
PACS:
0000
1111

## ABSTRACT

This study analyzes the role of dust particles on the formation of an anomalous charge structure in a thunderstorm observed on 14 October 2016 around Corsica. The cloud-resolving model Meso-NH with explicit aerosol-microphysics coupling is used to simulate realistically the interactions between the storm and the dust plume. This reference simulation shows no liquid water content in the convective region below -10 °C, which is conducive to only positive charging of the graupel according to traditional liquid water content temperature diagrams of the non-inductive charging mechanism. Differential hydrometeor fall speeds lead to a positive charge region below a negative charge region at the cloud scale, the so-called anomalous charge structure.

To disentangle between the radiative and microphysical role of dust particles on cloud structure, additional simulations are performed. First, using a climatological extinction of dust particles over Corsica, the microphysical structure of the storm is similar to the one of the reference simulation, excluding the radiative role of dust particles as a factor controlling the charge structure in this case. Secondly, a low, constant and homogeneous ice nuclei particle concentration profile is imposed in the microphysics scheme. It enables the presence of supercooled water at temperatures below -20 °C, allowing the negative charging of the graupel at higher levels of the cloud, and potentially leading to a normal tripole. It highlights the role of desert dust as ice nuclei in the depletion of liquid water content in the mixed phase region of the cloud, which could lead to an anomalous charge structure.

## 1. Introduction

A wide variety of electrical charge structures are observed in natural thunderstorms and reported in the literature. The basic tripolar structure has long been considered as the dominant electrical charge structure. It is made up of a negative charge center vertically surrounded by positive charge centers (Williams, 1989). From balloon-borne electric field soundings in different mid-latitude storms, Stolzenburg et al. (1998) identified more complex charge structures. For example, they showed that mesoscale convective systems can present up to four and six charge regions in convective updrafts and downdrafts, respectively. More recently, anomalous charge structures were widely reported (e.g. Rust and MacGorman, 2002; Tessendorf et al., 2007; Fuchs et al., 2018; Stough and Carey, 2020; Eddy et al., 2021; Stough et al., 2021; Coquillat et al., 2022). These anomalous charge structures exhibit mainly a positive region of electric charge below a negative charge region, i.e. a so-called negative dipole, while normal or positive charge structures refer to a negative charge region below a positive charge region, i.e. a so-

called positive dipole.

It is generally admitted that the non-inductive process (Saunders, 2008, and references therein) is the main mechanism responsible for thunderstorm electrification. The sign acquired by the rimer during collision with an ice crystal depends both on the temperature and the liquid water content (e.g. Takahashi, 1978; Saunders et al., 1991; Pereyra et al., 2000; Emersic and Saunders, 2010). Because the heavier rimer settles while the lighter crystal is transported upwards, a positive charging of the rimer is required to produce inverted charge structures. According to laboratory experiments (Takahashi, 1978; Pereyra et al., 2000; Saunders et al., 2006; Emersic and Saunders, 2010), it would occur for warm temperatures (> -10 °C), or for low temperatures but high or low water content. Most of the anomalous charge structures reported in the literature are from thunderstorms in the continental USA and are assumed to be caused by a high liquid water content in the mixed-phase updraft (e.g. Carey et al., 2003; Lang and Rutledge, 2011; Fuchs et al., 2018; Chmielewski et al., 2018).

Coquillat et al. (2022) analyzed 6 years of total lightning activity

<footnote>* Corresponding author.
E-mail address: christelle.barthe@cnrs.fr (C. Barthe).</footnote>
observed with the SAETTA (Suivi de l'Activit Electrique Tridimensionnelle Totale de l'Atmosphère; Coquillat et al., 2019) 3D lightning mapping array (Thomas et al., 2004) deployed over Corsica. They observed that anomalously electrified storms were systematically associated with African dust events. They classified these anomalous charge structures into two types of events: i) small thunderstorms propagating very quickly from the south-west to the north-east, and ii) strong convective events. A detailed meteorological analysis of the small events showed that they were associated with strong convective inhibition and water vapor shortage, and convection was triggered above the dry atmospheric boundary layer. The authors hypothesized that the anomalous charge structure could be due to low cloud liquid water content in the convective core. The physical processes associated with the anomalous charge structures in the strong convective events were not identified by Coquillat et al. (2022).

From the beginning of the 2000's, the impact of aerosols on lightning activity has been highlighted. Most studies focused on how anthropogenic aerosols can modify the cloud-to-ground lightning activity over urban areas (Orville et al., 2001; Naccarato et al., 2003; Wang et al., 2011; Coquillat et al., 2013; Farias et al., 2014; Tan et al., 2016; Li et al., 2018; Liu et al., 2020; Zhao et al., 2020; Shi et al., 2022; Yair et al., 2022). Most of these studies were not able to disentangle the thermal effect from the aerosol effects. The thermal hypothesis relies on the urban heat island effect that generate instabilities over the urban areas (Bourscheidt et al., 2016), helping convection triggering. Generally lightning activity enhancement is observed over and downwind of the urban area (e.g. Orville et al., 2001; Coquillat et al., 2013). The aerosol hypothesis breaks down into two effects. An increase in aerosol loading reduces the amount of solar radiation at the ground, lowering the convective available potential energy and decreasing the intensity of convective activity (Tan et al., 2016; Zhao et al., 2020). It is known as the thermal effect. The microphysical effect states that under polluted conditions, the aerosol concentration is increased, producing a large number of small droplets, decreasing the coalescence. More droplets are transported in altitude, increasing the supercooled water content. When small droplets freeze, latent heat is released, and buoyancy is increased leading to higher convective activity (e.g. Orville et al., 2001). Tan et al. (2016) stated that "the radiative effect of aerosol may be one of the main reason for the decrease of the lightning flash density in a long period, while the aerosol microphysical effect may be a major role in the increase of the percent of +CG flashes".

A few studies took place over less urbanized but polluted areas (Steiger and Orville, 2003; Thornton et al., 2017) or analyzed the Covid-19 lockdown effect on lightning activity over urbanized areas (Pinto Neto et al., 2020; Pérez-Invernón et al., 2021), neutralizing the thermal effect. They confirmed that pollution aerosols can impact the lightning activity. Generally a cloud-to-ground enhancement is associated with increased pollution. This increase of the cloud-to-ground lightning activity is also observed with increased concentration of volcanic aerosols (Yuan et al., 2011) and biomass burning aerosols (Altaratz et al., 2010).

The role of dust particles on lightning activity has been less studied. From MODIS aerosol optical depth (AOD) and lightning activity from GLD360 over the Arabian Peninsula from 2012 to 2019, Dayeh et al. (2021) found that lightning activity increases with increasing AOD. However, they observed that for AOD higher than 0.8, lightning activity reaches a threshold then decreases. Shukla et al. (2022) also observed on 16 April 2019 over India an "abysmally high number of lightning discharges" associated with a dust event. They suggested that dust particles act as cloud condensation nuclei and ice nuclei, which favours charge separation. Large proportion of positive cloud-to-ground flashes were observed to be associated with thunderstorm invaded by dust particles (Sun et al., 2023; Gangane et al., 2023); the presence of an inverted charge structure was hypothesized in the two studies.

Some modeling studies also investigated the effect of aerosols on cloud electrification and lightning activity. Using the 3D COMMAS model, Mansell and Ziegler (2013) first analyzed the impact of varying

cloud condensation nuclei (CCN) concentration on the total lightning activity. For an idealized multicell storm, they found an increase of the graupel production and the total lightning activity when the CCN concentration is increased up to 2000 cm⁻³. Using a 2D cumulus model with electrification, Tan et al. (2017) simulated an idealized continental storm and concluded that the formation of cloud droplet, graupel and ice crystal is enhanced when the CCN concentration increases from 50 to 1000 cm⁻³ resulting in an increased charge charge separation via non-inductive and inductive mechanisms. However, when the CCN concentration is in the range 1000–3000 cm⁻³, the non-inductive charging rate slightly decreases due to the reduction of ice crystal mixing ratio and size. When the CCN concentration exceeds 3000 cm⁻³, the magnitude of the charging rate is no more sensitive to the increase in aerosol concentration. Using the same model, Shi et al. (2019) simulated an idealized mountain thunderstorm with varying intensity and different CCN concentrations in the range 100–3000 cm⁻³. They observed different effects of a CCN concentration increase on the graupel production, charging rate and electrical charge structure depending on the storm intensity. Using WRF-ELEC Sun et al. (2021) simulated a storm over Beijing using polluted (2000 cm⁻³) and continental (1200 cm⁻³) CCN concentrations. They showed that under polluted conditions lightning activity is significantly enhanced during the developing and mature stages. Finally Yang et al. (2022) used a 1.5D aerosol-cloud bin model to simulate the CCOPE (Cooperative Convective Precipitation Experiment) 19 July 1981 storm. CCN and ice nuclei (IN) concentrations were varied in the range 824–1442 cm⁻³ and 0.5–2 cm⁻³, respectively. They found that increasing CCN concentration tends to decrease large ice particles formation and reduce charging rate and lightning frequency. On the contrary, when IN concentration was increased, larger ice particles were produced, enhancing the charging rate.

Previous observational studies only analyzed the impact of aerosols on lightning rates in thunderstorms. As for modeling studies investigating the role of aerosols on lightning activity, most of them were dedicated to idealized configurations of thunderstorms and/or only made the CCN concentration varied. Furthermore, previous modeling studies directly assimilated aerosols to CCN or IN; the radiative effect of aerosols is ignored. Therefore, the impact of aerosols on the electrical structure and polarity of storm cells has never been fully investigated.

The objective of this study is to investigate the role of African dust particles on the anomalous charge structure of a large storm over Corsica on the 14th of October 2016 observed by Coquillat et al. (2022). For this purpose a modeling study with the cloud-resolving model Meso-NH using explicit aerosol-microphysics coupling is conducted. To understand how dust particles can control the electrification of this convective system, sensitivity studies are performed. The 14th of October 2016 storm over Corsica is presented in Section 2. Section 3 describes the numerical set-up of the model, and Section 4 is dedicated to the results of the modeling experiments and their discussion.

## 2. The 14 October 2016 storm over Corsica: An overview

### 2.1. Meteorological situation

Fig. 1 exhibits the large-scale situation over Western Europe on the 14th of October 2016 at 0600 UTC. Close to the surface, a 1000 hPa pressure low centred over eastern Pyrenees (45.5°N; 3°E) drives a strong southwesterly flow over the Tyrrhenian sea. Strong values of potential temperature at 850 hPa (> 325 K) around Corsica and Sardinia are associated with the warm sector of this depression. The 500-hPa geopotential height indicates an upper-level trough extending from a low pressure system over Ireland and advecting cold air toward Corsica and Sardinia. A strong altitude jet is extending from the north of Algeria to the north-east of Europe. Moreover a dynamical tropopause anomaly associated with high potential vorticity values (not shown) is advected from the north of Algeria at 00 UTC to the south-east of France at 06 UTC, and is located west of the altitude jet. The meteorological
<figure><img src="image_5.png" /><figcaption>**Fig. 1.** a) Potential temperature at 850 hPa (K, colors), geopotential at 500 hPa (m, white contours) and wind at 500 hPa (m s⁻¹, grey barbs), on 14 October 2016 at 06 UTC from ECMWF operational analysis.</figcaption></figure>

environment is thus highly favorable to deep convection development and to dust outbreaks over western Europe (Cuevas-Agulló et al., 2024, and references therein).

## 2.2. Dust plume

The daily Aerosol Optical Depth (AOD) at 550 nm measured by MODIS (Moderate-Resolution Imaging Spectroradiometer) is shown on Fig. 2a for the 14th of October 2016. Due to an important cloud coverage in this region this day, AOD is only available south of Sardinia. However, it is clear that AOD larger than 0.5 are present over Tunisia and north-eastern Algeria. Values higher than 1.1 are located off the north coast of Africa. The dust AOD from the Copernicus Atmosphere Monitoring Service (CAMS) analysis is shown on Fig. 2b on the 14th of October at 06 UTC. Values of dust AOD exceeding 0.4 extend from the north of Africa to the south-east of France and the north of Italy. Dust AOD reaches 0.9 at the north-east of Corsica. CAMS analysis show that a region with significant dust particles emission is located in the north and central Algeria on the 12th, 13th and 14th of October (not shown).

Chiapello et al. (2021) reported climatological AOD values retrieved by POLDER at 550 nm in the range 0.1–0.2 in our region of interest for the autumn season. Gavrouzou et al. (2021) also reported climatological

mean AOD values below 0.2 in the region of Corsica and Sardinia. However, many studies have illustrated desert dust transport over Western Europe (e.g. Papayannis et al., 2005; Calastrini et al., 2012; Marconi et al., 2014; Huneeus et al., 2016; Mandija et al., 2017; Calidonna et al., 2020). Hermes et al. (2024) made an inventory of 48 situations between January 2018 and March 2022 with AODs greater than 0.5 over the Mediterranean or Spain. Exceptional situations such as those illustrated by Bègue et al. (2012) showed that these plumes could reach optical thicknesses of 1 as far as the Netherlands. Salvador et al. (2022) have shown that these type of dusts transport toward the western Europe Mediterranean sea increased during the last 50 years. The values encountered on 14 October 2016 around Corsica are well above the climatological values in this region, but in agreement with dust outbreaks observations.

## 2.3. Electrical activity of the storm

The SAETTA network consists in 12 standalone lightning mapping array (LMA, developed by New Mexico Tech, USA; Rison et al., 1999) stations spread over Corsica as fully described in Coquillat et al. (2019). The station altitude ranges from 3.8 to 1950 m above sea level. Each station detects the very high frequency (VHF) radiation emitted by the lightning discharges in the 60–66 MHz band at time intervals of 80 µs, with a time resolution of about 40 ns. The VHF radiation sources are located through the time-of-arrival method from at least 6 SAETTA stations. It enables mapping in three dimensions the VHF source locations. As detailed in Coquillat et al. (2019), the maximum detection range is ~350 km from the center of the network. The radial, azimuthal, and altitude errors for VHF sources located at 10 km altitude and seen from 12 SAETTA stations (geometrical model of Thomas et al., 2004), are about 15, 8, and 40 m at 50 km from the center of the SAETTA network, respectively. As in Coquillat et al. (2019), the present study considers only VHF sources that have been determined with a minimum of 7 stations and with a goodness of fit value $\chi^2 \le 0.5$.

The SAETTA network reported an intense lightning activity on the 14th of October 2016 over Corsica. Fig. 3 shows the evolution of hourly VHF sources density between 10 and 18 UTC. It clearly shows that the spatial distribution of VHF sources is advected eastward during the day. Between 10 and 11 UTC (Fig. 3a) the whole Corsica island is impacted by lightning, and the maximum of VHF sources density is located in the center of the island (42°N; 9°E). One hour later (Fig. 3b), the maximum VHF sources density is located in the northeastern Corsica (42.5°N; 9.4°E), while between 13 and 14 UTC, maximum values are observed over the sea, east of Cape Corsica (Fig. 3d). Between 14 and 15 UTC, the maximum density is located south-east of Corsica (41.2°N; 9.7°E), which indicates that a new storm is forming north of Sardinia. The maximum

<figure><img src="image_6.png" /><figcaption>**Fig. 2.** a) Daily AOD at 550 nm from MODIS (Dark Target and Deep Blue combined) on 14 October 2016. b) Dust AOD from CAMS analysis on 14 October 2016 at 06 UTC. The blue and pink boxes show the D1 and D2 domains of the Meso-NH simulation, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>**Fig. 3.** Normalized hourly SAETTA VHF sources density over Corsica on 14 October 2016 between 10 and 18 UTC. The VHF sources density is computed at a resolution of 0.01 × 0.01°, and is normalized by the maximum density. Only sources with $\chi^2 < 0.5$ are considered.</figcaption></figure>

<figure><img src="image_8.png" /><figcaption>**Fig. 4.** Normalized hourly vertical profiles of SAETTA VHF sources over Corsica on 14 October 2016 between 10 and 18 UTC. The total number of VHF sources is computed in 500-m altitude bins, and it is normalized by the maximum number of VHF sources over all levels. Only sources with $\chi^2 < 0.5$ are considered.</figcaption></figure>

density of VHF sources slightly moves northeastward toward Italy (Fig. 3f-h).

Fig. 4 shows the evolution of the vertical profiles of VHF sources. Basically, the peak in the vertical profile of VHF sources generally corresponds to the propagation of negative discharges through the region of positive charge, which emit more powerful electromagnetic radiation than positive discharges through the region of negative charge, and are therefore more easily and more often detected. Therefore, the vertical profiles in Fig. 4 show that from 10 UTC to 14 UTC, the main region of positive charge is at around 5 km altitude, while it rises to around 10 km altitude from 14 UTC to 18 UTC. In other words, from 10 UTC to 14 UTC the vertical profiles correspond to anomalous charge structures meanwhile from 14 UTC to 18 UTC they correspond to normal charge structures (Wiens et al., 2005; Bruning et al., 2014; Coquillat et al., 2022).

# 3. Experimental design

## 3.1. Numerical set-up of the reference simulation

The 14 October 2016 storm over Corsica is simulated with the Meso-NH atmospheric model (Lac et al., 2018) in version 5-5-1. Meso-NH is set up with double two-way nested domains at 2 km (D1) and 500 m (D2) horizontal grid spacing with grid sizes of 300 × 300 points and 600 × 800 points, respectively; the high-resolution domain being centered over Corsica (see blue and red boxes in Fig. 2b). 70 vertical levels are used with grid spacing varying between 40 m near the ground to 400 m at the top of the domain. The wind variables are advected with a weighted essentially non-oscillatory (WENO) discretization of fifth order scheme while the thermodynamic and scalar variables are
advected with the monotonic version of the piecewise parabolic method (PPM) (Colella and Woodward, 1984; Lin and Rood, 1996).

In the outer domain, deep convection is explicitly resolved while shallow convection is parameterized with an eddy diffusivity mass-flux scheme (Pergaud et al., 2009). In the inner domain, both deep and shallow convection are considered as explicitly resolved. Turbulence is parameterized with a 1.5-order closure (Cuxart et al., 2000). In the outer domain, purely vertical turbulent fluxes are assumed and computed using the mixing length of Bougeault and Lacarrere (1989), while in the inner domain, all turbulent fluxes are computed. The two-moment bulk microphysical scheme LIMA (Vié et al., 2016) is used and is coupled with the aerosol scheme ORILAM (Tulet et al., 2005) for sea salt and dust as described in Hoarau et al. (2018). ORILAM considers 3 lognormal modes for dust (Grini et al., 2006; Mokhtari et al., 2012) and 5 lognormal modes for sea salts upon Ovadnevaite et al. (2014). The size distribution chosen for dusts includes fine ($D = 78$ nm, $σ = 1.75$), medium ($D = 0.64$ µm, $σ = 1.76$) and coarse ($D = 5$ µm, $σ = 1.70$) modes observed during the 2006 AMMA (African Monsoon Multidisciplinary Analysis) campaign (Crumeyrolle et al., 2011); $D$ and $σ$ being the number median diameter and the geometric standard deviation, respectively. Note that all dust modes are included in the interstitial IN modes of LIMA. In LIMA, the IN heterogeneous nucleation is parameterized following Phillips et al. (2008, 2013), and IN particles with diameter less than 0.1 µm cannot serve as ice nuclei. The impaction scavenging of aerosols have been parameterized upon a kinetic mass transfer approach described by Tulet et al. (2010).

The radiative scheme is the one used at the European Centre for Medium-Range Weather Forecasts (ECMWF) (Gregory et al., 2000) including the Rapid Radiative Transfer Model (RRTM) parameterization for longwave radiation (Mlawer et al., 1997) and a scheme based on Fouquart and Bonnel (1980) for shortwave radiation. A calculation of the optical properties (single scattering albedo, asymmetry factor and

extinction) of aerosols according to Grini et al. (2006) is carried out at each time step on the six shortwave wavelength bands of the Meso-NH radiation scheme; this calculation enables to take into account the direct effect of prognostic aerosols.

Meso-NH is coupled to the Surface Externalisée (SURFEX) standardized surface platform (Masson et al., 2013). The COARE3.0 parameterization (Fairall et al., 2003) is used to represent the momentum and heat fluxes at the air-sea interface. In this study, Meso-NH is neither coupled to a wave model nor an ocean model.

The simulation starts on the 13th of October 2018 at 18 UTC and ends 24 h later. The 6-h Integrated Forecasting System (IFS) / ECMWF operational analysis are used to initialize Meso-NH and to provide the lateral boundary inflow conditions. Aerosols are initialized and forced at the lateral boundaries with the 6-h CAMS analysis (Morcrette et al., 2009) following the procedure described in Hoarau et al. (2018).

## 3.2. Sensitivity tests design

To disentangle between the radiative effect and the microphysical effect of dust particles on the electrical structure of the storm, two additional simulations are carried out in addition to the one described in Section 3 (and hereinafter referred to as REF). For these two simulations, the model is run as in the REF simulation up to 10 UTC, then it is restarted at 10 UTC with the same configuration except that:

* A climatological extinction of dust particles over Corsica is used instead of explicitly computing extinction from the aerosol scheme. This simulation is hereinafter referred to as RADCLIM.

* A constant and homogeneous IN profile with IN concentration ~ $10^{-1}$ L$^{-1}$ is imposed in the microphysics scheme. Such value corresponds roughly to the order of magnitude of dust IN concentration as shown

<figure><img src="image_9.png" /><figcaption>**Fig. 5.** (1st line) 1-h accumulated rainfall a) from the COMEPHORE product, and (2nd line) simulated by Meso-NH in the high-resolution domain on 14 October 2016 at 11 (1st column), 13 (2nd column), and 15 UTC (3rd column).</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>**Fig. 6.** a) Horizontal cross section of AOD and b) vertical cross section of total number concentration of dusts with diameter higher than 0.1 µm (cm⁻³) from Meso-NH on 14 October 2016 at 10 UTC. The white segment in a) corresponds to the track of the vertical cross section in b).</figcaption></figure>

<figure><img src="image_11.png" /><figcaption>**Fig. 7.** Contour frequency altitude diagram (CFAD) for a) cloud water content (g m⁻³), b) ice crystals number concentration (L⁻¹), and graupel mixing ratio (g kg⁻¹). Contours represent frequencies (%) of the occurrence of cloud water content, ice crystals number concentration and graupel mixing ratio within bins of width 0.2 g m⁻³, 2000 L⁻¹ and 0.5 g kg⁻¹, respectively, for all grid points belonging to the convective region of the high resolution domain (D2) at 13 UTC on 14 October 2016. The average altitudes of the 0, -10, -20, -30 and -40 °C isotherms are plotted with black lines.</figcaption></figure>

in Fig. 1–10 in Kanji et al. (2017). This simulation is hereinafter referred to as INCLIM.

# 4. Results

## 4.1. Analysis of the reference simulation

### 4.1.1. Precipitation patterns of the convective system

Fig. 5a-c show the 1-h accumulated rainfall from the COMEPHORE (COmbinaison en vue de la Meilleure Estimation de la Précipitation HOraiRE) product (Tabary et al., 2012) while Fig. 5d-f show the hourly accumulated rainfall simulated by Meso-NH. The COMEPHORE product is an hourly reanalysis of accumulated precipitation at 1 km horizontal resolution. It is the result of radar and rain gauge data fusion over France. In 2016, Corsica is covered by only two radars: Aleria on the eastern coast of Corsica (42.13°N, 9.50°E), and Collobrières on the southeast coast of continental France (43.22°N, 6.37°E). As stated by Scheffknecht et al. (2016), before 2018, radar observations and accumulated rainfall products are associated with some uncertainty west of Corsica due to masking by orography for the Aleria radar and remote location for the Collobrières one (see Fig. 1 in Tabary et al. (2013)).

At 11 UTC, Meso-NH displays several convective systems over the high-resolution domain (Fig. 5d). The most intense system is located north-west of Corsica with the maximum 1-h accumulated rainfall

exceeding 30 mm (43.3°N, 8.8°E). At the same time, the COMEPHORE product shows a large precipitating system crossing the Corsica island. Hourly accumulated rainfall higher than 30 mm are found on the north-eastern part of the island (Fig. 5a). Due to the poor radar coverage west of 9.2°E (Scheffknecht et al., 2016), it is difficult to state about the realism of convective systems in this area. In the simulation, a convective line is also present on the eastern side of the island with two peaks of the 1-h high accumulated rainfall (> 15 mm). Another convective system is located in the region between 10 and 11°E. This simulated system produces lower rainfall over Corsica compared to COMEPHORE estimates probably due to a location too far west compared to observations.

Two hours later, two convective lines oriented along a NE-SW axis are present in the region of interest as shown by the COMEPHORE product (Fig. 5b). The hourly accumulated rainfall reaches ~25 mm north-east of Sardinia and north-east of Corsica. At 13 UTC, two main large systems are also present in the region of interest in the Meso-NH simulation (Fig. 5c). The most intense one is located over the north-eastern part of Corsica, with 1-h rainfall exceeding 30 mm h⁻¹. Although more intense, the model's representation of this storm system is satisfactory. The second system is mainly located over the sea, in the eastern part of domain D2, shifted to the east compared to the COMEPHORE product (Fig. 5b).

At 15 UTC, COMEPHORE shows that the two convective lines have merged and a single precipitating line is extending from the region
<figure><img src="image_12.png" /><figcaption>**Fig. 8.** Rimer charge sign boundaries from various laboratory studies (colour lines) as a function of cloud water content (g m⁻³) and temperature (C). The grey dots show the points of the convective region of the storm at 13 UTC on the 14th of October. The charge reversal lines from the studies of Takahashi (1978), Pereyra et al. (2000), Saunders et al. (2006) and Emersic and Saunders (2010) (gold line) are plotted with blue, red, green and gold lines respectively. The “+” and “-” symbols mean that the rimer gains a positive or a negative charge in this portion of the diagram. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>

between Elba island and Italy to the north-eastern coast of Sardinia (Fig. 5c). 1-h accumulated rainfall higher than 30 mm are found both east of Sardinia and west of Italy. At 15 UTC, these two systems did not

merge in the simulation (Fig. 5f). They are mainly located over the sea, between Corsica and Italy. The region with large 1-h accumulated rainfall (> 15 mm) extends over a large area, east of 9.5°E.

Even if the convective systems are not perfectly reproduced in time and space by Meso-NH, it successfully manages to reproduce the general evolution of the convective systems in the region, i.e. two main convective systems north and south of Corsica in the morning and their moving to the western coast of Italy in the afternoon.

### 4.1.2. Dust over Corsica

The AOD simulated by Meso-NH is shown at 10 UTC on Fig. 6a. AOD varies between 0.2 and 1.2 in domain D1. A plume with AOD above 0.6 extends between 6°E and 11°E, and reaches the southern coast of France. North of 41°N, the AOD distribution is much more scattered due to the presence of deep convective clouds where dust particles are efficiently uplifted and redistributed by aqueous processes (Tulet et al., 2010). AOD values above 0.6 and reaching 1.2 are found all around Corsica, where thunderstorms develop and propagate.

As shown in Fig. 6b, strong values of total number concentration of dust particles are found over the whole troposphere with values ranging between less than 10 cm⁻³ near the tropopause to several thousands cm⁻³ below 6 km altitude. The maximum total number concentration of dust particles (~ 5000 cm⁻³) is found between 2.5 and 4 km altitude, south of Corsica. This is consistent with the attenuated total backscatter (ATB) from CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) overpasses on 14 October 2016 at 0129 and 1208 UTC that shows a stronger ATB between 2.5 and 5 km altitude, ~ 200 km west of Corsica (see Supplementary Material).

The number concentrations of dust particles simulated by Meso-NH are very high. Several studies have reported extremely high concentrations of dust particles in the Mediterranean region. Using the COSMO model, Bangert et al. (2012) simulated dust particles concentrations up

<figure><img src="image_13.png" /><figcaption>**Fig. 9.** 1-h accumulated rainfall (mm) in the RADCLIM (1st line) and INCLIM (2nd line) simulations in the high resolution domain (D2) on 14 October 2016 at 11 (1st column), 13 (2nd column), and 15 UTC (3rd column).</figcaption></figure>
<figure><img src="image_14.png" /><figcaption>**Fig. 10.** Same as Fig. 7 but for the a) RADCLIM and b) INCLIM simulations. The same width of bins as in REF are used, except for the ice crystals number concentration in INCLIM (f) where the bin width is 10 L⁻¹.</figcaption></figure>

to a few tens cm⁻³ during dust events in the western Mediterranean region. During the ChArMEx/ADRIMED field campaign, in situ aircraft measurements of Saharan dust transported over the western Mediterranean basin revealed dust concentration about 1–30 cm⁻³ and up to 3000 cm⁻³ in the coarse (D > 1 µm) and fine (5 nm < D < 1 µm) modes, respectively (Denjean et al., 2016). The dust number concentration seems to be overestimated in the Meso-NH simulation. Indeed, converting a mass of aerosols within a size range in CAMS to a number concentration distributed over a lognormal size distribution in ORILAM is not straightforward and may lead to an overestimation of nano-particles. Moreover, the coagulation process for dust particles is not taken into account in this simulation. These two reasons may lead to an overestimation of the number concentration of fine particles by the model. However, given that we are interested in the IN role of desert dust, most of these fine aerosols will not be taken into account, as only particles with a diameter greater than 0.1 µm can serve as IN.

Meso-NH is able to reproduce the overall spatio-temporal evolution of the main convective systems that developed and propagated in the northern part of Corsica on the 14th of October 2016, along with the African dust plume concomitantly reaching the south-east of France and the north of Italy. In the following, we will focus on the convective system located north of Corsica (42.5–44°N; 9–11°E) at 13 UTC. At this time, the convective activity responsible for the lightning activity (in the north-eastern region of Corsica) is relatively well represented by Meso-NH, and the vertical profile of the VHF sources from SAETTA reflects an anomalous charge structure.

### 4.1.3. Microphysical structure of the storm

The non-inductive mechanism is the main mechanism though to be responsible of cloud electrification (e.g. Reynolds et al., 1957; Dye et al.,

1986; Ziegler et al., 1991; Latham et al., 2007). It involves rebounding collisions between graupel and ice crystals in the presence of supercooled liquid water (e.g. Takahashi, 1978; Saunders et al., 1991). Fig. 7 displays the contour frequency per altitude diagram (CFAD; Yuter and Houze, 1995) computed in the convective region of the northern convective system simulated by Meso-NH at 13 UTC for cloud water content, ice crystal number concentration and graupel mixing ratio. The convective region is defined as the columns where the instantaneous precipitation rate is higher than 20 mm h⁻¹ or where the vertical velocity is higher than 5 m s⁻¹ in domain D2.

Cloud water content peaks at 3.6 g m⁻³ at 3 km altitude, just below the 0 °C isotherm (Fig. 7a). However, more than 70 % of the cloud water content values are below 1 g m⁻³ whatever the altitude. The cloud water content does not exceed 1.75 g m⁻³ at the altitude of the −10 °C isotherm, and there is no supercooled water reaching the −20 °C isotherm in the simulation.

Ice crystals concentration reaches extreme values in this simulation. Between 4 and 5 km altitude, ice concentration peaks at 70,000 L⁻¹, while between the −20 and the −40 °C isotherms, values as high as 100,000 L⁻¹ can be found locally. However, more than 50 % of the values of ice crystals concentration are below 4000 L⁻¹ whatever the altitude. This value is consistent with the results of Raga et al. (2022) who compiled 8 years of upper-tropospheric ice crystal measurements in tropical clouds in the framework of the In-Service Aircraft for a Global Observing System (IAGOS). They measured ice concentration reaching 5000 L⁻¹ at the 85th percentile above 8000 m altitude, and reported ice concentrations exceeding 50,000 L⁻¹ in some places. In this simulation, the high values below 6 km altitude can be partly attributed to the Hallett-Mossop secondary ice production mechanism active between −3 and −8 °C (Hallett and Mossop, 1974). However, the very high values
simulated above 7 km altitude in the convective region are mainly due to heterogeneous nucleation associated with extreme concentrations of dust particles.

As for the graupel mixing ratio (Fig. 7c), its maximum reaches 7.5 g kg⁻¹ around 9 km altitude, and more than 80 % of points in the mixed-phase layer of the convective part of the storm have values lower than 4–5 g kg⁻¹. Graupel is present over a large range of altitudes, between 3 and 14 km.

While graupel and ice crystals are present together over a broad range of altitudes in the convective region, cloud water content in this simulation is only available between 3.5 and 6 km altitude. Therefore, all ingredients are present for cloud electrification, but only in the lower part of the cloud, between 3.5 and 6 km altitude.

#### 4.1.4. Cloud electrification

Fig. 8 displays the scatterplot of the cloud water content versus the temperature at grid points belonging to the convective regions of the storm. The colored lines separate in the graph the cloud water content/temperature conditions for which the rimer acquires either a positive or a negative electric charge during the non-inductive mechanism. It clearly shows that there is no point in the convective region of this storm with supercooled water above the -10 °C isotherm in agreement with Fig. 7a. Cloud water content up to 2 g m⁻³ is simulated in the convective region, but for temperatures warmer than -3 °C. All points are located to the left of all the charge reversal lines leading to the exclusive positive charging of the rimer.

Numerous laboratory studies have investigated the sign and the amplitude of the electric charge separated during rebounding collisions between ice crystals and riming graupels (e.g. Reynolds et al., 1957; Takahashi, 1978; Jayaratne et al., 1983; Saunders et al., 1991; Brooks et al., 1997). However, the charge reversal line that corresponds to the temperature and supercooled water content for which the rimer changes sign can vary significantly in the different studies (see for example Fig. 1 in Takahashi et al. (2017)). This could be partly due to the difficulty in simulating natural conditions and controlling all aspects of the laboratory experiment that can impact the non-inductive charging process as outlined by Takahashi et al. (2017). Actually Saunders et al. (2004) showed that differences in charge transfer sign can be affected by ice crystal thermal preconditioning. It must be noted that the most recent laboratory experiments exhibit a charge reversal line quite similar to the one of Takahashi (1978) (Fig. 8). The main divergence in these charge reversal lines occurs for temperatures below -15 °C and for liquid water contents below 0.5 g m⁻³. In the reference simulation, no point in the convective zone reaches such values of temperature and liquid water content. Therefore, our results for the reference simulation show that a positive charging of the graupel is expected whatever the charge reversal line obtained from recent laboratory results, and an inverted dipole structure should results from such atmospheric conditions.

## 4.2. Analysis of the sensitivity tests

To disentangle between the radiative and microphysical effects of dust particles on the electrical structure of the storm, the RADCLIM and INCLIM simulations (as defined in Section 3.2) are analyzed in this section.

### 4.2.1. Radiative impact of dust particles

The 1-h accumulated rainfall at 11, 13 and 15 UTC for the RADCLIM simulation is presented in Fig. 9a-c. At 11 UTC, i.e. one hour after the sensitivity simulations have started, the 1-h accumulated rainfall is very similar in RADCLIM and REF (Fig. 5c). At 13 UTC, slight differences begin to appear in the southern part of the D2 domain (south of 42°N). The light precipitation (< 0.5 mm) present in REF between 10 and 11°N (Fig. 5e) is no more present in RADCLIM (Fig. 9b). On the contrary, light precipitation (~ 1 mm) appears north-east of Sardinia (9.5°E and 41–42°N) in RADCLIM while it is not present in REF (Fig. 5e). At 15

UTC, RADCLIM (Fig. 9c) and REF (Fig. 5f) display two main convective systems along the 10°E meridian. In both simulations the northern system is located north of 42.5°N. The southern one is located further east in RADCLIM compared to REF. This southern system seems to be less organized, and it produces much less precipitation in RADCLIM than in REF.

The CFAD of cloud water content, ice crystals number concentration and graupel mixing ratio have been plotted for RADCLIM (Fig. 10a-c), and are very similar to the REF ones (Fig. 7). In both simulations, cloud water content peaks at 3.7 g m⁻³ at 3 km altitude. In RADCLIM, cloud water content values around 0.5 g m⁻³ are found above the -10 °C isotherm (Fig. 10a), while there is no cloud water above this isotherm in REF (Fig. 7a). The ice crystals number concentration CFADs show no significant differences in RADCLIM (Fig. 10b) and REF (Fig. 7b). In RADCLIM, graupel mixing ratio reaches ~7.5 g kg⁻¹ between 7 and 12 km altitude (Fig. 10c) while it peaks at 8 g kg⁻¹ between 6 and 11.5 km altitude in REF (Fig. 7c). Additionally, less graupel mixing ratio is present above 13 km altitude in RADCLIM compared to REF.

It results in a very similar distribution of the scatterplot of cloud water content versus temperature (Fig. 11a). Cloud water content up to 2 g kg⁻¹ is found in the convective region of the system, but at temperature warmer than -10° preventing the negative charging of graupel whatever the charge reversal line considered. Therefore, in the present study, the radiative impact of dust does not have any influence on the microphysics and therefore on the non-inductive charging process. It does not appear to be a key mechanism in explaining the anomalous electrical structure of the storm studied.

### 4.2.2. Microphysical impact of dust particles

INCLIM shows a very similar behavior to REF and RADCLIM in terms of 1-h accumulated precipitation at 11 (Fig. 9d) and 13 UTC (Fig. 9e). At 11 UTC, the 1-h accumulated precipitation is similar in the three simulations. Two hours later, at 13 UTC, the precipitation field starts to diverge between the simulations. INCLIM tends to produce less precipitation than REF and RADCLIM south of 42°N. At 15 UTC, the differences between the precipitation fields in the southern part of the convective system had increased further. INCLIM produces a convective system less developed in its southern part (Fig. 9f) compared to REF and RADCLIM.

Therefore, the convective system located north of Corsica at 13 UTC has a fairly similar intensity and evolution in terms of precipitation in the three simulations.

The CFAD of cloud water content, ice crystal number concentration and graupel mixing ratio at 14 UTC in the INCLIM simulation are shown in Fig. 10d-f. In INCLIM, the cloud water content peaks at 3.7 g m⁻³ at 3 km altitude as in the REF and RADCLIM simulations. The main difference with REF (Fig. 7a) and RADCLIM (Fig. 10a) comes from the presence of cloud water content up to 11 km altitude. Cloud water content up to 0.5 g m⁻³ reaches the -20 °C isotherm, but it does not exceed 0.1 g m⁻³ between 8 and 11 km altitude. Ice crystal number concentration is significantly lower in INCLIM (Fig. 10e) compared to REF (Fig. 7b) and RADCLIM (Fig. 10b). Its maximum value is about 100 L⁻¹ between 4 and 6.5 km altitude. More than 50 % of the ice crystal number concentration values are below 10 L⁻¹. Concerning graupel mixing ratio, its maximum value (~ 11 g kg⁻¹) peaks between 9 and 14 km altitude, above the -40 °C isotherm. In INCLIM, all ingredients for efficient cloud electrification in a wide range of altitude via the non-inductive mechanism are present.

The cloud water content - temperature scatterplot for INCLIM shows that the points of the convective region are distributed over the whole range of temperatures (0 to -30 °C) (Fig. 11b). The maximum cloud water content decreases with temperature. At 0 °C, the maximum cloud water content is similar in the REF and INCLIM simulation (~ 1.5 g m⁻³). However at -10 °C there is no more cloud water content in REF while it peaks at 1.0 g m⁻³ in the convective region of the INCLIM simulation. If the parameterization of Takahashi (1978) (blue line in Fig. 11b) is considered, most points in the convective region of INCLIM
<figure><img src="image_15.png" /><figcaption>Fig. 11. Same as Fig. 8 but for the a) RADCLIM and b) INCLIM simulations.</figcaption></figure>

are below the charge reversal line meaning that graupels charge mainly positively everywhere in the cloud. If the charge reversal lines deduced from laboratory experiments by Takahashi (1978), Pereyra et al. (2000), Saunders et al. (2006) and Emersic and Saunders (2010) show a similar behavior for liquid water contents higher than $1 \text{ g m}^{-3}$ and for temperatures warmer than -15 °C, there are some discrepancies when the temperature and the liquid water content decrease. In Takahashi (1978) negative charging of the rimer only occurs for relatively high cloud water content (of the order of a few tenths of a gram per cubic meter) for temperatures below -10 °C. In Pereyra et al. (2000), Saunders et al. (2006) and Emersic and Saunders (2010) negative charging of the rimer can occur for temperatures below -20 °C whatever the cloud water content. From laboratory experiments Luque et al. (2020) reported a charge reversal temperature of -15 °C above (below) which the rimer charges positively (negatively), independently of the liquid water content in their experimental conditions. Then in the INCLIM simulation, graupel can charge negatively in the upper part of the mixed phase region of the cloud potentially leading to a normal tripolar charge structure.

Therefore, dramatically reducing the number concentration of dust particles acting as ice nuclei enables a sufficiently large supercooled water content for temperatures below -20 °C. Negative charging of the graupel is then possible in the upper part of the cloud leading to a tripolar charge structure.

## 4.3. Discussion

As discussed previously, anomalous charge structure can only be obtained if the graupel (the rimer) gains positive charge leaving the ice crystal with negative charge. Differential hydrometeor fall speeds lead basically to a positive charge region below a negative charge region at the cloud scale. As shown in Fig. 8, this situation can be obtained: (i) if the non-inductive charging is restricted to the region of the cloud between 0 and -10 °C (or -15 °C according to Pereyra et al. (2000), Saunders et al. (2006) or Emersic and Saunders (2010)), or (ii) if the non-inductive charging occurs in a region with very high liquid water content (> 1 to $4 \text{ g m}^{-3}$ depending on the laboratory study; see colored lines in Fig. 8) at low temperature.

In the literature, most storms with anomalous charge structure are found in the continental USA, and are assumed to be a consequence of high water content in the charging zone (Carey et al., 2003; Lang and Rutledge, 2011; Fuchs et al., 2018; Chmielewski et al., 2018; Stough and Carey, 2020). This situation corresponds to case (ii) above, with the occurrence of high liquid water content at low temperatures. On the contrary, the Meso-NH simulations of the 14 October 2016 storm in the region of Corsica show that the anomalous charge structure in this storm is probably associated with low liquid water content in the charging zone which corresponds to case (i) above. Therefore, the anomalous charge structure observed in the continental United States and the one

observed on the 14th of October 2016 storm do not have the same origin. This study highlighted the role of desert dust as IN in the depletion of liquid water content in the mixed phase region of the cloud, which leads to only positive charging of the graupel and to an anomalous charge structure of the storm.

The huge number concentration of dust particles advected from Africa can partly serve as IN, leading to very high ice crystal number concentration in the REF and RADCLIM simulations. Due to a lower saturation vapor pressure over ice than over liquid water, ice crystals grow faster by water deposition than droplets. If the water vapor pressure decreases below the water vapor saturation over liquid, droplets evaporate. Then ice crystals grow at the expense of cloud droplets which could lead to the glaciation of the cloud (Wegener-Bergeron-Findeisen effect). The very large number of small ice crystals between the 0 °C isotherm and the top of the cloud in REF and RADCLIM clearly supresses supercooled water above the -10 °C isotherm. In INCLIM, the IN concentration is drastically reduced compared to the one in REF and INCLIM. Consequently, the number concentration of ice crystals is also drastically reduced, and the Wegener-Bergeron-Findeisen effect is less effective. Supercooled droplets can thus be found up to the -40 °C isotherm in INCLIM. In this situation, the microphysical effect of dust is responsible for the exclusively positive charging of graupel, and thus for the anomalous charge structure.

## 5. Conclusion

Coquillat et al. (2022) observed an anomalous electric charge structure in a storm that developed in the vicinity of Corsica on the 14th of October 2016 and that interacted with a desert dust plume. The cloud-resolving model Meso-NH has been used to investigate the role of desert dust particles acting as IN on cloud electrification of this convective system. Hectometric-scale simulations has been performed over Corsica using an interactive and comprehensive aerosol-microphysics coupling (ORILAM-LIMA) as described in Hoarau et al. (2018). The interaction between the convective system located north-east of Corsica around 13 UTC and the dust plume coming from north Africa increases dramatically the ice crystal number concentration, which aims to reduce significantly the supercooled water content above the -10 °C isotherm, and therefore cloud electrification above this altitude. According to the liquid water content - temperature diagram of Takahashi (1978), Pereyra et al. (2000), Saunders et al. (2006) and Emersic and Saunders (2010), it would result in the exclusively positive charging of graupel, and in anomalous electrical structure.

Through sensitivity tests, it was shown that reducing the concentration of dust particles acting as IN in the microphysical scheme LIMA makes the liquid water content increases significantly above the -10 °C isotherm, allowing the positive charging of the graupel according to the non-inductive charging diagrams of Pereyra et al. (2000), Saunders et al. (2006) and Emersic and Saunders (2010). In contrast, the radiative
effect of desert dust does not play a significant role in the microphysical structure of the cloud once the storm is developed. However, the radiative impact of dust aerosols on the development and structure of the convective system was not investigated in this study.

This numerical study is a first attempt to investigate which factors could be responsible for the anomalous charge structures observed over Corsica during dust plume events. Additional numerical studies are needed to fully understand how desert dust particles interact with convective systems over Corsica. In particular, the effect of desert dust particles on the electrical structure of the fast moving and small storms should be investigated. Moreover, the effect of dust acting as CCN (Twohy et al., 2009; Bègue et al., 2015), and the possible competing effect between increased supercooled liquid water content by enhanced CCN concentration and increased ice crystal number concentration by enhanced IN concentration should be analyzed. In future studies, the electrical scheme of Meso-NH (CELLS; Barthe et al., 2012) will be used with ORILAM and LIMA to compare directly the lightning activity of the storms with SAETTA data.

## CRediT authorship contribution statement

**Christelle Barthe:** Writing – original draft, Visualization, Supervision, Methodology, Conceptualization. **Pierre Tulet:** Writing – review & editing, Validation, Supervision, Software, Conceptualization. **Sybille de Sevin:** Writing – review & editing, Visualization, Investigation, Formal analysis. **Inès Vongpaseut:** Writing – review & editing, Visualization, Resources. **Sylvain Coquillat:** Writing – review & editing, Supervision, Resources.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgments

This work was supported by ANR ICCARE under grant ANR-21-CE01-0006. Numerical modeling was made possible thanks to the computer resources of Météo-France. CALIPSO data have been kindly processed by Vincent Noël (LAERO). Clotilde Augros (CNRM) is warmly acknowledged for useful discussions on radar data over Corsica.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.atmosres.2025.107988.

## Data availability

The numerical model Meso-NH is freely available under CeCILL-C license agreement and can be downloaded at http://mesonh.aeroobs-mip.fr/. Public data used in this study are available in the following repositories: MODIS (https://ladsweb.modaps.eosdis.nasa.gov/archive/allData/61/MOD08_D3/), CAMS (https://atmosphere.copernicus.eu), ECMWF analysis (https://www.ecmwf.int), SAETTA data (https://saetta.aeris-data.fr/) and COMEPHORE product (https://radarsmf.aeris-data.fr/). The scientific colour maps nuuk and batlowW (Crameri, 2018) are used in this study to prevent visual distortion of the data and exclusion of readers with colour-vision deficiencies.

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